Patent Application
20180232689
The present inventions relate to systems and methods managing and using information regarding the nutritional, organoleptic, or aesthetic values of a nutritional substance.
Nutritional substances are traditionally grown (plants), raised (animals) or synthesized (synthetic compounds). Additionally, nutritional substances can be found in a wild, non-cultivated form, which can be caught or collected. While the collectors and creators of nutritional substances generally obtain and/or generate information about the source, history, caloric content and/or nutritional content of their products, they generally do not pass such information along to the users of their products. It would be desirable for such information be available to the consumers of nutritional substances, as well as all participants in the food and beverage industry—the nutritional substance supply system.
Caloric content refers to the energy in nutritional substances, commonly measured in calories. The caloric content could be represented as sugars, proteins, and/or carbohydrates in the nutritional substances. The nutritional content, also referred to herein as nutritional value, of foods and beverages, as used herein, refers to the non-caloric content of these nutritional substances which are beneficial to the organisms which consume these nutritional substances. For example, the nutritional content of a nutritional substance could include vitamins, minerals, and other non-caloric components which are necessary, or at least beneficial, to the organism consuming the nutritional substances.
Consumers are beginning to demand that the food and beverage industry offer products which include higher nutritional content, and/or at least information regarding nutritional content of such products, as well as information regarding the source, creation and other origin information for the nutritional substance. In fact, consumers are already willing to pay higher prices for higher nutritional content. This can be seen at high-end grocery stores which offer organic, minimally processed, fresh, non-adulterated nutritional substances. Further, as societies and governments seek to improve their constituents' health and lower healthcare costs, incentives and/or mandates will be given to the food and beverage industry to track, maintain, and/or increase the nutritional content of nutritional substances they handle. There will be a need for an industry-wide solution to allow the management of nutritional content across the entire cycle from creation to consumption. In order to manage the nutritional content of nutritional substances across the entire cycle from creation to consumption, the nutritional substance industry will need to identify, track, measure, estimate, preserve, transform, condition, and record nutritional content for nutritional substances. Of particular importance is the measurement, estimation, and tracking of changes to the nutritional content of a nutritional substance from creation to consumption. This information could be used, not only by the consumer in selecting particular nutritional substances to consume, but could be used by the other food and beverage industry participants, including creation, preservation, transformation, and conditioning, to make decisions on how to create, handle and process nutritional substances. Additionally, those who sell nutritional substances to consumers, such as restaurants and grocery stores, could communicate perceived qualitative values of the nutritional substance in their efforts to market and position their nutritional substance products. Further, a determinant of price of the nutritional substance could be particular nutritional, organoleptic, or aesthetic values, and if changes to those values are perceived as desirable. Still further, a system allowing creators, preservers, transformers, and conditioners of nutritional substances to update labeling content to reflect the most current information about the nutritional substance would provide consumers with the information they need to make informed decisions regarding the nutritional substances they purchase and consume. Such information updates could include nutritional, organoleptic, or aesthetic values of the nutritional substance, and may further include information regarding the source, creation and other origin information for the nutritional sub stance.
For example, the grower of sweet corn generally only provides basic information as the variety and grade of its corn to the packager, who preserves and ships the corn to a producer for use in a ready-to-eat dinner. The packager may only tell the producer that the corn has been frozen as loose kernels of sweet corn. The producer may only provide the consumer with rudimentary instructions how to cook or reheat the ready-to-eat dinner in a microwave oven, toaster oven or conventional oven, and only tell the consumer that the dinner contains whole kernel corn among the various items in the dinner. Finally, the consumer of the dinner will likely keep her opinions on the quality of the dinner to herself, unless it was an especially bad experience, where she might contact the producer's customer support program to complain. Very minimal, or no, information on the nutritional content of the ready-to-eat dinner is passed along to the consumer. The consumer knows essentially nothing about changes (generally a degradation, but could be a maintenance or even an improvement) to the nutritional content of the sweet corn from creation, processing, packaging, cooking, preservation, preparation by consumer, and finally consumption by the consumer. The consumer is even more unlikely to be aware of possible changes to labeling content that a creator, preserver, transformer, or conditioner may just have become be aware of, such as changes in information about nutritional, organoleptic, or aesthetic values of the nutritional substance or changes in information regarding the source, creation and other origin information about the nutritional substance. If communicated, such changes to labeling content could affect a purchasing preference or consumption preference of a consumer, and create a market for goods not only with high nutritional values, but for goods that have changed the least from their source.
Furthermore, the producer of the ready-to-eat dinner does not know the nutritional content and organoleptic state and aesthetic condition of the product after it has been reheated or cooked by the consumer, cannot predict changes to these properties, and cannot inform a consumer of this information to enable the consumer to better meet their needs. For example, the consumer may want to know what proportion of desired organoleptic properties or values, desired nutritional content or values, or desired aesthetic properties or values of the corn in the ready-to-eat dinner remain after cooking or reheating, and the change in the desired nutritional content or values, the desired organoleptic properties or values, or the desired aesthetic properties or values (usually a degradation, but could be a maintenance or even improvement). There is a need to preserve, measure, estimate, store and/or transmit information regarding such nutritional, organoleptic, and aesthetic values, including changes to these values, throughout the nutritional substance supply system. Given the opportunity and a system capable of receiving and processing real time consumer feedback and updates regarding changes in the nutritional, organoleptic, and/or aesthetic value of nutritional substances, consumers can even play a role in updating dynamic information about the nutritional substances they have purchased and/or prepared for consumption, such that the information is available and useful to others in the nutritional substance supply system. Ideally, equipment for local storage of nutritional substances by consumers, such as any food preparation appliance, storage location, portable container, tray, bag, and so forth, could interact with nutritional substance products to provide such consumer feedback and updates. Ideally, equipment for conditioning of nutritional substances by consumers, such as any food preparation appliance, oven, toaster oven, toaster, blender, stove top, grill, microwave, and so forth, could interact with nutritional substance products to provide such consumer feedback and updates. Further, equipment for local storage of medicament products by consumers, such as any pantry, storage location, portable container, tray, bag, and so forth, could interact with the medicament product to provide such consumer feedback and updates.
The caloric and nutritional content information for a prepared food that is provided to the consumer is often minimal. For example, when sugar is listed in the ingredient list, the consumer generally does not receive any information about the source of the sugar, which can come from a variety of plants, such as sugarcane, beets, or corn, which will affect its nutritional content. Conversely, some nutritional information that is provided to consumers is so detailed, the consumer can do little with it. For example, this list of ingredients is from a nutritional label on a consumer product: Vitamins—A 355 IU 7%, E 0.8 mg 4%, K 0.5 mcg, 1%, Thiamin 0.6 mg 43%, Riboflavin 0.3 mg 20%, Niacin 6.0 mg 30%, B6 1.0 mg 52%, Foliate 31.5 mcg 8%, Pantothenic 7%; Minerals Calcium 11.6 1%, Iron 4.5 mg 25%, Phosphorus 349 mg 35%, Potassium 476 mg 14%, Sodium 58.1 mg 2%, Zinc 3.7 mg 24%, Copper 0.5 mg 26%, Manganese 0.8 mg 40%, Selenium 25.7 mcg 37%; Carbohydrate 123 g, Dietary fiber 12.1 g, Saturated fat 7.9 g, Monosaturated Fat 2, 1 g, Polysaturated Fat 3.6 g, Omega 3 fatty acids 108 g, Omega 6 fatty acids 3481, Ash 2.0 g and Water 17.2 g. (%=Daily Value). Such information needs to be presented in a manner that meets the specific needs of a particular consumer. For example, consumers with a medical condition, such as diabetes, would want to track specific information regarding nutritional values associated with sugar and other nutrients in the foods and beverages they consume, and would benefit further from knowing changes in these values or having tools to quickly indicate or estimate these changes in a retrospective, current, or prospective fashion, and even tools to report these changes, or impressions of these changes, in a real-time fashion. Consumers would want to track medicaments for specific requirements, changes in their medicinal values, degradation, and for potential interactions with other medicaments and nutritional substances they are consuming or planning to consume.
In fact, each industry participant in the food and beverage industry already creates and tracks some information, including caloric and nutritional information, about their product internally. For example, the farmer who grew the corn knows the variety of the seed, condition of the soil, the source of the water, the fertilizers and pesticides used, and can measure the caloric and nutritional content at creation. The packager of the corn knows when it was picked, how it was transported to the packaging plant, how the corn was preserved and packaged before being sent to the ready-to-eat dinner producer, when it was delivered to the producer, and what degradation to caloric and nutritional content has occurred. The producer knows the source of each element of the ready-to-eat dinner, how it was processed, including the recipe followed, and how it was preserved and packaged for the consumer. Not only does such a producer know what degradation to caloric and nutritional content occurred, the producer can modify its processing and post-processing preservation to minimally affect nutritional content. The preparation of the nutritional substance for consumption can also degrade the nutritional content of nutritional substances. Finally, the consumer knows how she prepared the dinner, what condiments were added, and whether she did or did not enjoy it.
If there was a mechanism to share this information, the quality of the nutritional substances, including caloric and nutritional, organoleptic, and aesthetic value, could be preserved and improved. Consumers could be better informed about nutritional substances they select and consume, including the state, and changes in the state, of the nutritional substance throughout its lifecycle from creation to consumption. Feedback within the entire chain from creator to consumer could provide a closed-loop system that could improve quality (taste, appearance, and caloric and nutritional content), efficiency, value and profit. For example, in the milk supply chain, at least 10% of the milk produced is wasted due to lack available information for producers and consumers included in product expiration dates and methods of preparation. The use of more accurate tracking information, measured quality (including nutritional content) information, and historical environmental information could substantially reduce such waste.
Consumers of nutritional substances are sometimes given options on how to prepare nutritional substances they have obtained from the store, such as different cooking devices: microwave ovens, toaster ovens, conventional ovens, etc., and/or limited taste preferences such as crunchy or soft. However, if the consumer desires to prepare a specific recipe, they must obtain all the proper ingredients themselves, as well as prepare the recipe themselves including which cooking appliances need to be used. Further, the consumer has no way of knowing the history or current condition of the nutritional substances they obtain for preparing a desired recipe. Still further, the consumer has no way of knowing how to change or modify the conditioning process to achieve desired nutritional, organoleptic, and aesthetic properties after preparation. Consumers locally store, condition, and consume nutritional substances they acquire, but have no way to change the way they locally store, condition, and consume the nutritional substances based on the history or current condition of the nutritional substances.
Overall, the examples herein of some prior or related systems and their associated limitations are intended to be illustrative and not exclusive. Other limitations of existing or prior systems will become apparent to those of skill in the art upon reading the following Detailed Description.
In an embodiment of the present invention, a system is provided for the tracking of changes of nutritional, organoleptic, and/or aesthetic values of a nutritional substance, wherein the system may collect, store, and transmit information regarding the changes of nutritional, organoleptic, and/or aesthetic values of the nutritional substance, and information related to origin and creation of the nutritional substance, from creation through consumption, including all phases of preservation, transformation, local storage and conditioning.
In an embodiment of the present invention, local storage appliances and equipment modify or adapt local storage of a nutritional substance to maintain and/or minimize degradation of and/or improve, and/or display nutritional, organoleptic, and/or aesthetic values of the nutritional substance, responsive to information related to changes or degradation of nutritional, organoleptic, and/or aesthetic values of the nutritional substance, or residual nutritional, organoleptic, or aesthetic value of the nutritional substance at the initiation of said local storage.
In a further embodiment of the present invention, local storage appliances and equipment preserve, modify or adapt local storage of a nutritional substance to maintain and/or minimize degradation of and/or improve, and/or display nutritional, organoleptic, and/or aesthetic values of the nutritional substance, responsive to information sensed during said local storage regarding a nutritional, organoleptic, or aesthetic value of the nutritional substance.
In an embodiment of the present invention, conditioning appliances and equipment preserve, modify or adapt conditioning of a nutritional substance to maintain and/or minimize degradation of and/or improve, and/or display nutritional, organoleptic, and/or aesthetic values of the nutritional substance, responsive to information related to changes or degradation of nutritional, organoleptic, and/or aesthetic values of the nutritional substance and responsive to information sensed within the conditioner and/or the of the nutritional substance.
In a further embodiment of the present invention, conditioning appliances and equipment preserve, modify or adapt local storage of a nutritional substance to maintain and/or minimize degradation of and/or improve, and/or display nutritional, organoleptic, and/or aesthetic values of the nutritional substance responsive to information regarding a residual nutritional, organoleptic, or aesthetic value of the nutritional substance at the initiation of said conditioning.
In a further embodiment of the present invention, conditioning appliances and equipment preserve, modify or adapt local storage of a nutritional substance to maintain and/or minimize degradation of and/or improve, and/or display nutritional, organoleptic, and/or aesthetic values of the nutritional substance, responsive to information sensed during said conditioning regarding a nutritional, organoleptic, or aesthetic value of the nutritional substance
In an embodiment of the present invention, during local storage or conditioning of a nutritional substance, information related to changes or degradation of nutritional, organoleptic, and/or aesthetic values of the nutritional substance, including initial nutritional, organoleptic, and/or aesthetic values or other information related to the origin and creation of the nutritional substance, and information related to nutritional, organoleptic, and/or aesthetic values sensed during local storage and conditioning, is compared with general consumer requirements, or with a specific consumer's requirements, to confirm compliance, or non-compliance, regarding nutritional, organoleptic, and/or aesthetic values, or regarding origin and creation of the nutritional substance, or to display the nutritional, organoleptic, and/or aesthetic values to the consumer. In some embodiments, this includes by controlling multiple storage and conditioners with a seamless dynamic experience.
In an embodiment of the present invention, conditioning of a nutritional substance is modified or adapted to inform maintain and/or minimize degradation of and/or improve nutritional, organoleptic, and/or aesthetic values of the nutritional substance, responsive to at least one of current consumer information, current consumer input, or consumer input regarding prior experience.
In an embodiment of the present invention, information collected by sensors of, or sensors communicating with or residing within, a local storage appliance, for example weight measurement sensors, can collect all types of physical attribute data by sensing a nutritional substance, and can identify the nutritional substance and its current nutritional, organoleptic, and aesthetic state by comparing the sensed data to a library of data for known nutritional substances at known nutritional, organoleptic, and aesthetic states, and further can be adaptively store the nutritional substance responsive to: its initial nutritional, organoleptic, or aesthetic state; consumer input received through a consumer interface of the local storage appliance related to a desired nutritional, organoleptic, or aesthetic state after local storage; and information sensed during local storage related to changes in the nutritional substance's nutritional, organoleptic, or aesthetic state.
In an embodiment of the present invention, information collected by sensors of, or sensors communicating with, storage and conditioning appliance, can collect all types of physical attribute data by sensing a nutritional substance including size, shape, temperature, color, smell, weight data, among others and can be identify the nutritional substance and its current nutritional, organoleptic, and aesthetic state by comparing the sensed data to a library of data for known nutritional substances at known nutritional, organoleptic, and aesthetic states, and further can adaptively store and condition the nutritional substance responsive to: its initial nutritional, organoleptic, or aesthetic state; consumer input received through a consumer interface of the conditioning appliance related to a desired nutritional, organoleptic, or aesthetic state after conditioning; and information sensed during conditioning related to changes in the nutritional substance's nutritional, organoleptic, or aesthetic state.
Other advantages and features will become apparent from the following description and claims. It should be understood that the description and specific examples are intended for purposes of illustration only and not intended to limit the scope of the present disclosure.
The accompanying drawings, which are incorporated in and constitute a part of this specification, exemplify the embodiments of the present invention and, together with the description, serve to explain and illustrate principles of the invention. The drawings are intended to illustrate major features of the exemplary embodiments in a diagrammatic manner. The drawings are not intended to depict every feature of actual embodiments nor relative dimensions of the depicted elements, and are not drawn to scale.
In the drawings, the same reference numbers and any acronyms identify elements or acts with the same or similar structure or functionality for ease of understanding and convenience. To easily identify the discussion of any particular element or act, the most significant digit or digits in a reference number refer to the Figure number in which that element is first introduced.
Various examples of the invention will now be described. The following description provides specific details for a thorough understanding and enabling description of these examples. One skilled in the relevant art will understand, however, that the invention may be practiced without many of these details. Likewise, one skilled in the relevant art will also understand that the invention can include many other obvious features not described in detail herein. Additionally, some well-known structures or functions may not be shown or described in detail below, so as to avoid unnecessarily obscuring the relevant description.
The terminology used below is to be interpreted in its broadest reasonable manner, even though it is being used in conjunction with a detailed description of certain specific examples of the invention. Indeed, certain terms may even be emphasized below; however, any terminology intended to be interpreted in any restricted manner will be overtly and specifically defined as such in this Detailed Description section.
The following discussion provides a brief, general description of a representative environment in which the invention can be implemented. Although not required, aspects of the invention may be described below in the general context of computer-executable instructions, such as routines executed by a general-purpose data processing device (e.g., a server computer or a personal computer). Those skilled in the relevant art will appreciate that the invention can be practiced with other communications, data processing, or computer system configurations, including: wireless devices, Internet appliances, hand-held devices (including personal digital assistants (PDAs)), wearable computers, all manner of cellular or mobile phones, multi-processor systems, microprocessor-based or programmable consumer electronics, set-top boxes, network PCs, mini-computers, mainframe computers, and the like. Indeed, the terms “controller,” “computer,” “server,” and the like are used interchangeably herein, and may refer to any of the above devices and systems.
While aspects of the invention, such as certain functions, are described as being performed exclusively on a single device, the invention can also be practiced in distributed environments where functions or modules are shared among disparate processing devices. The disparate processing devices are linked through a communications network, such as a Local Area Network (LAN), Wide Area Network (WAN), or the Internet. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.
Aspects of the invention may be stored or distributed on tangible computer-readable media, including magnetically or optically readable computer discs, hard-wired or preprogrammed chips (e.g., EEPROM semiconductor chips), nanotechnology memory, biological memory, or other data storage media. Alternatively, computer implemented instructions, data structures, screen displays, and other data related to the invention may be distributed over the Internet or over other networks (including wireless networks), on a propagated signal on a propagation medium (e.g., an electromagnetic wave(s), a sound wave, etc.) over a period of time. In some implementations, the data may be provided on any analog or digital network (packet switched, circuit switched, or other scheme).
In some instances, the interconnection between modules is the internet, allowing the modules (with, for example, WiFi capability) to access web content offered through various web servers. The network may be any type of cellular, IP-based or converged telecommunications network, including but not limited to Global System for Mobile Communications (GSM), Time Division Multiple Access (TDMA), Code Division Multiple Access (CDMA), Orthogonal Frequency Division Multiple Access (OFDM), General Packet Radio Service (GPRS), Enhanced Data GSM Environment (EDGE), Advanced Mobile Phone System (AMPS), Worldwide Interoperability for Microwave Access (WiMAX), Universal Mobile Telecommunications System (UMTS), Evolution-Data Optimized (EVDO), Long Term Evolution (LTE), Ultra Mobile Broadband (UMB), Voice over Internet Protocol (VoIP), Unlicensed Mobile Access (UMA), etc.
The modules in the systems can be understood to be integrated in some instances and in particular embodiments, only particular modules may be interconnected.
A goal of the present invention for nutritional substance industry 10 is to create, preserve, transform and trace the change in nutritional, organoleptic and/or aesthetic values of nutritional substances, collectively and individually also referred to herein as ΔN, through their creation, preservation, transformation, conditioning and consumption. Since ΔN is a measure of the change in a value of a nutritional substance, knowledge of a prior value (or state) of a nutritional substance and the ΔN value will provide knowledge of the changed value (or state) of a nutritional substance, and can further provide the ability to estimate a change in value (or state) and provide relevant food information to make relevant food decisions. The ΔN value may be represented or displayed to a consumer but not excluding as a per unit weight (e.g., ΔN per ounce, or ΔN per gram) format or value, may be displayed as a graph showing the change of the in the nutritional substance over time or in various other formats that would demonstrate a change in a ΔN. For example, a consumer may be presented but not excluding with a graph showing the historical or prospective change in the nutritional, organoleptic and/or aesthetic values of the nutritional substance, over time, cooking temperatures, or other choices or attributes. This presents a continuum to the consumer of how ΔN may change with the change in various factors including time and cooking temperature.
The ΔN value may also represent a comparison between the gold standard or average for a nutritional substance, and a particular or actual nutritional substance a consumer is considering purchasing. Accordingly, the attributes of a particular nutritional substance can be compared to the expected or optimal attributes of that type or category of nutritional substance. This allows a consumer to make more informed choices about the nutritional value of a substance a consumer is contemplating purchasing, or make informed decisions about preparation of the nutritional substance. For example, ΔN may represent a difference in the vitamin C content between on optimal orange that is picked when ripe from the vine, and an actual orange that a consumer is considering purchasing. In this example, if the consumer's orange was picked from the vine early, it may have both different surface physical characteristics that may be detectable by the sensors and methods described herein, and different vitamin C content. A database as described herein may include information regarding the physical attributes of an orange and how those factors correlate to the vitamin C content and other nutritional information. Accordingly, the systems disclosed herein may be able to determine the difference in vitamin C between a specific orange and the average vitamin C in oranges or the optimal vitamin C of, for example, an orange just picked from the vine when ripe. Accordingly, ripeness of tomatoes, water content, vitamin content, and other nutritional, organoleptic and/or aesthetic values may be compared for a specific, actual item a consumer is considering purchasing to the average or gold standard for that item. Accordingly, a consumer may then discern whether that particular item is providing at least an average or optimal nutrient, organoleptic and/or aesthetic value.
These differences may be presented in absolute value, for instance the difference in vitamin C, as a per unit weight value, as a graph comparing the present item versus an average curve for that specific item, or may be presented as a difference in nutritional content per unit price. For example, certain oranges or farmer's market produce may claim to have higher nutritional content because they are fresher or were harvested from the vines/roots closer in time to when the fruit ripened, leading to a higher nutritional content. However, these fruits tend to be higher in price, and accordingly, the system may be utilized to determine whether higher priced fruits are actually worth the higher price, and the amount of nutritional value gained per dollar difference. Accordingly, consumers could make informed choices based on quantitative data about whether and how much more nutritious more expensive fruit may be actually worth to the consumer.
In other examples, ΔN may represent the difference between the nutritional content of different subtypes of a broader category of nutritional substance. For instance, wild caught salmon is claimed to have up to 10 times greater omega three content than farm raised salmon. Accordingly, the present system could compare the nutritional content of a specific farm raised salmon to different types of wild caught salmon to determine the difference or ΔN in the omega three values. As described herein, this difference may be presented as an absolute value based on weight, an omega three difference per dollar, a per unit weight difference, or a graph indicating difference points including, average, optimum, and the current value of the fish on the graph.
Module 200 is the creation module. This can be a system, organization, or individual which creates and/or originates nutritional substances. Examples of this module include a farm which grows produce; a ranch which raises beef; an aquaculture farm for growing shrimp; a factory that synthesizes nutritional compounds; a collector of wild truffles; or a deep sea crab trawler.
Preservation module 300, described in co-pending application U.S. Ser. No. 13/888,353, titled “Preservation System for Nutritional Substances”, and incorporated in its entirety by reference herein, is a preservation system for storing, preserving and protecting the nutritional substances created by creation module 200. Once the nutritional substance has been created, generally, it will need to be packaged in some manner for its transition to other modules in the nutritional substances industry 10. While preservation module 300 is shown in a particular position in the nutritional substance industry 10, following the creation module 200, it should be understood that the preservation module 300 actually can be placed anywhere nutritional substances need to be stored and preserved during their transition from creation to consumption. For instance, preservation module 300 may be placed after transformation module 400 but prior to conditioning module 500, to store the nutritional substance either in a retail establishment or in a consumer's household. This storage may include on a shelf, in a refrigerator, or in a freezer at a consumer residence, restaurant, grocery store or other retail establishment. It is understood that a nutritional substance may experience more than one preservation event, and that such preservation events may include the local storage of the nutritional substance, such as by a consumer prior to conditioning or consumption in addition to storage along the food processing chain.
A specific aspect of the present invention in achieving its goal related to ΔN information is to provide a system that tracks ΔN information during local storage or local preservation of a nutritional substance by a consumer. It is understood that a nutritional substance may experience more than one preservation event, and that such preservation events may include any known form of local storage or local preservation of a nutritional substance prior to conditioning and/or consumption, hereinafter referred to as local storage. Such local storage may take many forms, such as the storage of refrigerated items in a refrigerator, the storage of frozen items in a freezer, the storage of wine bottles in a wine-rack, the storage of canned or dry goods in a pantry, the storage of bread in a bread drawer, the storage of fruit in a counter top tray, and any other form of local nutritional substance storage known to those skilled in the art. It is understood that the present inventions include the local storage of consumable items such as medicaments, for example, medicaments stored in a refrigerator, medicaments stored in a medicine cabinet, or medicaments stored in any other known fashion.
Local storage according to the present invention can be enabled by local storage environments according to the present invention, such as a refrigerator, drawer, cabinet, portable cooler, pantry, and any other type of storage environment, wherein the local storage environment is provided with the same capabilities as the preservation module. In addition; local storage according to the present invention can be enabled by local storage containers according to the present invention, such as packaged food and storage bags, trays, resealable storage-ware, jars, boxes, bottles, and any other type of storage environment, wherein the local storage container is provided with the same capabilities as the preservation module. In a further embodiment of the present invention, currently known traditional formats of storage environments and storage containers are enabled to provide local storage according to the present invention by being coupled with a coupon, hereinafter referred to as a local storage coupon, wherein the local storage coupon provides a traditional storage environment or traditional storage container with the same capabilities as the preservation module. The local storage coupon can be attached to, placed within, or in any known fashion coupled with, any known formats of traditional storage environments and traditional storage containers.
Transformation module 400 is a nutritional substance processing system, such as a manufacturer who processes raw materials such as grains, milk etc. and packaged food. Transformation module 400 could also be a ready-to-eat dinner manufacturer who receives the components, or ingredients, also referred to herein as component nutritional substances, for a ready-to-eat dinner from preservation module 300 and prepares them into a frozen dinner. While transformation module 400 is depicted as one module, it will be understood that nutritional substances may be transformed by a number of transformation modules 400 on their path to consumption.
Conditioning module 500 is a consumer preparation system for preparing the nutritional substance immediately before consumption by the consumer. Conditioning module 500 can be a microwave oven, a blender, a toaster, a convection oven, toaster oven, a cook, etc. It can also be systems used by commercial establishments to prepare nutritional substance for consumers such as a restaurant, an espresso maker, pizza oven, and other devices located at businesses which provide nutritional substances to consumers. Such nutritional substances could be for consumption at the business or for the consumer to take out from the business. Conditioning module 500 can also be a combination of any of these devices used to prepare nutritional substances for consumption by consumers.
Consumer module 600 collects information from the living entity which consumes the nutritional substance which has passed through the various modules from creation to consumption. The consumer can be a human being, but could also be an animal, such as pets, zoo animals and livestock, which are they themselves nutritional substances for other consumption chains. Consumers could also be plant life which consumes nutritional substances to grow.
Information module 100 receives and transmits information regarding a nutritional substance between each of the modules in the nutritional substance industry 10 including, the creation module 200, the preservation module 300, the transformation module 400, the conditioning module 500, and the consumer module 600. The nutritional substance information module 100 can be an interconnecting information transmission system which allows the transmission of information between various modules. Information module 100 contains a database, also referred to herein as a dynamic nutritional value database, where the information regarding the nutritional substance resides, particularly ΔN for the nutritional substance. Information module 100 may also contain a massive database of physical attributes of known nutritional substances at known nutritional, organoleptic, and aesthetic states, also referred to herein as nutritional substance attribute library, which can be utilized for determining the identity and current nutritional, organoleptic, and aesthetic state of a nutritional substance. Information module 100 can be connected to the other modules by a variety of communication systems, such as paper, computer networks, the internet and telecommunication systems, such as wireless telecommunication systems. In a system capable of receiving and processing real time consumer feedback and updates regarding changes in the nutritional, organoleptic, and/or aesthetic value of nutritional substances, or ΔN, consumers can even play a role in updating a dynamic nutritional value database with observed or measured information about the nutritional substances they have purchased and/or prepared for consumption, so that the information is available and useful to others in the nutritional substance supply system, such as through reports reflecting the consumer input or through modification of ΔN.
In an embodiment of the present invention, such consumer feedback and updates related to ΔN information are provided during the local storage of a nutritional substance. In a preferred embodiment, such consumer feedback and updates related to ΔN information are obtained through, or provided by, local storage environments, local storage containers, and local storage coupons according to the present invention.
In some embodiments of the present invention, consumer feedback and updates regarding ΔN information may be obtainable from appliances that include the ability to display ΔN information, including ΔN information calculated based on a sensed physical attribute of the nutritional substance including raw and packaged nutritional substances. The ΔN value may be calculated, represented, or displayed to a consumer as a per unit weight (e.g., ΔN per ounce, or ΔN per gram) format or value. The ΔN value may also represent a comparison between the gold standard or average for a particular nutritional substance, and a particular nutritional substance. Accordingly, the attributes of a particular nutritional substance can be compared to the expected or optimal attributes of that type or category of nutritional substance. This allows a consumer to make more informed choices about the nutritional value of a substance a consumer is contemplating purchasing, or make informed decisions about preparation of the nutritional substance. For instance, a scale or other weight measurement device, alone or incorporated into another appliance may be provided with the ability to detect the weight and calculate a ΔN based on a current weight of the nutritional substance and be interconnected to nutritional substance information module 100. Accordingly, a standalone scale may be provided with the ability to detect the weight of a nutritional substance, and display ΔN information to the consumer based on the current weight of the nutritional substance and provide that information to the nutritional substance information module 100. Accordingly, this information may be integrated with the other modules including conditioning module 500 and preservation module 300. Additionally, a scale or other including for example weight, smell, temperature, humidity and all sensor may be integrated into a variety of other appliances to provide the ability to display ΔN information to the consumer based on the current weight of a nutritional substance. Accordingly, a weight sensor may be integrated into a storage container, shelf, drawer, refrigerator, microwave, smartoven, oven, conditioner 570, local storage container, or any other appliances that store, condition or otherwise interact with nutritional substances. An example of an electronic scale is described in, for example, U.S. Pat. No. 6,538,215, issued on Mar. 25, 2003, titled Programmable Digital Scale, which is incorporated by reference herein in its entirety.
In this example, where nutritional substance A and nutritional substance B are milk, this ΔN information regarding the nutritional substance degradation profile of each milk could be used by the consumer in the selection and/or consumption of the milk. If the consumer has this information at time zero when selecting a milk product for purchase, the consumer could consider when the consumer plans to consume the milk, and whether that is on one occasion or multiple occasions. For example, if the consumer planned to consume the milk prior to the point when the curve represented by nutritional substance B crosses the curve represented by nutritional substance A, then the consumer should choose the milk represented by nutritional substance B because it has a higher nutritional value until it crosses the curve represented by nutritional substance A. However, if the consumer expects to consume at least some of the milk at a point in time after the time when the curve represented by nutritional substance B crosses the curve represented by nutritional substance A, then the consumer might choose to select the milk represented by the nutritional substance A, even though milk represented by nutritional substance A has a lower nutritional value than the milk represented by nutritional substance B at an earlier time. This change to a desired nutritional value in a nutritional substance over a change in a condition of the nutritional substance described in
In fact, through the new food management system of this invention the consumer can predict the degradation of nutritional value of the milk that will occur from purchases it and locally stores it in his refrigerator, thus knowing the window of time in which it will maintain an acceptable nutritional level, as indicated by time 1 to 3. For example, the consumer may utilize an application on his smartphone to store. When he goes to the supermarket, he could scan the milk's dynamic information identifier with his smartphone, and the application can communicate with the nutritional substance information module to determine a current ΔN, and predict the ΔN of the milk when stored in his refrigerator and also check the inventory of milk available at that moment in time to only buy what is needed based on real time inventory of the consumer food inventory at home. Further, the consumer may utilize such an application on his smartphone to store, or even monitor, the internal conditions of various local storage environments, local storage containers, and local storage coupons. In this way, when he goes to the supermarket, he can scan the dynamic information identifier of a wide variety of nutritional substances with his smartphone, and the application can communicate with the nutritional substance information module to determine a current ΔN, and predict the ΔN of the nutritional substance when stored in the corresponding local storage environment or local storage container. In other embodiments, the consumer may place the milk, on a scale or other weight or volume measurement device that allows the consumer to determine the current ΔN based on the weight of the milk left in the carton and the dynamic information identifier. For instance, the scale may have its own reader, or may be wirelessly connected to a smartphone that reads the identifier, and sends the data to a remote server or directly to the scale to combine with the weight data to determine the current ΔN.
In some embodiments the nutritional substance, for example turkey, may be removed from the local storage or coupon and a portion of the nutritional substance placed on a scale, or another appliance that includes a weight measurement apparatus to sense the weight of the amount nutritional substance, and display ΔN information relating to that amount. In other embodiments, the local storage may contain a weight measurement apparatus. This allows the consumer to determine ΔN information for a portion of the nutritional substance the consumer may plan on eating that is less than the entire portion stored or purchased. For example, an oven or microwave may be provided that allows a consumer to place a portion of the turkey in the oven or microwave, and a scale or other weight measurement apparatus may be included that determines the amount of turkey removed, and ΔN information for that turkey. In some embodiments, the oven or microwave may then communicate different conditioning or cooking options that result in different ΔNs based on information in the database regarding cooking or conditioning regimes. For example, conditioning the turkey at a lower temperature for longer may retain more of the amino acid chains in a non-denatured and nutritionally viable form than conditioning the turkey at the highest setting for a short time. Accordingly, these different conditioning options may be displayed to the consumer together with the resultant ΔNs for each option and the final nutritional values that would result from selecting each option. This may also include the choice for the consumer regarding the type (e.g. oven or microwave) of conditioning and the associated ΔNs that would result from those options. In addition, these ΔNs may be displayed to the consumer as graphs.
It is understood that local storage environments according to the present invention can comprise any local storage environment for a nutritional substance provided with the features enabling it to identify a dynamic information identifier on the nutritional substance, track one or more conditions related to a ΔN of the nutritional substance, communicate with the nutritional substance information module, determine a current ΔN, such as by the use of any known environmental or nutritional substance attribute sensor including a weight measurement sensor or scale, track and predict the ΔN of the nutritional substance while stored therein, and communicate information related to the ΔN to a consumer. In some embodiments, a standalone scale may be provided for removing the nutritional substance from the local storage environment and determining the weight of all or a portion of the nutritional substance in preparation for conditioning or consumption in order to determine the ΔN of the portion of nutritional substance removed from the local storage environment. Examples of such local storage environments include, but are not limited to: a pantry capable of identifying a dynamic information identifier on canned or bottled goods and tracking one or more conditions related to a ΔN of the canned or bottled goods, such as time, storage temperature, and weight; a shelf capable of identifying a dynamic information identifier on dry goods and tracking one or more conditions related to a ΔN of the dry goods, such as time, storage humidity and weight; a vegetable bin capable of identifying a dynamic information identifier on vegetables and tracking one or more conditions related to a ΔN of the vegetables, such as time, storage temperature, gaseous or volatile emissions from the vegetables, color of the vegetables, weight, and storage humidity; a drawer capable of identifying a dynamic information identifier on fruit and tracking one or more conditions related to a ΔN of the fruit, such as time, storage temperature, gaseous or volatile emissions from the fruit, weight, color of the fruit, and exposure to light; a medicine cabinet capable of identifying a dynamic information identifier on medicaments and tracking one or more conditions related to a ΔN of the medicaments, such as time, storage temperature, storage humidity, weight and exposure to light; a standalone scale capable of identifying a dynamic information identifier on a nutritional substance or optically identifying the substance itself and determining the weight of the nutritional substance in order to calculate a ΔN. These local storage environments or standalone scales may be provided with a consumer interface, such as a screen, keyboard, sound system, or any known consumer interface. Standalone scales include any freestanding electronic scale that is capable of detecting the weight of a nutritional substance and outputting that weight to the nutritional substance information module 100 or other components of the system to determine a ΔN and display that a ΔN to the consumer.
In some embodiments weight, volume or mass determination may be utilized by an optical object recognition system, in place of or in addition to a scale. For example, various products are available that are capable of using optical technology to visually identify produce and other nutritional substances, and various other items. For example, an automated optical fruit recognition system developed by Fraunhofer is capable of detecting and identifying various produce optically as described by an article titled “Automated Fruit Recognition” available at http://www.isob.fraunhofer.de/servlet/is/33328/which is incorporated by reference herein in its entirety. Accordingly, a user could then utilize their mobile phone or other devices with optical sensors to identify nutritional substances. Additionally, an optical object recognition system is disclosed in U.S. Pat. No. 6,310,964 that is described as capable of detecting identity of produce and is incorporated herein by reference in its entirety
An application on the consumer's smartphone can enable these local storage environments or standalone scales to communicate with the smartphone such that the smartphone acts as the consumer interface. The consumer interface enables the local storage environment or standalone scale to communicate to the consumer that it contains a particular nutritional substance, information related to its ΔN including a ΔN based on the weight of the nutritional substance, including current nutritional, organoleptic, and aesthetic values of the nutritional substance while stored in the local storage environment. In some embodiments, the local storage environment may be placed directly on the scale in order to determine the weight of the nutritional substance inside the local storage environment.
It is understood that local storage containers according to the present invention can comprise any local storage container for a nutritional substance provided with the features enabling it to identify a dynamic information identifier on the nutritional substance, track one or more conditions related to a ΔN of the nutritional substance, communicate with the nutritional substance information module, determine a current ΔN, such as by the use of any known environmental or nutritional substance attribute sensor, track and predict the ΔN of the nutritional substance while stored therein, and communicate information related to the ΔN to a consumer. Examples of such local storage containers include, but are not limited to: a plastic, sealable container capable of identifying a dynamic information identifier on dry goods and tracking one or more conditions related to a ΔN of the dry goods, such as time, gaseous or volatile emissions from the dry goods, weight, color of the dry goods, and storage humidity; a tray capable of identifying a dynamic information identifier on fruit and tracking one or more conditions related to a ΔN of the fruit, such as time, gaseous or volatile emissions from the fruit, color of the fruit, weight, storage temperature, and exposure to light; a resealable bag capable of identifying a dynamic information identifier on vegetables and tracking one or more conditions related to a ΔN of the vegetables, such as time, storage temperature, gaseous or volatile emissions from the vegetables, color of the vegetables, and storage humidity; a purse capable of identifying a dynamic information identifier on a medicament and tracking one or more conditions related to a ΔN of the medicament, such as time, storage temperature, storage humidity, and exposure to light; a picnic cooler capable of identifying a dynamic information identifier on potato salad and tracking one or more conditions related to a ΔN of the potato salad, such as time, gaseous or volatile emissions from the potato salad, weight, color of the potato salad, and storage temperature. These local storage containers may be provided with a consumer interface, such as a screen, keyboard, sound system, or any known consumer interface. Alternatively, an application on the consumer's smartphone can enable these local storage containers to communicate with the smartphone such that the smartphone acts as the consumer interface. The consumer interface enables the local storage container to communicate to the consumer that it contains a particular nutritional substance, information related to its ΔN, including current nutritional, organoleptic, and aesthetic values of the nutritional substance while stored in the local storage container.
It is understood that local storage coupons according to the present invention can comprise any form of tag, badge, transponder, label, or any other device, individually and collectively referred to herein as a coupon, placed in proximity to a traditional local storage environment or traditional local storage container, and capable of identifying a dynamic information identifier on a nutritional substance stored in the traditional local storage environment or traditional local storage container, tracking one or more conditions related to a ΔN of the nutritional substance, communicating with the nutritional substance information module, determining a current ΔN, such as by the use of any known environmental or nutritional substance attribute sensor, tracking and predicting the ΔN of the nutritional substance, and communicating information related to the ΔN to a consumer. Examples of such local storage coupons include, but are not limited to: a coupon placed in a plastic container with dry goods, wherein the coupon is capable of identifying a dynamic information identifier on dry goods and tracking one or more conditions related to a ΔN of the dry goods, such as time, gaseous or volatile emissions from the dry goods, color of the dry goods, weight, and storage humidity; a coupon placed on a tray for holding fruit, wherein the coupon is capable of identifying a dynamic information identifier on fruit and tracking one or more conditions related to a ΔN of the fruit, such as time, storage temperature, gaseous or volatile emissions from the fruit, color of the fruit, and exposure to light; a coupon placed within a resealable vegetable bag, wherein the coupon is capable of identifying a dynamic information identifier on vegetables and tracking one or more conditions related to a ΔN of the vegetables, such as time, storage temperature, gaseous or volatile emissions from the vegetables, weight, color of the vegetables, and storage humidity; a coupon placed within a purse, wherein the coupon is capable of identifying a dynamic information identifier on a medicament placed within the purse and tracking one or more conditions related to a ΔN of the medicament, such as time, storage temperature, storage humidity, and exposure to light; a coupon attached to the inner surface of a picnic cooler, wherein the coupon is capable of identifying a dynamic information identifier on potato salad stored in the cooler and tracking one or more conditions related to a ΔN of the potato salad, such as time, gaseous or volatile emissions from the potato salad, color of the potato salad, and storage temperature; a coupon hung in a pantry, wherein the coupon is capable of identifying a dynamic information identifier on canned or bottled goods and tracking one or more conditions related to a ΔN of the canned or bottled goods, such as time, exposure to light (in the case of bottled goods), and storage temperature; a coupon attached to a shelf, wherein the coupon is capable of identifying a dynamic information identifier on dry goods and tracking one or more conditions related to a ΔN of the dry goods, such as time, gaseous or volatile emissions from the dry goods, color of the dry goods, weight, and storage humidity; a coupon attached to an inner surface of a vegetable bin, wherein the coupon is capable of identifying a dynamic information identifier on vegetables and tracking one or more conditions related to a ΔN of the vegetables, such as time, gaseous or volatile emissions from the vegetables, weight, color of the vegetables, storage temperature, and storage humidity; a coupon placed within a drawer, wherein the coupon is capable of identifying a dynamic information identifier on fruit and tracking one or more conditions related to a ΔN of the fruit, such as time, gaseous or volatile emissions from the fruit, color of the fruit, storage temperature, and exposure to light; a coupon attached to the inner surface of a medicine cabinet, wherein the coupon is capable of identifying a dynamic information identifier on medicaments and track one or more conditions related to a ΔN of the medicaments, such as time, storage temperature, storage humidity, and exposure to light.
In
Preservation module 300 includes packers and shippers of nutritional substances. The tracking of changes in nutritional, organoleptic, and/or aesthetic values, or a ΔN, during the preservation period within preservation module 300 allows for dynamic expiration dates for nutritional substances. For example, expiration dates for dairy products are currently based generally only on time using assumptions regarding minimal conditions at which dairy products are maintained. This extrapolated expiration date is based on a worst-case scenario for when the product becomes unsafe to consume during the preservation period. In reality, the degradation of dairy products may be significantly less than this worst-case. If preservation module 300 could measure or derive the actual degradation information such as ΔN, an actual expiration date, referred to herein as a dynamic expiration date, can be determined dynamically, and could be significantly later in time than an extrapolated expiration date. This would allow the nutritional substance supply system to dispose of fewer products due to expiration dates. This ability to dynamically generate expiration dates for nutritional substances is of particular significance when nutritional substances contain few or no preservatives. Such products are highly valued throughout nutritional substance supply system 10, including consumers who are willing to pay a premium for nutritional substances with few or no preservatives.
It should be noted that a dynamic expiration (good for consumption) date need not be indicated numerically (i.e., as a numerical date) but could be indicated symbolically as by the use of colors—such as green, yellow and red employed on semaphores—or other designations. In those instances, the dynamic expiration date would not be interpreted literally but, rather, as a dynamically-determined advisory date. In practice a dynamic expiration date will be provided for at least one component of a single or multi-component nutritional substance. For multi-component nutritional substances, the dynamic expiration date could be interpreted as a “best” date for consumption for particular components.
By law, in many localities, food processors such as those in transformation module 400 are required to provide nutritional substance information regarding their products. Often, this information takes the form of a nutritional table applied to the packaging of the nutritional substance. Currently, the information in this nutritional table is based on averages or minimums for their typical product. Using the nutritional substance information from information module 100 provided by creation module 200, preservation module 300, and/or information from the transformation of the nutritional substance by transformation module 400, and consumer feedback and updates related to ΔN, preferably obtained through or provided by local storage environments, appliances, scales and other weight measurement devices, local storage containers, and local storage coupons according to the present invention, the food processor could include a dynamically generated nutritional value table, also referred to herein as a dynamic nutritional value table, for the actual nutritional substance being supplied to a consumer and further being locally stored by the consumer. The information in such a dynamic nutritional value table could be used by conditioning module 500 in the preparation of the nutritional substance, and/or used by consumption module 600, so as to allow the ultimate consumer the ability to select the most desirable nutritional substance which meets their needs, and/or to track information regarding nutritional substances consumed.
Information about changes in nutritional, organoleptic, and/or aesthetic values of nutritional substances, or ΔN, is particularly useful in the conditioning module 500 of the present invention, as it allows knowing, or estimating, the pre-conditioning state of the nutritional, organoleptic, and/or aesthetic values of the nutritional substance, including the changes in nutritional, organoleptic, and/or aesthetic values occurring during local storage of the nutritional substance, and further allows for estimation of a ΔN associated with proposed conditioning parameters. The conditioning module 500 can therefore create conditioning parameters, such as by modifying existing or baseline conditioning parameters, to deliver desired nutritional, organoleptic, and/or aesthetic values after conditioning. The pre-conditioning state of the nutritional, organoleptic, and/or aesthetic value of a nutritional substance is not tracked or provided to the consumer by existing conditioners, nor is the ΔN expected from a proposed conditioning tracked or provided to the consumer either before or after conditioning. However, using information provided by information module 100 from creation module 200, preservation module 300, transformation module 400, and consumer feedback and updates related to ΔN, preferably obtained through or provided by local storage environments, local storage containers, and local storage coupons according to the present invention, and/or information measured or generated by conditioning module 500 prior to conditioning, and/or consumer input provided through the conditioning module 500 prior to conditioning, conditioning module 500 could provide the consumer with adaptively developed conditioning parameters responsive to the current ΔN of the nutritional substance and the consumer's input, and the estimated or expected ΔN that will result from the adaptive conditioning parameters, and the corresponding residual nutritional, organoleptic, or aesthetic value.
In a further embodiment, the conditioner is provided with various sensors which can be used to sense attributes of a nutritional substance prior to conditioning, wherein the sensed attribute values can be used in determining a current ΔN or corresponding residual nutritional, organoleptic, or aesthetic value of the nutritional substance. In yet a further embodiment, some or all of the various sensors can be used to sense attributes of the nutritional substance during conditioning, so as to determine intra-conditioning ΔN information regarding the nutritional substance during its conditioning. Such intra-conditioning ΔN information provides closed loop feedback to the conditioner's controller regarding the adaptive conditioning parameters being implemented. If the closed-loop feedback indicates that the adaptive conditioning parameters will achieve desired residual nutritional, organoleptic, and aesthetic values, the conditioner's controller will continue to implement the adaptive conditioning parameters. However, if the closed-loop feedback indicates that the adaptive conditioning parameters will not achieve desired residual nutritional, organoleptic, and aesthetic values, the conditioner's controller will modify the adaptive conditioning parameters and implement the modified adaptive conditioning parameters. In the same fashion, the sensors can continue to provide closed-loop feedback to indicate that currently implemented conditioning parameters will, or will not, achieve desired residual nutritional, organoleptic, and aesthetic values, and accordingly, the conditioner may continue to implement the current conditioning parameters, or modify the current conditioning parameters and implement the modified parameters.
An important benefit provided by local storage environments, local storage containers, and local storage coupons of the present invention is that consumer feedback and updates related to ΔN, such as observed or measured information of, or related to, a ΔN during local storage of the nutritional substance is obtained through, or provided by, the local storage environments, containers, and coupons. In this way consumer feedback and updates related to a ΔN during local storage of a nutritional substance can play a role in updating the dynamic nutritional value information about the nutritional substances consumers have purchased and placed in local storage, such as through modification of ΔN. Such information regarding the change to nutritional, organoleptic and/or aesthetic value of the nutritional substance, or ΔN, could be provided not only to a consumer through the consumption module 600 and conditioning module 500, but could also be provided to information module 100 for use by creation module 200, preservation module 300, transformation module 400, so as to track, and possibly improve nutritional substances throughout the entire nutritional substance supply system 10.
In a further embodiment, the local storage environments, local storage containers, scales, and local storage coupons are provided with various nutritional substance attribute sensors which can be used to sense attributes of a nutritional substance prior to local storage, wherein the sensed attribute data can be used in determining the nutritional substance content and an initial nutritional, organoleptic, or aesthetic value of the nutritional substance, such as when the nutritional substance is placed into the local storage environment or container. In yet a further embodiment, some or all of the various nutritional substance attribute sensors can be used to sense attributes of the nutritional substance during local storage, so as to determine intra-local storage ΔN information regarding the nutritional substance during its local storage. In a case wherein the local storage environment or container is provided with a controller which can modify the storage parameters, so as to modify the storage conditions, of the local storage environment or container, such intra-local storage ΔN information can provide closed loop feedback to the local storage controller regarding the currently implemented storage parameters. In this way, if the closed-loop feedback indicates that the currently implemented storage parameters will achieve desired rates of change in residual nutritional, organoleptic, and aesthetic values, the controller will continue to implement the currently implemented storage parameters. Such desired rates of change in residual nutritional, organoleptic, and aesthetic values may be predetermined, such as by the nutritional substance provider, may be determined by consumer input, such as provided through a consumer interface of the local storage environment, container, or coupon, or may be established in any known fashion. If the closed-loop feedback indicates that the currently implemented parameters will not achieve desired rates of change in residual nutritional, organoleptic, and aesthetic values, the controller will adaptively modify the storage parameters and implement the adaptively modified storage parameters. In the same fashion, the sensors can continue to provide closed-loop feedback to the controller regarding any current storage parameters, and depending upon whether the current storage parameters will, or will not, achieve desired rates of change in residual nutritional, organoleptic, and aesthetic values, the controller may continue to implement the current storage parameters, or adaptively modify the current storage parameters and implement the adaptively modified storage parameters.
In the embodiment above, the local storage environments, containers, scales, and coupons are provided with the ability to communicate the sensed attribute data with an alternate database that facilitates identification of the nutritional substance content and current nutritional, organoleptic, or aesthetic value. The alternate database consists of a massive library of nutritional substance attribute data, related to the visual appearance, taste, smell, texture, touch, chemical composition and any other known physical attributes, referenced to corresponding nutritional, organoleptic, and aesthetic states of known nutritional substances, and is herein referred to as the nutritional substance attribute library. The various nutritional substance attribute sensors may include, but are not limited to, sensors capable of measuring and collecting data regarding visual appearance, taste, smell, volatiles, texture, touch, sound, chemical composition, temperature, weight, volume, density, hardness, viscosity, surface tension, and any other known physical attribute of the nutritional substance. These may include, but are not limited to, optical sensors, spectrometers, biosensors, laser sensors, cameras, electric noses, microphones, olfactory sensors, surface topography measurement equipment, three dimensional measuring equipment, chemical assays, hardness measuring equipment, ultrasound equipment, impedance detectors, temperature measuring equipment, weight measurement equipment including scales, and any known sensor capable of providing data regarding a physical attribute of a nutritional substance. It is understood that such local storage environments, containers, and coupons may also be provided with a nutritional substance reader, such that they can interact with nutritional substances provided with, and without, dynamic information identifiers. The nutritional substance attribute library may be separate from a nutritional substance industry database, or is preferably part of the nutritional substance industry database. Further, the nutritional substance attribute library may be separate from a nutritional substance database, or may exist within the nutritional substance database. In a preferred embodiment, the nutritional substance attribute library coexists with the nutritional substance database, a recipe database, and a consumer database, within the nutritional substance industry database.
The information regarding nutritional substances provided by information module 100 to consumption module 600 can replace or complement existing information sources such as recipe books, food databases like www.epicurious.com, and Epicurious apps. Through the use of specific information regarding a nutritional substance from information module 100, consumers can use consumption module 600 to select nutritional substances according to nutritional, organoleptic, and/or aesthetic values. This will further allow consumers to make informed decisions regarding nutritional substance additives, preservatives, genetic modifications, origins, traceability, and other nutritional substance attributes that may also be tracked through the information module 100. This information can be provided by consumption module 600 through personal computers, laptop computers, tablet computers, and/or smartphones. Software running on these devices can include dedicated computer programs, modules within general programs, and/or smartphone apps. An example of such a smartphone app regarding nutritional substances is the iOS ShopNoGMO from the Institute for Responsible Technology. This iPhone app allows consumers access to information regarding non-genetically modified organisms they may select. Additionally, consumption module 600 may provide information for the consumer to operate conditioning module 500 in such a manner as to optimize nutritional, organoleptic, and/or aesthetic values of a nutritional substance and/or component nutritional substances thereof, according to the consumer's needs or preference or according to target values established by the provider of the nutritional substance, such as the transformer, and/or minimize degradation of, preserve, or improve nutritional, organoleptic, and/or aesthetic value of a nutritional substance and/or component nutritional substances thereof.
Through the use of nutritional substance information available from information module 100 nutritional substance supply system 10 can track nutritional, organoleptic, and/or aesthetic value. Using this information, nutritional substances travelling through nutritional substance supply system 10 can be dynamically valued and priced according to nutritional, organoleptic, and/or aesthetic values. For example, nutritional substances with longer dynamic expiration dates (longer shelf life) may be more highly valued than nutritional substances with shorter expiration dates. Additionally, nutritional substances with higher nutritional, organoleptic, and/or aesthetic values may be more highly valued, not just by the consumer, but also by each entity within nutritional substance supply system 10. This is because each entity will want to start with a nutritional substance with higher nutritional, organoleptic, and/or aesthetic value before it performs its function and passes the nutritional substance along to the next entity. Therefore, both the starting nutritional, organoleptic, and/or aesthetic value and the ΔN associated with those values are important factors in determining or estimating an actual, or residual, nutritional, organoleptic, and/or aesthetic value of a nutritional substance, and accordingly are important factors in establishing dynamically valued and priced nutritional substances.
The use of appliances, local storage environments, local storage containers, scales, and local storage coupons according to the present invention makes information related to a ΔN of a locally stored nutritional substance available to information module 100, so that information available from information module 100 can enable a consumer, or any entity inside or outside the nutritional substance supply system 10, to track nutritional, organoleptic, and/or aesthetic value of the nutritional substance during its local storage or prior to consumption or conditioning. It is understood that such local storage includes local storage by any entity that prepares or otherwise conditions nutritional substances for consumption by a consumer, and could include the consumer's residence, a restaurant, a hospital, a sports arena, a vending machine, or any other known entity providing nutritional substances for consumption.
Additionally, the use of appliances that can display or calculate current ΔN information based on sensed attributes, including weight, allowing a consumer to determine the current ΔN of a portion of the stored nutritional substance prior to conditioning or consumption. This ability may be incorporated into any appliance, or may be as a standalone scale or weight measurement apparatus, with a dynamic information identifier reader, or the ability wirelessly link with a consumer's smartphone. Additionally, the weight measurement device or sensors may be incorporated into ovens, smartovens, microwaves, refrigerators, or any other appliance.
During the period of implementation of the present inventions, there will be nutritional substances being marketed including those benefiting from the tracking of dynamic nutritional information such as ΔN, also referred to herein as information-enabled nutritional substances, and nutritional substances which do not benefit from the tracking of dynamic nutritional information such as ΔN, which are not information enabled and are referred to herein as static nutritional substances. Information-enabled nutritional substances, (e.g., packaging, processing, logistics may be information enabled) would be available in virtual internet marketplaces, as well as traditional marketplaces. Because of information provided by information-enabled nutritional substances, entities within the nutritional substance supply system 10, including consumers, would be able to review and select information-enabled nutritional substances for purchase. It should be expected that, initially, the information-enabled nutritional substances would enjoy a higher market value and price than static nutritional substances. However, as information-enabled nutritional substances become more the norm, the cost savings from less waste due to degradation of information-enabled nutritional substances could lead to their price actually becoming less than static nutritional substances.
For example, the producer of a ready-to-eat dinner would prefer to use corn of a high nutritional, organoleptic, and/or aesthetic value in the production of its product, the ready-to-eat dinner, so as to produce a premium product of high nutritional, organoleptic, and/or aesthetic value. Depending upon the levels of the nutritional, organoleptic, and/or aesthetic values, the ready-to-eat dinner producer may be able to charge a premium price and/or differentiate its product from that of other producers. When selecting the corn to be used in the ready-to-eat dinner, the producer will seek corn of high nutritional, organoleptic, and/or aesthetic value from preservation module 300 that meets its requirements for nutritional, organoleptic, and/or aesthetic value. The packager/shipper of preservation module 300 would also be able to charge a premium for corn which has high nutritional, organoleptic, and/or aesthetic values. And finally, the packager/shipper of preservation module 300 will select corn of high nutritional, organoleptic, and/or aesthetic value from the grower of creation module 200, who will also be able to charge a premium for corn of high nutritional, organoleptic, and/or aesthetic values.
Further, the consumer of the ready-to-eat dinner may want to, or in the case of a restaurant, cafeteria, or other regulated eating establishment, may be required to, track the nutritional, organoleptic, and/or aesthetic value of the corn during the local storage of the ready-to-eat dinner. The local storage environments, local storage containers, and local storage coupons of the present invention enable such tracking by making information related to ΔN during local storage available to information module 100 for updating the dynamic nutritional, organoleptic, and aesthetic values of a nutritional substance.
The change to nutritional, organoleptic, and/or aesthetic value for a nutritional substance, or ΔN, tracked through nutritional substance supply system 10 through nutritional substance information from information module 100 can be preferably determined from measured information. However, some or all such nutritional substance ΔN information may be derived through measurements of environmental conditions of the nutritional substance as it travelled through nutritional substance supply system 10. Additionally, some or all of the nutritional substance ΔN information can be derived from ΔN data of other nutritional substances which have travelled through nutritional substance supply system 10. Nutritional substance ΔN information can also be derived from laboratory experiments performed on other nutritional substances, which may approximate conditions and/or processes to which the actual nutritional substance has been exposed. This information may be utilized to estimate ΔN for a present nutritional substance 520 prior to conditioning by determine the average ΔN for the nutritional substance 520 for a given conditioning protocol or for the passage of a certain amount of time. In some embodiments, this may include determining an average ΔN per unit weight of the nutritional substance 520. Then, when a consumer 540 or other end user selects a nutritional substance 520 for conditioning, the weight of the nutritional substance 520 may be detected or provided by a dynamic nutritional identifier, and the ΔN per unit weight may be multiplied by the sensed or provided weight of the nutritional substance 520. That way a total ΔN may be output that is assumed to result to the present nutritional substance 520 based on selected conditioning protocol. In other embodiments, the nutritional substance 520 testing will be with a pre-packaged food that is the same weight or mass in every package and so the ΔN will not vary by weight. In still other embodiments, the ΔN may be determined for a range of conditioning protocols, but not every possible conditioning (or transformation) protocol for a given nutritional substance 520. Accordingly, if the end user is able to select a range of preferences, the system may have to extrapolate between two or more prior data points to determine an estimated ΔN for the specific conditioning protocol selected for the nutritional substance 520. For example, if a consumer decides to cook 16 ounces of salmon, and decides to have it medium well, the oven may be set at 12 minutes at 350 degrees. However, the system may only have experimental delta N for 12 ounces of salmon at 310 degrees and 18 ounces of salmon at 360 degrees. Accordingly, the system may either provide a curve or correlation line between tested data points and associated ΔN s to determine the present ΔN for the specific conditioning or transformation protocol selected for the piece of salmon. In other embodiments, other suitable methods may be utilized using experimental data to estimate ΔN.
The prior ΔN values may be determined in a variety of ways including: experimentation with specific conditioning protocols 610 on nutritional substances 520. This would allow one to provide more accurate and specific measures of ΔN values for specific conditioning protocols 610. Additionally, if data for ΔN is recorded for variations of the conditioning protocol 610 then the system may be able to more easily extrapolate ΔN values to determine a modified ΔN value for a conditioning protocol 610 with only slight modifications (i.e. certain times extended or cycles removed or added) as described above.
In other embodiments, prior ΔN values for similar nutritional substances 520 may be derived from the USDA's website, where tables of changes in nutritional content are presented. The USDA's values for changes in nutritional content are generally based on one recipe for each type of conditioning. For example, an example table from the USDA website is shown in
As further examples,
The USDA's generic protocols 610 are defined by the USDA and used to perform experiments to derive the values they publish for nutrient retention. The USDA accordingly utilizes a basic protocol for each of the baking, broiling, and other conditioning types mentioned, and tests various examples of the broad nutritional substance 520 category, (e.g. cheese) in order to determine an average for retention of certain nutrients. To calculate these data points, the USDA utilized equation (1) to calculate the percent retention:
% TR=(Nc*Gc)/(Nr*Gr)*100 (1)
where TR=true retention, Nc=nutrient content per gram of cooked food, Gc=grams of cooked food, Nr=nutrient content per g of raw food, and Gr=grams of food before cooking. This equation is then utilized by the USDA as detailed on its website, for example at http://www.ars.usda.gov/SP2UserFiles/Place/12354500/Data/SR26/sr26 doc.pdf as part of the National Nutrient Database for Standard Reference. Accordingly, these data points can be used as rough estimates for the ΔN experienced by specific nutritional substances 520 and specific conditioning protocols 610. In this embodiment, each specific conditioning protocol 610 that is stored in the database of the system would have to be linked or referenced to one of the basic conditioning protocols 610 for which the USDA has data. Accordingly, a prospective conditioning protocol 610 would be assumed to result in a ΔN associated with the general recipe it is linked to.
In further embodiments, to true retention, the percentage of weight retained after conditioning may also be calculated as yield percentage based on the following equation 2 from the USDA:
Yield (%)=100×(Wch/Wcr) (2)
where yield is the percentage of weight retained after conditioning, Wch is the weight of the cooked sample while hot, and Wcr is the weight of the raw sample to be cooked. Accordingly, this is one example of the change in weight can be estimated for a specific nutritional substance 520 based on an average for that nutritional substance 520 by multiplying the average percent yield by the weight of the specific nutritional substance 520. For example, if a nutritional substance 520 is provided with a dynamic nutrition identifier that includes the weight of the substance 520, the weight of the substance may be multiplied by the percent yield calculated for a specific conditioning protocol 610 to determine an estimate for the reduction in weight that the nutritional substance 520 will experience after cooking. Accordingly, this value may be utilized in conjunction with the moisture/fat change values of equation 3 from the USDA to determine overall reduction in nutritional and other ΔN values:
Moisture/Fat Change (%)=100×((Nc*Ec)−(Nr*Er))/Wcr (3)
where Nc is the nutrient content of the cooked sample (lean or edible portion) (i.e. fat or moisture), Nr is the nutrient content of the raw sample (lean or edible portion) (i.e. fat or moisture), Ec is the edible portion of the cooked sample, Er is the edible portion of the raw sample, Wcr is the weight of the cooked sample while hot, and Wcr is the weight of the raw sample to be cooked. Accordingly, the moisture/fat change % can be determined through experimentation and can be used to determine an estimated moisture and/or fat reduction for a particular nutritional substance 520 based on a particular conditioning protocol 610. These equations are disclosed by the USDA and utilized to determine their experimental based averages for changes in nutritional values. Similar equations may be utilized to determine precise changes for specific nutritional substances (e.g. 3 year aged cheddar v. cheese) based specific conditioning protocols (bake for 3 minutes then steam v. bake). Sample data in connection with cooking yields is shown in
Once these values are determined, these values could be displayed alongside choices for conditioning to allow a consumer to determine the optimal conditioning protocol based on their nutritional and taste preferences. As in the case with the USDA data, this specific experimental data may be referenced to the conditioning protocols in a database or using another system in order for the ΔN values to be properly accessed or associated with specific conditioning protocols 610 available to a user on a specific conditioner. In some embodiments, as disclosed herein, these estimated ΔN values may be utilized to derive conditioning protocols 610 to match to maximize or find local maximums for ΔN values based on indicated preferences for maximizing certain nutrients or taste preferences.
For example, laboratory experiments can be performed on bananas to determine effect on or change in nutritional, organoleptic, and/or aesthetic value, or ΔN, for a variety of environmental conditions bananas may be exposed to during packaging and shipment in preservation module 300. Using this experimental data, tables and/or algorithms could be developed which would predict the level of change of nutritional, organoleptic, and/or aesthetic values, or ΔN, for a particular banana based upon information collected regarding the environmental conditions to which the banana was exposed during its time in preservation module 300. While the ultimate goal for nutritional substance supply system 10 would be the actual measurement of nutritional, organoleptic, and/or aesthetic values to determine ΔN, use of derived nutritional, organoleptic, and/or aesthetic values from experimental data to determine ΔN would allow improved logistics planning because it provides the ability to prospectively estimate changes to nutritional, organoleptic, and/or aesthetic values, or ΔN, and because it allows more accurate tracking of changes to nutritional, organoleptic, and/or aesthetic values, or ΔN, while technology and systems are put in place to allow actual measurement.
For example, laboratory experiments can be performed on bananas to determine effect on or change in nutritional, organoleptic, and/or aesthetic value, or ΔN, for a variety of environmental conditions bananas may be exposed to during packaging and shipment in preservation module 300. Using this experimental data, tables and/or algorithms could be developed which would predict the level of change of nutritional, organoleptic, and/or aesthetic values, or ΔN, for a particular banana based upon information collected regarding the environmental conditions to which the banana was exposed during its time in preservation module 300. While the ultimate goal for nutritional substance supply system 10 would be the actual measurement of nutritional, organoleptic, and/or aesthetic values to determine ΔN, use of derived nutritional, organoleptic, and/or aesthetic values from experimental data to determine ΔN would allow improved logistics planning because it provides the ability to prospectively estimate changes to nutritional, organoleptic, and/or aesthetic values, or ΔN, and because it allows more accurate tracking of changes to nutritional, organoleptic, and/or aesthetic values, or ΔN, while technology and systems are put in place to allow actual measurement.
For example, sweet corn that arrives for processing by transformer 410 has information associated with it, including the corn variety, where it was planted, when it was planted, when it was picked, the soil it was grown in, the water used for irrigation, and the fertilizers and pesticides that were used during its growth. There may also be information on nutritional and/or organoleptic and/or aesthetic values of the corn when it was preserved for shipment. This information may be stored in the labeling of the corn. However, it may be stored in a database maintained by the grower, shipper, or the nutritional substances industry, also referred to herein as a dynamic nutritional value database. Such information could be accessed by means of telecommunications systems, such as wireless telecommunication systems.
Additionally, the corn may have information associated with it regarding how it was preserved for shipment from the farm to transformation module 400. Such information may include historical information on the environment exterior the container it was shipped in, internal conditions of the container and actual information about the corn during the shipment. Additionally, if the preservation system acted upon such information in preserving the corn, information about the preservation measures may also be available. Such information may be stored in the preservation system. However, it may be stored in a database maintained by the grower, shipper, or the nutritional substances industry, also referred to herein as a dynamic nutritional value database. Such information could be accessed by means of telecommunications systems, such as wireless telecommunication systems.
In the example where the nutritional substance 420 is corn, transformer 410 removes the husk and the silk from the corn. It then separates the kernels from the cob, washes the kernels, and cooks them. Finally, transformer 410 packages the cooked corn in a can and labels the can. The label on the can may contain all the information provided to information transmission module 430. Preferably, this information is referenced by a dynamic encode or tag, herein referred to as a dynamic information identifier, which identifies the information regarding the corn in the can that is being transmitted by information transmission module 430.
In practice, information transmission module 430 would receive the information regarding the nutritional substance 420 from a database that is being used to track the corn during its journey from the farm to the consumer. When transformer 410 transforms nutritional substance 420, information transmission module 430 retrieves the appropriate information from the database and transmits it to another database. Alternatively, the information retrieved by transmission module 430 would be transmitted back to the original database, noting that the transformation had occurred. Preferably, the information regarding the corn retrieved by transmission module 430 would simply be appended with the information that the transformation had occurred. Such databases are individually and collectively referred to herein as a dynamic nutritional value database.
If the nutritional substance 420 can no longer be tracked by the reference information or dynamic information identifier that accompanied the nutritional substance from the creator, then new reference information or a new dynamic information identifier may be created. For example, if the corn is combined with lima beans in the transformer 410, to make succotash, then the information for each may be combined and assigned a new reference number or a new dynamic information identifier. Preferably, a new entry is created in the dynamic nutritional value database, with references to the information related to the corn and the information related to the lima beans.
For example, sweet corn that arrives for processing by transformer 410 has information associated with it, including the corn variety, where it was planted, when it was planted, when it was picked, the soil it was grown in, the water used for irrigation, and the fertilizers and pesticides that were used during its growth. There may also be information on nutritional, organoleptic and aesthetic values of the corn when it was preserved for shipment. This information may be stored in the labeling of the corn. However, it may be stored in a dynamic nutritional value database maintained by the grower, shipper, or the nutritional substances industry. Such information could be accessed by telecommunications systems, such as wireless telecommunication systems.
Additionally, the corn may have information associated with it regarding how it was preserved for shipment from the farm to transformation module 400. Such information may include historical information on the environment exterior the container it was shipped in, internal conditions of the container and actual information about the corn during the shipment. Additionally, if the preservation system acted upon such information in preserving the corn, information about the preservation measures may also be available. Such information may be stored in the preservation system. However, it may be stored in a dynamic nutritional value database maintained by the grower, shipper, or the nutritional substances industry. Such information could be accessed by means of telecommunications systems, such as wireless telecommunication systems.
In the example where the nutritional substance 420 is corn, transformer 410 removes the husk and the silk from the corn. It then separates the kernels from the cob, washes the kernels, and cooks them. Finally, transformer 410 packages the cooked corn in a can and labels the can.
During this transformation of the nutritional substance 420 by transformer 410, information about the transformation can be captured by transformer 410 and sent to information transmission module 430. This information can include how the transformation was accomplished; including information on the transformer used, the recipe implemented by transformer 410, and the settings for transformer 410 when the transformation occurred. Additionally, any information created during the transformation by transformer 410 can be sent to the information transmission module 430. This could include measured information, such as the actual cooking temperature, length of time of each of the steps, or weight or volume measurements. Additionally, this information could include measured aesthetic, organoleptic and nutritional values.
The label on the can may contain all the information provided to information transmission module 430. Preferably, this information is referenced by a dynamic information identifier which identifies the information regarding the corn in the can that is being transmitted by information transmission module 430.
In practice, information transmission module 430 would receive the information regarding the nutritional substance 420 from a database that is being used to track the corn during its journey from the farm to the consumer. When transformer 410 transforms nutritional substance 420, information transmission module 430 retrieves the appropriate information from the database, appends it with the information from transformer 410 regarding the transformation, and transmits it to another database. Alternatively, such information would be transmitted back to the original database, including the transformation information. Preferably, the information regarding the corn would simply be appended with the information from transformer 410 about the transformation. Such databases are individually and collectively referred to herein as a dynamic nutritional value database
If the nutritional substance 420 can no longer be tracked by the reference information or a dynamic information identifier that accompanied the nutritional substance from the creator, then new reference information or a new dynamic information identifier may be created. For example, if the corn is combined with lima beans in the transformer 410, to make succotash, then the information for each may be combined and assigned a new reference number or a new dynamic information identifier. Preferably, a new entry is created in the dynamic nutritional value database, with references to the information related to the corn and the information related to the lima beans.
For example, sweet corn that arrives for processing by transformer 410 has origination information associated with it, including the corn variety, where it was planted, when it was planted, when it was picked, the soil it was grown in, the water used for irrigation, and the fertilizers and pesticides that were used during its growth. There may also be source information on nutritional, organoleptic and aesthetic values of the corn when it was preserved for shipment. This information may be stored in the labeling of the corn. However, it may be stored in a dynamic nutritional value database maintained by the grower, shipper, or the nutritional substances industry. Such information could be accessed by telecommunications systems, such as wireless telecommunication systems.
Additionally, the corn may have information associated with it regarding how it was preserved for shipment from the farm to transformation module 400. Such information may include historical information on the environment exterior the container it was shipped in, internal conditions of the container and actual information about the corn during the shipment. Additionally, if the preservation system acted upon such information in preserving the corn, information about the preservation measures may also be available. Such information may be stored in the preservation system. However, it may be stored in a database maintained by the grower, shipper, or the nutritional substances industry, also referred to herein as a dynamic nutritional value database. Such information could be accessed by means of telecommunications systems, such as wireless telecommunication systems.
Any, or all, of this information can be provided to transformer 410 by information transmission module 430. Transformer 410 can dynamically modify its transformation of nutritional substance 420 in response to such information to adaptively transform the nutritional substance in order to preserver or improve or minimize the degradation of the nutritional, organoleptic and/or aesthetic values of nutritional substance 420.
In the example where the nutritional substance 420 is corn, transformer 410 removes the husk and the silk from the corn. It then separates the kernels from the cob, washes the kernels, and cooks them. In response to the information provided by information transmission module 430, transformer can dynamically modify the cooking temperature and time. For example, if transformer 410 receives information that indicates that the corn is low in certain desirable nutrients, it might lower the cooking temperature and time to preserve those nutrients, thus achieving a more desirable nutritional value related to those specific nutrients in the transformed nutritional substance. However, if transformer 410 receives information that indicates that the corn is high in tough starches, it might raise the cooking temperature and time to soften the corn, thus achieving a more desirable organoleptic value related to the texture of the transformed nutritional substance. Finally, transformer 410 packages the cooked corn in a can and labels the can.
Additionally, transformer 410 can modify its transformation of the nutritional substance in response to measured attributes of the particular nutritional substance 420 being transformed. For example, transformer 410 can measure the color of the corn to be processed, and in response make adjustment to the transformation to preserve or enhance the color of the transformed corn, thus achieving a more desirable aesthetic value related to the appearance of the transformed nutritional substance.
During this adaptive transformation of the nutritional substance 420 by transformer 410, information about the transformation can be captured by transformer 410 and sent to information transmission module 430. This information can include how the transformation was accomplished; including information on any dynamic transformation modifications in response to information about the particular nutritional substance to be transformed, the recipe implemented by transformer 410, and the settings for transformer 410 when the transformation occurred. Additionally, any information created during the transformation by transformer 410 can be sent to the information transmission module 430. This could include measured information, such as the actual cooking temperature, length of time of each of the steps. Additionally, this information could include measured organoleptic, aesthetic, and nutritional information, weight, and physical dimension.
The label on the packaging may contain all the information provided to information transmission module 430. Preferably, this information is referenced by a dynamic information identifier which identifies the information regarding the nutritional substance in the packaging that is being transmitted by information transmission module 430.
In practice, information transmission module 430 would utilize a dynamic information identifier provided with the nutritional substance to retrieve and receive the information regarding the nutritional substance 420 from a database that is being used to track the corn during its journey from the farm to the consumer. When transformer 410 transforms nutritional substance 420, information transmission module 430 retrieves the appropriate information from the database, appends it with the information from transformer 410 regarding the transformation, and transmits it to another database. Alternatively, such information would be transmitted back to the original database, including the transformation information. Preferably, the information regarding the corn would simply be appended with the information from transformer 410 about the transformation. Such databases are individually and collectively referred to herein as a dynamic nutritional value database.
If the nutritional substance 420 can no longer be tracked by the reference information or dynamic information identifier that accompanied the nutritional substance from the creator, then new reference information or a new dynamic information identifier may be created. For example, if the corn is combined with lima beans in the transformer 410, to make succotash, then the information for each may be combined and assigned a new reference number or a new dynamic information identifier. Preferably, a new entry is created in the dynamic nutritional value database, with references to the information related to the corn and the information related to the lima beans.
Although
In an embodiment of the present invention, conditioner 570 is provided without controller 530, however it is provided in a format to be compatible with controller 530. Such a conditioner is also referred to herein as an information capable conditioner. In contrast, traditional conditioners, also referred to herein as dumb conditioners, are not information capable, are not compatible with controller 530, and accordingly will always be dumb conditioners. As information enabled nutritional substances and conditioning systems according to the present invention are increasingly available, dumb conditioners will become increasingly obsolete.
Information capable conditioners may be provided in a variety of configurations known to those skilled in the art, and the examples offered herein are for purposes of illustration and not intended to be limiting in any way. In one example of an information capable conditioner, it is provided with traditional functionality, that is, it will interact with nutritional substances in a traditional fashion, whether the nutritional substance is information enabled or not. However, the information capable conditioner is compatible with separately available controller 530, such that at any time during or after the manufacture and sale of the information capable conditioner, controller 530 may be coupled with the information capable conditioner to enable the full functionality and benefit of conditioner module 500. In some embodiments, the controller 530 may be coupled with multiple conditioners 570. Information capable conditioners provide appliance manufacturers and consumers great flexibility, and will not become obsolete like dumb conditioners. In some embodiments, the information capable conditioner is referred to as a dynamic appliance. In some instances the dynamic appliance has the full functionality and benefit of controller 530 (sometimes referred to as an appliance controller) built into, collocated, or coupled to the dynamic appliance.
The coupling of controller 530 to the information capable conditioner or conditioners may take any physical and/or communication format known to those skilled in the art. These may include, but are not limited to: an information capable conditioner(s) provided with Bluetooth, or other wireless near-field communication capability, to communicate with a communication-compatible controller 530 which may be any of a completely separate unit, an externally attachable unit, and an internally placed unit; an information capable conditioner provided with a USB port, or other electronic communication capability, to communicate with a communication-compatible controller 530 which may be any of a completely separate unit, an externally attachable unit, and an internally placed unit; an information capable conditioner provided with a fiber optic port, or other optical communication capability, to communicate with a communication-compatible controller 530 which may be any of a completely separate unit, an externally attachable unit, and an internally placed unit; or an information capable conditioner provided with WiFi, or other wireless communication capability, to communicate with a WiFi compatible controller 530 which may be any of a completely separate unit, an externally attachable unit, and an internally placed unit. It is understood that the controller 530 may be provided with its own consumer interface, may communicate and be operated through the consumer interface provided with the information capable conditioner(s), or a combination of both.
When conditioner system 510 receives nutritional substance 520 for conditioning, nutritional substance reader 590, sometimes referred to as appliance reader in the context of a dynamic appliance, either receives information regarding nutritional substance 520 and provides it to controller 530, which is the case if the nutritional substance 520 contains a label which includes the information about nutritional substance 520, and/or the nutritional substance reader 590 receives reference information allowing retrieval of the information and provides it to controller 530, which is the case if the nutritional substance 520 is associated with, or provided with a dynamic information identifier. In the case where nutritional substance 520 contains a label which includes the desired information about nutritional substance 520, nutritional substance reader 590 reads this information, provides it to controller 530, which makes it available to consumer 540 by means of consumer interface 560.
For example, if nutritional substance 520 is a ready-to-eat frozen dinner which needs to be heated by conditioner system 510, nutritional substance reader 590 would read a label on nutritional substance 520, thereby receiving the information regarding nutritional substance 520, and then provide the information to controller 530. This information could include creation information as to the creation of the various components which constitute the ready-to-eat dinner. This information could include information about where and how the corn in the ready-to-eat dinner was grown, including the corn seed used, where it was planted, how it was planted, how it was irrigated, when it was picked, and information on fertilizers and pesticides used during its growth. Additionally, this information could include the cattle lineage, health, immunization, dietary supplements that were fed to the cattle that was slaughtered to obtain the beef in the ready-to-eat dinner.
The information from a label on nutritional substance 520 could also include information on how the components were preserved for shipment from the farm or slaughterhouse on their path to the nutritional substance transformer who prepared the ready-to-eat dinner. Additional information could include how the nutritional substance transformer transformed the components into the ready-to-eat dinner, such as recipe used, additives to the dinner, and actual measured conditions during the transformation into the ready-to-eat dinner.
While such information could be stored on a label located on the packaging for nutritional substance 520 so as to be read by nutritional substance reader 590, provided to controller 530, and provided to consumer interface 560 for display to consumer 540, preferably, the label on the nutritional substance package includes reference information, such as a dynamic information identifier, which is read by nutritional substance reader 590 and provided to controller 530 that allows controller 530 to retrieve the information about nutritional substance 520 from nutritional substance database 550. Further, linking consumer feedback and updates regarding observed or measured changes in the nutritional, organoleptic, and/or aesthetic values of nutritional substances would provide for virtually real time updates of ΔN information from the actual consumer.
Nutritional substance database 550 could be a database maintained by the transformer of nutritional substance 520 for access by consumers of such nutritional substance 520 to track or estimate changes in the nutritional, organoleptic, and/or aesthetic values of those nutritional substances, as well as any other information about the nutritional substance that can be tracked, including but not limited to the examples previously described. However, preferably, nutritional substance database 550 is a database maintained by the nutritional substance industry for all such information regarding nutritional substances grown, raised, preserved, transformed, conditioned and consumed by consumer 540, in which case it is the database contained within information module 100 and also referred to herein as a dynamic nutritional value database.
It is important to note that while
In an alternate embodiment of the present invention, controller 530, in addition to providing information regarding nutritional substance 520 to consumer 540, also receives information from conditioner system 510 on how nutritional substance 520 was conditioned. Additionally, conditioner system 510 may also measure or sense information about nutritional substance 520 before or during its conditioning by conditioner system 510, and provide such information to controller 530, so that such information could also be provided to consumer 540, via consumer interface 560. Such information may be sensed by attribute sensors providing information related to ΔN of the nutritional substance to be utilized by the controller to confirm that conditioning parameters currently being implemented will achieve desired residual nutritional, organoleptic, or aesthetic values, and if it is determined that they will not, such information may be used to adaptively modify the conditioning parameters in order to achieve desired residual nutritional, organoleptic, or aesthetic values. Further, the controller 530 can receive information from the consumer via consumer interface 560 regarding observed or measured changes in the nutritional, organoleptic, and/or aesthetic values of nutritional substances before or after conditioning, to provide virtually real time updates of ΔN information from the actual consumer, for use by the controller and/or transmission to the nutritional substance database 550.
In a preferred embodiment of the present invention, controller 530 organizes and correlates the information it receives regarding nutritional substance 520 from the various sources of such information, including nutritional substance database 550 and conditioner system 510, and presents such information through consumer interface 560 to consumer 540 in a manner useful to consumer 540. For example, such information may be provided in a manner that assists consumer 540 in understanding how nutritional substance 520 meets consumer's 540 nutritional needs. It could organize information regarding nutritional substance 520 to track consumer's 540 weight loss program. Controller 530 could have access to, or maintain, information regarding consumer 540, so as to track and assist consumer 540 in meeting their specific nutritional needs.
In another embodiment of the present invention conditioner system 510 could be a plurality of conditioner devices or dynamic appliances which can be selectively operated by controller 530 to prepare nutritional substance 520. Conditioner system 510 can be either a single conditioning device, such as a microwave oven, toaster oven, conventional oven, toaster, blender, steamer, stovetop, or human cook. Conditioner system 510 may be a plurality of conditioners 570. In the case where a plurality of conditioners 570 comprise conditioner system 510, nutritional substance 520 may be manually or automatically transferred between conditioners 570 for eventual transfer to consumer 540. In another embodiment, the plurality of conditioners 570 may be operated by the same controller 530 or control system simultaneously. For example, a prepackaged meal may contain separate ingredients that all require different cooking protocols. Accordingly, the consumer may separately place each of the ingredients each in a separate conditioner 570 and the controller 530 could operate the conditioners 570 simultaneously or coordinate them appropriately so each ingredient is finished cooking at the same time. This will advantageously allow all the components of the nutritional substance 520 to be ready for the consumer to eat at the same time.
Nutritional substance reader 590 may be an automatic reader such as a barcode reader or RFID sensor which receives information from nutritional substance 520 or a reference code from nutritional substance 520, such as a dynamic information identifier associated with, or provided with the nutritional substance 520, and provides this information to controller 530. Nutritional substance reader 590 might also be a manual entry system where the reference code, such as a dynamic information identifier associated with, or provided with the nutritional substance 520, is manually entered into nutritional substance reader 590 for use by controller 530, or may alternatively be manually entered into consumer interface 560 for use by controller 530.
In other embodiments, the consumer 540 may enter information regarding the nutritional substance 520, including information identifying the nutritional substance 520. This may be manually through a user interface on the conditioner or other appliance, a mobile phone wirelessly linked to the appliance or other methods as disclosed herein. This allows the controller 530 to identify and access a database 550 with information regarding types or categories of nutritional substances 520. That way, if the nutritional substance 520 is not provided with an identifier, the consumer 540 can provide the necessary information to sufficiently identify the nutritional substance 520. Accordingly, various sensors may then sense various attributes of a the nutritional substance 520 to complement the information entered manually by the consumer 540, to provide further specific information on the nutritional substance 520 that may be used to optimize ΔN information provided to the user, optimize conditioning sequences or protocols performed on the nutritional substance 520 or optimize the conditioning protocols or recipes retrieved as options for performance on the nutritional substance 520. For example, the consumer 540 may enter in a category such as salmon. Then, a weight sensor in connection with a conditioner 570 could sense the mass or amount of salmon, and optionally, color or visual sensors could detect whether the salmon is wild salmon (reddish) or farm raised (light pink). In addition, various sensor arrays may be able to detect VOCs or volatile organic compounds that could determine the level of spoliation, or how fresh the fish is. This information taken from sensors could be utilized to derive or to tailor a conditioning protocol to the specific nutritional substance 520, including its weight, age, and other characteristics. In other embodiments, this information could be utilized to select an optimal conditioning protocol from a recipe database 555. For example, the cooking time and process may be modified for a salmon slab depending on its weight. Additionally, certain types of salmon may have more or less fat and therefore, optimal cooking times and temperatures will vary accordingly. If the information database contains data on different weights and types of salmon, and the sensors can detect this information, the conditioning sequence 610 or protocol can be optimized to account for the sensed attributes.
Nutritional substance database 550 could be a flat database, relational database or, preferably, a multi-dimensional database. Nutritional substance database 550 could be local but, preferably, it would be located remotely, such as on the internet, and accessed via a telecommunication system, such as a wireless telecommunication system. Controller 530 can be implemented using a computing device, such as a micro-controller, micro-processor, personal computer, or tablet computer. Controller 530 could be integrated to include nutritional substance reader 590, consumer interface 560, and/or nutritional substance database 550. Additionally, controller 530 may be integrated in conditioner system 510, including integration into conditioner 570.
In addition, nutritional substance reader 590 may be an optical nutritional substance identifier or sensor that optically determines the identity of the nutritional substance 520, and/or certain physical attributes of the nutritional substance 520 by evaluation of data output by sensors that optically sense the nutritional substance 520. For example, an optical sensor may be utilized that captures light or other radiation reflected or transmitted through the nutritional substance 520. Then, the system could evaluate the optical data output by the sensor to determine certain characteristics of the nutritional substance. For example, the optical data may be utilized to determine the color, intensity, shape, radius of curvature, texture, fiber size, and other attributes. These attributes may then be used to classify the nutritional substance 520, for example by identifying the nutritional substance as an apple, red delicious, red delicious from Washington, orange, navel orange, tangelo, or blood orange, carrot, steak, or filet mignon. This identification information may then be utilized to access information, including nutritional and ΔN information, regarding the nutritional substance 520 in the nutritional substance database 550 as described herein with respect to the nutritional substance reader 590. Thus, the optical sensor or reader may be utilized to identify the nutritional substance 520 in place of utilizing a dynamic information identifier on the nutritional substance 520. Various products are available that are capable of using optical technology to visually identify produce, and various other items. For example, an automated optical fruit recognition system developed by Fraunhofer is capable of detecting and identifying various produce optically as described by an article titled “Automated Fruit Recognition” available at http://www.isob.fraunhofer.de/servlet/is/33328/which is incorporated by reference herein in its entirety. Additionally, an optical object recognition system is disclosed in U.S. Pat. No. 6,310,964 that is described as capable of detecting identity and size of produce and is incorporated herein by reference in its entirety.
It is important to note that while
Consumer interface 560 can be implemented as a display device mounted on controller 530, conditioner system 510, or conditioner 570. However, consumer interface 560 is preferably a tablet computer, personal computer, personal assistant, or smart phone, running appropriate software, such as an app.
While conditioner module 500 can be located in the consumer's home, conditioner module 500 may be located at a restaurant or other food service establishment for use in preparing nutritional substances 520 for consumers who patronize such an establishment. Additionally, conditioner module 500 could be located at a nutritional substance seller such as a grocery store or health food store for preparation of nutritional substances 520 purchased by consumers at such an establishment. It could be foreseen that conditioner modules 500 could become standalone businesses where consumers select nutritional substances for preparation at the establishment or removal from the establishment for consumption elsewhere.
In another embodiment, conditioner may also detect certain attributes of nutritional substance 520, through nutritional substance attribute sensors 591. Nutritional substance attribute sensors 591 may be a variety of sensors as disclosed herein, including: (1) weight, (2) a visible light camera, (3) and infrared camera, (3) ambient moisture, (4) ambient temperature, (5) a wireless probe or (6) a spectrometer sensor. The information from the sensors may be provided to controller 530 in addition to or instead of the information provided by nutritional substance reader 590. For example, in some embodiments, the consumer 540 will input information regarding the nutritional substance 520, which may be for example, an identification of the nutritional substance 520, or the general type of nutritional substance 520. Accordingly, the nutritional substance attribute sensors 591 may detect additional information regarding the nutritional substance 520, that may be transferred to the controller 530, including weight, color, surface temperature, probe temperature, ambient temperature once the substance 520 is deposited in the conditioner 570. Data regarding these attributers output from the sensors 591, may be utilized to provide additional information regarding the nutritional substance 520 to the controller 530.
In an embodiment of the present invention, conditioner system 510 comprises conditioner 570. Conditioner 570 is a conditioning apparatus which can perform a number of operations on nutritional substance 520, separately and/or at the same time. For example, conditioner 570 could be a combination microwave oven, convection oven, grill, and conventional oven. In some embodiments, conditioner 570 may be a plurality of conditioners that comprise conditioner system 510. Controller 530 could operate conditioner 570 or several conditioners 570 to execute a sequence of conditioning cycles on nutritional substance 520 or its separate ingredients to complete its conditioning. In some embodiments, a controller 530 may calculate the appropriate time to coordinate the conditioning of a multi-component meal using multiple conditioners 570 so that each of the conditioners 570 finish conditioning at the same time or approximately the same time. Then, once this is calculated, the controller 530 may store this information an associated memory and turn on each of the conditioners 570 and initiate their conditioning cycles at the appropriate time so that each conditioning cycle of the separate conditioner will all finish within seconds, minutes or other appropriate time periods. Then consumer will be able to take each of the components and consume them as soon as the finished conditioning. For example, food tends to lose its nutritional, organoleptic, and aesthetic qualities the longer it sits after conditioning. This method allows the consumer to condition each component of the meal at the same time using one conditioning protocol or set of related protocols in order to provide instructions to controller 530 that controls each of the multiple conditioners 570.
For example, if nutritional substance 520 is a whole frozen turkey to be prepared for dinner, consumer 540 would place the turkey in conditioner 570, the combination cooking unit suggested above. Controller 530 would receive and/or create a protocol of conditioning cycles. Such a protocol could be read by nutritional substance reader 590 from a label on nutritional substance 520. Alternately, a protocol of conditioning cycles could be obtained from nutritional substance database 550 through reference information, such as a dynamic information identifier, obtained by nutritional substance reader 590 from nutritional substance 520. For example, a label on the turkey, could be read by nutritional substance reader 590, providing reference information for the turkey, such as a dynamic information identifier, which controller 530 uses to obtain a conditioning protocol for the turkey from nutritional substance database 550.
In this example, the whole frozen turkey may also be provided with a packet of stuffing and a packet of gravy. Because these separate components or ingredients of the nutritional substance 520, or the turkey dinner, all require different cooking times and potentially different cooking methods, each component may have a separate conditioning protocol 610. In some embodiments, a dynamic information identifier may be provided with the entire package of the turkey, stuffing and gravy that is referenced in a nutritional substance database 550. The database 550 may contain a separate conditioning protocol 610 for each of the turkey, stuffing, and gravy, complete with its own cooking time and conditioner preferences. Accordingly, once a consumer scans the dynamic information identifier with the nutritional substance reader 590 and the controller 530 or system identifies the food combination, the controller 530 could receive separate conditioning protocol 610 for each of the turkey, stuffing and gravy. Then the consumer interface 560 may instruct the consumer to place each of the three items (or two items) in separate conditioners that are all linked to the controller 530. Then once the conditioning cycle is initiated, the conditioning protocols 610 for each of the separate ingredients and conditioners 670 could be separately and simultaneously controlled by the controller 530. For example, in that case the conditioner 570 with the turkey may be turned on long before the other two conditioners 570 with the gravy and the stuffing. Accordingly, the controller 530 may calculate the appropriate times to initiate conditioning of each conditioner 570. Additionally, the conditioner 570 with the turkey may have a much high temperature and lower or higher humidity content to optimize cooking of the turkey. Then when the turkey would be nearly finished conditioning, the controller 530 may automatically initiate the cooking of the gravy and the stuffing using different temperature settings. The controller 530 may calculate in advance the optimal time to start each of the ingredients so that it can initiate cooking separately for each ingredient so that all three ingredients are finished at the same time. In this case, the turkey, gravy, and stuffing would all be warm, optimally moist and ready to eat at the same time. Otherwise, if the stuffing was finished early, as it cooled some of the organoleptic or aesthetic values may begin to deteriorate as a consumer waits for a turkey to finish conditioning.
Additionally, various conditioning protocols stored in nutritional substance database 550 may contain data or be mapped to information regarding certain attributes that are sensed by nutritional substance attribute sensors 591. In other embodiments, these may be maintained in a certain recipe database 555. These data may be utilized to modify conditioning protocols based on attribute data sensed by the sensors 591 and provided to controller 530. Accordingly, the controller 530 could modify or adapt a selected conditioning protocol to be optimized based on certain data sensed by the sensors 591. For example, if a nutritional substance protocol called for a certain surface temperature, or a cooking a nutritional substance 520 at a specific surface temperature sensed by an infrared temperature sensor for a predetermined time, various attribute sensors may modify the recipe or protocol. For instance, if an infrared sensor 591 initially determined that the starting temperature of the nutritional substance 520 was higher than expected or the average recipe is based on, then the target surface temperature may be lowered or raised accordingly, or the total cooking time may be altered, and therefore altering the conditioning protocol. In another example, a weight sensor 591 may determine that the weight of a substance 50 is higher than the average for which a selected conditioning protocol is based on. Accordingly, the target surface temperature may be raised or lowered, or the time for conditioning may be extended or shortened appropriately to optimize the conditioning protocol.
Nutritional substance database 550 may contain information regarding optimal modifications to recipes or conditioning protocols based on various the quantities of various sensed attributes. For example, the database 550 may contain protocol data based on various weights of the same nutritional substance 520. Accordingly, the sensors 591 could then detect the weight of a nutritional substance 520, a conditioning protocol could be retrieved from the database 550, and then the protocol could be modified based on further data, potentially also from the database 550 by the controller 530. For instance, the database 550 may contain equations for calculating optical cooking temperature and/or duration based on the weight of a nutritional substance 520. This could be using various data points and extrapolating between the points for optimal cooking times and/or temperatures, or could be based on a curve fit to certain examples of that specific type of nutritional substance 520 or more general categories of that nutritional substance 520. For example, if a recipe for cooking fish is 2 minutes at 350 per ounce, the controller 530 may vary the recipe appropriately based on a sensed weight of a piece of fish. Additionally, the starting temperature of the fish may affect the total cooking time, and the recipe may be modified accordingly. In other embodiments, the database 550 may contain information regarding various starting temperatures for fish, meat or other nutritional substances 520, and rearrange the entire protocol based on the starting temperature. This may also be applied using, moisture, elevation of conditioner 570, location, ambient humidity, color of nutritional substance 520 (could indicate fat content, spoliation, ripeness, type of nutritional substance 520, etc.) and other attributes sensed by sensors 591. In other embodiments, the consumer 540 may provide input regarding desired options, or based potential ΔN factors that may be optimized including nutrition, taste, texture, and other factors.
Additionally, in some embodiments, the conditioner 570 may be a combination conditioner 570 that includes the capability to bake, broil, convention cook, microwave, rotate the nutritional substance 520 on a turntable, or perform other conditioning options. These different conditioners 570 may be utilized simultaneously, serially, in parallel, alone, or in other various combinations to maximize certain ΔN factors or attributes, or consumer preferences for conditioning the nutritional substance 520. For example, as in the above example of the turkey, gravy, and stuffing, the conditioner 570 may be three separate conditioners 570 controlled by a single control system or controller 530 based on separate or a multi-faceted conditioning protocol(s) 610 where the consumer to optimize certain ΔN factors or attributes. Accordingly, the conditioning protocols 610 for each may be modified to optimally condition the substance based on the ΔN values desired or entered by a consumer in a consumer input 620 panel.
Accordingly, the database 550 may contain various data points or other indications of the combination of conditioning types that may be utilized to optimally condition a nutritional substance 520 and/or its separate ingredients or components based on the chosen criteria. For example, the database 550 may contain ΔN information on turkey, stuffing, and gravy, and including ΔN information based on various conditioning protocols 610 and there resultant ΔN values on each of the ingredients. Accordingly, a consumer may input their preferences for ΔN values which would allow the controller 530 to modify a conditioning protocol 610 appropriately to cook to the food to obtain the ΔN values preferred by the consumer. In another example, various sensors may be utilized to modify the condition protocols 610 to be tailored to a particular nutritional substance 520. For example, if a weight sensor 591 detects that a piece of fish weights more than an average piece of fish or a fish sample a conditioning protocol in the database 550 is based on, the controller 530 may elect to condition the fish first by utilizing the microwave to cook the fish through the fastest, so as not to overcook the outside using a convection or other non-microwave cooking option.
An example of such a conditioning protocol for a frozen turkey could be to operate conditioner 570, the combination cooking unit, in the following fashion. In some embodiments, the conditioner 570 may sense the weight, temperature and other attributes of the turkey using a weight measurement sensor, and determine the ΔN values that would result from different potential conditioning protocols 610 based on information stored in the nutritional substance database 550. This could also be applied to additional ingredients of the turkey, including the stuffing and gravy. This information stored in the nutritional substance database 550, may include the ΔN values that result from different conditioning protocols based on the weight of the nutritional substance 520 or ingredient, time, and other conditioning parameters (e.g. cooking temperature). The database 550 may also be easily updatable to allow new ΔN values to be substituted in based on additional testing or analysis. In these embodiments, the consumer may be presented with various conditioning options and allowed to select the desired conditioning option that results in the desired ΔN value. Once the consumer selected the conditioning option, the controller 530 may, for example, first instruct conditioner 570 to use the microwave function of the combination cooking unit to defrost the turkey according to the conditioning protocol 610 obtained for the turkey from nutritional substance database 550 and possibly according to information provided by conditioner 570, such as the weight of the turkey obtained from a weight measurement sensor within conditioner 570, information regarding the defrosting process as measured by conditioner 570, or values related to ΔN provided by nutritional attribute sensors before or during defrosting. Following defrosting of the turkey, controller 530 next instructs the combination cooking unit to operate as a convection oven to cook the turkey, according to the conditioning protocol obtained for the turkey from nutritional substance database 550 and the weight of the turkey, for a sufficient length of time so as to ensure that the turkey reaches the proper internal temperature to meet safety requirements, and to maximize organoleptic and/or nutritional properties based on the ΔN and conditioning protocol selected by the consumer and/or determined by the controller 530. Alternatively, or additionally, the conditioning protocol 610 obtained for the turkey from nutritional substance database 550 may depend upon a direct measurement of the internal temperature of the turkey, the weight of the turkey, or a combination of measured temperature and time and weight, or values related to ΔN provided by nutritional attribute sensors before or during conditioning. Following the convection oven cooking of the turkey, controller 530 could instruct the combination cooking unit to grill the turkey, according to the conditioning protocol 610 obtained for the turkey from nutritional substance database 550, for a sufficient period of time to create a desirable golden and crispy skin, which could be based on a modification to a recipe based on sensed attributes of the turkey, including weight, color, moisture and starting temperature. Alternatively, or additionally, the conditioning protocol 610 obtained for the turkey from nutritional substance database 550 may depend upon a direct measurement by a nutritional attribute sensor to measure a ΔN, such as an optical sensor to sense external aesthetic values of the turkey such as color, change of color, texture, or change of texture, temperature, or a weight measurement sensor to sense the weight of the turkey. Alternatively, or additionally, the conditioning protocol 610 obtained for the turkey from nutritional substance database 550 may depend upon a direct measurement by an infrared sensor of the surface temperature of the turkey, or a combination time, measured aesthetic values, weight, and/or measured surface temperature and/or measured ΔN information. Finally, controller 530 could instruct the combination cooking unit to use all three cooking functions at the same time to prepare the turkey for optimal consumption according to the conditioning protocol obtained for the turkey from nutritional substance database 550.
Alternatively, conditioner system 510 could be composed of a plurality of conditioners 570. While an automated system for moving a nutritional substance between such conditioners would be optimal, conditioner system 510 could be operated manually by consumer 540 from instructions provided by the controller 530 to consumer interface 560. In this embodiment, controller 530 could provide consumer 540 with instructions as to where to move the turkey after each step in the conditioning protocol. In this example, controller 530 instructs consumer 540 through consumer interface 560 to first place the frozen turkey in conditioner 570, a microwave oven. Controller 530 instructs the microwave oven to defrost the turkey based on information possibly provided by nutritional substance reader 590, nutritional substance database 550 and/or conditioner 570. Upon completion of defrosting by the microwave oven, controller 530 could instruct consumer 540 through interface 560 to move the defrosted turkey from the microwave oven to another conditioner 570, a convection oven. Controller 530 would operate the convection oven to cook the turkey for a sufficient length of time so as to ensure that the turkey reaches the proper internal temperature to meet safety requirements, and to maximize organoleptic and/or nutritional properties. Finally, following the cooking cycle in the convection oven, controller 530 could instruct consumer 540 through consumer interface 560 to move the turkey from the convection oven to another conditioner 570, a grill. Controller 530 would operate the grill so as to grill the turkey for a sufficient period of time to create a desirable golden and crispy skin. In these embodiments, the consumer 540 may be instructed to place the turkey on an electronic scale to determine the weight of the turkey in between each step, so the conditioning system 510 may record the change in weight of the turkey. The electronic scale may be in electronic communication with the system 510 to allow the weight information to be transferred throughout the system and utilized to calculate an updated ΔN. The change in weight may then be used by the controller 530 to further refine or determine the ΔN from conditioning the turkey and to provide the consumer 540 with updates regarding the ΔN. This may be an alternative to having a weight sensor or scale in each of the conditioners.
As discussed herein, the plurality of conditioners 570 may be utilized to separately condition each portion of a frozen turkey meal in overlapping conditioning cycles rather than separately condition the turkey in stages. For example, the gravy could go through a similar protocol above in a separate conditioner 570 that is controlled by the same controller 530. Additionally, each of the plurality of conditioners 570 in this example may only be separate conditioning spaces that are environmentally separate from each other conditioner 570 but each are capable of conditioning using various methods—microwave, convention, etc. that are possible inside the conditioner 570.
Alternatively, conditioner system 510 could be composed of a plurality of conditioners 570; and a consumer 540 (which would include any individuals preparing the turkey for consumption), fulfilling additional conditioner roles, as will be explained. While an automated system for moving a nutritional substance between such conditioners would be optimal, conditioner system 510 could be operated manually by consumer 540 from instructions provided by a consumer interface 560, which in this case could be a handheld device such as a cellular phone, tablet computer, PDA, or any other device useful for communicating with nutritional substance database 550 and the consumer 540. The handheld device additionally fulfills the role of nutritional substance reader 590 and controller 530. For example, the consumer 540 can utilize a camera function of the handheld device to read a barcode, or QR code, on or associated with the turkey, wherein the code provides a dynamic information identifier. The handheld device can then use the dynamic information identifier to retrieve information regarding the turkey from nutritional substance database 550. In this example, consumer 540 utilizes the handheld device to read a barcode (or any other readable code) on the turkey, the barcode containing a dynamic information identifier associated with information regarding the turkey within the nutritional substance database 550. The consumer 540 uses the handheld device to retrieve and review a conditioning protocol from nutritional substance database 550, and is accordingly instructed as to where to move the turkey for each step in the conditioning protocol and further instructed on the conditioning parameters required for each step of the conditioning protocol. In this example, consumer 540 retrieves and reviews a conditioning protocol from nutritional substance database 550 using the handheld device and is instructed to first place the frozen turkey in conditioner 570, a microwave oven, and further instructed on conditioning parameters for the microwave oven to defrost the turkey. Consumer 540 is instructed that upon completion of defrosting by the microwave oven, the turkey is to be moved to another conditioner 570, a convection oven. Consumer 540 is further instructed on conditioning parameters for the convection oven to cook the turkey for a sufficient length of time so as to ensure that the turkey reaches the proper internal temperature to meet safety requirements, and to maximize organoleptic and/or nutritional properties. Finally, consumer 540 is instructed that upon completion of cooking by the convection oven, the turkey is to be moved to another conditioner 570, a grill, and further instructed on conditioning parameters for the grill so as to grill the turkey for a sufficient period of time to create a desirable golden and crispy skin.
In the case where conditioner system 510 is a plurality of conditioners 570, it would also be possible for controller 530 to manage conditioners 570 within conditioner system 510 so as to produce a complete meal. For example, controller 530 could select conditioning protocols which would maximize the use of each conditioner 570. For example, in a meal comprising a turkey, home baked bread, and acorn squash, controller 530 could stage and operate the microwave oven, convection oven, and grill to minimize preparation time for the meal by determining which item should be cooked in which conditioner 570, in which order, to maximize usage of each conditioner 570 in conditioning system 510. In this example, while the turkey is being defrosted in the microwave oven, controller 530 could instruct consumer 540 through interface 560 to place the bread dough in the convection oven and the acorn squash on the grill. Following the defrosting of the turkey, when the turkey is moved to the convection oven, which finished baking the bread, the bread could be moved to the grill for browning, and the acorn squash could be moved to microwave oven to keep warm until the entire meal is ready. In another example, the conditioners 570 may all be multi conditioner capable (i.e. microwave, convention) and instruct the consumer to place the nutritional substance components (i.e. turkey, home backed bread, and acorn squash) in three separate conditioners 570 in the beginning of the recipe or prior to conditioning. Then the controller 530 could turn on each conditioner using the appropriate conditioning method at appropriate times to result in a meal that is ready to eat with all its ingredients at the same time. For example, the turkey may be placed in a first conditioner 570 which first begins defrosting the turkey by operating in a microwave mode, then switches to a convention oven and/or grill to cook the turkey. The home baked bread may also be placed in a second conditioner 570, where the second conditioner 570 would begin conditioning for the last few minutes at the end of the condition protocol 610 for the turkey. Finally, the same is true for the acorn squash, which may be placed in third conditioner 570 and conditioned according to a third conditioning protocol 610 or a third portion of the same conditioning protocol 610 at the same time.
For example, if nutritional substance 520 is a ready-to-eat frozen dinner which needs to be heated by conditioner system 510, nutritional substance reader 590 would read a label on nutritional substance 520, thereby receiving information regarding nutritional substance 520, and then provide the information to controller 530. This information could include creation information as to the creation and conditioning protocols 610 for the various components which constitute the ready-to-eat dinner. This information could include information about where and how the corn in the ready-to-eat dinner was grown, including the corn seed used, where it was planted, how it was planted, how it was irrigated, when it was picked, and information on fertilizers and pesticides used during its growth. Additionally, this information could include the cattle lineage, health, immunization, dietary supplements that were fed to the cattle that was slaughtered to obtain the beef in the ready-to-eat dinner.
The information from a label on nutritional substance 520 could also include information on how the components were preserved for shipment from the farm or slaughterhouse on their path to the nutritional substance transformer who prepared the ready-to-eat dinner. Additional information could include how the nutritional substance transformer transformed the components into the ready-to-eat dinner, such as recipe used, additives to the dinner, and actual measured conditions during the transformation into the ready-to-eat dinner.
While such information could be stored on a label located on the packaging for nutritional substance 520 so as to be read by nutritional substance reader 590, provided to controller 530, and provided to consumer interface 560 for display to consumer 540, preferably, the label on the nutritional substance package includes reference information, such as a dynamic information identifier, which is read by nutritional substance reader 590 and provided to controller 530 that allows controller 530 to retrieve the information about nutritional substance 520 from nutritional substance database 550. Further, linking consumer feedback and updates regarding observed or measured changes in the nutritional, organoleptic, and/or aesthetic values of nutritional substances would provide for virtually real time updates of ΔN information from the actual consumer.
Nutritional substance database 550 could be a database maintained by the transformer of nutritional substance 520 for access by consumers of such nutritional substance 520 to track, estimate, or predict changes in the nutritional, organoleptic, and/or aesthetic values of those nutritional substances and/or their component ingredients, including those based on weight and conditioning protocols and other factors, as well as any other information about the nutritional substance that can be tracked, including but not limited the weight of the substances, previous conditioning of the substances and the other examples previously described. However, preferably, nutritional substance database 550 is a database within information module 100 that is maintained by the nutritional substance industry for all such information regarding nutritional substances grown, raised, preserved, transformed, conditioned and consumed by consumer 540, in which case it is the database contained within information module 100 and also referred to herein as a dynamic nutritional value database.
Nutritional substance database 550 may contain information regarding optimal modifications to recipes or conditioning protocols based on various the quantities of various sensed attributes for nutritional substances 520 and/or their component ingredients. For example, the database 550 may contain protocol data based on various weights of the same nutritional substance 520 or ingredients. Accordingly, the sensors 591 could then detect the weight of a nutritional substance 520 or each separate ingredient, a conditioning protocol could be retrieved from the database 550 and/or for each separately conditioned ingredient, and then the protocol could be modified based on further data, potentially also from the database 550 by the controller 530. For instance, the database may contain equations for calculating optical cooking temperature and/or duration based on the weight of a nutritional substance 520 and/or ingredient. This could be using various data points and extrapolating between the points for optimal cooking times and/or temperatures, or could be based on a curve fit to certain examples of that specific type of nutritional substance 520 or more general categories of that nutritional substance 520. For example, if a recipe for cooking fish is 2 minutes at 350 per ounce, the controller 530 may vary the recipe appropriately based on a sensed weight of a piece of fish. Additionally, the starting temperature of the fish may affect the total cooking time, and the recipe may be modified accordingly. In other embodiments, the database 550 may contain information regarding various starting temperatures for fish, meat or other nutritional substances 520, and rearrange the entire protocol based on the starting temperature. This may also be applied using, moisture, elevation of conditioner 570, location, ambient humidity, color of nutritional substance 520 (could indicate fat content, spoliation, ripeness, type of nutritional substance 520, etc.) and other attributes sensed by sensors 591. In other embodiments, the consumer 540 may provide input regarding desired options, or based potential ΔN factors that may be optimized including nutrition, taste, texture, and other factors.
In an alternate embodiment of the present invention, controller 530, in addition to providing information regarding nutritional substance 520 to consumer 540, also receives information from conditioner system 510 on how nutritional substance 520 was conditioned. Additionally, conditioner system 510 may also measure or sense information about nutritional substance 520 before or during its conditioning by conditioner system 510, and provide such information to controller 530, including the weight of the substance 520, so that such information could also be provided to consumer 540, via consumer interface 560. Such information may be sensed by attribute sensors providing information related to ΔN of the nutritional substance to be utilized by the controller to confirm that conditioning parameters currently being implemented will achieve desired residual nutritional, organoleptic, or aesthetic values, and if it is determined that they will not, such information may be used to adaptively modify the conditioning parameters in order to achieve desired residual nutritional, organoleptic, or aesthetic values.
In a preferred embodiment of the present invention, controller 530 organizes and correlates the information it receives regarding nutritional substance 520 from the various sources of such information, including nutritional substance database 550 and conditioner system 510, and presents such information through consumer interface 560 to consumer 540 in a manner useful to consumer 540. For example, such information may be provided in a manner that assists consumer 540 in understanding how nutritional substance 520 meets consumer's 540 nutritional needs before or after conditioning, or how it meets the consumer's needs based on various proposed conditioning parameters. This may include how the nutritional substance's 520 current weight and ΔN will be affected by proposed conditioning parameters. It could organize information regarding nutritional substance 520 to track consumer's 540 weight loss program. Controller 530 could have access to, or maintain, information regarding consumer 540, so as to track and assist consumer 540 in meeting their specific nutritional needs.
In another embodiment of the present invention conditioner system 510 could be a plurality of conditioner devices or dynamic appliances which can be selectively operated by controller 530 to prepare nutritional substance 520. Conditioner system 510 can be either a single conditioning device, such as a microwave oven, toaster oven, conventional oven, toaster, blender, steamer, stovetop, or human cook. Conditioner system 510 may be a plurality of conditioners 570. In the case where a plurality of conditioners 570 comprise conditioner system 510, nutritional substance 520 may be manually or automatically transferred between conditioners 570 for eventual transfer to consumer 540. In other embodiments, the plurality of conditioners 570 may be controlled simultaneously to cook a component meal for a consumer, for example a frozen meal in separately packaged components.
Nutritional substance reader 590 may be an automatic reader such as a barcode reader or RFID sensor which receives information from nutritional substance 520 or a reference code from nutritional substance 520, such as a dynamic information identifier, and provides this information to controller 530. Nutritional substance reader 590 might also be a manual entry system where the reference code, such as a dynamic information identifier associated with, or provided with the nutritional substance 520, is manually entered into nutritional substance reader 590 for controller 530.
Nutritional substance database 550 could be a flat database, relational database or, preferably, a multi-dimensional database. Nutritional substance database 550 could be local but, preferably, it would be located remotely, such as on the internet, and accessed via a telecommunication system, such as a wireless telecommunication system. Controller 530 can be implemented using a computing device, such as a micro-controller, micro-processor, personal computer, or tablet computer. Controller 530 could be integrated to include nutritional substance reader 590, consumer interface 560, and/or nutritional substance database 550. Additionally, controller 530 may be integrated in conditioner system 510, including integration into conditioner 570.
It is important to note that while
Consumer interface 560 can be implemented as a display device mounted on controller 530, conditioner system 510, or conditioner(s) 570. However, consumer interface 560 is preferably a tablet computer, personal computer, personal assistant, or smart phone, running appropriate software, such as an app.
While conditioner module 500 can be located in the consumer's home, conditioner module 500 may be located at a restaurant or other food service establishment for use in preparing nutritional substances 520 for consumers who patronize such an establishment. Additionally, conditioner module 500 could be located at a nutritional substance seller such as a grocery store or health food store for preparation of nutritional substances 520 purchased by consumers at such an establishment. It could be foreseen that conditioner modules 500 could become standalone businesses where consumers select nutritional substances for preparation at the establishment or removal from the establishment for consumption elsewhere.
Additionally, controller 530 uses nutritional substance information retrieved by nutritional substance reader 590 from nutritional substance 520, or retrieved from nutritional substance database 550 using reference information obtained by nutritional substance reader 590 from nutritional substance 520, to dynamically modify the operation of conditioner system 510 to maintain organoleptic and nutritional properties of nutritional substance 520. For example, if the nutritional substance 520 is a ready-to-eat dinner, controller 530 could modify the instructions to conditioner system 530 in response to information regarding a ΔN of the corn used in the ready-to-eat dinner such that a temperature and cooking duration can be modified to affect the residual nutritional, organoleptic, and aesthetic value of the corn.
In an embodiment, the label on nutritional substance 520 could contain the conditioning instructions for nutritional substance 520, or a reference, such as a dynamic information identifier, to such conditioning instructions in nutritional substance database 550. In operation, this would allow controller 530 to obtain information about nutritional substance 520 on how to dynamically operate conditioner system 510 to condition nutritional substance 520, without consumer intervention. Additionally, conditioning instructions for nutritional substance 520 could be provided for a variety of different conditioner systems 510, or conditioners 570, and controller could select the proper conditioning instructions.
In an embodiment, nutritional substance reader 590 and/or conditioner system 510 measures or senses information about a current nutritional, organoleptic, and aesthetic value of nutritional substance 520, such as with nutritional substance attribute sensors, and provides such information to controller 530 to allow controller 530 to dynamically modify operation of conditioner system 510 including by modifying a conditioning protocol based on previously recorded data regarding conditioning of the nutritional substance 520 at various quantities of the sensed attribute. This may include sensing a weight of the nutritional substance 520, and the conditioner system 510 may be dynamically controlled based on feedback from the weight measurement sensors incorporated or in communication with the conditioner system 510. In other embodiments, a separate scale or appliance with a weight measurement sensor may be provided that allows a consumer to weigh the nutritional substance 520 periodically, before, or after conditioning. The separate scale or appliance may include a nutritional substance reader 590, or may be integrated with the conditioning system 510 and not require a separate reader 590, and rather the information regarding the nutritional substance 520 originally detected by the reader 590 for the system 510 may be automatically associated with the nutritional substance 520 placed on the scale.
For example, a conditioner may also detect certain attributes of nutritional substance 520 through nutritional substance attribute sensors 591. Nutritional substance attribute sensors 591 may be a variety of sensors as disclosed herein, including: (1) weight, (2) a visible light camera, (3) and infrared camera, (3) ambient moisture, (4) ambient temperature, (5) a wireless probe or (6) a spectrometer sensor. The information from the sensors may be provided to controller 530 in addition to or instead of the information provided by nutritional substance reader 590. For example, in some embodiments, the consumer 540 will input information regarding the nutritional substance 520, which may be for example, an identification of the nutritional substance 520, or the general type of nutritional substance 520. Accordingly, the nutritional substance attribute sensors 591 may detect additional information regarding the nutritional substance 520, that may be transferred to the controller 530, including weight, color, surface temperature, probe temperature, ambient temperature once the substance 520 is deposited in the conditioner 570. Data regarding these attributers output from the sensors 591, may be utilized to provide additional information regarding the nutritional substance 520 to the controller 530.
Additionally, various conditioning protocols stored in nutritional substance database 550 may contain data regarding certain attributes that are sensed by nutritional substance attribute sensors 591. These data may be utilized to modify conditioning protocols based on attribute data sensed by the sensors 591 and provided to controller 530. Accordingly, the controller 530 could modify or adapt a selected conditioning protocol to be optimized based on certain data sensed by the sensors 591. For example, if a nutritional substance protocol called for a certain surface temperature, or a cooking a nutritional substance 520 at a specific surface temperature sensed by an infrared temperature sensor for a predetermined time, various attribute sensors may modify the recipe or protocol. For instance, if an infrared sensor 591 initially determined that the starting temperature of the nutritional substance 520 was higher than expected or the average starting temperature a recipe or data set is based on, then the target surface temperature may be lowered or raised accordingly, or the total cooking time may be altered, and therefore altering the conditioning protocol. In another example, a weight sensor 591 may determine that the weight of a substance 50 is higher than the average for which a selected conditioning protocol data set is based on. Accordingly, the target surface temperature may be raised or lowered, or the time for conditioning may be extended or shortened appropriately to optimize the conditioning protocol.
In an additional embodiment of the present invention, consumer 540 provides information regarding their needs and/or desires with regard to the nutritional substance 520 to consumer interface 560. Consumer interface 560 provides this information to controller 530 so as to allow controller 530 to dynamically modify conditioning parameters used by conditioner system 510 in the conditioning of nutritional substance 520, or to request from nutritional substance database 550 dynamically modified conditioning parameters to be used by conditioner system 510 in the conditioning of nutritional substance 520, responsive to the consumer provided information. Consumer's 540 needs and/or desires could include nutritional parameters, taste parameters, aesthetic parameters. For example, consumer 540 may have needs for certain nutrients which are present in nutritional substance 520 prior to conditioning. Controller 530 could modify operation of conditioner system 510 so as to preserve such nutrients. For example, conditioner system 500 can cook the nutritional substance at a lower temperature and/or for a shorter duration so as to minimize nutrient loss. The consumer's 540 needs and/or desires may be related to particular nutritional, organoleptic, an/or aesthetic values, and may additionally be related to other nutritional substance attributes that are retrievable through the nutritional substance database 550 using a dynamic information identifier, such as nutritional substance additives, preservatives, genetic modifications, origins, potential conditioning parameters, and traceability. Further, the consumer's needs and/or desires could be part of a consumer profile provided to the controller 530 through the consumer interface 560 or otherwise available to controller 530. The consumer's needs and/or desires could be exclusionary in nature, for example no products of animal origin, no peanuts or peanut-derived products, no farm raised products, no pork products, or no imported products. In these cases, the nutritional substance database 550 could provide information that would prevent the consumer from preparing and/or consuming products that the consumer cannot, should not, or prefers not to consume.
The consumer's 540 organoleptic and/or aesthetic desires could include how rare or well done they prefer a particular nutritional substance to be prepared. For example, consumer 540 may prefer his vegetables to be crisp or pasta to be prepared al dente. With such information provided by consumer 540 to controller 530 through consumer interface 560, controller 530 can dynamically modify operation of conditioner system 510 responsive to the consumer information and provide a nutritional substance 520 according to the consumer's desires. In addition, the consumer may input certain known or consumer estimated attributes of the nutritional substance 520 in place of them being detected using an information substance reader 590 or attribute sensors 591 when the sensors and/or reader are not available.
In the preferred embodiment of the present invention, controller 530 receives information regarding the history of nutritional substance 520, current information on nutritional substance 520 (e.g. weight), and consumer 540 needs and/or desires, and dynamically modifies operation of conditioner system 510 responsive to the information so as to provide a nutritional substance according to the consumer's needs and/or desires. For example, if nutritional substance 520 is a steak, controller 530 would receive reference information regarding the steak, nutritional substance 520, from nutritional substance reader 590, from attribute sensors 591, including optionally from a weight measurement sensor to determine the weight of the steak. Controller 530 would use this reference information to obtain information about the steak from nutritional substance database 550, including using the weight to determine more precise ΔN and other organoleptic, nutritional, and aesthetic properties of the steak. Controller 530 could also receive current information about the steak and/or its ingredients from nutritional substance reader 590 and/or conditioner 510. Additionally, controller 530 could receive consumer 540 preferences from consumer interface 560. Then, the controller 530 may determine potential organoleptic, nutritional, and aesthetic values that may result from various conditioning options for the steak including the associated ΔN values that may result from each of the conditioning options. Next the consumer 540 may enter which of the conditioning options they desire in consumer interface 560. The controller 530 could then modify an existing, or develop a new conditioning protocol 610 to condition the steak to the consumer's preference based on various sensed attributes of the steak, including for example, the weight and color of the steak. For example, in one embodiment, a color sensor may be able to determine the leanness of a steak and implement an optimal condition regime based on the fat content, starting temperature, and weight of the steak. Finally, controller 530 could receive information from conditioner system 510 during the conditioning of the steak, nutritional substance 520. Responsive to some or all of such information, controller 530 would dynamically modify the cooking and/or recipe chosen or adapted for the steak to preserve, optimize, or enhance organoleptic, nutritional, and aesthetic properties to meet consumer 540 needs and/or the desired organoleptic, nutritional, and aesthetic properties or ΔN based on the condition option entered by the consumer. For example, the steak could be cooked slowly to preserve iron levels within the meat, and also cooked to well-done to meet consumer's 540 taste or cooked in another fashion to overall minimize ΔN.
As reader 590 transmits information to a database 550 and conditioner 570 the current invention includes a proprietary machine-readable recipes module. This method allows for recipes to seamlessly recommend and guide you through options based on the inventory you have on hand without the need to type in or go through human read instructions. The method if integrating this database is breakthrough to the Industry and work has begun in this direction with content providers like Good House Keeping and the New York Times.
In an embodiment of the present invention, conditioner system 510 comprises conditioner 570. Conditioner 570 is a conditioning apparatus which can perform a number of operations on nutritional substance 520, separately and/or at the same time. For example, conditioner 570 could be a combination microwave oven, convection oven, grill, and conventional oven. Controller 530 could operate conditioner 570 to execute a sequence of conditioning cycles on nutritional substance 520 to complete its conditioning. In another embodiment, controller 530 could operate a plurality of conditioners as disclosed herein.
For example, if nutritional substance 520 is a whole frozen turkey to be prepared for dinner, consumer 540 would place the turkey in conditioner 570, the combination cooking unit suggested above. Controller 530 would receive and/or create a protocol of conditioning cycles. Such a protocol could be read by nutritional substance reader 590 from a label on nutritional substance 520. Alternately, a protocol of conditioning cycles could be obtained from nutritional substance database 550 through reference information such as a dynamic information identifier, obtained by nutritional substance reader 590 from nutritional substance 520. For example, a label on the turkey could be read by nutritional substance reader 590, providing reference information for the turkey, such as a dynamic information identifier, which controller 530 uses to obtain an adaptive conditioning protocol or several options for adaptive conditioning protocols that result in different ΔN values, for the turkey from nutritional substance database 550. The adaptive conditioning protocol obtained is at least partially responsive to ΔN information in the nutritional substance database 550 referenced to the dynamic information identifier.
An example of such a conditioning protocol for a frozen turkey could be to operate conditioner 570, the combination cooking unit in the following fashion. First, controller 530 instructs conditioner 570 to use the microwave function of the combination cooking unit to defrost the turkey according to the conditioning protocol obtained for the turkey from nutritional substance database 550 or selected by the consumer after presented with various conditioning options that are predicted to result in associated ΔN values, and possibly according to information provided by conditioner 570, such as information from attribute sensors regarding the weight, volume, and/or temperature of the turkey, regarding the defrosting process as measured by attribute sensors, or information related to ΔN values provided by attribute sensors before or during defrosting. Information regarding the actual recognition of the Turkey as well as weight, temperature, humidity etc. of the turkey could be provided by a weight measurement sensor in the conditioner 570, or it could be a separate appliance or a standalone scale for example that is integrated or separate from conditioning system 510. Additionally, an infrared sensor 591 may detect the surface temperature of the turkey and/or a temperature probe may be placed in the turkey for another level of granularity of information and feedback on the state and varying temperatures of the turkey. Following defrosting of the turkey, controller 530 next instructs the combination cooking unit to operate as a convection oven to cook the turkey, according to the conditioning protocol obtained for the turkey from nutritional substance database 550 and modified by the feedback from the attribute sensors 591 and/or input from the consumer 540, for a sufficient length of time so as to ensure that the turkey reaches the proper internal temperature to meet safety requirements, and to maximize organoleptic and/or nutritional properties or meet the desired ΔN or other requirements entered by the consumer 540. Alternatively, or additionally, the conditioning protocol obtained for the turkey from nutritional substance database 550 may depend upon a direct measurement of the internal temperature of the turkey, or a combination of measured temperature and time, or information related to ΔN values provided by attribute sensors before or during conditioning, including the weight of the turkey, color of the turkey, moisture or humidity, the ambient pressure (i.e. elevation of the conditioner), and other sensed attributes. Following the convection oven cooking of the turkey, controller 530 could instruct the combination cooking unit to grill the turkey, according to the conditioning protocol obtained and/or adapted for the turkey from nutritional substance database 550, for a sufficient period of time to create a desirable golden and crispy skin. Alternatively, or additionally, the conditioning protocol obtained for the turkey from nutritional substance database 550 may depend upon a direct measurement by attribute sensors of a ΔN value, such as an optical sensor to sense external aesthetic values of the turkey such as color, change of color, texture, or change of texture, temperature, humidity, or other attributes. In other embodiments, a scale or weight measurement sensor in the conditioner 570 may measure the weight of the turkey, and the conditioning protocol may be depend on the direct measurement of the weight and modified during conditioning as the weight of the turkey changes. Alternatively, or additionally, the conditioning protocol obtained for the turkey from nutritional substance database 550 may depend upon a direct measurement by an infrared sensor of the surface temperature of the turkey, or a combination of time, measured aesthetic values, and/or measured surface temperature and/or measured ΔN information. Finally, controller 530 could instruct the combination cooking unit to use all three cooking functions at the same time to prepare the turkey for optimal consumption according to the conditioning protocol obtained for the turkey from nutritional substance database 550 or entered by the consumer in response to the presentation of different conditioning options and resultant ΔN values.
Alternatively, conditioner system 510 could be composed of a plurality of conditioners 570. While an automated system for moving a nutritional substance between such conditioners would be optimal, conditioner system 510 could be operated manually by consumer 540 from instructions regarding an adaptive conditioning protocol provided by the controller 530 to consumer interface 560. In this embodiment, controller 530 could provide consumer 540 with instructions as to where to move the turkey after each step in the adaptive conditioning protocol. In this example, controller 530 instructs consumer 540 through consumer interface 560 to first place the frozen turkey in conditioner 570, a microwave oven. Controller 530 instructs the microwave oven to defrost the turkey based on information possibly provided by nutritional substance reader 590, nutritional substance database 550 and/or attribute sensors of the conditioner 570, including weight sensors. Upon completion of defrosting by the microwave oven, controller 530 could instruct consumer 540 through interface 560 to move the defrosted turkey from the microwave oven to another conditioner 570, a convection oven. Controller 530 would operate the convection oven to cook the turkey for a sufficient length of time so as to ensure that the turkey reaches the proper internal temperature to meet safety requirements, and to maximize organoleptic and/or nutritional properties. Finally, following the cooking cycle in the convection oven, controller 530 could instruct consumer 540 through consumer interface 560 to move the turkey from the convection oven to another conditioner 570, a grill. Controller 530 would operate the grill so as to grill the turkey for a sufficient period of time to create a desirable golden and crispy skin.
Alternatively, conditioner system 510 could be composed of a plurality of conditioners 570; and a consumer 540 (which would include any individuals preparing the turkey for consumption), fulfilling additional conditioner roles, as will be explained. While an automated system for moving a nutritional substance between such conditioners would be optimal, conditioner system 510 could be operated manually by consumer 540 from instructions regarding an adaptive conditioning protocol provided by a consumer interface 560, which in this case could be a handheld device such as a cellular phone, smartphone, tablet computer, PDA, or any other device useful for communicating with nutritional substance database 550 and the consumer 540. The handheld device additionally fulfills the roll of nutritional substance reader 590 and controller 530. For example, the consumer 540 can utilize a camera function of the handheld device to read a barcode, or QR code, on or associated with the turkey, wherein the code provides a dynamic information identifier. The handheld device can then use the dynamic information identifier to retrieve information regarding the turkey from nutritional substance database 550. In this example, consumer 540 utilizes the handheld device to read a barcode (or any other readable code) on the turkey, the barcode containing a dynamic information identifier associated with information regarding the turkey within the nutritional substance database 550, including ΔN information referenced to the dynamic information identifier. The consumer 540 uses the handheld device to retrieve and review an adaptive conditioning protocol from nutritional substance database 550, and is accordingly instructed as to where to move the turkey for each step in the adaptive conditioning protocol and further instructed on the corresponding conditioning parameters required for each step of the adaptive conditioning protocol. The consumer 540 may also be provided various conditioning protocols that result in various ΔN amounts and are displayed to the consumer. In this example, the consumer 540 may then select one of the adaptive conditioning protocols presented to the consumer 540 from nutritional substance database 550 using the handheld device and will then be instructed to first place the frozen turkey in conditioner 570, a microwave oven, and further instructed on the adaptive conditioning parameters for the microwave oven to defrost the turkey. For a particular protocol, consumer 540 may be instructed that upon completion of defrosting by the microwave oven, the turkey is to be moved to another conditioner 570, a convection oven. Consumer 540 is further instructed on the adaptive conditioning parameters for the convection oven to cook the turkey for a sufficient length of time so as to ensure that the turkey reaches the proper internal temperature to meet safety requirements, and to maximize organoleptic and/or nutritional properties. Finally, consumer 540 is instructed that upon completion of cooking by the convection oven, the turkey is to be moved to another conditioner 570, a grill, and further instructed on the adaptive conditioning parameters for the grill so as to grill the turkey for a sufficient period of time to create a desirable golden and crispy skin. In another embodiment and as explained herein, the turkey may come in a package with gravy and stuffing and contain a dynamic information identifying includes information identifying each of the components. In some embodiments, the dynamic information identifier may contain the specific weight of that turkey, stuffing, and gravy. Accordingly, once the consumer scans the dynamic information identifier in the nutritional substance reader 590, the controller 530 may then use the information from the dynamic information identifier to retrieve associated conditioning protocols and/or ΔN information based on the conditioning protocols 610 for each of the turkey, gravy and stuffing. This may be performed using a mobile phone as suggested above. In some embodiments, a single conditioning protocol 610 with instructions for separately conditioning all three of the components—the turkey, gravy and stuffing may be retrieved. Accordingly, then the protocol 610 may provide instructions to display to the consumer, various options for conditioning each component, including options to optimize ΔN for each of those components of the nutritional substance 520. Once the consumer has selected the options for each component, the controller 530 may instruct the mobile or other display device to display instructions to the consumer to insert each of the nutritional substance 520 in each of the separate conditioners 570.
In the case where conditioner system 510 is a plurality of conditioners 570, it would also be possible for controller 530 to manage conditioners 570 within conditioner system 510 so as to produce a complete meal, and optionally a complete meal that minimizes certain ΔN values. For example, controller 530 could select conditioning protocols which would maximize the use of each conditioner 570. For example, in a meal comprising a turkey, home baked bread, and acorn squash, controller 530 could stage and operate the microwave oven, convection oven, and grill to minimize preparation time for the meal by determining which item should be cooked in which conditioner 570, in which order, to maximize usage of each conditioner 570 in conditioning system 510. In this example, while the turkey is being defrosted in the microwave oven, controller 530 could instruct consumer 540 through interface 560 to place the bread dough in the convection oven and the acorn squash on the grill. Following the defrosting of the turkey, when the turkey is moved to the convection oven, which finished baking the bread, the bread could be moved to the grill for browning, and the acorn squash could be moved to microwave oven to keep warm, until the entire meal is ready.
For example, if nutritional substance 520 is a ready-to-eat frozen dinner which needs to be heated by conditioner system 510, nutritional substance reader 590 would read a label on nutritional substance 520 thereby receiving information regarding nutritional substance 520, and then provide the information to controller 530. This information could include creation information as to the creation of the various components which constitute the ready-to-eat dinner. This information could include information about where and how the corn in the ready-to-eat dinner was grown, including the corn seed used, where it was planted, how it was planted, how it was irrigated, when it was picked, and information on fertilizers and pesticides used during its growth. Additionally, this information could include the cattle lineage, health, immunization, dietary supplements that were fed to the cattle that was slaughtered to obtain the beef in the ready-to-eat dinner.
The information from a label on nutritional substance 520 could also include information on how the components were preserved for shipment from the farm or slaughterhouse on their path to the nutritional substance transformer who prepared the ready-to-eat dinner. Additional information could include how the nutritional substance transformer transformed the components into the ready-to-eat dinner, such as recipe used, additives to the dinner, and actual measured conditions during the transformation into the ready-to-eat dinner. For example, the information from the label may also contain contingent information to be utilized to optimize a recipe based on various attribute sensors. For example, the label may contain information regarding optimal cooking times and temperatures based on the starting temperature of the read-to-eat frozen dinner as various consumers may set their freezers or refrigerators at different temperatures.
While such information could be stored on a label located on the packaging for nutritional substance 520 so as to be read by nutritional substance reader 590, provided to controller 530, and provided to consumer interface 560 for display to consumer 540, preferably, the label on the nutritional substance package includes reference information, such as a dynamic information identifier, which is read by nutritional substance reader 590 and provided to controller 530 that allows controller 530 to retrieve the information about nutritional substance 520 from nutritional substance database 550, including ΔN information referenced to the dynamic information identifier. Further, linking consumer feedback and updates regarding observed or measured changes in the nutritional, organoleptic, weight, and/or aesthetic values of nutritional substances would provide for virtually real time updates of ΔN information from the actual consumer.
Nutritional substance database 550 could be a database maintained by the transformer of nutritional substance 520 for access by consumers of such nutritional substance 520 to track or estimate changes in the nutritional, organoleptic, and/or aesthetic values of those nutritional substances, as well as any other information about the nutritional substance that can be tracked, including but not limited to the examples previously described. However, preferably, nutritional substance database 550 is a database within information module 100 that is maintained by the nutritional substance industry for all such information regarding nutritional substances grown, raised, preserved, transformed, conditioned and consumed by consumer 540, in which case it is the database contained within information module 100 and also referred to herein as a dynamic nutritional value database. The nutritional substance database 550 may contain information regarding ΔN information for various conditioning protocols applied to specific nutritional substances 520 and/or their components. These ΔN values may be modified based on a sensed weight of a nutritional substance 520 or other sensed characteristics by nutritional attribute sensors 591, and accordingly utilized to provide precise ΔN information to a consumer 540 regarding the particular nutritional substance 520 a consumer may consume or plan on conditioning. Additionally, the conditioning protocols may be easily updatable to allow for various changes to the protocols as described herein, and ΔN information associated with the conditioning protocols may also be updated. Accordingly, the nutritional substance database 550 may be a dynamic database that allows for continually updating and improving the data, so that consumer or end users may have the most current information available or conditioners that access the database 550 may utilize the most current ΔN information allowing the conditioning protocols to be optimized.
In an alternate embodiment of the present invention, controller 530, in addition to providing information regarding nutritional substance 520 to consumer 540, also receives information from conditioner system 510 on how nutritional substance 520 was conditioned. Attribute sensors of conditioner system 510 may measure or sense information about nutritional substance 520 before or during its conditioning by conditioner system 510, including information related to a nutritional, organoleptic, weight, or aesthetic value of the nutritional substance, or a ΔN, and provide such information to controller 530, so that such information could also be provided to consumer 540, via consumer interface 560. Such sensed information may further be required and utilized by an adaptive conditioning protocol.
In a preferred embodiment of the present invention, controller 530 organizes and correlates the information it receives regarding nutritional substance 520 from the various sources of such information, including nutritional substance database 550 and attribute sensors of the conditioner system 510, and presents such information through consumer interface 560 to consumer 540 in a manner useful to consumer 540. For example, such information may be provided in a manner that assists consumer 540 in understanding how nutritional substance 520 meets consumer's 540 nutritional needs before or after conditioning, or how it meets the consumer's needs based on various proposed conditioning parameters. Thus, in one example, the conditioner system may sense an initial weight of the nutritional substance 520, and determine an initial ΔN value prior to conditioning the food based on the weight of the substance and the information in the nutritional substance database 550. Then, the consumer 540 could be presented with various conditioning options, and ΔN values associated with each option so a consumer 540 may determine what is the optimal conditioning method based on their needs. After the consumer 540 selects a conditioning option, and the conditioner 570 conditions the nutritional substance 520, the controller 530 may determine the final nutritional value or ΔN value of the nutritional substance based on the weight, temperature, color, conditioning protocol and reference information in the nutritional substance database 550. Thus, the consumer 540 can track the precise amount of nutrition ingested during the meal. Accordingly, the controller 530 could organize this information regarding nutritional substance 520 to track consumer's 540 weight loss program. Controller 530 could have access to, or maintain, information regarding consumer 540, so as to track and assist consumer 540 in meeting their specific nutritional needs and potentially suggest optimal weights of nutritional substance 540 and/or conditioning protocols to meet a consumer's 540 goals.
In another embodiment of the present invention conditioner system 510 could be a plurality of conditioner devices which can be selectively operated by controller 530 to prepare nutritional substance 520. Conditioner system 510 can be either a single conditioning device, such as a microwave oven, toaster oven, conventional oven, toaster, blender, steamer, stovetop, or human cook. Conditioner system 510 may be a plurality of conditioners 570. In the case where a plurality of conditioners 570 comprise conditioner system 510, nutritional substance 520 may be manually or automatically transferred between conditioners 570 for eventual transfer to consumer 540. Or in other embodiments, different components of a nutritional substance 520 may be placed in the separate conditioners and the controller 530 may condition each component using overlapping condition periods so that each of the components finish conditioning at the same time.
Nutritional substance reader 590 may be an automatic reader such as a barcode reader, QR code reader, or RFID sensor which receives information from nutritional substance 520 or a reference code from nutritional substance 520, such as a dynamic information identifier, and provides this information to controller 530. Nutritional substance reader 590 might also be a manual entry system where the reference code, such as a dynamic information identifier associated with, or provided with the nutritional substance 520 is manually entered into nutritional substance reader 590 for controller 530.
Nutritional substance database 550 could be a flat database, relational database or, preferably, a multi-dimensional database. Nutritional substance database 550 could be local but, preferably, it would be located remotely, such as on the internet, and accessed via a telecommunication system, such as a wireless telecommunication system. Controller 530 can be implemented using a computing device, such as a micro-controller, micro-processor, personal computer, or tablet computer. Controller 530 could be integrated to include nutritional substance reader 590, consumer interface 560, and/or nutritional substance database 550. Additionally, controller 530 may be integrated in conditioner system 510, including integration into conditioner 570.
It is important to note that while
Consumer interface 560 can be implemented as a display device mounted on controller 530, conditioner system 510, or conditioner 570. However, consumer interface 560 is preferably a tablet computer, personal computer, personal assistant, or smartphone, running appropriate software, such as an application.
While conditioner module 500 can be located in the consumer's home, conditioner module 500 may be located at a restaurant or other food service establishment for use in preparing nutritional substances 520 for consumers who patronize such an establishment. Additionally, conditioner module 500 could be located at a nutritional substance seller such as a grocery store or health food store for preparation of nutritional substances 520 purchased by consumers at such an establishment. It could be foreseen that conditioner modules 500 could become standalone businesses where consumers select nutritional substances for preparation at the establishment or removal from the establishment for consumption elsewhere.
Additionally, controller 530 uses nutritional substance information retrieved by nutritional substance reader 590 from nutritional substance 520, or retrieved from nutritional substance database 550 using reference information obtained by nutritional substance reader 590 from nutritional substance 520, to dynamically modify the operation of conditioner system 510 to maintain nutritional, organoleptic, and aesthetic properties of nutritional substance 520. For example, if the nutritional substance 520 is a ready-to-eat dinner, controller 530 could modify the instructions to conditioner system 530 in response to source and ΔN information regarding corn used in the ready-to-eat dinner such that a temperature and cooking duration can be modified to affect the nutritional, organoleptic, or aesthetic properties of the corn. Further, the dynamically modified conditioning parameters, also referred to herein as adaptive conditioning parameters, may be directly intended to optimize a nutritional, organoleptic, or aesthetic property of the corn targeted by the transformer of the ready-to-eat dinner during transformation.
In an embodiment of the present invention, the label on nutritional substance 520 could contain the conditioning instructions for nutritional substance 520, or a reference, such as a dynamic information identifier, to such conditioning instructions in nutritional substance database 550. The conditioning instructions in such a database may include easily modifiable or replaceable instructions to allow the instructions to be updated but accessed using the same dynamic information identifier. In some embodiments, the label on the nutritional substance 520 could contain a variety of conditioning instructions and an associated ΔN value by weight of the nutritional substance 520 for each conditioning option or for each separate component or ingredient of the nutritional substance 520. This may also include various contingent conditioning instructions, including weight based, or temperature based conditioning instructions as described herein. In operation, this would allow controller 530 to obtain information about nutritional substance 520 on how to dynamically operate conditioner system 510 to condition nutritional substance 520, without consumer intervention based on the weight of the nutritional substance 520 as determined by a weight sensor or scale integrated with the conditioner 570 or separately connected to the conditioning system 100 as a standalone appliance. Additionally, adaptive conditioning instructions for nutritional substance 520 could be provided for a variety of different conditioner systems 510, or conditioners 570, and controller could select the proper adaptive conditioning instructions, based on, for example, a desired ΔN value and the weight of the nutritional substance 520. The dynamic operation of conditioner system 510 may be directly intended to optimize a nutritional, organoleptic, or aesthetic property of the nutritional substance 520 targeted by the transformer of the nutritional substance during transformation. In such a case, the operation of conditioner system 510 is according to adaptive conditioning parameters determined by the transformer and responsive to the transformer's knowledge of post transformation residual nutritional, organoleptic, or aesthetic values. The transformer's knowledge of post transformation residual nutritional, organoleptic, or aesthetic values is preferably determined by measurements made during or at completion of transformation, such as data obtained from nutritional substance attribute sensors, including weight sensors.
Adaptive control is the control method used by a controller adapts to a controlled system with parameters which vary or are initially uncertain. In the context of the present disclosure, adaptive control is provided by an adaptive nutritional substance 520 conditioning system responsive to information regarding a nutritional or organoleptic value, including the weight of the substance 520, hydration of the substance 520, or other sensed attributes, before and during conditioning. In an exemplary embodiment the adaptive nutritional substance conditioning system includes a dynamic information identifier associated with a nutritional substance by a provider of the nutritional substance and referenced to a nutritional or organoleptic value determined prior to conditioning. An attribute sensor is provided for sensing information related to the nutritional or organoleptic value during conditioning, which may include a weight sensor or scale. The weight sensor or scale may be integrated with the conditioner 570, to allow the continuous sensing of the weight of the nutritional substance 520 during conditioning. Various other attribute sensors may be included, including (1) weight, (2) a visible light camera, (3) and infrared camera, (3) ambient moisture, (4) ambient temperature, (5) a wireless probe or (6) a spectrometer sensor. A reader reads the dynamic information identifier and retrieves adaptive conditioning parameters referenced to the dynamic information identifier. A controller is provided and configured to provide adaptive conditioning parameters responsive to the nutritional or organoleptic value determined prior to conditioning, the information sensed during conditioning, for maintaining a target post conditioning residual nutritional or organoleptic value. In another exemplary embodiment an adaptive nutritional substance conditioning system includes an attribute sensor for obtaining information related to a nutritional or organoleptic value prior to conditioning and during conditioning. A database is provided comprising historical attribute information for known nutritional substances at known nutritional or organoleptic values. The system also includes a controller configured to provide adaptive conditioning parameters responsive to sensing information obtained prior to conditioning, sensing information obtained during conditioning, and a desired target for the nutritional or organoleptic value following conditioning. The system and database may be a dynamic database that contains dynamic conditioning protocols and associated target nutritional or organoleptic values that may be changed or modified as further testing or consumer feedback determines that certain optimal values are more beneficial.
In an embodiment, information for the adaptive conditioning of a nutritional substance, responsive to a post transformation residual nutritional, organoleptic, or aesthetic value of the nutritional substance or component nutritional substances thereof, as measured by the transformer, is provided by the transformer with the nutritional substance. Such adaptive conditioning information may be provided in any known manner, to be directly read by a reader of the conditioning module, including, but not limited to a dedicated part of a conditioning appliance, a smartphone, or a consumer. Labeling or tags provided with the nutritional substance, such as, but not limited to, QR codes, RFID tags, or written language instructions, could directly communicate the adaptive conditioning information to a reader of the conditioning module, such as an optical scanner, a RFID reader, or a consumer, respectively. Such adaptive conditioning information would comprise one or more adaptive conditioning sequences responsive to the post transformation residual nutritional, organoleptic, or aesthetic value and further responsive to, and unique to, one or more target post conditioning residual nutritional, organoleptic, or aesthetic values, including the weight of the nutritional substance 520. The one or more target post conditioning residual values are predetermined by the transformer and communicated to the consumer as options, such as through written language instructions provided with the nutritional substance, or through a consumer interface of the conditioning module, including, but not limited to, the screen of a conditioning appliance or smartphone. The post adaptive conditioning residual values of a transformed nutritional substance may be determined by the transformer in any known fashion, including, but not limited to, knowledge of a post transformation nutritional, organoleptic, or aesthetic value and estimation of a ΔN associated with specific adaptive conditioning sequences based on historical data regarding ΔNs, knowledge of a post transformation nutritional, organoleptic, or aesthetic value and calculation of a ΔN associated with specific adaptive conditioning sequences based on algorithms developed using historical data regarding ΔNs, or by measurement of the post conditioning residual value after conditioning by specific adaptive conditioning sequences, such as in the transformer's test kitchen or laboratory. Upon selection of the desired option, the corresponding adaptive conditioning sequence can be provided to the controller of the conditioning module. The adaptive conditioning sequence can be entered into the controller of the conditioning appliance manually by the consumer, or might be entered directly by the reader of the conditioning appliance, or by a smartphone communicating in a wired or wireless fashion with the conditioning appliance.
In another embodiment, such adaptive conditioning information may be provided by reference to a unique identifier provided with the nutritional substance, wherein the unique identifier may be read by a reader of the conditioning module, including, but not limited to a dedicated part of a conditioning appliance or a smartphone. Labeling or tags provided with the nutritional substance, such as, but not limited to, QR codes, RFID tags, or written language instructions, could communicate the unique identifier referenced to the adaptive conditioning information to a reader of the conditioning module, such as an optical scanner for scanning a QR code or a RFID reader for scanning a RFID tag. The unique identifier could then be used to retrieve the adaptive conditioning information referenced to it from an adaptive conditioning database. This database may be updatable to allow for additional adaptive conditioning protocols to be added, and/or new information regarding the protocols to be associated with them as described herein. Such a database might be an independent database maintained by the transformer of the nutritional substance or maintained by the nutritional substance industry, and may further be part of the nutritional substance industry database 558 or a part of any database within the nutritional substance industry database 558. The adaptive conditioning information would comprise one or more adaptive conditioning sequences responsive to the post transformation residual nutritional, organoleptic, or aesthetic value and further responsive to, and unique to, one or more target post conditioning residual nutritional, organoleptic, weight, or aesthetic values. The one or more target post conditioning residual values are predetermined by the transformer and communicated to the consumer as options, such as through a consumer interface of the conditioning module, including, but not limited to, the screen of a conditioning appliance or smartphone. The post adaptive conditioning residual values of a transformed nutritional substance may be determined by the transformer in any known fashion, including, but not limited to, knowledge of a post transformation nutritional, organoleptic, or aesthetic value and estimation of a ΔN associated with specific adaptive conditioning sequences based on historical data regarding ΔNs, knowledge of a post transformation nutritional, organoleptic, or aesthetic value and calculation of a ΔN associated with specific adaptive conditioning sequences based on algorithms developed using historical data regarding ΔNs, or by measurement of the post conditioning residual value after conditioning by specific adaptive conditioning sequences, such as in the transformer's test kitchen or laboratory. Upon selection of the desired option, the corresponding adaptive conditioning sequence can be provided to the controller of the conditioning module. The adaptive conditioning sequence can be entered into the controller of the conditioning appliance manually by the consumer, or might be entered directly by the reader of the conditioning appliance, or by a smartphone communicating in a wired or wireless fashion with the conditioning appliance.
Regardless of whether the adaptive conditioning information is provided directly by the nutritional substance or provided by reference to a unique identifier provided with the nutritional substance, the conditioning appliance may be provided with nutritional substance attribute sensors and the adaptive conditioning sequence may require feedback from some or all of the attribute sensors, in which case the nutritional substance is adaptively conditioned responsive to post transformation nutritional, organoleptic, or aesthetic values determined by the transformer, target post conditioning nutritional, organoleptic, or aesthetic values determined by the transformer and selected by the consumer, and feedback from nutritional substance attribute sensors provided before or during conditioning. Such conditioning appliances and adaptive conditioning sequences may be particularly effective in achieving the same desired post conditioning results from different conditioning appliances, different conditioning appliance model numbers, and conditioning appliances from different manufacturers.
In an embodiment of the present invention, nutritional substance reader 590 and/or attribute sensors of conditioner system 510 measure or sense information about the current state of nutritional substance 520, particularly about a nutritional, weight, organoleptic, or aesthetic value, and provides such information to controller 530 before or during conditioning to allow controller 530 to dynamically modify operation of conditioner system 510.
In an additional embodiment of the present invention, consumer 540 provides information regarding their needs and/or desires with regard to the nutritional substance 520 to consumer interface 560. Consumer interface 560 provides this information to controller 530 so as to allow controller 530 to dynamically modify conditioning parameters used by conditioner system 510 in the conditioning of nutritional substance 520 or separately for its components or ingredients, or to request from nutritional substance database 550 dynamically modified conditioning parameters to be used by conditioner system 510 in the conditioning of nutritional substance 520. These parameters provided by the consumer 540 may be saved in a local memory or may be added to a consumer 540 profile in the nutritional substance database 550. Consumer's 540 needs and/or desires could include nutritional parameters, taste parameters, aesthetic parameters. For example, consumer 540 may have needs for certain nutrients which are present in nutritional substance 520 prior to conditioning. Controller 530 could modify operation of conditioner system 510 so as to preserve such nutrients based, for example, on the weight, temperature, or color of the substance. For example, conditioner system 500 can cook the nutritional substance at a lower temperature and/or for a shorter duration so as to minimize nutrient loss, and depending on the overall weight, starting temperature, of the substance may target a specific quantity of a certain nutrient. The consumer's 540 needs and/or desires may be related to particular nutritional, organoleptic, an/or aesthetic values, and may additionally be related to other nutritional substance attributes that are retrievable through the nutritional substance database 550 using a dynamic information identifier, such as nutritional substance additives, preservatives, genetic modifications, origins, and traceability. Further, the consumer's needs and/or desires could be part of a consumer profile provided to the controller 530 through the consumer interface 560 or otherwise available to controller 530. The consumer's needs and/or desires could be exclusionary in nature, for example no products of animal origin, no peanuts or peanut-derived products, no farm raised products, no pork products, no horsemeat products, or no imported products. In these cases, the nutritional substance database 550 could provide information that would prevent the consumer from preparing and/or consuming products that the consumer cannot, should not, or prefers not to consume.
The consumer's 540 nutritional, organoleptic or aesthetic desires could include how rare or well done they prefer a particular nutritional substance to be prepared. For example, consumer 540 may prefer his vegetables to be crisp or pasta to be prepared al dente. With such information provided by consumer 540 to controller 530 through consumer interface 560, controller 530 can dynamically modify operation of conditioner system 510 responsive to the consumer information and provide a nutritional substance according to the consumer's desires.
In an embodiment of the present invention, controller 530 receives information regarding the history of nutritional substance 520, current information on nutritional substance 520, including information regarding a ΔN and weight, and consumer 540 needs or desires, and dynamically modifies operation of conditioner system 510 responsive to the information so as to provide a nutritional substance according to the consumer's needs or desires. For example, if nutritional substance 520 is a steak, controller 530 would receive reference information, such as a dynamic information identifier, regarding the steak, nutritional substance 520, from nutritional substance reader 590, and determine the weight of the steak, using a scale or other weight sensor. Controller 530 would use this reference information to obtain information about the steak from nutritional substance database 550, including information regarding a ΔN and modify the ΔN value based on the weight detected. Controller 530 could also receive current information about the steak from nutritional substance reader 590 or from other attribute sensors of the conditioner 510. Additionally, controller 530 could receive consumer 540 preferences from consumer interface 560. Finally, controller 530 could receive information from attribute sensors of the conditioner system 510 during the conditioning of the steak, nutritional substance 520, including the weight of the steak. Using some or all of such information, controller 530 would dynamically modify the cooking of the steak to preserve, optimize, or enhance organoleptic, nutritional, and aesthetic properties to meet the consumer's 540 needs. For example, the steak could be cooked slowly to preserve iron levels within the meat, and also cooked to well-done to meet consumer's 540 taste.
In a further embodiment, the consumer may provide experience input, such as through consumer interface 560, regarding his experience and satisfaction with the adaptively conditioned nutritional substance. Such experience input may be stored by controller 530, so that it can be utilized in the future for possible further modification of conditioning parameters for similar nutritional substance. In this way, the controller learns how to adapt, or not adapt, conditioning parameters responsive to the consumer's experience input. For example, the consumer input through the consumer interface of a toaster oven when placing a piece of fish into the toaster oven may be that he desires the fish to be rare after conditioning. After conditioning, the consumer may provide his experience input regarding the conditioned fish through the consumer interface, such as by selecting a description of the conditioned fish from a screen providing the options of “under cooked”, “rare”, “medium”, and “well done”. If the consumer selected “under cooked”, the toaster oven controller could further modify future conditioning parameters for fish to provide longer exposure to heat. If the consumer selected “rare”, the controller would not further modify future conditioning parameters for fish. If the consumer selected “medium”, the controller could adapt future conditioning parameters for fish to provide less exposure to heat. If the consumer selected “well done”, the controller could adapt future conditioning parameters for fish to provide reduced heat and duration of exposure to heat.
Conditioner system 510 can prepare a nutritional substance for consumer 540 which contains a plurality of nutritional substances 520. Conditioner module 500 includes recipe database 555 which is operably connected to controller 530. Recipe database 555 can be part of nutritional substance database 550, or it can be a stand-alone database . . . . While recipe database 555 can be located locally, it is preferably accessible to many conditioner modules 500 through a telecommunications system such as the internet, including wireless telecommunications systems. Accordingly, the recipe database 555 may be contained at a remote server within a center where the recipes can be modified and updated.
In some embodiments, recipe database 555 will contain a database of dynamic recipes or dynamic conditioning protocols that may be modified or replaced. This will allow the recipes to be updated as improvements are made to the recipes or recipes are developed for a particular nutritional substance 520 and/or its component ingredients. Nutritional substance may be an entire meal or individual ingredients or portions of a meal or food, and other things as described herein. Accordingly, a manufacturer of food items using the disclosed system would be able to update recipes 555 without printing new labels or reconfiguring electronic tags that store cooking instructions. Accordingly, end users with conditioners 520 that access the recipe database 555 with dynamic recipes will be provided the latest and best available recipes.
The recipe database 555 that has dynamic conditioning protocols or recipes may be indexed in any appropriate fashion and may have a variety of organizational hierarchies and associations. For example, the database may contain certain conditioning protocols that are associated with or linked to certain specific nutritional substances 520. In some embodiments, the nutritional substance 520 will be associated with a dynamic information identifier which may be linked to at least one or a plurality of dynamic conditioning protocols in the recipe database 555. Accordingly, as new nutritional substances 520 are added to the database 555, they may be associated with existing dynamic information identifiers or associated with a new dynamic information identifier. Thus, the conditioning protocols associated with a specific dynamic information identifier may be modified or changed or added to without altering the dynamic information identifier. This will allow the conditioning protocols to be updated or added with minimal cost and disruption to the system. As new dynamic information identifiers are added to the system, they may also be easily associated with existing conditioning protocols to allow for easy adding of new nutritional substances 520 to the system that are similar to existing nutritional substances in recipe database 555.
Dynamic recipes or conditioning protocols 610 may be conditioning protocols that that are updated including by modifying or replacing information in the recipe database 555. Various aspects of the dynamic recipes or conditioning protocols may be updated including total cooking time, target temperatures, or any other factors that may be controlled with a conditioning protocol 610 as disclosed herein. In some embodiments, the dynamic conditioning protocol may be to cook a nutritional substance at a certain temperature for a certain amount of time. In other embodiments, the dynamic conditioning protocols may include other instructions, including a variable or stepped cooking, a curve of temperature versus time for the oven, controls of other aspects of a conditioner 520. Additionally, the dynamic conditioning protocols may include information regarding the type of conditioner 520 employed for usage, or include references to multiple conditioners 520. For example, a recipe for cooking salmon may vary based on whether it is being cooked by a conventional convection oven, a microwave oven, others. In other embodiments, separate conditioning protocols may be utilized for separate conditioners 520. single meal. For example, each conditioner 570 may have a different set of dynamic conditioning protocols. These may be stored in the same recipe database 555 or in different recipe databases 555. In another embodiment, a single conditioning protocol 610 may control multiple conditioners to condition the components of a
In some embodiments, recipes may contain various options that require consumer input 620 once a certain conditioning protocol has been selected. Accordingly, the recipe may contain options or conditional parameters that are implemented based on consumer input. These parameters may be a level of cooking (e.g., well done, medium rare) for meat, crispiness for crust or other nutritional, organoleptic, or aesthetic values. In other embodiments, the consumer 540 may even be presented with various ranges or scales in which a consumer 540 can select a preference over a continuum, for example the range of doneness for meat to fine tune their preference. The associated dynamic conditioning protocol in such an embodiment than may include dynamic ranges and preference indications or requirements that a consumer provide feedback on the doneness.
An example of a dynamic recipe for cooking, wild salmon may include various instructions for a smart oven or other conditioner 570 that includes both convention and microwave elements. The dynamic recipe may first require input of whether the salmon is frozen or chilled. Accordingly, the dynamic recipe may include a thawing out step that is triggered or implemented if consumer input 620 indicates that the salmon is frozen. Additionally, the system may require the salmon to be microwaved first for a brief amount of time to cook the inside, and this may include a microwave execution instruction at a specific intensity for a given amount of time. The recipe may then specify that after the microwaving stage is complete, that a convention oven heating element be initiated at a certain output or temperature for a second time span. In other embodiments, alternating conditioning types, or a variable temperature or intensity scheme may be utilized for the recipe. Additionally, the amount of doneness may also be selected by the consumer.
The dynamic recipe may be a hierarchy of different recipes that may be selected depending on input from the system or a consumer 620 or both. For instance, several recipes may be linked in a tree based on system and consumer input, or the system and consumer input 620 may modify the appropriate portions of the recipe. As one example, the first input may be data indicating the type of conditioner that is requesting the recipe, including either: (1) a convection oven, a (2) microwave oven, (3) or a combination smart oven, or (4) other conditioner types. For each of these types of conditioner 620, there may be a different conditioning protocol linked in the hierarchy that provides instructions to control the specified conditioner 520. Then, the hierarchy may include different types of recipes for a certain type of food. For example, for a piece of chicken there may be the choice of simple baked chicken, chicken parmesan or other recipes. For recipes like chicken parmesan, there may be parts of the recipe that indicate when, for example, cheese should be added and to modify the temperature to optimize the melting and texture of the cheese. After choosing the type of recipe, an end user may also fine tune how they would like the recipe executed. In some embodiments, the recipe or conditioning protocol may include ranges for the temperature and time periods that may result in various nutritional, organoleptic or aesthetic values after conditioning. For example, the temperature may be raised or lowered for certain stages or time periods or raised or lowered overall in order to change the crispiness of chicken skin. Accordingly, these variables may be conditionally built into the recipe to allow for user input 620. The recipe itself may be made of any suitable data structure and variables. In some embodiments, the data structure is constructed to allow for easy modification or replacement of certain portions. The recipe data may also be encrypted as it is sent over networks.
In some embodiments, the recipe may include multiple portions that are responsible for independently instructing a separate conditioner 570 for conditioning a separate part of a meal—for instance a frozen meal in separate portions. Therefore, the recipe may be a unified whole for cooking a meal, for example a frozen meal sold together, and its various components in separate conditioners 570. Therefore, the recipe will be able to coordinate the conditioning of the various components of the nutritional substance 520 so that they are all ready at the same time. The dynamic condition protocols for multi-ingredient foods therefore may be composed of multiple dynamic recipes 610 for each separate ingredient that are capable of independently controlling separate conditioners 570 at times and temperatures that would coordinate the conditioning between each ingredient of the nutritional substance.
The dynamic recipe may also be updatable or able to replace certain portions in order to account for modifications to the recipe. For example, if testing shows that the organoleptic, aesthetic, or nutritional value is enhanced by a hotter but shorter conditioning period, the cooking temperature and/or time may be modified. In embodiments in which the main recipe comprises multiple recipes in a hierarchy or a recipe with contingent instructions, only certain sub recipes may be updated or contingent portions of the recipe may be updated. In other embodiments, the modification may incorporate a new subordinate recipe in the hierarchy or add a new contingent portion of the recipe that requires consumer input 620. For example, if it is a recipe for baking chicken, perhaps experimental cooking has found that the chicken is better cooked for a very hot final short temperature to obtain crispy skin and the current temperature is too low. There may be a module connected with the database that would receive input from a user interface or automated input that updated the temperature and or time for the final cook. The new temperature data point could then be substitute in the recipe and various sub-portions of the dynamic recipe in the recipe database 555.
The system may also include a conditioner module 500 or controller 530 that retrieves a dynamic conditioning protocol over a port, interface or some kind of input and implements it by controlling the conditioner 570. As described throughout, a conditioner module 500, a conditioner 570, or other components may include a nutritional substance reader 590 that reads a label or other identifying information from the nutritional substance 520 in order to identify the nutritional substance 520. That identity information detected from the nutritional substance 520 or label may then be transmitted to the controller 530, for instance by sending to a port which may be received by a module 500 in which the controller 530 may be incorporated. The controller 530 may then send or reincorporate the data into a request packet(s) sent out of a port or interface over a network to a servers or other computing platforms that host a recipe database 555 and/or a nutritional substance database 550 in order to retrieve or request an appropriate conditioning protocol to be sent back to the same port and/or IP address of the sender or in some embodiments a different address. In some embodiments, the controller 530 may also append information to the packet of information identifying the type or specific conditioner 570 utilized in the requesting system. Accordingly, this may include information regarding what types and the capabilities or specific identity of the conditioner to allow the recipe to be modified or selected to match the conditioner. For example, if the conditioner 570 is a microwave, the conditioning protocol selected would be one that only includes microwave instructions. Additionally, the conditioning protocol selected must be compatible with the particular microwave, as it may have certain settings or pre-set radiation levels that the recipe can only utilize. Accordingly, once a remote server that hosts the database 555 receives the packet, the server will access and send the appropriate dynamic conditioning protocol(s) to the module 500 and/or controller 530. In some embodiments, the server may host several databases and the packet sent may include identifying information specific to the food and/or associated conditioner that allows the server to route the packet to the appropriate database or to request data from the appropriate database.
The recipe information sent over the network back to the module 500 or controller 530 may include instructions directly executable by the controller 530 or module 500 which in turn controls the conditioner 570 or may require a translation module to prepare instructions that are executable directly by the conditioner 570. In some embodiments, these instructions received by the module 500 and/or controller 530 may include an ability to display options for a consumer 540 prior to receiving consumer input 620. This may include displaying the contingent portions of the dynamic conditioning protocol and/or displaying the alternative conditioning options available. For example, various types of recipes and conditioning protocols could be displayed, (e.g. chicken masala, baked chicken, chicken parmesan) and various ranges or preferences for each type of recipe could be displayed (well done, crispy skin, juicy, etc.). Accordingly, the end user could then enter input regarding their preference for recipe and any specifics required including separate ingredients that would be separately conditioned. Once the user input 620 is received, the controller 530 could then process and synthesize the recipe, any information derived from either the recipe database 555 and/or the nutritional substance database 550 and compile or synthesize the data into an executable instruction set that the conditioner(s) 570 may then execute.
In some embodiments the recipe or conditioning protocol may be modifiable in real time via feedback from nutritional substance attributes sensors 591 as disclosed herein or may be modifiable based on consumer modifications during cooking. This may include new or other consumer input 620.
Controller 530 is also preferably connected to consumer database 580. Consumer database 580 may be additionally connected to consumer interface 560. Consumer database 580 could include consumer's 540 organoleptic and nutritional needs, and consumer 540 preferences, and could be in the form of a consumer profile custom tailored to an individual consumer or selected from a menu of consumer profiles. Consumer database 580 may receive input regarding consumer 540 from consumer 540, but could also include information supplied by consumer's 540 medical records, exercise records for the consumer's gym, and other information sources. Consumer database 580 could include information regarding regulatory actions and/or manufacturer warnings or recalls of nutritional substances which may be obtained, have been obtained, or may be prepared or consumed by the consumer. Additionally, consumer database 580 could include information regarding consumer's 540 preferences provided by controller 530 for previous nutritional substance 520 conditionings, and may further include consumer experience input regarding his experience and satisfaction with previously conditioned nutritional substances. Consumer database 580 could include consumer preferences from external sources such as restaurants and grocery stores where consumer 540 purchases nutritional substances 520. Finally, consumer database 580 could include information from consumer module 600, in
Consumer database 580 could be a local database maintained by controller 530 or consumer interface 560. Preferably, consumer database 580 is part of a nutritional substance industry database containing such information regarding a plurality of consumers 540.
For example, controller 530 can operate to select the necessary ingredients, nutritional substance 520, to prepare a meal. In this case, nutritional substance 520 could be a plurality of nutritional substances 520. In operation, consumer 540 could select a dinner menu using consumer interface 560. Additionally, consumer 540 could select a specific recipe from recipe database 555 or could select a recipe source within database 555, such as low salt meals or recipes by a certain well-known chef. Controller 530 could prepare a shopping list for consumer 540 through consumer interface 560. Alternatively, controller 530 could transmit a shopping list to a nutritional substance 520 supplier such as a grocery store, so consumer 540 could pick up such items already selected or could have such items delivered.
Alternatively, if instructed by consumer 540 to utilize nutritional substances on hand, which have been logged into controller 530 through nutritional substance reader 590, controller 530 could modify or suggest a recipe that used only nutritional substances 520 available to conditioner module 500. For example, if consumer 540 instructs conditioner module 500 through conditioner interface 560 that consumer 540 would like Italian food in the style of a well-known Italian chef, controller 530 would utilize information in its various databases to prepare such a meal. In this case, controller 530 would match its inventory of available nutritional substances with recipes from the well-known Italian chef in recipe database 555 and find available recipes. Controller 530 could select a recipe that optimized consumer's 540 needs and preferences and prepare a meal using conditioner system 510. Alternatively, controller 530 could present various options to consumer 540 using consumer interface 560, highlighting features of each available meal from the standpoint of consumer's 540 nutritional needs and/or preferences. In another embodiment, nutritional substances 520 available to conditioner module 500 may additionally, or alternatively, comprise nutritional substances 520 which have been logged into local storage environments, containers, and coupons in proximity to the conditioner system 510, such as through nutritional substance readers associated with the local storage environments, containers, and coupons.
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In an embodiment of the present invention, a consumer wishing to condition a nutritional substance using a conditioning appliance according to the present invention can determine, and knowingly affect, the true residual nutritional, organoleptic, or aesthetic value of the nutritional substance after he puts it in the conditioning appliance. To do so, the consumer would scan a dynamic information identifier provided with the nutritional substance using a scanner provided with, or associated with, the conditioning appliance. This enables the conditioning appliance's controller to retrieve, from the nutritional substance industry database, information related to changes in nutritional, organoleptic, or aesthetic values (ΔN information) referenced to the dynamic information identifier. Thereafter, the conditioning appliance controller can request and receive input from the consumer by providing options for the consumer to choose from through a consumer interface, also referred to herein as a dynamic nutritional substance menu panel, which may be a panel, screen, keyboard, or any known type of user interface. The dynamic nutritional substance menu panel provides the consumer with the ability to input the desired end results for the residual nutritional, organoleptic, or aesthetic value that will remain after conditioning, such as by choosing among different possible end results offered by the dynamic nutritional substance menu panel. The controller then creates, or retrieves from the nutritional substance industry database, adaptive conditioning parameters that are responsive to: the ΔN information retrieved from the nutritional substance industry database using the dynamic information identifier; and the consumer input obtained through the dynamic nutritional substance menu panel. As described herein, the database may contain recipes or adaptive conditioning protocols that have various parameters that are associated with various ΔN values. This allows a controller 530 to create a specialized recipe optimized to the consumer's desired ΔN values.
As mentioned before reader 590 transmits information with in database 550 and conditioner systems 570 the current invention includes a proprietary machine-readable recipes module 555. This method allows for recipes to seamlessly recommend options with the inventory on hand without the need to type in or go through human read instructions. The method if integrating this database is breaktrough to the Industry and work has begun in this direction with content providers like Good House Keeping and the New York Times.
In other embodiments, the adaptive conditioning parameters or recipe may first be retrieved from a nutritional substance industry database. Then the parameters may indicate the consumer feedback or preferences are required as input consumer feedback, including the ΔN values. It is understood that in the case of conditioning appliances provided with nutritional substance attribute sensors, the adaptive conditioning parameters may further be responsive to information provided by the attribute sensors before or during conditioning, including the weight of the nutritional substance 520. It is also understood that in the case of conditioning appliances provided with the ability to obtain experience input from a consumer, the adaptive conditioning parameters may further be responsive to information provided by the consumer regarding a previous consumption of a similar nutritional substance. These adaptive conditioning parameters, also referred to herein as an adaptive preparation sequence, are then communicated to the consumer for implementation through the dynamic nutritional substance menu panel, or alternatively, automatically implemented by the controller.
For example, the consumer 540 is ready to prepare a macaroni and cheese entrée using a combination microwave, convection, and grill oven, according to the present invention. Further, the consumer wants to serve the entrée as soon as possible. The consumer first uses the combination oven's scanner to scan the dynamic information identifier provided with the macaroni and cheese entrée. The dynamic information identifier may be an optically readable label, an RFID tag, or any other known format compatible with the combination oven's scanner, attached to, or incorporated into, the nutritional substance or its packaging. The combination oven controller then retrieves the ΔN information referenced to the dynamic information identifier from the nutritional substance industry database. The conditioning appliance's controller additionally requests input from the consumer regarding the desired residual nutritional, organoleptic, or aesthetic value of the macaroni and cheese entrée following conditioning, by providing options for the consumer to choose from through its dynamic nutritional substance menu panel. It is understood that these options may be presented in any known fashion, and while particular presentation forms will be discussed herein, they are in no way limiting. In this example, the dynamic nutritional substance menu panel presents options for the consumer to choose from in a format similar to the options provided by routing and navigation applications (i.e. “shortest distance”, “shortest time”, “least freeway travel”, and so forth). For instance, the options provided by the dynamic nutritional substance menu panel may be “fastest preparation time”, “highest nutritional value”, and “crispy topping” (corresponding to highest organoleptic value for texture). The consumer can find out more detailed information regarding the residual nutritional, organoleptic, and aesthetic values that will result from a particular option by selecting that option, whereupon the dynamic nutritional substance menu panel will provide a summary of the corresponding residual nutritional, organoleptic, and aesthetic values, also referred to herein as a nutritional substance residual value table. The dynamic nutritional substance menu panel may further provide other useful information, such as, but not limited to, the corresponding amount of conditioning time required to achieve the selected option. If the consumer determines that he is not pleased with his selection based upon the more detailed information provided through the dynamic nutritional substance menu panel, particularly the information in the nutritional substance residual value table, he can return to the previous screen and choose another option. The consumer can continue to select options, review the more detailed information in the corresponding nutritional substance residual value table, as well as the other useful information provided, until he determines that an option meets his requirements. Upon determining that an option meets his needs, particularly needs related to the information about residual nutritional, organoleptic, and aesthetic values summarized by the nutritional substance residual value table, the consumer proceeds with the option using the dynamic nutritional substance menu panel, such as by selecting “proceed”. The conditioning appliance controller then implements the adaptive preparation sequence, that is, the adaptive conditioning parameters that are responsive to: the ΔN information it has retrieved from the nutritional substance industry database using the dynamic information identifier provided with the macaroni and cheese entrée; and the consumer input obtained through the dynamic nutritional substance menu panel. The adaptive preparation sequence assures that the consumer will be provided with a conditioned macaroni and cheese entrée that meets his needs, particularly his needs related to residual nutritional, organoleptic, and aesthetic values of the conditioned entrée.
In one example of the present invention, the consumer wishing to prepare the macaroni and cheese entrée selects the “fastest preparation time” option on the dynamic nutritional substance menu panel, as he needs to eat as soon as possible. The dynamic nutritional substance menu panel then provides the consumer with a nutritional substance residual value table showing the residual nutritional, organoleptic, and aesthetic values that will result from adaptively conditioning the macaroni and cheese entrée with the corresponding adaptive preparation sequence, and additionally provides the amount of time required to do so. The consumer determines from the nutritional substance residual value table that one of the entrée's residual nutritional values, for the purpose of this example, its complex carbohydrate content, will be 20% of its starting value. It is understood that the nutritional substance residual value table may provide any number of individual residual nutritional values, such as residual protein content, residual folic acid content, and so forth, and that those provided for the purpose of this example are in no way limiting. It is also understood that residual nutritional value may be provided as an aggregated value based on several independent residual nutritional values. The consumer may additionally determine from the nutritional substance residual value table that the entrée's residual organoleptic value for the crispness of its topping after conditioning, will be 10%, where 0% represents not at all crisp and 100% represents very crisp. It is understood that the nutritional substance residual value table may provide any number of individual residual organoleptic values, such as a rating to determine if the macaroni will be al dente, a rating for overall moistness of the casserole, and so forth, and that those provided for the purpose of this example are in no way limiting. It is also understood that residual organoleptic value may be provided as an aggregated value based on several independent residual organoleptic values. The consumer also determines from the dynamic nutritional substance menu panel that the conditioning will take only 10 minutes. Today, preparation time is the most important criteria to the consumer, so he proceeds by placing the macaroni and cheese entrée into the combination oven, closing its door, and selecting the “proceed” option on the dynamic nutritional substance menu panel. The combination oven can now instruct the consumer through its dynamic nutritional substance menu panel on the various settings and time requirements to adaptively condition the macaroni and cheese entrée according to the adaptive preparation sequence. Alternatively, the combination oven's controller can automatically implement the adaptive preparation sequence, so that the consumer is free to do other things while the entrée is adaptively conditioned. If the combination microwave, convection, and grill oven is provided with nutritional substance attribute sensors, for instance weight measurement sensors, temperature sensors, humidity sensors, or color sensors, the adaptive conditioning parameters might further be modified responsive to information provided by the attribute sensors before or during conditioning. For example, if weight sensors are provided, the adaptive conditioning parameters may be modified to target a specific quantity of a nutrient based on the known quantity of this nutrition retrieved from the nutritional substance database by weight and the dissipation by weight for different conditioning protocols.
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It is understood that ΔN meters may take many forms and communicate various messages regarding a ΔN value or a residual nutritional, organoleptic, and/or aesthetic value of nutritional substances, and the examples provided above are for illustrative purposes and not intended to be limiting in any way. It is further understood that ΔN meters may be utilized to communicate ΔN values and residual nutritional, organoleptic, and/or aesthetic values determined or estimated in any fashion. In preferred embodiments, the ΔN value or the residual nutritional, organoleptic, and/or aesthetic value are determined utilizing the nutritional substance information systems disclosed herein, including systems utilizing dynamic information identifiers and corresponding nutritional substance database, systems utilizing nutritional attribute sensors and corresponding nutritional substance attribute library, or a combination of both.
On another day, the same consumer is again going to prepare another one of the same macaroni and cheese entrées in his combination oven. He remembers that the last time he did, he was impressed with the speed of preparation, but wished it would have had higher residual complex carbohydrate values and also wished it had a more crispy topping. Today he has no time constraints, and is more interested in the residual nutritional, organoleptic, and aesthetic values that can be achieved. He scans the dynamic information identifier with the scanner on his combination oven. The oven's controller retrieves ΔN information referenced to the dynamic information identifier from the nutritional substance industry database and additionally requests input from the consumer regarding the desired residual nutritional, organoleptic, or aesthetic value of the macaroni and cheese entrée following conditioning, by providing options for the consumer to choose from through its dynamic nutritional substance menu panel. The options are “fastest preparation time”, “highest nutritional value”, and “crispy topping”. The consumer selects the “highest nutritional value” option from the dynamic nutritional substance menu panel, as he wants to eat a healthy meal. The dynamic nutritional substance menu panel then provides the consumer with a nutritional substance residual value table showing the residual nutritional, organoleptic, and aesthetic values that will result from adaptively conditioning the macaroni and cheese entrée with the corresponding adaptive preparation sequence, and additionally provides the amount of time required to do so. The consumer determines from the nutritional substance residual value table that one of the entrée's residual nutritional values, for the purpose of this example, its complex carbohydrate content, will be 80% of its starting value. It is understood that the nutritional substance residual value table may provide any number of individual residual nutritional values, such as residual protein content, residual folic acid content, and so forth, and that those provided for the purpose of this example are in no way limiting. It is also understood that residual nutritional value may be provided as an aggregated value based on several independent residual nutritional values. The consumer may also be interested in the absolute value of carbohydrates rather than the percentage decrease and accordingly a weight sensor or scale may be used to determine the weight of the nutritional substance, from which the actual nutritional content and prospective change from conditioning may be calculated. The consumer may additionally determine from the nutritional substance residual value table that the entrée's residual organoleptic value for the crispness of its topping after conditioning, will be 30%, where 0% represents not at all crisp and 100% represents very crisp. It is understood that the nutritional substance residual value table may provide any number of individual residual organoleptic values, such as a rating to determine if the macaroni will be al dente, a rating for overall moistness of the casserole, and so forth, and that those provided for the purpose of this example are in no way limiting. It is also understood that residual organoleptic value may be provided as an aggregated value based on several independent residual organoleptic values. The consumer also determines from the dynamic nutritional substance menu panel that the conditioning will take 40 minutes. Today, residual nutritional value is the most important criteria to the consumer, so he proceeds by placing the macaroni and cheese entrée into the combination oven, closing its door, and selecting the “proceed” option on the dynamic nutritional substance menu panel. The combination oven can now instruct the consumer through its dynamic nutritional substance menu panel on the various settings and time requirements to adaptively condition the macaroni and cheese entrée according to the corresponding adaptive preparation sequence. Alternatively, the combination oven's controller can automatically implement the adaptive preparation sequence, so that the consumer is free to do other things while the entrée is adaptively conditioned. If the combination microwave, convection, and grill oven is provided with nutritional substance attribute sensors, such as weight sensors, the adaptive conditioning parameters might further be modified responsive to information provided by the attribute sensors before or during conditioning. In this example, the adaptive preparation sequence requires mostly the application of convection heat with a minute of grill at the end of the sequence to cause a small amount of crispness in the topping without burning the cheese exposed to the grill.
On yet another day, the same consumer is again going to prepare another one of the same macaroni and cheese entrées in his combination oven. He remembers that the last time he did, he was impressed with the high residual nutritional value of the entrée, but wondered if he could achieve a still more crispy topping while achieving acceptable residual nutritional value. Today he has no time constraints, and is more interested in the residual nutritional, organoleptic, and aesthetic values that can be achieved. He scans the dynamic information identifier with the scanner on his combination oven. The oven's controller retrieves ΔN information referenced to the dynamic information identifier from the nutritional substance industry database and additionally requests input from the consumer regarding the desired residual nutritional, organoleptic, or aesthetic value of the macaroni and cheese entrée following conditioning, by providing options for the consumer to choose from through a consumer interface, also referred to herein as a dynamic nutritional substance menu panel. The options are “fastest preparation time”, “highest nutritional value”, and “crispy topping”. The consumer selects the “crispy topping” option from the dynamic nutritional substance menu panel, as he initially wants to find out what the residual nutritional value will be if he prepares the entrée according to his organoleptic preference for a crispy topping. The dynamic nutritional substance menu panel then provides the consumer with a nutritional substance residual value table showing the residual nutritional, organoleptic, and aesthetic values that will result from adaptively conditioning the macaroni and cheese entrée with the corresponding adaptive preparation sequence, and additionally provides the amount of time required to do so. On this day, the amount of macaroni and cheese detected by a weight sensor of the conditioning system 510 is less than on the other day, and the prospective nutritional, organoleptic, and aesthetic values that will result from the proposed adaptive conditioning protocols that will be displayed on the dynamic nutritional substance panel will be modified accordingly. The consumer determines from the nutritional substance residual value table that one of the entrée's residual nutritional values, for the purpose of this example, its complex carbohydrate content, will be 75% of its starting value. It is understood that the nutritional substance residual value table may provide any number of individual residual nutritional values, such as residual protein content, residual folic acid content, and so forth, and that those provided for the purpose of this example are in no way limiting. It is also understood that residual nutritional value may be provided as an aggregated value based on several independent residual nutritional values. The consumer may additionally determine from the nutritional substance residual value table that the entrée's residual organoleptic value for the crispness of its topping after conditioning, will be 97%, where 0% represents not at all crisp and 100% represents very crisp. It is understood that the nutritional substance residual value table may provide any number of individual residual organoleptic values, such as a rating to determine if the macaroni will be al dente, a rating for overall moistness of the casserole, and so forth, and that those provided for the purpose of this example are in no way limiting. It is also understood that residual organoleptic value may be provided as an aggregated value based on several independent residual organoleptic values. The consumer also determines from the dynamic nutritional substance menu panel that the conditioning will take 90 minutes. Today, the residual organoleptic value related to the topping crispness is the most important criteria to the consumer, and he has verified that he makes only a small sacrifice in the residual nutritional value to achieve this, so he proceeds by placing the macaroni and cheese entrée into the combination oven, closing its door, and selecting the “proceed” option on the dynamic nutritional substance menu panel. The combination oven can now instruct the consumer through its dynamic nutritional substance menu panel on the various settings and time requirements to adaptively condition the macaroni and cheese entrée according to the corresponding adaptive preparation sequence. Alternatively, the combination oven's controller can automatically implement the adaptive preparation sequence, so that the consumer is free to do other things while the entrée is adaptively conditioned. If the combination microwave, convection, and grill oven is provided with nutritional substance attribute sensors, the adaptive conditioning parameters might further be modified responsive to information provided by the attribute sensors before or during conditioning. In this example, the adaptive preparation sequence requires mostly the application of low convection heat with 3 intervals of 1 minute of grill at the end of the sequence to cause a significant amount of crispness in the topping.
In a further example, the combination microwave, convection, and grill oven in the used to condition the macaroni and cheese entrée is provided with the ability to obtain experience input from the consumer. In this case, the adaptive conditioning parameters may further be responsive to information provided by the consumer regarding previous consumption of macaroni and cheese entrées prepared by the combination oven. For instance, in the past, the consumer's input regarding the desired texture of macaroni in a macaroni and cheese, or possible other pasta entrées, may have been “al dente”, however his corresponding experience input indicated that the pasta was “overcooked”. The controller of the combination oven can modify the current adaptive conditioning parameters responsive to the previous consumer experience input regarding macaroni and cheese.
There are many examples of sensor technology that might be utilized as a nutritional substance attribute sensor, including, but are not limited to: Surface plasmon resonance sensors (SPR) such as a cell phone based sensor platform disclosed by Preechaburana et at, Angew. Chem. Int. Ed. 2012, 51, 11585-11588, “Surface plasmon resonance chemical sensing on cell phones”; SPR sensors such as those disclosed by Zhang, et al, Zhejiang University, Hangzhou 310058, P. R. China “Detection of penicillin via surface plasmon resonance biosensor”; the combination of microfluidics with Lab-on-a-Chip and Lab-on-a-Foil solutions disclosed by Focke, et al, www.rsc.org/loc, 19 Mar. 2010, “Lab-on-a-Foil: microfluidics on thin and flexible films”; Localized surface plasmon response sensors (LSPR) such as those disclosed by Roche, et al, Journal of Sensors, volume 2011, article ID 406425, doi: 10.1155/2011/406425, “A camera phone localized surface plasmon biosensing platform towards low-cost label-free diagnostic testing”; printed sensors such as those available from Thin Film Electronics ASA, for example the Thinfilm Time-Temperature Sensor; wireless pH sensors such as those discussed in IEE Sensors Journal, Vol 12, No. 3, March 2012 487 “A passive radio-frequency pH sensing tag for wireless food quality monitoring”; sensing of biological quantities such as that discussed in Appl Microbiol Biotechnol (2013) 97:1829-1840 “An overview of transducers as platform for the rapid detection of foodborne pathogens”; cell phone based E. Coli sensor using florescent imaging to detect bacteria in food and water, developed at UCLA Henry Samueli School of Engineering and Applied Science; sensors discussed in Journal of Food Engineering 100 (2010) 377-387 “Biomimetric-based odor and taste sensing systems to food quality and safety characterization: An overview on basic principles and recent achievements”; sensors discussed in Sensors 2010, 10, 3411-3443, doi 10.3390/s100403411 “Advanced Taste Sensors Based on Artificial Lipids with Global Selectivity to Basic Taste Qualities and High Correlation to Sensory Scores”; sensing described in Chem. Sci., 2012, 3, 2542 “Fluorescent DNAs printed on paper: sensing food spoilage and ripening in the vapor phase”; the use of a Silicon Integrated Spectrometer to sense food for ripeness and other qualities is described in IEEE Photonics Journal, 1 (4), p. 225-235 (2009); electronic noses like those discussed by Walt D R., Anal chem 2005 77:A-45; electronic noses like those discussed by Gardner J W et al., Electronic noses: principles an applications. Oxford University press, New York, 1999; colorimetric sensor arrays like those discussed by Suslick et al., Anal Chem 2010 82(5):2067-2073; numerous sensing techniques described in analytica chima acta 605 (2007) 111-129 “A review on novel developments and applications of immunosensors in food analysis”; numerous sensing techniques described in J. Biophotonics 5, No. 7, 483-501 (2012)/doi 10.1002/jbio.201200015 “Surface plasmon resonance based biosensor technique: A review”; LSPR techniques to sense bitterness of tea described in Agric. Food Chem., 2010, 58 (14), pp. 8351-8356 “B-Cyclodextrin/Surface plasmon response detection system for sensing bitter astringent taste intensity of green tea catechins”; a review on nano-biosensors to measure tastes and odors discussed in Bio-Nanotechnology: A revolution in food biomedical and health sciences, first edition, 2013, John Wiley & Sons, Ltd. “Nano-Biosensors for mimicking gustatory and olfactory senses”; techniques described in Science Daily, http://www.sciencedaily.com/releases/2013/02/130214111612.htm, 14 Feb. 2013 “World's most sensitive plasmon resonance sensor inspired by the ancient roman cup”; ethylene sensors discussed in Anal. Chem., 2011, 83 (16), pp. 6300-6307, doi: 10.1021/ac2009756 “Electrochemical sensing of ethylene employing a thin ionic-liquid layer”; multiplex SPR techniques described in Anal Bioanl Chem (2011) 400: 3005-3011, doi 10.1007/s00216-011-4973-8 “Imaging surface plasmon resonance for multiplex microassay sensing of mycotoxins”; a review of noble metal nono-optical sensors based on LSPR by Zhao, et al, “Localized surface plasmon resonance biosensors”; colorimetric plasmon resonance imaging described by Gartia, et al, Advanced Optical Materials 2013, 1, 68-76, doi: 10.1002/adom.201200040 “Colorimetric plasmon resonance imaging using nano Lycurgus cup arrays”; sensor using multiplex fiber-optic biosensor implemented by integrating multiple particle plasmon resonances (PPRs), molecular bioassays, and microfluidics is disclosed by Lin, et al, Proc. SPIE 8351, Third Asia Pacific Optical Sensors Conference, 835125 (Jan. 31, 2012), doi: 10.117/12.914383 “Multiplex fiber-optic biosensor using multiple particle plasmon resonances”; sensor based on multilayered graphene SPR-based transmission disclosed by Kim, et al, J. Nonosci. Nanotechnol, 2012 July 12(7):5381-5 “Evaluation of multi-layered graphene surface plasmon resonance-based transmission type fiber optic sensor”; sensors to detect Mercury values such as the biosensors, chemical sensors, conductometric sensors, microcantilevel sensors, SAW sensors, piezoelectric sensors, and nanosensors similar to those described by: Selid et al, Sensors 2009, 9, 5446-5459; doi: 10.3390/s90705446; and Katherine Davies, Royal Society of Chemistry, Chemistry World, New chemosensor for mercury_detection (http://www.rsc.org/chemistryworld/Issues/2005/July/mercury detection.asp); sensors to detect caffeine values may be similar to those described by: Chung I C, et al, J Nanosci Nanotechnol. 2011 December; 11(12):10633-8, A portable electrochemical sensor for caffeine and (-)epigallocatechin gallate based on molecularly imprinted poly(ethylene-co-vinyl alcohol) recognition element.; or Ebarvia, et al, Analytical and Bioanalytical Chemistry, March 2004, Volume 378, Issue 5, pp. 1331-1337, Biomimetic piezoelectric quartz sensor for caffeine based on a molecularly imprinted polymer.; or Zhao, et al, http://www.researchgate.net/publication/225410860, Department of Material and Chemistry Engineering, Henan Institute of Engineering, Zhengzhou, 450007 China, Article-Voltammetric sensor for caffeine based on a glassy carbon electrode modified with Nafion and graphene oxide; sensors to detect sugar values may be similar to those described by: Kumar, et al, Study of fiber optic sugar sensor; or Scampicchio, et al, Nanotechnology 20 135501 doi:10.1088/0957-4484/20/13/135501, Issue 13, 1 Apr. 2009, Optical nanoprobes based on gold nanoparticles for sugar sensing; sensors to detect temperature values may be similar to those manufactured by MICRO-EPSILON, and described at www.micro-epsilon as miniature non-contact IR sensors thermoMETER CSmicro and non-contact IR sensors with laser aiming thermoMETER CSlaser; sensors for detecting temperature values may also include any thermocouple type sensor suitable for contact sensing of temperature. It is understood that sensors may be configured to perform multiple test assays in a single use to develop a multidimensional dataset from each use.
Other examples of sensor technology that might be utilized includes sensors similar to those manufactured by MICRO-EPSILON and described at www.micro-epsilon as fixed lens color sensors color SENSOR OT-3-GL and OT-3-LU. These sensors illuminate a surface with white light and sense the reflected color values, and are particularly useful for color recognition of non-homogeneous targets and glossy targets, for instance, a piece of beef or other animal tissue packaged in clear cellophane, packaged in shrink-wrap, or not currently packaged. These sensors can also provide useful information regarding the turbidity of liquids. Alternatively, sensors may be similar to those manufactured by MICRO-EPSILON and described at www.micro-epsilon as fiber color sensors, color SENSOR LT-1-LC-20, WLCS-M-41, and LT-2. These sensors use a modulated white light LED to project a spot onto or through a target, and focusing part of the reflected or transmitted light with fiber optic onto a color detector element. Common sensing techniques include, but are not limited to: projecting a spot directly on and normal to an inspection target and focusing part of the back-scattered light with fiber optic onto a color detector; projecting a spot indirectly, that is at an angle to, an inspection target and focusing part of the reflected light with fiber optic onto a color detector; and projecting a spot directly through an inspection target and focusing part of the transmitted light with fiber optic onto a color detector. Such a nutritional substance attribute sensor may be configured to include a white light source and color detector as a permanent part of a detector, for instance, a detector provided as part of a nutritional substance reader or dynamic appliance reader, and a coupler that enables attachment of the detector to the mating coupler of various fiber optic probe configurations to project light from the light source onto or through a target and to focus reflected or transmitted light from the target onto the color detector. Such fiber optic probes may be provided as a permanent part of a sealed nutritional substance package, wherein the portions of the probe required to interface with the nutritional substance are in direct contact with the nutritional substance, and the mating coupler that allows removable attachment to the sensor coupler provided with the detector is available externally of the package. Permanently incorporating the sensor probe into the package has many benefits. The portion of the sensor probes in contact with the nutritional substance can be tailored to the specific product and package, while the mating coupler on the outside of the package is always provided in the configuration compatible with the sensor coupler on the detector. This enables sensing of a wide array of packaged nutritional substances without disrupting package integrity. It also simplifies the task greatly for a user, and ensures consistent and accurate sensing technique.
Sensing technologies utilizing hyperspectral imaging are potentially useful as nutritional substance attribute sensors, and because of their speed and ability to provide in-process detection, may be particularly useful for applications during local storage and conditioning of nutritional substances. Hyperspectral imaging may be utilized in some embodiments of the present invention, for example, for in-line inspection of multiple produce items, such as apples or strawberries, as they are placed into a dynamic appliance such as a refrigerator, or alternatively, for rapid inspection of meat products such as poultry or seafood, as they are removed from a dynamic appliance such as a refrigerator, or placed into a dynamic appliance such as a toaster oven. This technology is particularly useful for identifying anomalies in nutritional substances without disrupting the nutritional substance. All substances have unique spectral signatures, which can be saved in a library. Libraries including the spectral responses of known nutritional substances in known nutritional, organoleptic, or aesthetic conditions, and further including known sources of adulteration, such as fecal matter, chemical contamination, micro-organisms and other pathogens or disease conditions, can be used for comparison to spectral responses of nutritional substances currently being sensed, and in this way the currently sensed nutritional substance can be quickly identified according to desired criteria. Hyperspectral sensing may further be utilized for plant and crop phenotyping, whereby a composite of a nutritional substance's observable characteristics provides a unique nutritional substance fingerprint. This can be particularly beneficial to rule out adulteration such as by partial or total ingredient substitution, and may be accomplished by an appropriately equipped dynamic appliance.
Sensing technologies utilizing near-infrared spectroscopy may be potentially useful as nutritional substance attribute sensors, because of their ability to provide detection below the surface of a sensed object, may be particularly useful for identifying the type and concentration of various components of a nutritional substance. Examples of this type of sensor include the microPHAZIR RX from Thermo Fisher Scientific and near-infrared technologies under development by Fraunhofer Institute for Electronic Nano Systems.
Other examples of optical sensor technology that might be utilized include, but are not limited to: handheld Raman spectrometers available from Serstech, www.serstech.com; PinPointer™ handheld Raman spectrometer available from Ocean Optics, www.oceanoptics.com; TruScan RM handheld Raman spectrometer available from Thermo Fisher Scientific; near infra-red sensor available from Thermo Fisher Scientific; Xantus Mini™ remote controlled, smartphone compatible Raman spectrometer available from Rigaku, www.rigaku.com; Lighting Passport handheld or remote smartphone compatible spectrometer from Asensetek, www.alliedscientificpro.com.
At this juncture it can be understood that a nutritional, organoleptic or aesthetic value of a nutritional substance can be indicated by its olfactory values or its taste values. Typically, but not necessarily, olfactory values and taste values are detectable by the human sense of smell. However, nutritional substances may emit or produce gaseous components that are not detectable or discernible by the human sense of smell, or components not detectable or discernible by human sense of taste, but, nevertheless, may be indicative of a particular nutritional, organoleptic, and aesthetic state of the nutritional substance. In addition, olfactory values and taste values can be indicative of adulteration of nutritional substances, such as by spoilage, contamination, or substitution of other nutritional substances.
It is understood that the utilization of the nutritional substance attribute sensors according to the present invention can provide beneficial information regarding adulteration or mislabeling of nutritional substances.
In an example of a conditioning appliance equipped with nutritional substance attribute sensors, a consumer places a turkey breast in a combination microwave, convection, and grill oven equipped with nutritional substance attribute sensors. The nutritional substance attribute sensors collect a variety of physical attribute data from the turkey breast. The conditioning appliance's controller then transmits the physical attribute data collected to the nutritional substance industry database, for comparison to the nutritional substance attribute library contained therein. For example, the weight, color, temperature, texture, moisture, or other attributes of the turkey breast may be detected and communicated to the nutritional substance attribute library. It is understood that while
In the above example, the consumer is ready to prepare a turkey breast using a combination microwave, convection, and grill oven equipped with nutritional substance attribute sensors. The consumer places the turkey breast in the combination oven, where the oven's nutritional substance attribute sensors sense various physical attribute data from the turkey breast, for example the weight, color, temperature, and texture. The combination oven controller then transmits the sensed attribute data to the nutritional substance industry database for comparison to the nutritional substance attribute library. The nutritional substance industry database determines that the sensed data matches the nutritional substance attribute library dataset corresponding to turkey breast having specific nutritional, organoleptic, and aesthetic values, and a certain weight and temperature. The conditioning appliance's controller additionally requests input from the consumer regarding the desired residual nutritional, organoleptic, or aesthetic value of the turkey breast following conditioning, by providing options for the consumer to choose from through its dynamic nutritional substance menu panel. It is understood that these options may be presented in any known fashion, and while particular presentation forms will be discussed herein, they are in no way limiting. In this example, the dynamic nutritional substance menu panel presents options for the consumer to choose from in a format similar to the options provided by routing and navigation applications (i.e. “shortest distance”, “shortest time”, “least freeway travel”, and so forth). For instance, the options provided by the dynamic nutritional substance menu panel may be “fastest preparation time”, “highest nutritional value”, and “tender” (corresponding to highest residual organoleptic value for texture). The consumer can find out more detailed information regarding the residual nutritional, organoleptic, and aesthetic values that will result from a particular option by selecting that option, whereupon the dynamic nutritional substance menu panel will provide a summary of the corresponding residual nutritional, organoleptic, and aesthetic values, also referred to herein as a nutritional substance residual value table. The dynamic nutritional substance menu panel may further provide other useful information, such as, but not limited to, the corresponding amount of conditioning time required to achieve the selected option based on, among other factors, the weight of the nutritional substance. If the consumer determines that he is not pleased with his selection based upon the more detailed information provided through the dynamic nutritional substance menu panel, particularly the information in the nutritional substance residual value table, he can return to the previous screen and choose another option. The consumer can continue to select options, review the more detailed information in the nutritional substance residual value table, as well as the other useful information provided, until he determines that an option meets his requirements. Upon determining that an option meets his needs, particularly needs related to the information about residual nutritional, organoleptic, and aesthetic values summarized by the nutritional substance residual value table, the consumer can proceed with the option by using the dynamic nutritional substance menu panel, such as by selecting “proceed”. The conditioning appliance controller then implements adaptive conditioning parameters that are responsive to: the information it has retrieved from the nutritional substance industry database by comparing sensed physical attribute data to the nutritional substance attribute library; and/or the consumer input obtained through the dynamic nutritional substance menu panel. These adaptive conditioning parameters, also referred to herein as adaptive preparation sequence, assure that the consumer will be provided with an adaptively conditioned turkey breast that meets his needs, particularly his needs related to residual nutritional, organoleptic, and aesthetic values of the adaptively conditioned turkey breast.
In one example of the present invention, the consumer wishing to prepare the turkey breast selects the “fastest preparation time” option on the dynamic nutritional substance menu panel, as he needs to eat as soon as possible. The dynamic nutritional substance menu panel then provides the consumer with a nutritional substance residual value table showing the residual nutritional, organoleptic, and aesthetic values that will result from adaptively conditioning the turkey breast with the corresponding adaptive preparation sequence, and additionally provides the amount of time required to do so for the piece of turkey at the certain temperature and weight, for example. The consumer determines from the nutritional substance residual value table that one of the turkey breast's residual nutritional values, for the purpose of this example, its residual protein content, will be 60% of its starting value or may provide the residue value or change in value in an actual quantity of protein such as 50 grams remaining or a decrease of 30 grams of protein. It is understood that the nutritional substance residual value table may provide any number of individual residual nutritional values, such as residual complex carbohydrate content, residual fat content, residual folic acid content, and so forth, and that those provided for the purpose of this example are in no way limiting. It is also understood that residual nutritional value may be provided as an aggregated value based on several independent residual nutritional values. The consumer may additionally determine from the nutritional substance residual value table that the turkey breast's residual organoleptic value for tenderness after conditioning will be 10%, where 0% represents not at all tender and 100% represents very tender. It is understood that the nutritional substance residual value table may provide any number of individual residual organoleptic values, such as a rating to determine if the turkey breast will be well done, a rating for overall moistness of the turkey breast, and so forth, and that those provided for the purpose of this example are in no way limiting. It is also understood that residual organoleptic value may be provided as an aggregated value based on several independent residual organoleptic values. The consumer also determines from the dynamic nutritional substance menu panel that the adaptive conditioning will take only 8 minutes. Today, preparation time is the most important criteria to the consumer, so he proceeds by selecting the “proceed” option on the dynamic nutritional substance menu panel. The combination oven can now instruct the consumer through its dynamic nutritional substance menu panel on the various settings and time requirements to adaptively condition the turkey breast according to the corresponding adaptive preparation sequence. Alternatively, the combination oven's controller can automatically implement the adaptive preparation sequence, so that the consumer is free to do other things while the turkey breast is adaptively conditioned. The adaptive preparation sequence may further be responsive to input obtained from one or more attribute sensors during conditioning. In this example, the adaptive preparation sequence requires mostly the application of microwave at high intensity with a few seconds of grill at the end of the sequence to cause a small amount of crispness in the skin.
On another day, the same consumer is again going to prepare a similar turkey breast in his combination oven. He remembers that the last time he did, he was impressed with the speed of preparation, but wished it would have had higher residual protein value and also wished it had been more tender. Today he has no time constraints, and is more interested in the residual nutritional, organoleptic, and aesthetic values that can be achieved. He places the turkey breast in the combination oven, where the oven's nutritional substance attribute sensors sense various physical attribute data from the turkey breast, including its weight and temperature. The conditioning appliance's controller then transmits the physical attribute data collected to the nutritional substance industry database, for comparison to the nutritional substance attribute library contained therein. In other examples, the physical attributes may include elevation, ambient pressure in the conditioner, texture, moisture, relative humidity in the conditioner, color of the turkey, and other attributes. When a match is found for the physical attribute data collected from the turkey breast, the nutritional substance industry database can determine that the matching nutritional substance attribute library dataset corresponds to a turkey breast with known nutritional, organoleptic, and aesthetic values, and that it weighs 2.2 pounds and is at a temperature of 42 deg. F. The controller additionally requests input from the consumer regarding the desired residual nutritional, organoleptic, or aesthetic value of the turkey breast following conditioning, by providing options for the consumer to choose from through its dynamic nutritional substance menu panel. The options are “fastest preparation time”, “highest nutritional value”, and “tender”. The consumer selects the “highest nutritional value” option from the dynamic nutritional substance menu panel, as he wants to eat a healthy meal. The dynamic nutritional substance menu panel then provides the consumer with a nutritional substance residual value table showing the residual nutritional, organoleptic, and aesthetic values that will result from adaptively conditioning the turkey breast with the corresponding adaptive preparation sequence, and additionally provides the amount of time required to do so. The consumer determines from the nutritional substance residual value table that one of the turkey breast's residual nutritional values, for the purpose of this example, its protein content, will be 90% of its starting value, 90 grams total or a change in 10 grams. It is understood that the nutritional substance residual value table may provide any number of individual residual nutritional values, such as residual complex carbohydrate content, residual folic acid content, residual fat content, and so forth, and that those provided for the purpose of this example are in no way limiting, and this data could be provided in many different forms, such as percentages, graphs, or absolute values. It is also understood that residual nutritional value may be provided as an aggregated value based on several independent residual nutritional values. The consumer may additionally determine from the nutritional substance residual value table that the turkey breast's residual organoleptic value for tenderness after conditioning will be 50%, where 0% represents not at all tender and 100% represents very tender. It is understood that the nutritional substance residual value table may provide any number of individual residual organoleptic values, such as a rating to determine if the turkey breast will be well done, a rating for overall moistness of the turkey breast, and so forth, and that those provided for the purpose of this example are in no way limiting. It is also understood that residual organoleptic value may be provided as an aggregated value based on several independent residual organoleptic values. The consumer also determines from the dynamic nutritional substance menu panel that the conditioning will take 40 minutes. Today, residual nutritional value is the most important criteria to the consumer, so he proceeds by selecting the “proceed” option on the dynamic nutritional substance menu panel. The combination oven can now instruct the consumer through its dynamic nutritional substance menu panel on the various settings and time requirements to adaptively condition the turkey breast according to the corresponding adaptive preparation sequence. Alternatively, the combination oven's controller can automatically implement the adaptive preparation sequence, so that the consumer is free to do other things while the turkey breast is adaptively conditioned. The adaptive preparation sequence may further be responsive to input obtained from one or more attribute sensors during conditioning. In this example, the adaptive preparation sequence requires mostly the application of convection heat with two minutes of grill at the end of the sequence to cause a small amount of crispness in the skin without burning the skin exposed to the grill.
On yet another day, the same consumer is again going to prepare a similar turkey breast in his combination oven. He remembers that the last time he did this he was impressed with the high residual nutritional value of the turkey breast, but wondered if he could achieve a still more tender turkey breast with acceptable residual nutritional values. Today he has no time constraints, and is more interested in the residual nutritional, organoleptic, and aesthetic values that can be achieved. He places the turkey breast in the combination oven, where the oven's nutritional substance attribute sensors sense various physical attribute data from the turkey breast. The conditioning appliance's controller then transmits the physical attribute data collected to the nutritional substance industry database, for comparison to the nutritional substance attribute library contained therein. When a match is found for the physical attribute data collected from the turkey breast, the nutritional substance industry database can determine that the matching nutritional substance attribute library dataset corresponds to a turkey breast with known nutritional, organoleptic, and aesthetic values, and that it weighs 2.1 pounds and is at a temperature of 41 deg. F. In other examples, the physical attributes may include elevation, ambient pressure in the conditioner, texture, moisture, relative humidity in the conditioner, color of the turkey, and other attributes. The controller additionally requests input from the consumer regarding the desired residual nutritional, organoleptic, or aesthetic value of the turkey breast following conditioning, by providing options for the consumer to choose from through its dynamic nutritional substance menu panel. The options are “fastest preparation time”, “highest nutritional value”, and “tender”. The consumer selects the “tender” option from the dynamic nutritional substance menu panel, as he prefers to eat a tender piece of turkey breast if he can determine that it is still a healthy meal. The dynamic nutritional substance menu panel then provides the consumer with a nutritional substance residual value table showing the residual nutritional, organoleptic, and aesthetic values that will result from adaptively conditioning the turkey breast with the corresponding adaptive preparation sequence, and additionally provides the amount of time required to do so. The consumer determines from the nutritional substance residual value table that one of the turkey breast's residual nutritional values, for the purpose of this example, its residual protein content, will be 88% of its starting value. It is understood that the nutritional substance residual value table may provide any number of individual residual nutritional values, such as residual complex carbohydrate content, residual folic acid content, residual fat content, and so forth, and that those provided for the purpose of this example are in no way limiting. It is also understood that residual nutritional value may be provided as an aggregated value based on several independent residual nutritional values. The consumer may additionally determine from the nutritional substance residual value table that the turkey breast's residual organoleptic value for tenderness after conditioning will be 98%, where 0% represents not at all tender and 100% represents very tender. It is understood that the nutritional substance residual value table may provide any number of individual residual organoleptic values, such as a rating to determine if the turkey breast will be well done, a rating for overall moistness of the turkey breast, and so forth, and that those provided for the purpose of this example are in no way limiting. It is also understood that residual organoleptic value may be provided as an aggregated value based on several independent residual organoleptic values. The consumer also determines from the dynamic nutritional substance menu panel that the conditioning will take 80 minutes. Today, residual organoleptic value, specifically tenderness, is the most important criteria to the consumer, so he proceeds by selecting the “proceed” option on the dynamic nutritional substance menu panel. The combination oven can now instruct the consumer through its dynamic nutritional substance menu panel on the various settings and time requirements to adaptively condition the turkey breast according to the corresponding adaptive preparation sequence. Alternatively, the combination oven's controller can automatically implement the adaptive preparation sequence, so that the consumer is free to do other things while the turkey breast is adaptively conditioned. The adaptive preparation sequence may further be responsive to input obtained from one or more attribute sensors during conditioning. In this example, the adaptive preparation sequence requires mostly the application of low convection heat with two cycles of 3 minutes of grill at the end of the sequence to cause a moderate amount of crispness in the skin.
In a further embodiment, the consumer may provide experience input, such as through consumer interface 560, regarding his experience and satisfaction with the adaptively conditioned nutritional substance. Such experience input may be stored by controller 530, so that it can be utilized in the future for possible further modification of conditioning parameters for similar nutritional substances. In this way, the controller learns how to adapt, or not adapt, conditioning parameters responsive to the consumer's experience input. For example, the consumer input through the consumer interface of a toaster oven when placing a turkey breast into the toaster oven may be that he desires it to be rare after conditioning. After conditioning, the consumer may provide his experience input regarding the conditioned turkey breast, such as by selecting a description of the conditioned turkey breast from a screen providing the options of “under cooked”, “rare”, “medium”, and “well done”. If the consumer selected “under cooked”, the toaster oven's controller could further modify future conditioning parameters for turkey breast to provide longer exposure to heat. If the consumer selected “rare”, the controller would not further modify future conditioning parameters for turkey breast. If the consumer selected “medium”, the controller could adapt future conditioning parameters for turkey breast to provide less exposure to heat. If the consumer selected “well done”, the controller could adapt future conditioning parameters for turkey breast to provide reduced heat and duration of exposure to heat.
In another embodiment, a conditioning appliance is provided with nutritional substance reader 590 and nutritional substance attribute sensors 591. The nutritional substance reader 590 scans a dynamic information identifier associated with a nutritional substance, and the nutritional substance attribute sensors 591 scan the nutritional substance. The controller of the conditioning appliance uses the dynamic information identifier to determine the nutritional substance content and current nutritional, organoleptic, or aesthetic value referenced to the dynamic information identifier in the nutritional substance database. The controller uses the data obtained from the nutritional substance attribute sensors to determine the nutritional substance content and current nutritional, organoleptic, or aesthetic value corresponding to the values in the nutritional substance attribute library, including for example the weight of the nutritional substance. In other examples, the physical attributes may include elevation, ambient pressure in the conditioner, texture, moisture, relative humidity in the conditioner, color of the turkey, and other attributes. The controller compares the nutritional substance content and nutritional, organoleptic, or aesthetic value information determined from the nutritional substance database to that determined from the nutritional substance attribute library. If the information is determined to be similar, adaptive conditioning parameters responsive to the current nutritional, organoleptic, and aesthetic values of the nutritional substance can be provided. If the information is determined to be dis-similar, adaptive conditioning parameters may not be provided, or alternatively, the consumer may be provided with options through the consumer interface. Options may include, but are not limited to, proceeding with conditioning by manually entered conditioning parameters; proceeding with adaptive conditioning parameters responsive to information determined from nutritional substance database; proceeding with adaptive conditioning parameters responsive to information determined from nutritional substance attribute library; or not proceeding with conditioning.
For instance, a piece of salmon may be scanned with the nutritional substance reader 590, or identified using the attribute sensors 591. The sensors 591 used to identify the nutritional substance 520 may be colorimetric sensor arrays, color sensors, spectrometer, standard optical detectors or others matching profiles using statistical analysis or other methods as disclosed herein. Next, once the category or type of nutritional substance 520 is identified, (i.e. salmon) the specific attributes of that nutritional substance 520 may be identified and stored as sensed attributes 640. These sensed attributes 640 may include the initial weight of the salmon, the color (i.e. wild versus farm raised), the initial temperature, the texture, the shape, and other relevant factors. In other embodiments, these attributes may be wholly or partially obtained from a nutritional substance reader 590 associated with the conditioner 570 that reads a nutritional substance identifier where the nutritional substance is pre weighed, and the other attributes are predetermined before packaging and provided on information in a label or in a database. In some embodiments, only the nutritional substance is identified, and no specific attributes are sensed 640 and rather average or estimated data is utilized. Next, the conditioner optionally may consider location data, including using GPS, or consumer input 620 to determine the local ambient conditions that are relevant to conditioning. For example, certain climates may be more humid or certain geographic locations may have significantly different elevations that substantially affect cooking. Next, various information or nutritional data 630 may be stored in the nutritional information database 550 regarding the nutritional substance 520 (i.e. salmon) and how the nutritional, organoleptic, or aesthetic values of the nutritional substance 520 changes based on various conditioning protocols. This nutritional data 630, or change in nutritional data may be obtained from prior tests of conditioning protocols on various nutritional substances 520, including the same type of nutritional substances but in different quantities, initial temperatures, initial colors, and other sensed attributes 640. Accordingly, this information may be utilized to predict how a particular nutritional substance 520 will change over various conditioning protocols based on its unique sensed attributes 640, including how its various nutritional, organoleptic, or aesthetic values will change. Accordingly, this may be an estimated change.
A database 550 or recipe database 555 that provides information on sensed attributes 640 may include information on, various weights, lengths, and shapes of salmon that were conditioned using various protocols and the resulting nutritional, organoleptic, or aesthetic values that were recorded. For instance, a larger piece of salmon will need to be cooked longer to ensure the inside is not raw, but also that the outside is not tough and rubbery. Contrarily, a smaller piece of salmon will need a different conditioning protocol to optimally condition the salmon without overcooking it, or denaturing too many of its omega three fatty acids. Accordingly, the database 550 may have the appropriate cooking time for various weights of salmon, and use that to extrapolate in between for a particular piece of salmon or to accommodate its precise sensed weight. Additionally, the same could be performed for starting temperature, color and other sensed attributes 640. In other embodiments, mathematical models may be developed based on experimental data for conditioning certain types of foods, for instance more popular foods such as fish or salmon that are notoriously harder to condition to perfection without sensing the attributes of the actual nutritional substance about to be conditioned. Additionally, the location of the conditioner 570 may be utilized to determine the ambient pressure and other characteristics that are important to cooking times and utilized to output a modified conditioning protocol 660.
Then, the controller 530 may output various conditioning options to the consumer for conditioning the salmon as disclosed herein, to maximize nutritional, organoleptic, or aesthetic values, or other consumer preferences or the options may be presented for various ingredients of a recipe. The controller 530 would then take the consumer input 620 to further modify the conditioning protocol to output a new modified conditioning protocol 660 that may be implemented to condition the salmon. For example, the consumer may input their desire to preserve the maximum amount of omega 3 fatty acids in the piece of salmon. Therefore, the controller 530 will determine based on the modified conditioning protocols 660 provided by input from the sensed attributes 640, nutritional data 630, and location data 650, how to further modify the protocols or select the optimum protocol to maximize the omega three content of the salmon. For instance, it may be known, or testing may show that both microwaving and the shortest cooking time maximize the omega 3. Therefore, the conditioner may implement the modified conditioning protocol 660 that primarily or solely microwaves the fish. In another embodiment, a combination of microwaving and convection or grilling may be used for a modified conditioning protocol 660 that preserves most omega threes but also maximizes taste.
Conditioning protocols 610, may include various protocols for cooking or condition nutritional substances 520 based on time, heat, surface temperature of food, different cycles, different conditioning methods, including microwaving, convention, grilling, etc. For instance, it may be noted that for salmon, microwaving is the optimal way to preserve the nutritional value of a piece of salmon as determined by the controller 530 accessing the nutritional data 630 from the database. Other embodiments may use a combination of microwave, convention, grilling or other methods to maximize the nutritional, organoleptic, or aesthetic values desired by the consumer based on the consumer input 620. As described herein, those conditioning protocols may be stored in a database where they can be modified.
Once the conditioner begins conditioning the nutritional substance 520, the attribute sensors 591 may continue provide data regarding sensed attributes 640 of the nutritional substance during cooking. This data may be utilized to further modify the conditioning protocol 610 based on deviations from the expected values. For example, if a piece of salmon is used and an infrared surface temperature attribute sensor 591 detects the salmon surface temperature, once the modified conditioning protocol 660 is determined and implemented, the sensor 591 may continue to detect the surface temperature and compare it to data from the database 550 from prior tests. It may be that this salmon surface temperature rises more quickly, perhaps because although the salmon weighs the same, the salmon is thicker than the tested salmon. Therefore, the modified conditioning protocol 660 may be further modified based on feedback from the sensors in the form of sensed attributes 640. This may be a continuous or periodic feedback loop that allows the various attribute sensors 591 to detect various factors to indicate the progress of cooking and whether the conditioning protocol needs to be modified to account for individual variation. In this case, if the temperature rises faster than expected the overall cooking time or target surface temperature may be decreased appropriately to form a new modified conditioning protocol 660. In other examples, color based sensors may be able to detect changes in food that are associated with being cooked or finished cooking. Accordingly, a combination of visual, temperature, and weight data may be utilized to find the optimal stopping time for when the nutritional substance 520 is finished cooking.
In another embodiment, a conditioning appliance is provided with at least one of a nutritional substance reader 590 and nutritional substance attribute sensors 591, including a weight sensor. In other examples, the physical attributes sensors may include elevation (i.e. GPS), ambient pressure, texture, moisture, relative humidity, color, and other attribute sensors. The conditioning appliance is further provided with the ability to identify specific types of containers, including, but not limited to, plates, bowls, pan, grill, cookware, and so forth. The conditioning appliance may identify such a container by using the nutritional substance reader to identify an identifier on the container unique to that type of container, using an attribute sensor to identify an attribute unique to such a container, or using container detectors to identify unique types of containers, for instance the container may have an RFID tag enabling an RFID reader used as the container detector to identify it. Such a conditioning appliance can be used to determine adaptive conditioning parameters that are responsive to the current nutritional, organoleptic, and aesthetic values of the nutritional substance, consumer input, consumer experience input, and attribute sensor information during conditioning, but are additionally responsive to the specific container being used (for example by subtracting the weight of the specific container from the sensed weight of the nutritional substance 520). In this way, the adaptive conditioning parameters may even account for the physical properties of the container holding the nutritional substance, including, but not limited to, the container's weight, thermal conductivity, and so forth.
In an embodiment of the present invention, conditioner 570 is provided without controller 530 and nutritional substance attribute sensors 591, however it is provided in a format to be compatible with controller 530 and nutritional substance attribute sensors 591. Such a conditioner is also referred to herein as an information and sensing capable conditioner. In contrast, traditional conditioners, also referred to herein as dumb conditioners, are not information and sensing capable, are not compatible with controller 530 and nutritional attribute sensors 591, and accordingly will always be dumb conditioners. As information and sensing enabled conditioning systems according to the present invention are increasingly available, dumb conditioners will become increasingly obsolete.
Information and sensing capable conditioners may be provided in a variety of configurations known to those skilled in the art, and the examples offered herein are for purposed of illustration and not intended to be limiting in any way. In one example of an information and sensing capable conditioner, it is provided with traditional functionality, that is, it will interact with nutritional substances in a traditional fashion. However, the information and sensing capable conditioner is compatible with separately available controller 530 and nutritional substance attribute sensors 591, such that at any time during or after the manufacture and sale of the information and sensing capable conditioner, controller 530 and nutritional substance attribute sensors 591 may be coupled with the information and sensing capable conditioner to enable the full functionality and benefit of conditioner module 500. Information and sensing capable conditioners provide appliance manufacturers and consumers great flexibility, and will not become obsolete like dumb conditioners.
The coupling of controller 530 and nutritional attribute sensors 591 to the information and sensing capable conditioner may take any physical and/or communication format known to those skilled in the art. These may include, but are not limited to: an information and sensing capable conditioner provided with Bluetooth, or other wireless near-field communication capability, to communicate with a communication-compatible controller 530, wherein nutritional substance attribute sensors 591 are coupled with, or in communication with, controller 530. The controller 530 may be any of a completely separate unit, an externally attachable unit, and an internally placed unit, while portions of the nutritional substance attribute sensors may be positioned in proximity to, on, or within the conditioner 570, such as in ports or windows provided with the information and sensing capable conditioner; an information and sensing capable conditioner provided with a USB port, or other electrical communication capability, to communicate with a communication-compatible controller 530, wherein nutritional substance attribute sensors 591 are coupled with, or in communication with, controller 530. The controller 530 may be any of a completely separate unit, an externally attachable unit, and an internally placed unit, while portions of the nutritional substance attribute sensors may be positioned in proximity to, on, or within the information and sensing capable conditioner, such as in ports or windows provided with the information and sensing capable conditioner; an information and sensing capable conditioner provided with a fiber optic port, or other optical communication capability, to communicate with a communication-compatible controller 530, wherein nutritional substance attribute sensors 591 are coupled with, or in communication with, controller 530. The controller 530 may be any of a completely separate unit, an externally attachable unit, and an internally placed unit, while portions of the nutritional substance attribute sensors may be positioned in proximity to, on, or within the information and sensing capable conditioner, such as in ports or windows provided with the information and sensing capable conditioner; or an information and sensing capable conditioner provided with WiFi, or other wireless communication capability, to communicate with a WiFi compatible controller 530, wherein nutritional substance attribute sensors 591 are coupled with, or in communication with, controller 530. The controller 530 may be any of a completely separate unit, an externally attachable unit, and an internally placed unit, while portions of the nutritional substance attribute sensors may be positioned in proximity to, on, or within the conditioner 570, such as in ports or windows provided with the information and sensing capable conditioner. It is understood that the controller 530 may be provided with its own consumer interface, may communicate and be operated through the consumer interface provided with the information and sensing capable conditioner, or a combination of both.
For example, an external weight sensor may be provided that may be wirelessly coupled to conditioner 570 or provided any other means of connecting the weight sensor to conditioner 570, for instance, by a USB port. The external weight sensor 591 may take the form of a separate scale that is provided with its own nutritional substance reader 590. Accordingly, the consumer 540 may scan a dynamic information identifier on a nutritional substance 520, and then weigh the nutritional substance on the external weight sensor 591 in order to determine a current ΔN value of the nutritional substance by reference to a nutritional substance database 550, and/or a nutritional substance attribute library dataset within the database. This external weight sensor 591 may be integrated with any of the various systems disclosed herein and may be utilized at any time to determine a ΔN value of the nutritional substance 520 that is approximated more precisely based on the actual weight of the substance 520. This may be beneficial to allow a consumer that wishes to consume a portion of a nutritional substance 520 that is prepackaged as a specific size, or a portion that does not fall neatly within a predetermined or pre-calculated serving size of a nutritional substance 520. This external weight sensor may be a freestanding electronic scale or integrated into any other appliance, in order to allow a consumer 540 to retrieve current ΔN information of a nutritional substance 520, regardless of the portion size the consumer or other entities along the food chain wish to evaluate and/or consumer.
The multi-conditioner system illustrated in
Additional examples relevant to the multi-conditioner system include various frozen dinners that are packaged with ingredients or components packaged separately so they can be easily inserted into different conditioners 570 for conditioning. For example, a frozen dinner may contain a protein that is either microwaved, convention oven cooked, and/or grilled, and a vegetable package that is steamed or microwaved in a separate conditioner 570. In a three pack frozen dinner could be a protein, vegetables, and bread, all prepared in separate conditioners 570 using the same or different conditioning methods.
At the same time a consumer places the hamburger in conditioner A, the consumer may place a bun in conditioner B. First the conditioning protocol 610 may wait for some time to initiate the convention oven until the amount of time remaining in the conditioning protocol for conditioner A (the hamburger) is equal or nearly equal to the total conditioning time contained in the conditioning protocol 610 for conditioner B. Then, once initiated, the conditioner protocol for conditioner B controlled or instructed by the same or a separate part of conditioner protocol 610 that controlled conditioner A, may instruct the convection oven to turn on to warm up the bun for the hamburger. Then, near the end, the grill may turn on in combination with the convention oven, or may turn on alone to produce grill marks on the bun or a crispy outside.
Accordingly, the graph in
In some embodiments, a multi-conditioner system may condition nutritional substance 1 and nutritional substance 2 at the same time if nutritional substance 1 and 2 or components of a multi-component meal. For example, nutritional substance 1 and 2 may be two separate components of a multi-component meal and it may be desired that their conditioning cycles finish at the same time or within a few seconds or minutes (depending on whether there is a cooling period in some cases) In this embodiment, the conditioning protocol that may include instructions for both nutritional substance 1 and nutritional substance 2 and instructions for when to initiate the desired or selected conditioning protocol 610 for each at the appropriate time in order to coordinate the conditioning so they complete at the same time. In some embodiments, a controller 530 may coordinate the conditioning by calculating the appropriate time to start the shorter conditioning protocol 610, without the conditioning protocol being linked to the other conditioning protocol 610. As illustrated with respect to the “other conditioning” step in the second conditioning protocol 610 of nutritional substance 2, various other types of conditioning may be utilized beyond Microwave, Convection, Grill, Steam, and rest for a dynamic conditioning protocol.
In some embodiments, preference for the desired nutritional, organoleptic, or aesthetic values may be chosen by the consumer or preferences for these values may be chosen by the consumer 540 so that the optimal dynamic conditioning protocol 610 may be chosen to implement by the system. For instance, as disclosed herein, various conditioning protocols 610 may be stored in advanced and indexed to a dynamic information identifier or other identifier associated with a nutritional substance 520. Each of those conditioning protocols 610 may contain an associated average or expected residual value and therefore the consumer 540 may be provided with choices for which index residual value or what desired organoleptic, nutritional, and/or aesthetic values a consumer 540 desires based on the available options for conditioning protocols 610. Accordingly, the recipe may be proactively able to respond to the particular food in terms of the desired organoleptic, nutritional, and aesthetic values.
In some embodiments, either or both the conditioners 570A and 570B may be set on a timer to begin conditioning at a set time so that the food will be ready at some time in the future. For example, a consumer may want a croissant and omelet ready at 7:30 a.m. in the morning. Therefore, before they go to sleep, they could insert the omelet in the bottom (in other embodiments, the multiple conditioners 570 could have any spatial relationship) conditioner 570B and the croissant in the top conditioner 570A and the system set to have the croissant and omelet finished conditioning at 7:30 a.m. so it is ready to eat. In that embodiment, the controller 530 may calculate the appropriate times to beginning conditioning in both the top and bottom conditioner 570 so both are ready at 7:30 a.m. and accordingly initiate conditioning in each conditioner 570 at the appropriate times (and remain in “stand by” mode until that time). In some embodiments, the multi-conditioner 570 system may include a cooling ability, to preserve the nutritional substance 520 at a certain temperature so it may be inserted in the conditioner 570 well in advance of conditioning. Similarly, after conditioning is finished, the conditioner 570 may be utilized to keep a nutritional substance 520 that has been conditioned at the ideal temperature for several minutes or hours. In further embodiments, the ideal temperature may be calculated with reference to ΔN values, so that the rest or preservation of the nutritional, organoleptic, and aesthetic values will be tailored to the preferences of the consumer based on the amount of time between conditioning and consumption or the preservation period prior to conditioning.
In other embodiments, as disclosed herein, the recipes may be dynamically modified by the conditioner 570 based on feedback from sensors, and may short or lengthen cooking times, may change types, or exposure, or other factors in order to reach the desired nutritional, organoleptic, and/or aesthetic values.
The control module 710 may contain various ports 720 to interface with the conditioner 570, network 760, server 770, and other components of the system in order to transfer information. Ports 720 may be physical ports, including data connections such as any RS-232 ports, RS-423, RS-485, serial ports, parallel ports, Ethernet, firewall, USB, Mini, PCI, Serial ATA, FireWire, and other various other suitable ports. In some embodiments, ports 720 may be software ports (i.e. virtual ports) for receiving communications from the various components of the system based on various appropriate protocols, including RS-232. The ports 720 may include ports for receiving and requesting conditioning protocols 610 from the server 770 and database 550, ports for communicating with the conditioner 570, and ports for receiving consumer input. In some embodiments, the various ports 720 may be combined and receive input from more than one component of the system. Ports 720 may be software ports, or may be hardware ports/interfaces or both. For example, the control module 710 may include an input port 720 or first port 720 for receiving information related to a dynamic information identifier or other information related to a nutritional substance (for example attribute data). Additionally, the control module may include a second port 720 in communication with the database 550 with information referenced to dynamic information identifiers and/or types of known nutritional substances. Furthermore, the control module 710 may also include a third port 720 for receiving consumer input.
The control module 710 may contain various forms of memory to locally store conditioning protocols 610 for easier access when a network 760 connection is not functioning or for faster access. The control module 710 may also contain software for updating conditioning protocols 610 to appropriately format for execution by an associated conditioner 570. This may include the ability to load software for each particular conditioner 570 associated with the control module 710.
The recipe database 550 and server 770 may be a centrally located system that provides access to conditioning protocols 610 and modified condition protocols 660 that are referenced to particular nutritional substances 520 and/or an associated dynamic information identifier(s). The database 550 may contain information referenced to dynamic information identifiers that identify a particular nutritional substance 520. For example, each dynamic information identifier may be referenced or assigned to a particular conditioning protocol 610 or numerous conditioning protocols 610 and/or modified condition protocols 660. Additionally, various other information may be associated with each conditioning protocol 610 or 660 in the database 550, including data relating to changes in nutritional, organoleptic, and/or aesthetic values of a particular nutritional substance 520 that is subject to the particular conditioning protocol 610 as described herein.
Control modules 710 attached to conditioners 570 will then be able to retrieve the most up to date conditioning protocols 610 that are referenced to a particular nutritional substance 520 or dynamic information identifier. The database 550 may be easily updatable to change various aspects of the conditioning protocols 610 referenced to certain dynamic information identifiers and to update the conditioning protocols 610 to create modified conditioning protocols 660. These modified conditioning protocols 660 may then be referenced to the same dynamic information identifiers so the modified conditioning protocol 660 may be retrieved instead of the original conditioning protocol 610. A control module's request for a conditioning protocol 610 referenced to that dynamic information identifier would be returned with the modified conditioning protocol 660.
The control module 710 may then send a retrieved or modified condition protocol 710 to the conditioner 570 for implementation to condition the nutritional substance 520. In some embodiments, the control module 710 may directly control or send control instructions to the conditioner 570 to operate its heating and other conditioning elements appropriately, or may send the condition protocol(s) 610 for implementation by a controller 530 associated with the conditioner 540.
The control module 710 may utilize methods for accessing and implementing appropriate condition protocols 610. For example, a consumer 540 may unpack a nutritional substance 520 that the consumer 540 would like to condition. The consumer 540 may then scan a dynamic information identifier associated with the nutritional substance 520 with the nutritional substance reader 590, or enter identifying information in the consumer interface 560.
This information may be entered into a consumer interface 560 on the conditioner or optionally a consumer interface 560 on or connected to the control module 710. This information may then be sent to the control module 710. The control module 710 may then send a request for a condition protocol 610 to the server 770. Once receiving the request, the server's 770 controller 530 may then process the identifying data, and use it to access the database 550 and select conditioning protocols 610 that are appropriate. Then, the server 770 may create a response to the request for condition protocol 610 that includes the appropriate protocols 610 identified from the database 550, and send the protocols back to the control module 710 over the network 760.
The control module 710 may then either send the conditioning protocols 610 to the conditioner 570 or display the various options to the consumer 540 on its own consumer interface 560. Then the consumer 540 may select the condition protocol 610 it desires and enter any preferences for the particular conditioning protocol 610 that may be modifiable. Once this information is entered, the control module 710 (or in some embodiments, the conditioner 570 and/or the server 770) may process the condition protocol 610 and the parameters for the consumer 540 input to create a conditioning protocol 610 that is executable by the conditioner 570. This may be created by modifying the selected and uploaded condition protocol from the database 550.
Then, the conditioning protocol 610 may be associated with a sub-type of nutritional substance 520 or a specific type of nutritional substance 520, for instance Trade Joe's wild salmon or Golden Plump free range chicken. Conditioning protocols 610 for a specific nutritional substance 520 are categorized in
In some embodiments, more or less layers or categories of hierarchical classification may be utilized to in a data structure storing conditioning protocols 610. These categories facilitate identification of the options available to a consumer for cooking a nutritional substance based on consumer input. In some embodiments, a consumer interface 560 will present options for identification of the specific nutritional substance 520 so that a subset of conditioning protocols and/or categories of conditioning protocols 610 may be presented to the consumer to select for conditioning. These may be presented as a series of choices including: (1) first meat or vegetables, then (2) fish, chicken, steak, etc., then (3) golden plump chicken, Trader's Joe's chicken, then (4) breast or things, or wings, etc. In other embodiments, a nutritional substance reader 590 may read a label and automatically identify the specific nutritional substance 520 and retrieve the conditioning protocols 610 associated with that nutritional substance 520. In other embodiments, image recognition system or other systems may be utilized to identify the nutritional substance 520 that will be cooked.
Once a nutritional substance 520 is identified and/or the subset of protocols 610 that are associated with that substance are retrieved the consumer may be presented with options for cooking the identified nutritional substance 520. These options and categories may be based on the further hierarchy of conditioning protocols 610, an example of which is illustrated in
Then, as described with respect to the nutritional substance 520 identification, the consumer may be provided various additional options for narrowing down the choice of conditioning protocols 610, until specific conditioning protocols 615 are presented to the consumer. Then a user may select that conditioning protocol 610 for implementation.
The disclosed system may use various logical data flows to implement the selection process of the conditioning protocol 610 prior to execution. In some embodiments, only data relating to the categories and user input will be sent back and forth. For example, when the user turns on the conditioner 570, to select a recipe, the conditioner 570 may send a request to a server 770 that asks for categories of conditioning protocols 610. The server 770 may then access a database, retrieve the categories and then send those to the conditioner 570 or local processing module in communication with the conditioner 570. In other embodiments, a batch of conditioning protocols 610 may be sent to the conditioner 570 immediately, or after a few categories of protocols have been narrowed down. In some embodiments, the server 770 only sends the conditioning protocols 610 once the nutritional substance 520 is identified. In other embodiments, the server 770 only sends the complete conditioning protocol until the exact protocol is selected and only sends information relating to the conditioning protocols available (without the underlying executable instructions for a control module). In this embodiment, data flow will be minimized likely increasing the speed of responsiveness of the system. Once a protocol is used, it may also be saved locally in some embodiments. The local processing module may also allow a consumer to search and download batches of conditioning protocols 610 that they may want to use without an internet connection.
Once a specific conditioning protocol 610 is selected or otherwise determined, the protocol 610 may be executed to condition the nutritional substance 520. Then after the conditioning, in some embodiments, the consumer may be presented with pre fixed post conditioning protocols 616 in order to complete the conditioning if the consumer is not satisfied with the cooking. For example, in some cases, the nutritional substance 520 may not be fully cooked after the conditioning protocol 610 originally selected is executed. Therefore, pre-fixed end protocols 616 may be presented and/or available to condition a nutritional substance 520 after conditioning include protocols like, “STILL RAW”, “CRISPIER”, and other options. These options may be presented to the consumer on the customer interface 560 once the first selected conditioning protocol 610 has been fully executed 619. These pre-fixed end protocols 616 may include standard conditioning sequences that provide a relatively small incremental conditioning amount. Accordingly, in some embodiments, a consumer could push “STILL RAW” for several cycles of a nutritional substance 520 the consumer conditioned was left very raw after execution of the first conditioning sequence.
The consumer may then be presented with the option to save a conditioning protocol 610 that has been modified 660 as a custom conditioning protocol or alternatively, alter that conditioning protocol 610 every time it happens to be utilized by the same consumer. Then in some embodiments, machine learning, or other formulas or algorithms may be utilized to customize similar conditioning protocols 661 with the same pre-fixed end protocol 616. This may be for example, by adding the same pre-fixed end protocol 616 to other for example all chicken recipes or all “FAST” chicken recipes. In other embodiments, proportional changes could be made between protocols, for example based on weight or a predetermined formula (for example with experimentation correlating an amount of conditioning to a per unit change in organoleptic value of the nutritional substance 520). For instance, X minutes of cooking a chicken leg at 350 degrees F., may translate to 1.1 times X minutes of cooking a chicken breast at 350 degrees F. In some embodiments, a different modification may be made to MASTER chicken recipes that compensate for the difference in protocols between the FAST and MASTER conditioning protocols for example. In some embodiments, after similar conditioning protocols are customized 661, they may be saved as CUSTOM conditioning protocols. In other embodiments, a consumer may be prompted to add a similar customization next time they utilize a similar conditioning protocol 610. Custom conditioning protocols 610 may be saved locally on memory associated with the control module 710 or remote memory associated with a database 550 or both.
In some embodiments, an option to enter a manual mode 614 either after the conditioning protocol 610 has completed or during the conditioning protocol 610. The modifications made with manual mode may then be recorded and stored as custom recipes as well. In some embodiments, manual mode 614 may allow changes in time of cooking or temperature by degree (for example), or qualitative changes in certain categories, for example, doneness, crispiness, etc. In some embodiments, the qualitative scale may be based on a dial or numeric indicator that is a proxy for doneness, crispiness, juiciness or other qualities of a cooked nutritional substance 520.
Accordingly, the nutritional, organoleptic, and aesthetic qualities of a nutritional substance 520 can be tracked throughout its storage and conditioning in a kitchen. In some embodiments, the current degradation rate of a nutritional substance can be estimated by comparison of the currently sensed factors (e.g., temperature) to prior experimental data for specific nutritional substances 520 stored at particular temperatures or subjected to particular conditioning methods. Accordingly, in some embodiments, the ΔN values of a nutritional substance 520 may be tracked throughout the storage and conditioning modules of a kitchen. In some embodiments, these values may be estimated based on weight differences or other correlations to characteristics or attributes of the nutritional substance sensed by the system. Accordingly, with this information, the system can provide notifications to users when nutritional substances 520 are about to expire (e.g. lose all there nutritional content or become harmful to ingest), provide recommendations for recipes based on the nutritional substances 520 in inventory in the kitchen, provide nutritional information including current nutritional information of a nutritional substance 520 based on the changes and the starting nutritional information, display changes in nutritional content (for example with prospective conditioning methods), and provide recommendations for recipes that maximize nutritional or other values.
Accordingly, each of the storage modules 810 and conditioners 570 contain a controller 530, a port 720, a consumer interface 560 and an optical sensor 820. Accordingly, this allows the storage modules 810 and conditioners 570, in some embodiments, to optically record an inventory and relay information regarding the inventory as discussed further herein. This information may then be relayed back to control module 710 for storage and coordination among each of the storage modules 810 and conditioners 570.
In some embodiments, an optical recognition system may be utilized for identification of nutritional substances 520 and in some embodiments the tracking of the amount and ΔN values for each nutritional substance 520. The optical recognition system may include an optical sensor 820 such as a camera, infra-red sensor, or other sensor 820 that may be able to detect optical data from inside of the storage module 810 or conditioner 570. The optical sensor 820 may detect the nutritional substances 520 inside of the storage module 810 or the conditioner 570. In some embodiments, the optical sensor 820 may include a camera hub and multiple cameras inside one of the modules that will allow the optical sensors 820 to recognize and identify the type and the quantity of a particular nutritional substance 520 within the module. The optical recognition technology disclosed herein may be utilized for this purpose.
Furthermore, the optical sensors 820 may provide information that may be analyzed to determine nutritional, organoleptic, and/or aesthetic information about the nutritional substances 520 as discussed herein. For example, the sensor 820 may examine a color, heat signature, or other qualities and may compare those qualities to a data base of tested data to determine, for example, nutritional information for a particular nutritional substance 520. The information determined may also include information such as quantity (example of milk left) by the analysis of the visual images, average consumption rate, length of time out of refrigeration, or other usage patterns. The analysis may be performed by the local controller 530 associated with each module or may be performed by the control module 710 or may be performed after sending sensed data to a remote server over the network 760.
The storage and conditioner modules may also include turn tables, for rotating the nutritional substances inside the modules to provide appropriate angles for the optical sensor(s). In some embodiments, the nutritional substances 520 will be rotated on the turntable until a 3D module of the nutritional substances 520 can be captured and processed, or until the camera detects a label with a dynamic information identifier it can scan.
The storage modules may also include smart Tupperware, where optical sensors 820 and computer vision are utilized to track nutritional substances inside the Tupperware on a temporarily basis, including in cases where the Tupperware is inside of other storage modules.
Various sensors may also be associated with the optical sensor 820 and/or may be located inside the various modules, including temperature sensors 820, pressure sensors 820, light sensors 820, and a door/open close sensors 820. Accordingly, these sensors 820 may be utilized to determine when the optical sensor 820 is required to take images. For instance, in each of the modules there generally will be a door that is required to open before a consumer 540 may remove or manipulate any of the nutritional substances 520. Accordingly, the optical sensor 820 could be configured to only record data during or after each time a door on one of the modules is opened or closed. This will conserve energy and provide an accurate inventory record because the nutritional substances 520 could not be moved unless access to the module is obtained by opening a door.
In some embodiments, access sensors 820 including temperature sensors 820 and light sensors 820 may determine when a door is opened and closed. These sensors could trigger the capture of an image or barcode of a substance as it is placed into or removed from the storage area. That information could then be used to retrieve information, make recipe or shopping recommendations, or adapt storage/conditioning parameters. In other embodiments, the access sensors 820 may be switches, pressure sensors, or other mechanical based sensors that sense when a door is opened and closed. In additional, temperature sensors 820 may keep track of the temperature of the modules 810 and conditioners 570. This will allow a temperature record of each inventory item to be recorded in order to enhance any ΔN values calculated.
In some embodiments, the access sensors 820 will disable sensors 820 readings while the door is open. In some embodiments, if a control module or other control system 530 senses that the door is open, then the sensor 820 could be rescheduled for a time when the door is closed.
For each item recorded into inventory using either the modules or the control module, in some embodiments, the controller or control system 530 of the module that first detects a new inventory item, or in some embodiments, a scanner or reader in electrical/electronic communication with the control module 710, may send the information to the control module 710 and store the inventory in a memory associated with the control module 710. This will allow all inventory items in the kitchen may be tracked.
Adding Items into Inventory
For each nutritional substance 520 that is entered into inventory, a dynamic information identifier or other unique code may be assigned or referenced to the nutritional substance. This may take place by optical recognition as discussed above, or by scanning a dynamic information identifier on a label, an RFID chip in the nutritional substance 520 or other system to identify each unique nutritional substance so that it may be tracked while in the kitchen through consumption. For instance, the optical recognition technology called “findSimilar” available from Cortexica will recognize images with 95% accuracy. As discussed herein, once an item is identified, if a dynamic information identifier is utilized, then a set of data may already be associated with the nutritional substance 520 that will provide a starting point. This information may include: source information, ΔN, quality, weight, and other information.
In other embodiments, when added into a storage module 810, the system may utilize optical recognition to detect the nutritional substance 520, and various sensors may be utilized to detect other attributes of the nutritional substance 520 as discussed herein. For instance, a weight sensor in one of the storage modules 810 or in electrical communication with the control module 710 may provide the weight of a substance which, in some embodiments, in combination with a visual image, may provide information on quantity of the substance being added into inventory. In some embodiments, an optical sensor 820 may include several cameras that reconstructed a 3D image of a nutritional substance 520 to better determine the quantity of the nutritional substance 520.
In some embodiments, 3D modeling and changes in images of the nutritional substance 520 over time can be utilized to determine how much of a nutritional substance has been used and what quantity is remaining. As an example, a ketchup bottle may be added with a certain shape and/or weight. As the ketchup is utilized, the level of red liquid will decrease in the bottle and the weight will decrease. Accordingly, an optical sensor 820 could detect the lower level of the ketchup in the bottle. This information could then be utilized, in combination with a 3D model, to determine the volume of ketchup left. Additionally, each time a door is opened or closed, the system would detect the opening and closing with a sensor, which would send a signal to the control system 530 of the module 810 or conditioner 5740, which would send instructions to the optical sensor 810 to capture a new image. The new image could be compared with prior optical sensor 810 data, to determine changes in quantities and provide a new, real time inventory. In another embodiment, the system may determine that the weight of the ketchup has decreased a certain amount which would be used to calculate a corresponding change in inventory.
Accordingly, a real time inventory of the kitchen could be maintained in this manner, and tracked and stored by the control module 710. The control module 710 could then update this and send data and information to various displays and consumer interfaces 560, such as on any of the modules, or an associated device by sending over a network 760 such as a mobile phone, or other computer. This way, a consumer 540 could have constant updates and check the inventory of the kitchen at all times.
The sensors 820 additionally could use optical 820 or other sensors to detect certain attributes of the nutritional substance that may be correlated with nutritional, organoleptic, or aesthetic values. For instance, as discussed herein, the color of an orange may indicate ripeness and corresponding vitamin C content. Accordingly, the image data from the optical sensors 820 could be sent to the control module 710 and over the network 760 for analysis with a database as discussed herein, with experimental data showing nutritional or other content corrected with image color, for example. Then analysis of the data could determine a likely nutritional value and changes in nutritional values.
Similarly, an infrared image detector may determine a surface heat signature in the conditioners 570 as discussed herein to monitor the conditioning of one of the inventoried nutritional substances 520. Accordingly, this data could be utilized to track changes in the ΔN values of nutritional substances 520 in inventory over time and may also be used to predict changes in ΔN and when a particular nutritional substance 520 may be nearing the end of its useful life. Accordingly, the control module 710 could send alerts when certain nutritional substances 520 are about to expire or provide suggestions for recipes based on the available inventory, conditioners 570, conditioning protocols 610, and the desired ΔN from cooking as discussed herein.
In some embodiments, the system could manipulate the storage conditions of a storage module 810 by examining the nutritional substance 520 in that storage module 810 and optimizing (e.g. minimizing) ΔN or slowing down the degradation while maximizing energy efficiency. This may be utilized in connection with temperature sensors contained with the freezer 810 or refrigerator 810. In some embodiments, certain methods of freezing may be utilized that minimize the degradation of a fish, for example that freeze from the inside to the outside. For example, the technology known as cells alive system, freezes fish from the inside out, so that the cells of the fish are not destroyed in the freezing process. This technology is available from ABI, Co. Ltd. In some embodiments, the system can determine when a new item (e.g. fish) is added to one of the storage modules 810 because the optical sensor 820 or door sensor will determine that a door has been opened, and the optical sensor 820 may determine that a new item of inventory has been placed within the freezer 810. Accordingly, the control module 710 may take that information to alter the conditions within the storage module 810 for example, it may utilize an “inside out” freezing method to preserve the quality of the fish just inserted into a freezer.
In some embodiments, a storage modules 810 control system 530 may also alter the temperature to maximize or provide certain threshold benefits to certain nutritional substances 520. For instance, in some embodiments, when produce is placed in a refrigerator 810, it requires higher moisture and a different optimal temperature than cheese or other items such as items in containers. Accordingly, on detecting a salad, the control module 710 or the local controller 530 on the storage module 810 may determine that it the humidity level is below an acceptable threshold and raise the humidity or it would determine that the temperature is below an acceptable threshold and increase the temperature. This may be based on all the detected attributes of the nutritional substances 520 in a given storage module 810 and may be changed or modified based on data from the optical sensors 820, such as an indication that the lettuce is wilting, for example.
As discussed herein, the control modules 710 may then recommend recipes, based on the following: (1) nutritional substances 520 currently in inventory, (2) their ΔN values, (3) the available conditioners 520, (4) available conditioning protocols 610, (5) the desired ΔN values of a consumer (for example, maximizing nutrition as discussed herein), and (6) consumer preferences. To perform this operation, the control module 710 through ports 720 may retrieve conditioning protocols 610 over the network as discussed herein, and then send appropriate conditioning protocols to the conditioner 540 as discussed herein.
As disclosed throughout, the first step of receiving the information regarding the identity of the nutritional substance 910, may include data output from various different attribute sensing technologies, data scanned from a dynamic information identifier, or other identifying data. This data may then be compared to information in a database or other methods as disclosed herein to determine an identity of the nutritional substance 520. For instance, the nutritional substance's 520 identity may include at least two categories of information: (1) the type of nutritional substance 520, and (2) a specific identifier for a particular nutritional substance 520. Data regarding the type of nutritional substance 520 may be utilized to categorize the nutritional substance 520 in various categories to provide an inventory that can be organized and presented in such a way to efficiently communicate valuable information to the consumer. For example, the type of nutritional substance 520 may include different classification hierarchy categories including fruits, vegetables, oranges, granny smith apples, and other classification specificity. Additionally, each identified and inventoried nutritional substance 520 will be separately maintained to track the ΔN value and other specific information associated with each unique item as disclosed herein.
Once a nutritional substance 520 has been identified and categorized, it may be added to a specific inventory that it represents in the real world (e.g., Bob's Kitchen Inventory). Accordingly, this will allow the item to be stored in a database (e.g. a relational database) in various memories locally or remotely as disclosed herein. Accordingly, the inventory can then be accessed via a smartphone or other devices from any location, and the ΔN values for each nutritional substance can be displayed.
In some embodiments, a ΔN value will also be determined and associated with the inventoried nutritional substance 520. In those embodiments, information will be received by a module or other component that represent sensed attributes of the nutritional substance 940, then a ΔN value will be determined for the nutritional substance 950 based on the sensed attribute information as disclosed herein, and then the ΔN value will be associated with the inventory record of the nutritional substance 960, as an instance of a ΔN value in an inventory of nutritional substances 520.
Accordingly, the ΔN value may be determined from a variety of sensed attributes of the nutritional substance 520. Once this information is determined and inventoried, the ΔN value over time of each nutritional substance 520 may be tracked and therefore trends analyzed. In some embodiments, the systems and methods disclosed herein may be able to determine a likely time that a nutritional substance 520 may expire and send a warning based on the trend of ΔN values. Accordingly, various other similar methods maybe utilized for tracking and managing an inventory of nutritional substances 520 and the ΔN values of those nutritional substances 520.
In some embodiments, multi-sensor hubs 2900 may be added to various storage modules 810 and/or conditioning modules 500 to implement the inventory tracking and managing functions discussed herein.
Each of the multi-sensor hubs 2900 may connect or incorporate a variable number of sensors 820 that are useful in identifying and tracking the nutritional substances 520. For instance, these sensors may include (1) temperature sensors, (2) infrared sensors, (3) spectrometers, (4) optical sensors, (5) weight sensors, (6) freshness sensors, (7) humidity sensors, (8) accelerometers, (9) light sensors and (10) and others as disclosed herein. These sensors 820 may be easily removed or replaced or added to in certain embodiments, or may be not removable. Various combinations of sensors may be utilized. Further, the hubs 2900 may include their own processing software, or may send information to a control module 710 for processing the data output from the sensors 820 as disclosed herein.
The hubs 2900 may be wired or wireless (although an optical sensor 820 may require so much additional power that a wireless hub may not include an optical sensor 820 in some embodiments). The hubs 2900 may have the ability to connect to each other, including various input and output ports. For instance, in some embodiments, they hubs 2900 may include four output ports to daisy chain the hubs 2900 together in a multi-sensor array 2910.
In some embodiments, the hubs 2900 including various optical sensors 820 and other sensors 820 may be strategically placed in the various modules including the freezer 810, refrigerator 810, cupboard 810, grill 570, and oven 570, and food preparation area 570, to optimally identify and recognize individual nutritional substances 520. Optical sensors 820 may be a multi-sensor array 1910, and maybe a standalone unit, or may be mechanically integrated into food storage appliances or areas.
As illustrated in
In some embodiments, the sensor 820 data may be trained or calibrated to determine the relative positions of each of the optical sensors 820 so that they may more easily associate or identify optical data that is output relating to the same nutritional substance 520. In other embodiments, the optical sensors 520 may be placed facing down (for example on the bottom of each shelf) towards the tops of products to ensure that none of the nutritional substances 520 will be blocked by other nutritional substances 520.
In some embodiments, an oven or other conditioner 570 may include various optical sensors 820. In some embodiments, the optical sensors 820 in an oven may contain lights that surround the perimeter of the optical sensor 820 for consistent lighting and convenient identification of the camera optical path. In some embodiments, the conditioner 570 may include a motorized turntable that will turn the nutritional substance 520 so that a single camera, or a cluster of cameras in the same position, will be able to record multiple images to reconstruct a 3D image, or to acquire optical data from each side of the nutritional substance 520. In some embodiments, the conditioner will automatically rotate the nutritional substance 520 until the machine learning algorithms have identified the nutritional substance 520 and/or determined its ΔN values.
In some embodiments, the lighting may be optimized for determining the nutritional content or identifying a nutritional substance 520. In other embodiments, the conditioner or oven may contain a filter on the window, or a method to block out all ambient light except for a light associated with the camera or other optical sensor 820. Accordingly, the light from the optical sensor 820 will be the only light reflecting off of the nutritional substance 520 and accordingly will allow the optical data output from the sensor to be more reliable. This will allow the machine learning algorithms to determine more consistent values of ΔN for nutritional substances 520.
Additionally, since the hubs 2900 can be located at any position in the storage module (e.g. refrigerator), if an array 2910 of hubs 2900 is utilized inside a single storage compartment, then the hubs 2900 may be placed at different locations and heights within the storage module, to record local conditions within the storage module. This could be quite useful, because the light, temperature, humidity and other conditions may vary significantly within a storage or conditioning module and may affect ΔN values experienced by each item in the inventory placed at different locations. In some embodiments, the hubs 2900 may include probes that could be routed from the hubs 2900 and placed inside various compartments (e.g. inside the crisper) to allow even greater flexibility in determining localized conditions.
For instance, an array 2910 of hubs 2900 may be placed at various heights on a refrigerator. Each hub 2900 of the array 2900 may include an optical sensor 820, a temperature sensor 820, and a humidity sensor 820, for example. Accordingly, the different hubs 2900 will detect the conditions at localized locations within the refrigerator, and could separately track different inventory items on, for example, each shelf. For instance, each shelf may have a hub 2900 positioned above and/or on the side of the shelf, and the hub 2900 could optically identify new inventory items added to the shelf, and then track the local conditions.
If a head of lettuce is added to the top shelf, the optical sensor 820 incorporated into the hub 2900 on the top shelf may then detect a head of lettuce has been added a specific time. Then, the hub 2900 or associated control system 710 could process the visual data and identify the food item as iceberg lettuce head. Additionally, the humidity and temperature sensors 820 can track the environment on the top of the shelf to estimate times including expiration date, and other changes including an approximate time frame for when the lettuce may wilt. In some examples, the system may alert the user that the top shelf is the least humid (by comparing the humidity levels from all three hubs 2900) and then recommend the lettuce head be placed in the lowest shelf or the crisper where the humidity will be the highest. Also, as discussed herein, the system could monitor the conditions on different levels, and optimize the conditions at each level or overall through feedback of the local environment conditions and based on the inventory currently inside the refrigerator.
The temperature sensors 820 may include any suitable temperature sensors. This may include thermistors, infra-red temperature sensors (to sense temperatures inside compartments, or other suitable temperature sensors 820. The temperature sensors 820 may be strategically placed inside of a storage container at the bottom, middle and top to acquire a distribution of temperature along the container. The humidity sensors, spectrometers and other sensors 820 may be any suitable sensors that are able to be connected to the hubs 2900.
Additionally, the hubs 2900 may include freshness sensors 820 that may sense volatile organic compounds (e.g. VOCs) or other molecules emitted as volatile gases emitted from nutritional substances 520. For instance, sensors 820 may be designed to detect levels of biogenic amines, or ethylene emitted. These sensors 820 may then be output to control modules 710 to determine or monitor the gas concentrations at certain areas of the refrigerator, or the total levels. For instance, the control system, in some embodiments, may sense a moment when the threshold level of VOCs indicate some nutritional substance has spoiled. This may be quite useful, because when one substance spoils, additional substances may spoil soon after, due to conditions and/or time of addition into the inventory (all being added at similar time) or that they may spread mold, mildew or other communicable rotting pheromones that speed up ripening of close by fruit or other nutritional substances.
Accordingly, a threshold detector may send an alert when the entire storage module 810, or specific areas experience a higher than acceptable level of VOC that indicates a nutritional substance 520 is losing freshness. Accordingly, alerts could be sent to the user through the variety of interfaces disclosed herein.
The hubs 2900 may also include an accelerometer sensor 820 to determine position, or indicate movement. For instance, the accelerometer could determine an orientation of the hub 2900 with respect to gravity which could provide it helpful information for the machine learning processing or other functions. For instance, the accelerometer could determine when the hub 2900 is facing vertically (e.g. on the bottom side of a shelf facing down to detect the visual image of the tops of the nutritional substances 520 below.
The accelerometer could also be utilized to detect movement of the hub 2900, for several reasons. First, the hub 2900 may be connected to a moveable portion of a storage module 810, for example a drawer or door. Accordingly, as disclosed herein with respect to the access sensors 820, the accelerometer data may indicate that the user has opened a door and either added or removed items. Accordingly, that could be utilized to initiate capturing of a new image, or recording a new sensor readings because (1) opening the door/moving the drawer could indicate that the inventory has changed and (2) opening the door/moving drawings may alter the ambient conditions or the position of the inventory items. Therefore, utilization of the accelerometer data may allow the control module 710 or other control system to determine various time points to take sensor readings or re-determine the inventory.
In some embodiments, the hub 2900 may include an optical sensor(s) 820. The optical sensor 820 may be a camera or series of cameras, and may be utilized to identify various nutritional substances 520 utilizing machine vision algorithms or other methods. In some embodiments, the cameras may include wide angle or fish eye lenses optimized for capturing a wide area of a storage environment. In some embodiments, the optical sensor 820 on the hub 2900 or the entire hub 2900 may include a motorized function to move the optical sensor 820 to capture an image(s) of the entire storage module 810. In other embodiments, the optical sensor 820 and/or hub may be stationary and can capture the entire cupboard using multiple optical sensors 820.
Optical sensors 820 may be various cameras or other detectors, that may be fixed, may have magnetic or mechanical mounting options so they can be moved around for optical positioning. In some embodiments, the optical sensor 820 may be attached to a mobile phone, and could be waved through a shelf, oven, or refrigerator to detect the optical data. In some embodiments, an application may provide feedback to a user to determine when they have gained enough optical data to identify a particular nutritional substance and/or identify ΔN values associated with the nutritional substance 520.
In some embodiments, the optical sensors 820 and/or hubs 2900 may be paired by reading a QR or other code on the computer screen of the main application. This will enable fast pairing of a camera system in each part of a kitchen for example. In order to implement this solution, each camera could have a Bluetooth, other wireless, or wired connection. Then, once each individual camera is purchased, it could be paired by aiming it at the screen for a particular code, and software associated with the camera could determine the appropriate settings, or appropriately manage the protocols or communication utilized to pair the devices.
The data output from the optical sensor(s) 820 may be processed in various ways for (1) identification of inventory items including by associating it with a UPC, or (2) determination of ΔN status of various nutritional items, or (3) other purposes as disclosed herein. For instance, various machine learning algorithms may be utilized to identify nutritional substances 520 through utilizing various data related to the nutritional substances 520. For instance, the data may relate to visual data captured of the nutritional substance 520 (for e.g., by a camera), other data captured including infrared data, the size, weight, color, shape, packaging, patterns, detected tags including color or shape-coded smart labels, RFID information, various other optical data, combinations of images from various cameras and other detected or sensed data regarding the nutritional substance. As disclosed herein, that data may then be matched on a server or with a database of information relating to sensed attributes and nutritional substance categories, ΔN values, other relevant information.
This data may be utilized as training data to classify nutritional substances using machine learning algorithms. For instance, types of algorithms utilized may include logistic regression, support vector machines (SVM), feature descriptors, feature matching, nearest-neighbors computation, hierarchical structures (such as kd-trees), multinomial logistic regression, factorization machines, OW-LQN Optimizer, Elastic-net and custom regularization per feature type, Hidden Markov Chain modeling, Latent Dirichlet Allocation (LDA), neural networks, random forests, and others. In some embodiments, a user may tag items after they are sensed to train the algorithms for a specific user or generally for use later. This may be advantageous for each user to tag their own items, to simplify the machine learning algorithms that can be optimized for the subset of nutritional substance 520 a particular user uses. This is because each user's select set of items may be different enough to recognize more reliably, especially because a user may have unique appliances with sensors that need to be calibrated, unique lighting conditions, and other unique features. Accordingly, the tagging data for each user may be analyzed and utilized to improve the algorithms utilized for all users.
As one example, the control module 710, other associated control system or servers 770 may analyze the optical data to identify a nutritional substance 920. Although many different types of techniques may be utilized to identify nutritional substances, in some embodiments, a nutritional substance identification system may utilize shape and color in order to identify a nutritional substance 520. In some embodiments, this may include nutritional substances 520 that include packaging.
Accordingly, a computer vision system that utilizes color to identify nutritional substances may be particular advantageous, because for packaged goods, the color(s) utilized on packaging or labels will always be the same, unless changed the producer. However, there will not be variability within a specific color scheme chose for the label packaging—the printer will print nearly the exact same color each time. Accordingly, because color varies widely among nutritional substances and product packaging, color will be a highly useful tool for identifying nutritional substances.
Additionally, the shape and/or spatial relationship of colors may be utilized to identify the nutritional substances. Like color, the shape of both unpackaged ingredients and packages will usually be highly distinctive, and be utilized for categorization utilizing visual processing methods. In some embodiments, simple statistical analysis will be performed for comparisons (such as principal component analysis, etc.). In other embodiments, sophisticated machine learning algorithms may be employed.
Although some embodiments involve the identification of raw or unpackaged ingredients (e.g., when a nutritional substance 520 is cooked in an oven), many times the nutritional substances 520 will include packaging 830. In these embodiments, the computer vision algorithm utilized to identify and track ΔN values associated with the nutritional substance 520 may be simplified by identifying brand names, various shapes (e.g., beer bottles, wine bottles, cheese, butter, etc.) or other packaging 830 characteristics.
As illustrated in
In some embodiments, systems and methods may be utilized to recognize unpackaged ingredients. In these embodiments, the systems and methods may categorize these items into groups such as carrots, fish, mackerel, or other varying degrees of specificity. In some embodiments, various systems and methods disclosed herein may be utilized to recognize various nutritional substances 520 including individual separate nutritional substances 520 in a group of nutritional substances 520 that may constitute a meal. For instance, the optical recognition technology called “findSimilar” available from Cortexica will recognize images with 95% accuracy.
In other examples, various products are available capable of using optical technology to visually identify produce and other nutritional substances, and various other items. For example, an automated optical fruit recognition system developed by Fraunhofer is capable of detecting and identifying various produce optically as described by an article titled “Automated Fruit Recognition” available at http://www.isob.fraunhofer.de/servlet/is/33328/which is incorporated by reference herein in its entirety. Accordingly, the Fraunhofer system may be utilized to determine the identity of a nutritional substance by utilizing optical data detected from the nutritional substance. Accordingly, a user could then utilize their mobile phone or other devices with optical sensors to identify nutritional substances. Additionally, an optical object recognition system is disclosed in U.S. Pat. No. 6,310,964 that is described as capable of identifying produce and is incorporated herein by reference in its entirety.
Other embodiments of machine learning and machine vision algorithms or other methods. algorithms that learn to distinguish individual items in a bowl of raw ingredients are disclosed as well. These algorithms may learn to distinguish boundaries of separate food items and identify each separate food item by color and perhaps by the fact that it is included together for a meal (e.g., hamburger is more likely to be associated with a bun).
In some embodiments, the computer vision will be utilized to return a UPC (universal purchase code) for each nutritional substance 520 identified in an inventory 920. This may allow additional information to be extracted, including weight, source, nutritional, processing history, and other attributes that may be relevant to ΔN as described herein.
Accordingly, a database of UPC associated with known nutritional substances 520 and associated images of those nutritional substances 520 may be utilized. These images and image information may be utilized to train classifiers to identify a particular nutritional substance 520 in an inventory with a particular UPC code. Accordingly, once an image of a nutritional substance 520 is output from an optical sensor 820 in a hub 2900, the image may be run through a classifier, including by analysis of the shape and color, to identify a particular UPC. As disclosed herein, that item may then be saved into a database of items in an inventory.
In one example, the inventors have built a system for recognizing food items using a multi-node or classifier approach to identifying nutritional substances. In some examples, the system uses the context or background information (e.g. the scene) to assist in identification. The system may be optimized or trained to operate in the food domain, and embodiments of the system may operate in the context of any of: transportation, storage, preservation, conditioning, or transformation of food. The combination of domain specificity (e.g. food), apparatus capabilities, and method for orchestrating the computer vision process makes it possible to achieve results that are better and more meaningful to the user as compared to existing computer vision system. In some embodiments, food substances identified by the system and method of the present invention are then communicated to users for various applications, such as for example using the identified food substance in a user's profile, and/or making recommendations to a user.
In some examples, the system utilizes optical sensors 820 to capture images that are analyzed to identify nutritional substances 520. The optical sensors 820 may capture images that include: visible light images, non-visible spectrum images, depth maps and others that are obtained by a variety of means and/or at various resolutions. Accordingly, various types of appropriate optical sensors 820 may be utilized that record this information. For instance, optical sensors 820 may be RGB sensors, infrared sensors/cameras, hyperspectral sensors, and other suitable sensors capable of sensing different visible and non-visible light waves.
Very importantly, other sensors 820 may acquire information in addition to optical information directly from the nutritional substance 520 and/or its packaging. For instance, sensors 820 may also detect: ambient light, temperature (e.g. thermistors, etc.), humidity, activity indicators (e.g motion), object or aggregate weight, geographical location (e.g. GPS), device state, physical orientation (accelerometer/gyroscope), linear or rotational speed, sounds, etc.
Further, in some embodiments, the system can utilize this data output from sensors 820 that sense various aspects of the environment to improve the outcome of computer vision processing. For instance, these sensors 820 may output data that indicates various environmental factors should be changed. Examples of actions that may change the environment may include: changing the intensity or composition of light for image capture, changing temperature or humidity (including for the purpose of defogging a lens), changing an orientation for the capture sensors or object/scene, etc.
For instance, various machine learning or other algorithms may be trained optimally at a certain light level that for example, may not be optimal for maintaining food, or for a user to see the products. Accordingly, the system may modify these factors for the purpose of capturing an image by an optical sensor 820 optimized for identification using existing algorithms, and then restore the lighting conditions (or other conditions).
Additionally, images processed that are output from an optical sensor 820 or other sensors to determine the identity of a product may be assisted or complemented by physical context information such as scene coordinates or dimensions—this can be either done by the apparatus based on knowledge of its environment (including but not limited to physical orientation, distance measurements, and hardware context/location within a larger appliance/model number), or indirectly based on information provided by the user at some time.
It is to be noted that all of the above attributes of the apparatus can operate independently, and in some cases the system may need to operate exclusively on visible light images of objects or scenes.
The method for operating the computer vision system involves a service implemented in software which may execute in physical proximity to the capture apparatus (on a locally present CPU or GPU), remotely (such as in the cloud), or using a mix of these (some local processing and some remote processing).
The method can both involve passively receiving images and associated data from the various sensors 820, as well as potentially requesting information or directing the apparatus to capture data from sensors 820 in order to ensure optimal computer vision results. For example, the method can involve changing the light conditions, object/scene/camera orientation, or capturing multiple images, potentially in different conditions, with the purpose of post-processing.
The method may also incorporate the state or background environment of the captured nutritional substance 520, whereby scenes produced in similar conditions (such as physical location, same enclosing appliance, etc.) can be compared either directly or in terms of the analysis results, using the advance knowledge of similarity.
In one example, the image and other data output from various sensors 820 (or input by the user or through other information databases) may be sent through a pipeline that has several image data analysis stages or classifiers which from a graph (formally or implicitly). The pipeline structure and specific stage implementation are particularly attuned or trained for the food domain, and the types of scenes or environment typically capture alongside food. For example, there can be nodes in the graph of the image data processing pipeline that distinguish and identify only raw or packaged goods, or certain stages may involve distinguishing among several types of background scenes (such as “grocery aisle”, “fridge”, “cabinet”, “countertop”, etc.) and then activating other stages based on that analysis.
In this graph, for a particular scene being analyzed some nodes may be skipped as not relevant to the particular image frame(s). For example (but not to limit the scope of the invention), if one stage of the analysis determines the image data frame includes background that indicates it was captured in a store shelf with packaged goods, analysis for raw ingredients may be skipped and the system may assume that the nutritional substance 520 pictured is a packaged good.
The system has been specialized for the food domain, and using specialized types of computer vision stages and relationships between them. For instance, in some examples the various stages may include but are not limited to: scene classification (SC) to determine the background or environmental factors in which the optical data from the optical sensor 820 was captured. In some examples, this will be performed first to determine the background. The background scene may then be utilized to limit the nodes that are utilized, or to modify the training set applied to the frames. For instance, as mentioned above, if the background indicates that the scene is a store shelf, then raw ingredients will not be considered to match the nutritional substances 520 in the data frames output from the sensor 820. Additionally, then the image or training set utilized (or model that was trained) may be related to images only from store shelves, which may have approximately similar lighting conditions. In another example, if the scene is a refrigerator or a cabinet, then both packaged and raw ingredients may be considered and matched.
In some examples, the scene detection may be determined by analyzing the frames, for example if the optical sensor 820 is from a mobile phone where it may be used in different scenes. In other examples, if the optical sensor 820 is a refrigerator or if it is somewhere else that is a stationary location, the system will automatically determine the scene, and so that step may be skipped and/or the results of the outcome immediately applied without first processing the frames.
The next step may be object detection (OD). This step may include object detection (OD) and more concretely produce detection (PD), package/container detection (CPD), produce classification (PC), container classification (CC), TOP N classification (TNC), precise matching (PM). Each of these stages may have a variety of implementations, based on different underlying algorithms. For instance, the first step may determine whether produce detection is performed (for example, if on a grocery shelf, perhaps not—but elsewhere in a grocery store it may be performed). Accordingly, each classification step may include a variety of different classifiers that are optimized for certain lighting conditions and other contextual information or for certain users.
Accordingly, following is an example of a node based implementation of a computer vision recognition system for nutritional substances 520. The following steps are merely exemplary, and may be changed, modified or added to in order to refine or optimize various machine learning algorithms for identification of food items.
In the first step, the system may take an image with an optical sensor 820. If the system is using a stationary optical sensor 820, the system may first determine whether there is a change from a previous image taken by the same optical sensor 820. If the system detects that there was a big change (product was added or removed) then the image frame or frames may be forwarded (or a portion of the frame) to the next step for recognizing the products in the frame(s) of the image data output from the optical sensor 820.
After taking an image, the image data may first be processed to identify the top N products likely contained in the image data frame(s). In some examples, the system will be based on a KD-tree with local non-binary descriptors of all products in DB that will have to be initially trained. For each image in the database, various descriptors will need to be retrieved.
For each descriptor of analyzed image frame, the system may retrieve the 10 closest descriptors, for example, in the KD-tree. Then, the system will rank the products based on how close the descriptors match. For instance, the Rank 1 product may receive an additional 10 points to its total score, the Rank 2 product gets 9 points, etc. Accordingly, the system will then sort all products descending by aggregate score. Then, the top-N (e.g. 50) products from this list will be passed to next step for precise matching of the product. This phase therefore comes up with an N number of possible matches for a nutritional substance 520 in an image frame output from an optical sensor 820.
The next step will use precise matching based on the top N products narrowed down from the database. In this step, the system will analyze the image data to identify matching features for each product.
For instance, in one example, the system may estimate perspective transforms using Random Sample Consensus (RANSAC). Then, these transforms may be filtered.
Next the system may estimate the bounds of a product by drawing boundaries on the image data or frame that likely contain a single product. Then, the boxes or rectangles may be filtered based on the rectangle size (e.g., filter box or rectangles that are to small and too large). Then, the system may group rectangles by rectangle intersection and same matched descriptors.
In each group of rectangles, in each group sort matches by similarity estimated as:
In some examples, the system will superimpose a dot on the user interface for each group of boxes with a description. The identity of the product may be determined based on all previously recognized products on all devices of a user, all corrections done by the user, and list of recognized products for this group from previous step.
In some examples, the user can modify the product if the user determines the system has misidentified the product or indicated the product is not in the system. If the user indicates the product is incorrect, the system may display images of all of the top N products identified for that particular image box, and the user can select the correct product if it is in the list of top N products. The system may then display all list of products in this group as suggestions. If the product is not in the top N products, the user can choose the product manually from all the products in the database DB (by name, by bar code scan etc.). Accordingly, the system can record that user A changed product P1 to P2 and potentially update the machine learning models or training set for a particular classifier or other algorithm.
Following is an example of one system developed by the inventor(s) that detects products based on an image of a refrigerator. For instance, in this case an image sensor 820 has taken an image inside of a refrigerator and output one or more frames of the image for processing by the system.
The output of this first step will be 30-200 products (in one example), with a high probability that items on the output image of the refrigerator shelf are in this list, but most of the output will be non-related items. For example, if the image contains 20 recognizable items, perhaps 15 of them are in the list of 30-200, and the rest of the 30-200 items are “false positives” as illustrated in
For good scaling to large amount of products the system has a computational complexity O(log(N)), where N is count of different items that system can recognize. This means that if it takes 10 seconds to do search over 1000 images, then it takes ˜11 seconds for 2000 images, and ˜20 seconds for 1,000,000 images. So this is fast, high recall and low precision stage. Accordingly, bifurcating the system into a two stage step saves large amounts of processing time, and allows the system to perform image identification in a reasonable amount of time with respect to the user.
In order to train the system to identify the top N products, for each image of a product in a trainset, the system will detect keypoints (e.g. by using a corner detector, like Harris method, etc.). For each keypoint, the system then estimates local non-binary feature descriptor (for instance, in some examples the system uses color local non-binary feature descriptor).
After identifying keypoints, then the system may build a KD-tree with local non-binary descriptors of all products in DB for example as illustrated in
Accordingly, after the system is trained, it may then be used to detect products that are in the frame of an image output from an optical sensor 820. Accordingly, the system then detects keypoints on the given image and extracts feature descriptors for each point. This step is same as for training stage.
For each feature descriptor on the given image from one of the keypoints identified on the image, the system may identify top 10 approximate nearest neighbors in KD-tree built on training stage. Accordingly, products in the database corresponding to nearest feature will get additional 11 points of score, second will get 10 points, etc. Every product not in top 10 will not receive any additional score as illustrated in
Then, the system may sum points per product for each feature, then sort array of scores descending. Top-50 products with largest scores will be returned.
Following top N products identification, a precise matching step may be initiated on the top N products that are utilized to identify one specific product. For instance, the input to the precise matching algorithm may be the same image
Next, the system will retrieve the small subset of images from the trainset that were identified for detected products on Top-N step as illustrated in
In some examples, the first step of detection will be done independently for each product in train set. That's why this step can be easily parallelized on multi-core PC. Each product in train set can be run on a different thread.
For each feature descriptor on an analyzed image, the system may find two exact nearest neighbors on image from the train set. A noise filter may match by the following rule: let distances be d1 and d2. If d2/d1<T, then this is a valid feature descriptor, otherwise it's noise. Accordingly, there is some threshold, which can be tuned and depends on descriptor type that will be used.
Based on extracted matches, the system can find perspective transforms using RANSAC. Next, the system may filter unrealistic transforms. First, unrealistic transforms occur when a perspective part of the transform, which is contained in 3rd row of transformation matrix (a b 1), causes division by 0 for some coordinates inside image. In other words: 1 x*a+y*b+1=0 has a solution inside image.
The system may check this by checking the sign of “x*a+y*b+1” for with coordinates of corners of image. If the sign changes, then the system may filter this product. Next the system may use an inverse perspective transform to calculate estimated bounding boxes of products on source image.
Another method to sort unrealistic transforms is based on checking the area of the rectangles. The system may filter small rectangles below a particular size threshold, because none of the products in the train set are smaller than a threshold size. This may be possible in some cases by estimating the distance from the products to the camera, for instance when the distance is known (as in the case of a fixed optical sensor 820 in the fridge). Additionally, the system may filter boxes because we know based on their size they will not fit on a shelf in the fridge.
In the next step, the system may group rectangles that were detected in same place as illustrated in
To do this, the system may check if two rectangles intersect for more than 70% both ways or they share more than 50% of matched features. This often happens when they share the same logo. In this case it can be totally differently shaped rectangles, but this check will still group them.
Next, the system will need to choose one product from each group, which is a best match. First, the system needs to identify precise boundaries of product on image from train set, then use the extracted transformation, to estimate this boundary on analyzed image.
Images in train set always have a white background around the product, accordingly in some examples the system may use floodfill algorithm to estimate mask as illustrated in
After the system returns the mask, the system can compare color histograms for two images, for example by comparing
In some embodiments, after a nutritional substance 520 is identified and inventoried 930, the optical sensor 820 data and other data may be utilized to determine the nutritional content or ΔN values of a nutritional substance 520 that is being stored or conditioned over time. In some embodiments, ΔN values may be determined at regular intervals or based on some trigger (e.g., a door is opened). Various sensors and other data, including computer vision may be utilized to track the ΔN values of each nutritional substance 520.
Various sensors that may be utilized to track the ΔN values may include (1) temperature sensors, (2) infrared sensors, (3) spectrometers, (4) optical sensors, (5) weight sensors, (6) freshness sensors, (7) humidity sensors, (8) accelerometers, (9) light sensors and (10) and others as disclosed herein.
In some embodiments, the optical sensors 820 may be used alone or in combination with various other sensor data to determine ΔN values. For instance, the optical sensors may track the color, shape, and size of a nutritional substance to determine its ΔN values. For instance, an orange may be inventoried at a certain time when it is placed inside of a refrigerator. Once an optical sensor 820 records an image, the system may determine the identity 920 of that nutritional substance 520 and store it as an item in an inventory 940. Additionally, sensed data (e.g. optical data) may be also received 940 in order to determine an initial ΔN value of the orange. In other embodiments, ΔN values and other information may be known about the particular nutritional substance 520 based on information on a label or its association with a database that has already tracked the nutritional substance 520.
Accordingly, the initial ΔN value or values upon inventorying may be determined or looked up. In some embodiments, an optical sensor 820 may record the visual image of an orange and be compared to a database of information regarding ΔN values and various nutritional substances 520 including oranges. The machine learning algorithms or other algorithms may then be utilized to determine or estimate an approximate value of ΔN for that particular nutritional substance. For instance, the color of the orange may indicate ripeness, water content, and other ΔN information. The system may also analyze information from multiple nutritional substances 520 in inventory, and calculate a score that indicates overall healthiness, nutritional profile, or quality level.
As the orange is stored in the refrigerator over time, additional ΔN values may be determined for the nutritional substance 520. These may indicate a change in nutritional content, for instance the orange may lose shape as it dehydrates, and may start to brown as it spoils. The algorithms and visual data alone may be enough to determine ΔN values of a nutritional substance. In some embodiments, the systems and methods will not determine absolute values of ΔN, but instead track the relative degradation or spoliation from the initial inventorying 930, and calculate a percentage degradation. Additionally, the rate of degradation may be tracked over time and determined to project an expiration date. In some embodiments, the system may be trained to determine a threshold date that each particular nutritional substance 520 will likely expire. In some embodiments, the system will estimate the length of time nutritional substance 520 has been outside of the storage environment (e.g. refrigerator), and estimate ΔN based on the change in environmental variables (e.g. higher temperature leading to faster bacteria growth).
In some embodiments, other data may be utilized with the computer vision data to determine additional information. For instance, in some embodiments, a combination of computer vision and temperature data may be easily utilized to determine the likely ΔN values of each nutritional substance 520 based on the methods described herein. For instance, the temperature values may be useful in determining changes in nutritional content and to project future nutritional content changes.
Weight sensors 820 (e.g. scales in shelving) may also be utilized to determine the ΔN values of inventoried nutritional substance in combination with the computer vision or alone. Weight data may be useful to determine the change in water content of produce and other nutritional substances 520 for example. In some embodiments, weight sensors alone will determine when produce has spoiled. In some embodiments, an oven 570 may contain an optical sensor 820, and a scale and a temperature sensor. As disclosed herein, the combination of data from the sensors may be correlated to determine optimal cooking times.
In some embodiments, the system may utilized 3D sensors to estimate the weight and/or volume of nutritional substances, instead of using direct weight sensors. For instance, products available from Intel RealSense have this capability.
Additionally, the computer vision algorithms may be utilized to determine how well done a nutritional substance 520 is cooked. In general the computer vision algorithms may be trained to accurately predict the doneness of meat or other nutritional substances 520 based on optical sensor 820 data alone, or in combination with temperature, weight or other sensor data.
In some embodiments, the systems and methods may identify particular users or consumers, and associate a profile with that particular user. For instance, in some embodiments, a user may enter information like, age, height, weight, allergies, food preferences (e.g., meat well done), favorite recipes, custom recipes as disclosed above, or other information. Then the computer vision could be utilized to recognize individual users (e.g. by the hand or an outward facing camera to identify the entire person. Then, that user's recipes and preferences could be utilized for example, when cooking a nutritional substance in an oven 570.
User preferences or history may be utilized to bias or weight classifications made of nutritional substance 520 for a particular user or household. Accordingly, the system may remember past selections based on input sensor data 820, and bias conflicting or borderline results, for example, to identify a nutritional substance a user has previously utilized. Additionally, options for allowing user to select or correct identifications may also be utilized to optimize identification for a particular user.
It should initially be understood that the disclosure herein may be implemented with any type of hardware and/or software, and may be a pre-programmed general purpose computing device. For example, the system may be implemented using a server, a personal computer, a portable computer, a thin client, or any suitable device or devices. The disclosure and/or components thereof may be a single device at a single location, or multiple devices at a single, or multiple, locations that are connected together using any appropriate communication protocols over any communication medium such as electric cable, fiber optic cable, or in a wireless manner.
In practice, a motorized tilt-able camera mechanism can be employed in a multi-sensor array. This will help increase the field of view and can expand the capability of a camera. and reduce the need for multiple cameras.
It should also be noted that the disclosure is illustrated and discussed herein as having a plurality of modules which perform particular functions. It should be understood that these modules are merely schematically illustrated based on their function for clarity purposes only, and do not necessary represent specific hardware or software. In this regard, these modules may be hardware and/or software implemented to substantially perform the particular functions discussed. Moreover, the modules may be combined together within the disclosure, or divided into additional modules based on the particular function desired. Thus, the disclosure should not be construed to limit the present invention, but merely be understood to illustrate one example implementation thereof.
The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. In some implementations, a server transmits data (e.g., an HTML page) to a client device (e.g., for purposes of displaying data to and receiving user input from a user interacting with the client device). Data generated at the client device (e.g., a result of the user interaction) can be received from the client device at the server.
Implementations of the subject matter described in this specification can be implemented in a computing system that includes a back-end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front-end component, e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the subject matter described in this specification, or any combination of one or more such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (“LAN”) and a wide area network (“WAN”), an inter-network (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks).
Implementations of the subject matter and the operations described in this specification can be implemented in digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them. Implementations of the subject matter described in this specification can be implemented as one or more computer programs, i.e., one or more modules of computer program instructions, encoded on computer storage medium for execution by, or to control the operation of, data processing apparatus. Alternatively or in addition, the program instructions can be encoded on an artificially-generated propagated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information for transmission to suitable receiver apparatus for execution by a data processing apparatus. A computer storage medium can be, or be included in, a computer-readable storage device, a computer-readable storage substrate, a random or serial access memory array or device, or a combination of one or more of them. Moreover, while a computer storage medium is not a propagated signal, a computer storage medium can be a source or destination of computer program instructions encoded in an artificially-generated propagated signal. The computer storage medium can also be, or be included in, one or more separate physical components or media (e.g., multiple CDs, disks, or other storage devices).
The operations described in this specification can be implemented as operations performed by a “data processing apparatus” on data stored on one or more computer-readable storage devices or received from other sources.
The term “data processing apparatus” encompasses all kinds of apparatus, devices, and machines for processing data, including by way of example a programmable processor, a computer, a system on a chip, or multiple ones, or combinations, of the foregoing The apparatus can include special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit). The apparatus can also include, in addition to hardware, code that creates an execution environment for the computer program in question, e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, a cross-platform runtime environment, a virtual machine, or a combination of one or more of them. The apparatus and execution environment can realize various different computing model infrastructures, such as web services, distributed computing and grid computing infrastructures.
A computer program (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted languages, declarative or procedural languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, object, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub-programs, or portions of code). A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.
The processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computer programs to perform actions by operating on input data and generating output. The processes and logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit).
Processors suitable for the execution of a computer program include, by way of example, Raspberry processors. both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from a read-only memory or a random access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks. However, a computer need not have such devices. Moreover, a computer can be embedded in another device, e.g., a mobile telephone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a Global Positioning System (GPS) receiver, or a portable storage device (e.g., a universal serial bus (USB) flash drive), to name just a few. Devices suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.
It is understood that nutritional substance attribute sensors according to the present inventions, can beneficially be provided with, or combined with, other nutritional substance modules, including transformation, preservation, and consumer modules. For example, the nutritional substance attribute sensors could be provided with the local storage environments, containers, and coupons described herein. Nutritional substance attribute sensors, or at least a portion of the nutritional substance attribute sensor, could be provided with or incorporated into the package of any pre-packaged nutritional substance, such that a consumer may interrogate the package without disrupting its integrity to obtain information related to a nutritional, organoleptic, or aesthetic value of the nutritional substance contained therein. Further, nutritional substance attribute sensors, or at least a portion of the nutritional substance attribute sensor, could be provided with, coupled to, or incorporated into smartphones. This would enable a wide array of users and scenarios wherein nutritional substances can be identified and their current nutritional, organoleptic, and aesthetic state can be determined. As a specific example, a smartphone user may view a specific item (e.g., eggs, apples, or milk) in a refrigerator, and then click on the specific item to gain more information about it. The additional information can be related, for instance, to the organoleptic state of the item, its freshness, its present nutritional value, changes in its nutritional value, its quantity, and so forth. As a very specific example, the additional information may be used to improve or modify an estimate of shelf life of a product as compared to its “standard” shelf life depending upon the local environment of a product (e.g., the local temperature, humidity, exposure to light, exposure to neighboring products, and so forth). The additional information may relate or be related to the projected state of food (organoleptic and ΔN values) replenishment, inventory control, recipe selection, meal planning and so on. Inventory information can, for example, be cumulative between various storage locations, such as cupboards, refrigerators, pantries, preparation stations and the like in a home or apartment. Recipe selection and meal planning can related the quantities of various products to digital recipes to provide quantitative information on serving size, nutritional content and so forth. The recipe selection and meal planning can be based upon calculations that account for remaining shelf life, changes in ΔN values, and so forth.
The above-described multi-sensor array for identifying and tracking an inventory of nutritional substances at local location can be embedded in a storage unit such a refrigerator or modular in the sense that the array can be removed by a user. In any event, the storage unit can include power and communication bus capabilities for multi-sensor array. In the modular embodiments, a multi-sensor array could be updated as additional or improved sensors become available and older sensors/processors become technologically obsolete. Thus, the information-providing capabilities of a storage unit can be updated without replacement of the storage unit itself.
The information gained from the above-described multi-sensor arrays can not only be used for the above-mentioned purposes but, also, can be used to modify the operation of the storage unit itself. More particularly, an adaptive food storage system modifies the operation of any food storage area in response to sensor output, including changes in temperature, ventilation, light, ultraviolet light, etc. dependent upon the sensed state of particular food substances themselves. In other words, the sensed state of a particular food substance can be used to adaptively control the storage environment of the food substance itself.
In addition, using information from the above-described multi-sensor arrays, a food conditioning system could, for instance, capture an image of storage container, and associates it with one or more nutritional substances 520 that have been or are being conditioned, or otherwise under management by the system (e.g. in a tracked food storage or food preparation area.) The system could track this temporary or permanent association, and provide information to users or devices based on the associated information.
In other embodiments, the image captured may be made with an optical sensor on a multi-sensor hub, a mobile phone, or other external devices. The database and server, or other control systems will then identify the nutritional substances 520 and provide the food recognition, food management and all other services.
Food conditioning system uses MV to identify a food package or container under management, and the system applies an adaptive conditioning protocol based on the associated information (may include contents, previous conditioning protocols applied, weight, temperature, age, or any other projected or sensor-derived status).
In addition, the system may make recommendations to users for actions to optimize the condition of food, including covering or uncovering food, moving within different food storage areas, applying a food conditioning protocol, or any other user action.
Unless the context clearly requires otherwise, throughout the description and the claims, the words “comprise,” “comprising,” and the like are to be construed in an inclusive sense (i.e., to say, in the sense of “including, but not limited to”), as opposed to an exclusive or exhaustive sense. As used herein, the terms “connected,” “coupled,” or any variant thereof means any connection or coupling, either direct or indirect, between two or more elements. Such a coupling or connection between the elements can be physical, logical, or a combination thereof. Additionally, the words “herein,” “above,” “below,” and words of similar import, when used in this application, refer to this application as a whole and not to any particular portions of this application. Where the context permits, words in the above Detailed Description using the singular or plural number may also include the plural or singular number respectively. The word “or,” in reference to a list of two or more items, covers all of the following interpretations of the word: any of the items in the list, all of the items in the list, and any combination of the items in the list.
The above Detailed Description of examples of the invention is not intended to be exhaustive or to limit the invention to the precise form disclosed above. While specific examples for the invention are described above for illustrative purposes, various equivalent modifications are possible within the scope of the invention, as those skilled in the relevant art will recognize. While processes or blocks are presented in a given order in this application, alternative implementations may perform routines having steps performed in a different order, or employ systems having blocks in a different order. Some processes or blocks may be deleted, moved, added, subdivided, combined, and/or modified to provide alternative or sub-combinations. Also, while processes or blocks are at times shown as being performed in series, these processes or blocks may instead be performed or implemented in parallel, or may be performed at different times. Further any specific numbers noted herein are only examples. It is understood that alternative implementations may employ differing values or ranges.
The various illustrations and teachings provided herein can also be applied to systems other than the system described above. The elements and acts of the various examples described above can be combined to provide further implementations of the invention.
Any patents and applications and other references noted above, including any that may be listed in accompanying filing papers, are incorporated herein by reference. Aspects of the invention can be modified, if necessary, to employ the systems, functions, and concepts included in such references to provide further implementations of the invention.
These and other changes can be made to the invention in light of the above Detailed Description. While the above description describes certain examples of the invention, and describes the best mode contemplated, no matter how detailed the above appears in text, the invention can be practiced in many ways. Details of the system may vary considerably in its specific implementation, while still being encompassed by the invention disclosed herein. As noted above, particular terminology used when describing certain features or aspects of the invention should not be taken to imply that the terminology is being redefined herein to be restricted to any specific characteristics, features, or aspects of the invention with which that terminology is associated. In general, the terms used in the following claims should not be construed to limit the invention to the specific examples disclosed in the specification, unless the above Detailed Description section explicitly defines such terms. Accordingly, the actual scope of the invention encompasses not only the disclosed examples, but also all equivalent ways of practicing or implementing the invention under the claims.
While certain aspects of the invention are presented below in certain claim forms, the applicant contemplates the various aspects of the invention in any number of claim forms. For example, while only one aspect of the invention is recited as a means-plus-function claim under 35 U.S.C. § 112, sixth paragraph, other aspects may likewise be embodied as a means-plus-function claim, or in other forms, such as being embodied in a computer-readable medium. Any claims intended to be treated under 35 U.S.C. § 112, ¶6 will begin with the words “means for.” Accordingly, the applicant reserves the right to add additional claims after filing the application to pursue such additional claim forms for other aspects of the invention.
This application claims the benefit of, and priority to, U.S. Provisional Patent Application Ser. No. 62/458,439, filed on Feb. 13, 2017 and entitled “Computer Vision Based Food System and Method,” the disclosure of which is hereby incorporated by reference in its entirety.
| Number | Date | Country | |
|---|---|---|---|
| 62458439 | Feb 2017 | US |
