Patent Application
20150358777
Embodiments relate to generating a location profile of an internet of things (IoT) device based on augmented location information (ALI) associated with one or more nearby IoT devices.
The Internet is a global system of interconnected computers and computer networks that use a standard Internet protocol suite (e.g., the Transmission Control Protocol (TCP) and Internet Protocol (IP)) to communicate with each other. The Internet of Things (IoT) is based on the idea that everyday objects, not just computers and computer networks, can be readable, recognizable, locatable, addressable, and controllable via an IoT communications network (e.g., an ad-hoc system or the Internet).
A number of market trends are driving development of IoT devices. For example, increasing energy costs are driving governments' strategic investments in smart grids and support for future consumption, such as for electric vehicles and public charging stations. Increasing health care costs and aging populations are driving development for remote/connected health care and fitness services. A technological revolution in the home is driving development for new “smart” services (e.g. smart home appliances), including consolidation by service providers marketing ‘N’ play (e.g., data, voice, video, security, energy management, etc.) and expanding home networks. Buildings are getting smarter and more convenient as a means to reduce operational costs for enterprise facilities.
There are a number of key applications for the IoT. For example, in the area of smart grids and energy management, utility companies can optimize delivery of energy to homes and businesses while customers can better manage energy usage. In the area of home and building automation, smart homes and buildings can have centralized control over virtually any device or system in the home or office, from appliances to plug-in electric vehicle (PEV) security systems. In the field of asset tracking, enterprises, hospitals, factories, and other large organizations can accurately track the locations of high-value equipment, patients, vehicles, and so on. In the area of health and wellness, doctors can remotely monitor patients' health while people can track the progress of fitness routines.
Certain IoT devices may be mobile, in which case, a user may misplace or forget where he/she placed one or more mobile IoT devices from time to time. It is generally difficult to pinpoint the location of such mobile IoT devices at a granularity that would be relevant to a user searching for the devices within a particular IoT environment. For example, conventional solutions for identifying a lost IoT device (e.g., a cell phone, a tablet PC, etc.) include requesting that the “lost” IoT device emit a noise (e.g., a periodic beeping noise or other alert sound) that is detectable by the user from which the user can track down the device location, or to report a coarse location estimate such as a GPS location or a current WiFi hotspot or cell tower to which the lost IoT device is connected. However, the user may be out-of-range of the noise (or the IoT environment could simply be really loud) and the GPS location may only function to confirm that the lost device is in a particular IoT environment (as opposed to being stolen or otherwise off the premises) without providing much information on where the lost device is located within the IoT environment.
In an embodiment, an Internet of Things (IoT) device obtains augmented location information (ALI) that identifies (i) one or more device classifications (e.g., mobile, geo-static, etc.) for one or more IoT devices near the IoT device in the IoT environment and/or (ii) immediate surroundings (e.g., a picture, an audio recording, etc.) of the one or more IoT devices, and generates a location profile of the IoT device based on the obtained ALI. In another embodiment, a power-limited IoT device selects a proxy IoT device. The selected proxy IoT device performs an ALI reporting function on behalf of the power-limited IoT device, while the power-limited IoT device refrains from performing the ALI reporting function.
A more complete appreciation of aspects of the disclosure and many of the attendant advantages thereof will be readily obtained as the same becomes better understood by reference to the following detailed description when considered in connection with the accompanying drawings which are presented solely for illustration and not limitation of the disclosure, and in which:
Various aspects are disclosed in the following description and related drawings to show specific examples relating to exemplary embodiments of proximity detection between Internet of Things (IoT) devices. Alternate embodiments will be apparent to those skilled in the pertinent art upon reading this disclosure, and may be constructed and practiced without departing from the scope or spirit of the disclosure. Additionally, well-known elements will not be described in detail or may be omitted so as to not obscure the relevant details of the aspects and embodiments disclosed herein.
The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments. Likewise, the term “embodiments” does not require that all embodiments include the discussed feature, advantage or mode of operation.
The terminology used herein describes particular embodiments only and should be construed to limit any embodiments disclosed herein. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes,” and/or “including,” when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
Further, many aspects are described in terms of sequences of actions to be performed by, for example, elements of a computing device. It will be recognized that various actions described herein can be performed by specific circuits (e.g., an application specific integrated circuit (ASIC)), by program instructions being executed by one or more processors, or by a combination of both. Additionally, these sequence of actions described herein can be considered to be embodied entirely within any form of computer readable storage medium having stored therein a corresponding set of computer instructions that upon execution would cause an associated processor to perform the functionality described herein. Thus, the various aspects of the disclosure may be embodied in a number of different forms, all of which have been contemplated to be within the scope of the claimed subject matter. In addition, for each of the aspects described herein, the corresponding form of any such aspects may be described herein as, for example, “logic configured to” perform the described action.
As used herein, the term “Internet of Things device” (or “IoT device”) may refer to any object (e.g., an appliance, a sensor, etc.) that has an addressable interface (e.g., an Internet protocol (IP) address, a Bluetooth identifier (ID), a near-field communication (NFC) ID, etc.) and can transmit information to one or more other devices over a wired or wireless connection. An IoT device may have a passive communication interface, such as a quick response (QR) code, a radio-frequency identification (RFID) tag, an NFC tag, or the like, or an active communication interface, such as a modem, a transceiver, a transmitter-receiver, or the like. An IoT device can have a particular set of attributes (e.g., a device state or status, such as whether the IoT device is on or off, open or closed, idle or active, available for task execution or busy, and so on, a cooling or heating function, an environmental monitoring or recording function, a light-emitting function, a sound-emitting function, etc.) that can be embedded in and/or controlled/monitored by a central processing unit (CPU), microprocessor, ASIC, or the like, and configured for connection to an IoT network such as a local ad-hoc network or the Internet. For example, IoT devices may include, but are not limited to, refrigerators, toasters, ovens, microwaves, freezers, dishwashers, dishes, hand tools, clothes washers, clothes dryers, furnaces, air conditioners, thermostats, televisions, light fixtures, vacuum cleaners, sprinklers, electricity meters, gas meters, etc., so long as the devices are equipped with an addressable communications interface for communicating with the IoT network. IoT devices may also include cell phones, desktop computers, laptop computers, tablet computers, personal digital assistants (PDAs), etc. Accordingly, the IoT network may be comprised of a combination of “legacy” Internet-accessible devices (e.g., laptop or desktop computers, cell phones, etc.) in addition to devices that do not typically have Internet-connectivity (e.g., dishwashers, etc.).
Referring to
The Internet 175 includes a number of routing agents and processing agents (not shown in
In
The access point 125 may be connected to the Internet 175 via, for example, an optical communication system, such as FiOS, a cable modem, a digital subscriber line (DSL) modem, or the like. The access point 125 may communicate with IoT devices 110-120 and the Internet 175 using the standard Internet protocols (e.g., TCP/IP).
Referring to
In a peer-to-peer network, service discovery schemes can multicast the presence of nodes, their capabilities, and group membership. The peer-to-peer devices can establish associations and subsequent interactions based on this information.
In accordance with an aspect of the disclosure,
Referring to
In one embodiment, the supervisor device 130 may generally observe, monitor, control, or otherwise manage the various other components in the wireless communications system 100B. For example, the supervisor device 130 can communicate with an access network (e.g., access point 125) over air interface 108 and/or a direct wired connection 109 to monitor or manage attributes, activities, or other states associated with the various IoT devices 110-120 in the wireless communications system 100B. The supervisor device 130 may have a wired or wireless connection to the Internet 175 and optionally to the IoT server 170 (shown as a dotted line). The supervisor device 130 may obtain information from the Internet 175 and/or the IoT server 170 that can be used to further monitor or manage attributes, activities, or other states associated with the various IoT devices 110-120. The supervisor device 130 may be a standalone device or one of IoT devices 110-120, such as computer 120. The supervisor device 130 may be a physical device or a software application running on a physical device. The supervisor device 130 may include a user interface that can output information relating to the monitored attributes, activities, or other states associated with the IoT devices 110-120 and receive input information to control or otherwise manage the attributes, activities, or other states associated therewith. Accordingly, the supervisor device 130 may generally include various components and support various wired and wireless communication interfaces to observe, monitor, control, or otherwise manage the various components in the wireless communications system 100B.
The wireless communications system 100B shown in
For example, passive IoT devices 105 may include a coffee cup and a container of orange juice that each have an RFID tag or barcode. A cabinet IoT device and the refrigerator IoT device 116 may each have an appropriate scanner or reader that can read the RFID tag or barcode to detect when the coffee cup and/or the container of orange juice passive IoT devices 105 have been added or removed. In response to the cabinet IoT device detecting the removal of the coffee cup passive IoT device 105 and the refrigerator IoT device 116 detecting the removal of the container of the orange juice passive IoT device 105, the supervisor device 130 may receive one or more signals that relate to the activities detected at the cabinet IoT device and the refrigerator IoT device 116. The supervisor device 130 may then infer that a user is drinking orange juice from the coffee cup and/or likes to drink orange juice from a coffee cup.
Although the foregoing describes the passive IoT devices 105 as having some form of RF or barcode communication interfaces, the passive IoT devices 105 may include one or more devices or other physical objects that do not have such communication capabilities. For example, certain IoT devices may have appropriate scanner or reader mechanisms that can detect shapes, sizes, colors, and/or other observable features associated with the passive IoT devices 105 to identify the passive IoT devices 105. In this manner, any suitable physical object may communicate its identity and attributes and become part of the wireless communications system 100B and be observed, monitored, controlled, or otherwise managed with the supervisor device 130. Further, passive IoT devices 105 may be coupled to or otherwise made part of the wireless communications system 100A in
In accordance with another aspect of the disclosure,
The wireless communications system 100C shown in
The IoT devices 110-118 make up an IoT device group 160. The IoT device group 160 is a group of locally connected IoT devices, such as the IoT devices connected to a user's home network. Although not shown, multiple IoT device groups may be connected to and/or communicate with each other via an IoT SuperAgent 140 connected to the Internet 175. At a high level, the supervisor device 130 manages intra-group communications, while the IoT SuperAgent 140 can manage inter-group communications. Although shown as separate devices, the supervisor device 130 and the IoT SuperAgent 140 may be, or reside on, the same device (e.g., a standalone device or an IoT device, such as computer 120 in
Each IoT device 110-118 can treat the supervisor device 130 as a peer and transmit attribute/schema updates to the supervisor device 130. When an IoT device needs to communicate with another IoT device, it can request the pointer to that IoT device from the supervisor device 130 and then communicate with the target IoT device as a peer. The IoT devices 110-118 communicate with each other over a peer-to-peer communication network using a common messaging protocol (CMP). As long as two IoT devices are CMP-enabled and connected over a common communication transport, they can communicate with each other. In the protocol stack, the CMP layer 154 is below the application layer 152 and above the transport layer 156 and the physical layer 158.
In accordance with another aspect of the disclosure,
The Internet 175 is a “resource” that can be regulated using the concept of the IoT. However, the Internet 175 is just one example of a resource that is regulated, and any resource could be regulated using the concept of the IoT. Other resources that can be regulated include, but are not limited to, electricity, gas, storage, security, and the like. An IoT device may be connected to the resource and thereby regulate it, or the resource could be regulated over the Internet 175.
IoT devices can communicate with each other to regulate their use of a resource 180. For example, IoT devices such as a toaster, a computer, and a hairdryer may communicate with each other over a Bluetooth communication interface to regulate their use of electricity (the resource 180). As another example, IoT devices such as a desktop computer, a telephone, and a tablet computer may communicate over a Wi-Fi communication interface to regulate their access to the Internet 175 (the resource 180). As yet another example, IoT devices such as a stove, a clothes dryer, and a water heater may communicate over a Wi-Fi communication interface to regulate their use of gas. Alternatively, or additionally, each IoT device may be connected to an IoT server, such as IoT server 170, which has logic to regulate their use of the resource 180 based on information received from the IoT devices.
In accordance with another aspect of the disclosure,
The wireless communications system 100E includes two IoT device groups 160A and 160B. Multiple IoT device groups may be connected to and/or communicate with each other via an IoT SuperAgent connected to the Internet 175. At a high level, an IoT SuperAgent may manage inter-group communications among IoT device groups. For example, in
As shown in
While internal components of IoT devices, such as IoT device 200A, can be embodied with different hardware configurations, a basic high-level configuration for internal hardware components is shown as platform 202 in
Accordingly, an aspect of the disclosure can include an IoT device (e.g., IoT device 200A) including the ability to perform the functions described herein. As will be appreciated by those skilled in the art, the various logic elements can be embodied in discrete elements, software modules executed on a processor (e.g., processor 208) or any combination of software and hardware to achieve the functionality disclosed herein. For example, transceiver 206, processor 208, memory 212, and I/O interface 214 may all be used cooperatively to load, store and execute the various functions disclosed herein and thus the logic to perform these functions may be distributed over various elements. Alternatively, the functionality could be incorporated into one discrete component. Therefore, the features of the IoT device 200A in
The passive IoT device 200B shown in
Although the foregoing describes the passive IoT device 200B as having some form of RF, barcode, or other I/O interface 214, the passive IoT device 200B may comprise a device or other physical object that does not have such an I/O interface 214. For example, certain IoT devices may have appropriate scanner or reader mechanisms that can detect shapes, sizes, colors, and/or other observable features associated with the passive IoT device 200B to identify the passive IoT device 200B. In this manner, any suitable physical object may communicate its identity and attributes and be observed, monitored, controlled, or otherwise managed within a controlled IoT network.
Referring to
Referring to
Referring to
Referring to
Referring to
Referring to
Generally, unless stated otherwise explicitly, the phrase “logic configured to” as used throughout this disclosure is intended to invoke an aspect that is at least partially implemented with hardware, and is not intended to map to software-only implementations that are independent of hardware. Also, it will be appreciated that the configured logic or “logic configured to” in the various blocks are not limited to specific logic gates or elements, but generally refer to the ability to perform the functionality described herein (either via hardware or a combination of hardware and software). Thus, the configured logics or “logic configured to” as illustrated in the various blocks are not necessarily implemented as logic gates or logic elements despite sharing the word “logic.” Other interactions or cooperation between the logic in the various blocks will become clear to one of ordinary skill in the art from a review of the aspects described below in more detail.
The various embodiments may be implemented on any of a variety of commercially available server devices, such as server 400 illustrated in
Also shown in
Certain IoT devices may be mobile, in which case a user may misplace or forget where he/she placed one or more mobile IoT devices from time to time. It is generally difficult to pinpoint the location of such mobile IoT devices at a granularity that would be relevant to a user searching for the devices within a particular IoT environment. For example, conventional solutions for identifying a lost IoT device (e.g., a cell phone, a tablet PC, etc.) include requesting that the “lost” IoT device emit a noise (e.g., a periodic beeping noise or other alert sound) that is detectable by the user from which the user can track down the device location, or to report a coarse location estimate such as a GPS location or a current WiFi hotspot or cell tower to which the lost IoT device is connected. However, the user may be out-of-range of the noise (or the IoT environment could simply be really loud) and the GPS location may only function to confirm that the lost device is in a particular IoT environment (as opposed to being stolen or otherwise off the premises) without providing much information on where the lost device is located within the IoT environment.
Embodiments of the invention are thereby directed to obtaining augmented location information (ALI) associated with nearby IoT devices that can be used to generate a location profile of a target IoT device, such as a lost IoT device from the above-noted examples. Unlike coarse location estimates (e.g., GPS location, WiFi hotspot or router identification, etc.), the ALI permits a user to ascertain where the target IoT device is located within a particular IoT environment, as will be explained below in more detail.
As will be explained in more detail below, the device classifications can identify type(s) of the IoT devices and/or location-descriptive name(s) of the IoT devices and can be used to imply a location association (e.g., an IoT device classified as a geo-static refrigerator is likely to be in a kitchen, and a user is likely to know where the refrigerator and kitchen are located which will help the user to converge on the target IoT device). In another example, if a home has two refrigerators (one in the kitchen and one in the basement), a user can name these devices as “kitchen refrigerator” and “basement refrigerator”, and these location-descriptive device names can be made part of the respective ALIs for the two refrigerators, which will help the user to converge on a target IoT device's location. Also, as will be explained in more detail below, the immediate surroundings of the nearby IoT devices can be conveyed in a variety of ways, such as by having the nearby IoT devices snap photographs of their surroundings. In this example, when these photographs are sent to the user, the user may be able to converge on the location of the given IoT device based on recognition of a general area shown in the photographs, based on the target IoT device itself being shown as an object in the photographs (e.g., in which case the angle or orientation between the camera and the target IoT device can be used as part of the ALI), and so on. In another example, the immediate surroundings of the nearby IoT devices can be conveyed via an audio recording (e.g., the audio recording may record a recognizable sound, such as a drying machine executing a dry cycle, which the user can use to converge on the location of the target IoT device).
After obtaining the ALI at 600, the given IoT device generates a location profile of the given IoT device based on the ALI, 605. In an example, the location profile can be generated at 605 simply by aggregating all of the ALI obtained at 600. In an alternative example, the given IoT device can apply one or more filtering rules to the ALI obtained at 600 so that a filtered version of the ALI obtained at 600 is populated within the location profile in order to increase a relevance of the information contained in the location profile. Accordingly, some or all of the ALI obtained at 600 may be populated within the location profile.
The given IoT device can also optionally augment the location profile of the given IoT device based on ALI captured by the given IoT device itself relevant to the given IoT device's immediate surroundings, 610. For example, in addition to populating the location profile with one or more images captured by nearby IoT devices, the given IoT device could also populate the location profile with its own captured image assuming the given IoT device had image capture capability (e.g., the given IoT device takes a picture that shows a landmark, and this picture can be sent to another device so that the given IoT device can be recognized as being close to the landmark and potentially a camera angle or orientation of the landmark can be used to further pinpoint the given IoT device's relative location). Also, the given IoT device can optionally transmit the location profile to another device, 615. For example, in a scenario where the given IoT device is misplaced by a user and the user is trying to track down the location of the given IoT device, the location profile can be transmitted to another device being operated by the user at 615. In another example, in a scenario where the given IoT device is operated by a child and a parent is trying to track down the location of his/her child, the location profile can be transmitted to another device being operated by the parent at 615, and so on.
In response to the scanning of 700, IoT devices 2 . . . 4 deliver ALI to IoT devices over an IoT communications interface (e.g., WiFi, Bluetooth, etc.) at 705, 710 and 715, respectively. The IoT communications interface used to provide ALI at 705 through 715 will generally correspond to the SRT by which the respective IoT device was first contacted via the scanning of 700. So, if IoT device 2 is within Bluetooth range of IoT device 1 and was first contacted by IoT device 1 via Bluetooth, IoT device 2 can send its ALI to IoT device 1 via Bluetooth at 705 in an example. In an example, the IoT communications interface used to provide ALI at 705 through 715 can correspond to the SRT by which the respective IoT device was first contacted via the scanning of 700 based on IoT device 1 issuing requests for the ALI from the respective IoT device(s) over the corresponding SRT(s) where the respective IoT device(s) were discovered. These requests can be transmitted by IoT device 1 in association with the scanning of 700 in an example.
In the embodiment of
At 720, IoT device 1 selects the ALI from some or all of IoT devices 2 . . . N to populate within its location profile. After selecting the ALI at 720, IoT device generates the location profile by populating the selected ALI within the location profile, 725. While not shown explicitly in
Generally, some ALI may be deemed to be more relevant (or to have a higher priority) than other ALI, and the selection of 720 may opt to select the more relevant ALI for inclusion within the location profile. For example, detection of a nearby IoT device with a “geo-static” device classification will generally be more relevant than a detection of a nearby “mobile” IoT device. As used herein, a geo-static IoT device refers to an IoT device that is expected to permanently or semi-permanently remain at its current position within the IoT environment. For example, a refrigerator is probably geo-static while a mobile phone is probably not geo-static, because refrigerators likely move within the IoT environment much less frequently than mobile phones. Thereby, knowledge that IoT device 1 is close to a geo-static IoT device is more likely to be relevant to ascertaining a current location of IoT device 1 as compared with knowledge that IoT device 1 is close to a mobile IoT device. However, a geo-static IoT device that is far away from IoT device 1 (e.g., only reachable via WiFi and not Bluetooth) may have less relevance than a closer mobile IoT device (e.g., reachable by Bluetooth or NFC). Also, if a nearby IoT device has the capability to take a contemporaneous photograph of its surroundings (or gather other types of contemporaneous data), the photograph itself may be highly relevant towards conveying a location of IoT device 1 irrespective of whether the device classification of the nearby IoT device is mobile or geo-static.
Accordingly, the selection of 720 can weigh a set of factors for its decision on which ALI to populate within the location profile for IoT device 1 at 720. This set of factors can include, for a corresponding nearby IoT device providing particular ALI, (i) whether the corresponding nearby IoT device is geo-static (e.g., refrigerator, oven, television, master bedroom lamp, family room television or family room photo frame, etc.) or non-geo-static (e.g., phone, iPad, kindle, etc.), (ii) whether the corresponding nearby IoT device is not geo-static but provides contemporaneous information related to its immediate environment (e.g., a picture or photograph, etc.), (iii) whether the corresponding nearby IoT device is non-geo-static but is expected to be easy to locate (e.g., a vehicle Bluetooth controller, whereby the vehicle is mobile but the user would normally be expected to know where his/her vehicle is located), (iv) a transport mechanism through which the corresponding nearby IoT device is reachable (e.g., a refrigerator reachable via Bluetooth indicates the given IoT device is in the kitchen, whereas a television reachable via WiFi is less relevant because the given IoT device is likely to be farther away from the television) and/or a (v) quality of the ALI (e.g., the ALI may correspond to a photograph, but if the room is dark, the photograph may be excluded from the location profile due to its poor quality).
Table 1 (below) shows an example generation of the location profile based on different types of ALI provided from nearby IoT Devices X, Y and Z. In Table 1, each enumerated example on each row is independent of each other, such the respective IoT Devices X, Y and Z vary from example to example such that Example #1 is not necessarily related (or correlated with) Example #2, and so on.
As shown in Table 1 (above), in example #1, IoT device X provides a device classification of “mobile phone” via WiFi, IoT device Y provides a device classification of “geo-static Family Room TV” along with a photograph via Bluetooth LE, IoT device Z provides a device classification of “geo-static refrigerator” via Bluetooth, and the location profile for IoT device 1 includes the photograph from IoT device Y and the identification of IoT device Z as a geo-static refrigerator. In this case, IoT device X's device classification of “mobile phone” is omitted because WiFi has a wider coverage area than Bluetooth LE or Bluetooth and mobile phones are not geo-static, so IoT device X's ALI is less reliable or helpful as compared to the ALI from IoT devices Y or Z.
In example #2 from Table 1 (above), IoT device X provides a device classification of “mobile phone” via Bluetooth LE and also includes a photograph taken by the mobile phone at its current location (e.g., a contemporaneous photograph), IoT device Y provides a device classification of “geo-static master bedroom lamp” via WiFi, IoT device Z provides a device classification of “geo-static refrigerator” via Bluetooth, and the location profile for IoT device 1 includes the photograph from IoT device X and the identification of IoT device Z as a geo-static refrigerator. In this case, IoT device Y's device classification of “geo-static master bedroom lamp” is omitted because WiFi has a wider coverage area than Bluetooth LE or Bluetooth and a closer geo-static reference point is available (i.e., the geo-static refrigerator or IoT device Z), so IoT device Y's ALI is less reliable or helpful as compared to the ALI from IoT devices X or Z.
In example #3 from Table 1 (above), IoT device X provides a device classification of “mobile phone” via WiFi, IoT device Y provides a device classification of “geo-static master bedroom lamp” via WiFi, IoT device Z provides a device classification of “geo-static refrigerator” via Bluetooth, and the location profile for IoT device 1 includes the identification of IoT device Z as a geo-static refrigerator. In this case, IoT device X's device classification as a “mobile phone” is omitted both because it is geo-static and received over WiFi, and IoT device Y's device classification of “geo-static master bedroom lamp” is omitted because WiFi has a wider coverage area than Bluetooth and a closer geo-static reference point is available (i.e., the geo-static refrigerator or IoT device Z), so IoT device X and Y's ALI is less reliable or helpful as compared to the ALI from IoT device Z.
In example #4 from Table 1 (above), IoT device X provides a device classification of “mobile phone” via WiFi, IoT device Y provides a device classification of “geo-static master bedroom lamp” via WiFi, IoT device Z provides a device classification of “car” via Bluetooth, and the location profile for IoT device 1 includes the identification of IoT device Z as a car. In this case, IoT device X's device classification as a “ mobile phone” is omitted both because it is not geo-static and received over WiFi, and IoT device Y's device classification of “geo-static master bedroom lamp” is omitted because WiFi has a wider coverage area than Bluetooth. In this case, even though a car is not geo-static, the car is easy for users to recognize and acts as a good reference point, so IoT device X and Y's ALI is less reliable or helpful as compared to the ALI from IoT device Z.
While
Referring to
In response to the scanning of 800, IoT devices 2...4 send device information characterizing IoT devices 2 . . . 4 to IoT device 1 over an IoT communications interface (e.g., WiFi, Bluetooth, etc.) at 805, 810 and 815, respectively. The scanning of IoT devices could be achieved over broadcast, multicast and/or unicast e.g. scanning for devices could be sent out as multicast and the response from nearby devices could be sent out as unicast to IoT device 1. The IoT communications interface used to provide ALI at 805 through 815 will generally correspond to the SRT by which the respective IoT device was first contacted via the scanning of 800. So, if IoT device 2 is within Bluetooth range of IoT device 1 and was first contacted by IoT device 1 via Bluetooth, IoT device 2 can send its ALI to IoT device 1 via Bluetooth at 805 in an example.
In the embodiment of
At 820, IoT device selects one or more IoT devices from which to acquire ALI based on the device information received at 805, 810 and 815. As noted above, the device information can already include some ALI such as device classification, so the selection at 820 can be interpreted as a selection of IoT devices from which to request additional ALI in certain scenarios. For example, a security camera reachable via WiFi may be omitted from selection at 820 if a geo-static device with a camera is available over a shorter-range SRT is available, and so on. Generally, the same type of considerations as discussed above with respect to 720 are also relevant to the selection of 820, except 720 relates to filtering ALI already received at IoT device 1 and 820 relates to filtering IoT devices from which to request ALI.
After selecting the one or more IoT devices at 820, IoT device 1 requests ALI from the selected one or more IoT devices, 825. The ALI requested at 825 can be referred to as targeted ALI, as the ALI is being requested in a more targeted manner relative to the process of
In the embodiment of
Referring to
After determining to start the location determination procedure at 900, IoT device 1 selects a first SRT to use for discovery of nearby IoT devices within an IoT environment, 905. In an example, the first SRT can be selected based at least in part upon an operating environment of IoT device 1. For example, if IoT device 1 is located in a car, the first SRT may correspond to Bluetooth, whereas if IoT device is located in a shopping mall the first SRT may correspond to WiFi. So, the first SRT does not necessarily correspond to the SRT with the shortest absolute range (although this is certainly possible), but could rather instead be environmentally selected.
In another example, the first SRT can simply correspond to an SRT with the shortest effective range among available SRTs that are used as IoT communication interfaces within a respective IoT environment, although this need not be true in all implementations. As shown in
At 925, IoT device 1 selects a second SRT to use for discovery of nearby IoT devices within an IoT environment. As shown in
At 945, IoT device 1 selects a third SRT to use for discovery of nearby IoT devices within an IoT environment. As shown in
After sufficient ALI is acquired for generation of the location profile, the IoT device 1 selects, from among its acquired ALI, ALI to be used within the location profile, 960 (e.g., similar to 720 of
In the embodiments described above with respect to
Conventionally, each IoT device in the IoT environment 500 would be individually responsible for continuously monitoring the IoT communications interface for incoming communications while also transmitting its own communications over the IoT communications interface, in part because any IoT device incapable of doing so would be assumed incapable of operating within the IoT environment 500 in any case. However, it will be appreciated that requiring each IoT device to continuously monitor the IoT communications interface and to transmit its own communications places a disproportionate burden on “power-limited” IoT devices in the IoT environment 500, as will now be explained.
As used herein, whether an IoT device is “power-limited” is a relative terminology that indicates that the power resources of one IoT device have a higher priority than the power resources of at least one other IoT device. Referring to
Accordingly, embodiments of the invention are directed to a proxy ALI scheme whereby the function of providing ALI (“ALI reporting function”) on behalf of a power-limited IoT device is transferred, in whole or in part, to at least one other IoT device.
Referring to
Further, while not shown explicitly in
Referring to
After selecting IoT device 2 as the proxy for the ALI reporting function, IoT device 1 coordinates with IoT device 2 to act as the proxy, 1120. For example, IoT device 1 can instruct IoT device 2 with respect to how to configure an ALI message to be transmitted on behalf of IoT device 1 (e.g., it invokes a “SendALI (device ID, app ID, ALI msg ID, ALI message with proxy flag, TTL)” interface on the proxy device to send its ALI information, whereby the proxy flag indicates that the ALI information transmitted by the proxy should be marked as originated from a proxy as opposed to IoT device 1 itself). For example, IoT device 1 may provide ALI such as a device classification (e.g., “car”, “television”, “mobile phone”, “living room photo frame”, “basement smoke detector”, etc.) and/or information related to IoT device 1's immediate surroundings (e.g., a photograph captured by IoT device 1, or another IoT device in its surrounding etc.) to IoT device 2. IoT device 2 can be packaged ALI for IoT device 1 into a periodically transmitted ALI message in one example (e.g., containing the device classification, etc.), or alternatively could provide ALI information explicitly when requested. In a further example, IoT device 1 can provide IoT device 2 with a defined wake-up schedule (e.g., every 30 seconds for 1 seconds, etc.) so that IoT device 2 knows when to forward any incoming ALI related messages to IoT device 1, and can optionally provide filtering criteria to IoT device 2. This permits IoT device 1 to go to sleep between scheduled wake-up times in order to conserve power. As will be explained below in more detail, the filtering criteria specifies one or more filters that are used by the IoT device 2 to decide whether or not a particular message should be transmitted to IoT device 1. For example, if IoT device 4 sends a message that requests a current photograph captured by IoT device 1 and a photograph maintained at IoT device 2 as part of IoT device 1's ALI is too old, IoT device 2 may determine to ping IoT device 1 to obtain an updated photograph to provide to IoT device 4. In another example, if IoT device 5 sends a message that requests a current audio recording captured by IoT device 1 and an audio recording is not maintained at IoT device 2 at all, IoT device 2 may determine to ping IoT device 1 to obtain the audio recording in order to provide to IoT device 4. Alternatively in some cases, proxy IoT device 2 could provide answers on behalf of IoT device 1 based on ALI information it has received from IoT device 1. For example, if IoT device 4 sends a message that requests a photograph captured by IoT device 1 and a photograph maintained at IoT device 2 as part of IoT device 1's ALI is recent enough, IoT device 2 will provide that photograph to IoT device 4 indicating that the photograph is sent from a proxy device.
In the embodiment of
At some point after 1140, IoT device 1 is permitted to power off and go to sleep, 1160 (e.g., similar to 1125). Periodically, IoT device 1 wakes up in accordance with its wake-up schedule, 1165 (e g , similar to 1130), to determine whether any change to ALI #2 needs to be made, 1175. For example, IoT device 1 can decide whether to change ALI #2 to a different ALI message (e.g., if IoT device 1 takes a new photograph of its surroundings it can replace an older photograph being provided by IoT device 2 as IoT device 1's ALI), or to stop transmission of all ALI messages by IoT device 2 on behalf of IoT device 1 (e.g. if IoT Device 1 decides to remain awake because of its power status of being plugged in). If IoT device 1 determines not to change ALI #2 at 1175, the process returns to 1160 and IoT device 1 goes back to sleep until a next wake-up period. At 1175, assume that if IoT device 1 decides to cancel the ALI reporting function altogether. Therefore, at 1180, IoT device 1 negotiates with IoT device 2 in order to stop the ALI reporting function. Accordingly, at 1185, IoT device 2 stops transmitting ALI #2—and ceases the ALI reporting function for IoT device 1.
Referring to
After determining the device details in 1205, IoT device 1 executes decision logic for selecting at least one proxy from the discovered set of nearby IoT devices based on the device details, 1210. IoT device 1 then sends ALI to its selected at least one proxy for transmission to IoT devices in the IoT environment, 1215. The IoT device 1 could optionally specify transmission details via an optional “transmission details” field in the sendALI( )message to the selected proxy device that specifies how to transmit the ALI e.g., either as a periodically transmitted ALI message or in an on-demand manner, as part of 1215. Different proxy selection rules which can be executed at 1210 are described below in Table 2. In Table 2, assume that IoT device 1 has discovered proxy candidates #1 and #2 along with their associated device details, and is attempting to select one (or both) of these proxy candidates to act as a proxy for IoT device 1. In Table 2., the ALI reporting function is shortened to “ARF”:
Referring to Table 2 (above), a number of different proxy selection rule examples are provided. In examples 1 and 2 from Table 2, a single IoT device that is less power-limited than IoT device 1, which supports the ALI reporting function and which (preferably) is geo-static is selected as the proxy. As shown in example 1 from Table 2, IoT device 1 is battery-powered at 80%, proxy candidate #1 supports the ALI reporting function while being intermittently outlet-connected and proxy candidate #2 does not support the ALI reporting function, so proxy candidate #1 is selected as the proxy. As shown in example 2 from Table 2, IoT device 1 is battery-powered at 80%, proxy candidate #1 is geo-static and supports the ALI reporting function while being intermittently outlet-connected, and proxy candidate #2 is not geo-static and supports the ALI reporting function while being battery powered at 30%, so proxy candidate #1 is selected as the proxy.
Referring to example 3 from Table 2, IoT device 1 is battery-powered at 80%, proxy candidate #1 is geo-static and supports the ALI reporting function while being intermittently outlet-connected, and proxy candidate #2 is geo-static and supports the ALI reporting function while being battery powered at 90%. In this case, proxy candidate #2 is selected to support the ALI reporting function. This selection can be made in part because proxy candidate #1 is intermittently outlet-connected while proxy candidate #2 is not outlet-connected but has access to a non-intermittent power source.
Referring to example 4 from Table 2, IoT device 1 is a high-priority smoke detector that is battery-powered at 75%, and proxy candidates #1 and #2 are each low-priority alarm clocks that each support the ALI reporting function. Proxy candidate #1 is battery-powered at 90% while proxy candidate #2 is battery-powered at 60%. In this example, proxy candidate #1 is selected to support the ALI reporting function because it has more battery power than IoT device 1. Also, proxy candidate #2 is redundantly selected to support the ALI reporting function due to the higher priority of smoke detectors over alarm clocks. In an example, the ALI reporting function can be interleaved between proxy candidates #1 and #2 so that ALI messages are transmitted by proxy candidates #1 and #2 in an alternating sequence to conserve power at proxy candidates #1 and #2.
Referring to example 5 from Table 2, IoT device 1 is battery-powered at 40%, and proxy candidates #1 and #2 each permanently outlet-connected and each support the ALI reporting function. In this scenario, the interface-support and power statuses of proxy candidates #1 and #2 are equal, so IoT device 1 can select between the respective proxy candidates #1 and #2 based on secondary criteria. In particular, assume that IoT device 1 determines that its distance to proxy candidate #1 is 22.3 meters while its distance to proxy candidate #2 is 0.7 meters. Under an assumption whereby a more proximate IoT device is expected to operate better as a proxy, proxy candidate #2 can be selected for supporting the ALI reporting function based on its closer proximity to IoT device 1. In an example, the proximity between IoT device 1 and any other IoT devices in the same IoT environment can be ascertained using sound chirps as described in U.S. Publication No. 2015/0029880, entitled “PROXIMITY DETECTION OF INTERNET OF THINGS (IoT) DEVICES USING SOUND CHIRPS”.
Referring to example 6 from Table 2, similar to example 5, IoT device 1 is battery-powered at 40%, and proxy candidates #1 and #2 are each geo-static, permanently outlet-connected and support the ALI reporting function. However, in example 6, IoT device 1 is able to determine that proxy candidates #1 and #2 are each 15.0 meters away from IoT device 1 in different directions (e.g., North and South). In this scenario, IoT device 1 can redundantly select both proxy candidates #1 and #2 to support the ALI reporting function. As will be appreciated, because proxy candidates #1 and #2 are spread apart from each other within the IoT environment, selecting both proxy candidates #1 and #2 as proxies can extend the effective range of IoT device 1 within the IoT environment.
While IoT device 1 is still asleep, assume that IoT device 3 determines to contact IoT device 1 to request ALI related to IoT device 1. IoT device 3 thereby generates an ALI request based on the determination and transmits the ALI request over the IoT communication interface within the IoT environment via multicast/broadcast, 1315. In a first example, a target address for the ALI request of 1315 can correspond to an address (or identifier) of IoT device 1, whereby IoT device 2 is configured to intercept any ALI requests targeted to IoT device 1 via the monitoring from 1305. In a second example, the target address for the ALI request of 1315 can correspond to an address (or identifier) of IoT device 2 because IoT device 3 may recognize via the proxy flag from the proxy ALI message of 1310 that IoT device 2 is collecting ALI requests directed to IoT device 1 for delivery. In either case, assume that IoT device 2 receives the ALI request from 1315 due to the continuous monitoring from 1305, but IoT device 1 does not receive the ALI request because IoT device 1 is still asleep at this point, 1320. At 1325, IoT device 2 transmits the ALI for IoT device 1 to IoT device 3 in response to the request from 1315. As will be appreciated from a review of
Those skilled in the art will appreciate that information and signals may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.
Further, those skilled in the art will appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the aspects disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted to depart from the scope of the present disclosure.
The various illustrative logical blocks, modules, and circuits described in connection with the aspects disclosed herein may be implemented or performed with a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices (e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration).
The methods, sequences and/or algorithms described in connection with the aspects disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM, flash memory, ROM, EPROM, EEPROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in an IoT device. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.
In one or more exemplary aspects, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk and disc, as used herein, includes CD, laser disc, optical disc, DVD, floppy disk and Blu-ray disc where disks usually reproduce data magnetically and/or optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
While the foregoing disclosure shows illustrative aspects of the disclosure, it should be noted that various changes and modifications could be made herein without departing from the scope of the disclosure as defined by the appended claims. The functions, steps and/or actions of the method claims in accordance with the aspects of the disclosure described herein need not be performed in any particular order. Furthermore, although elements of the disclosure may be described or claimed in the singular, the plural is contemplated unless limitation to the singular is explicitly stated.
The present Application for Patent claims benefit of U.S. Provisional Application No. 62/007,720, entitled “GENERATING A LOCATION PROFILE OF AN INTERNET OF THINGS DEVICE BASED ON AUGMENTED LOCATION INFORMATION ASSOCIATED WITH ONE OR MORE NEARBY INTERNET OF THINGS DEVICES”, filed Jun. 4, 2014, assigned to the assignee hereof, and expressly incorporated herein by reference in its entirety.
| Number | Date | Country | |
|---|---|---|---|
| 62007720 | Jun 2014 | US |
