Influencing Consumer Behavior Modification with Utility Consumption Disaggregation

Abstract

A method for performing utility consumption disaggregation includes measuring a total utility consumption of a consumer during a specified time period, generating a first disaggregated utility consumption segment and a second disaggregated utility consumption segment, based on the total utility consumption of the consumer, and providing the consumer with disaggregated utility consumption statistics based on at least one of the first and second disaggregated utility consumption segments.

Description

BACKGROUND

1. Technical Field

The present disclosure relates to influencing consumer behavior modification, and more particularly, to a system and method for influencing consumer behavior modification with utility consumption disaggregation.

2. Discussion of Related Art

Understanding human activity-related consumption helps trigger consumer consumption behavior change. For example, utility meters are often used to relay consumption information to users. A typical reading from a utility meter may inform the user of his/her aggregate consumption, which does not aid the user in determining ways to reduce his/her consumption. Decomposing a user's aggregate consumption readings provides the user with insight into ways to reduce his/her consumption. For example, if a user consumes 50 gallons of water in a two hour time period, and the user is informed that 30 gallons were used during the first hour by a washing machine and 20 gallons were used during the second hour by a shower, the user will have a better understanding of the effects different fixtures and appliances have on his/her total water consumption. Further, by providing the user with information related to the average water consumption of similar fixtures and appliances, the user may recognize that certain fixtures or appliances that he/she is using are significantly above the average. Thus, the user may decide to replace a certain fixture or device, or adjust his/her usage habits.

Therefore, a need exists for tools to provide a user with information allowing the user to adjust his/her consumption habits.

BRIEF SUMMARY

According to an exemplary embodiment of the present disclosure, a computer readable storage medium embodying instructions executed by a processor to perform a method for utility consumption disaggregation includes measuring a total utility consumption of a consumer during a specified time period, generating a first disaggregated utility consumption segment and a second disaggregated utility consumption segment, based on the total utility consumption of the consumer, and providing the consumer with disaggregated consumer utility consumption statistics based on at least one of the first and second disaggregated utility consumption segments.

According to an exemplary embodiment of the present disclosure, a utility consumption disaggregation system includes a utility consumption recording component, a utility consumption disaggregation component, a utility consumption statistics component, and a utility consumption recommendation component. The utility consumption recording component is configured to measure a total utility consumption of a consumer during a specified period. The utility consumption disaggregation component is configured to generate a first disaggregated utility consumption segment and a second disaggregated utility consumption segment, based on the total utility consumption of the consumer. The utility consumption statistics component is configured to generate group utility consumption statistics corresponding to a group of consumers similar to the consumer, wherein the utility consumption statistics are generated based on a consumer profile corresponding to the consumer. The utility consumption recommendation component is configured to generate a suggestion for modifying behavior of the consumer, based on a comparison of at least one of the first and second disaggregated utility consumption segments and the group utility consumption statistics.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

Preferred embodiments of the present disclosure will be described below in more detail, with reference to the accompanying drawings:

FIG. 1 is a block diagram showing the components included in a utility consumption disaggregation system, according to an exemplary embodiment of the present disclosure.

FIG. 2 is a flowchart of a method of utility consumption disaggregation, according to an exemplary embodiment of the present disclosure.

FIG. 3 is a chart displaying disaggregated utility consumption information, according to an exemplary embodiment of the present disclosure.

FIG. 4 is a user profile, according to an exemplary embodiment of the present disclosure.

FIG. 5 is a computer system for implementing a method according to an exemplary embodiment of the present disclosure.

DETAILED DESCRIPTION

According to an exemplary embodiment of the present disclosure, utility consumption may be measured and used as input to a utility consumption disaggregation system. The utility consumption may be measured via a utility meter such as, for example, a smart meter. A smart meter is an advanced utility meter capable of recording utility consumption at a specified sample rate. For example, a smart meter may record utility consumption every minute, every 15 minutes, or every hour. The recorded utility consumption information may be decomposed and visually presented to a user to illustrate specific consumption information for each activity engaged in by the user, as well as each device, fixture, or appliance used by the user, together with statistics of average uses. The user can use this information as a reference for his/her consumption behavior change.

Exemplary embodiments of the present disclosure now will be described more fully hereinafter with reference to the accompanying drawings. This disclosure, may however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein.

As will be appreciated by one skilled in the art, aspects of the present disclosure may be embodied as a system, method or computer program product. Accordingly, aspects of the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, aspects of the present disclosure may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

Exemplary embodiments of the present disclosure are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

Although exemplary embodiments described herein describe utility consumption in terms of water consumption for clarity, the present disclosure is not limited thereto. For example, the systems and methods described in the present disclosure may be used to measure utility consumption related to energy consumption such as, for example, natural gas or electricity consumption, as well as other types of consumption, as will be appreciated by one having ordinary skill in the art. Similarly, although exemplary embodiments described herein describe utility consumption in terms of a user, the present disclosure is not limited thereto. For example, the systems and methods described in the present disclosure may be used to perform utility consumption disaggregation for various types of consumers. A consumer may include any entity capable of consuming resources. For example, a consumer may include, but is not limited to, a user, a computer server farm, a wind faun or solar panels.

FIG. 1 is a block diagram showing the components included in a utility consumption disaggregation system, according to an exemplary embodiment of the present disclosure.

Referring to FIG. 1, the utility consumption disaggregation system 100 includes a utility consumption recording component 101, a prior knowledge component 102, a utility consumption disaggregation component 103, a utility consumption visualization component 104, a utility consumption statistics component 105, and a utility consumption recommendation component 106. The utility consumption recording component 101 records the total utility consumption with a certain sample rate. Functions performed by the utility consumption recording component 101 are described in more detail in reference to block 201 of FIG. 2. The prior knowledge component 102 supplements the total utility consumption information recorded by the recording component 101 with prior knowledge (e.g., user input). Functions performed by the prior knowledge component 102 are described in more detail in reference to block 202 of FIG. 2. The utility consumption disaggregation component 103 performs analytics and separates the total utility consumption into smaller segments which can be used to provide a consumer with disaggregated consumer utility consumption statistics, or visually presented to a user. Functions performed by the utility consumption disaggregation component 103 are described in more detail in reference to block 203 of FIG. 2. The utility consumption visualization component 104 visually presents disaggregated utility consumption information to the user. Functions performed by the utility consumption visualization component 104 are described in more detail in reference to block 204 of FIG. 2. The utility consumption statistics component 105 generates and presents group utility consumption statistics corresponding to other users to the user. Functions performed by the utility consumption statistics component 105 are described in more detail in reference to block 205 of FIG. 2. The utility consumption recommendation component 106 presents suggestions of how to lower utility consumption to the user. Functions performed by the utility consumption recommendation component are described in more detail in reference to block 206 of FIG. 2.

FIG. 2 is a flowchart of a method of utility consumption disaggregation, according to an exemplary embodiment of the present disclosure. For clarity, the flowchart is described in reference to recording a user's water consumption, however the present disclosure is not limited thereto. For example, as will be appreciated by one having ordinary skill in the art, the method of utility consumption disaggregation according to exemplary embodiments of the present disclosure may be implemented to measure utility consumption relating to energy such as, for example, electricity and natural gas.

Referring to FIG. 2, at block 201, utility consumption is recorded with a certain sample rate. For example, a smart meter may be used to record a user's water consumption at 1 minute intervals, 15 minute intervals, or 1 hour intervals. This allows the user to specify certain time periods corresponding to certain activities engaged in by the user. For example, a user may designate 7:00 am to 8:00 am as the user's “lawn watering” usage and 6:00 pm to 6:30 pm as the user's “dishwashing” usage.

At block 202, the user may supplement the utility consumption information recorded by the smart meter at block 201 with additional information known by the user. For example, the user may segment the recorded water consumption information with additional information related to certain devices, fixtures or appliances that were being used during the specified time period. This additional information is used by the consumption disaggregation system to classify the segmented consumption information into categories with labels corresponding to the device, appliance or fixture responsible for the specific utility consumption. For example, the consumption disaggregation system may create a first category labeled “lawn watering” which includes the water consumption of a sprinkler, a second category labeled “before work usage” which includes the water consumption of a shower and a running faucet, a third category labeled “dishwashing” which includes the water consumption of a dishwasher or a running faucet, and a fourth category labeled “washing clothes” which includes the water consumption of a washing machine.

At block 203, the recorded water consumption information is disaggregated into smaller segments. For example, water consumption during a first time period running from 7:00 am to 10:00 am and a second time period running from 6:00 pm to 8:00 pm may have been recorded at block 201. The first time period may be disaggregated into a first segment corresponding to 7:00 am to 8:00 am and a second segment corresponding to 8:00 am to 10:00 am. Similarly, the second time period may be disaggregated into a first segment corresponding to 6:00 pm to 6:30 pm and a second segment corresponding to 7:00 pm to 8:00 pm.

The disaggregated utility consumption information is visually presented to the user at block 204 via, for example, a chart, graph, or outline. An exemplary embodiment of a chart displaying disaggregated water consumption information to a user is shown in FIG. 3. The chart 300 in FIG. 3 presents the user with the disaggregated utility consumption segments 301, the activity 302 corresponding to each disaggregated segments, the device(s), fixture(s), and/or appliance(s) 303 used during each activity, and the water consumption 304 corresponding to each disaggregated utility consumption segment.

At block 205, utility consumption statistics of other users (e.g., group utility consumption statistics) are obtained and presented to the user. The group utility consumption statistics presented to the user are based on a user profile of the user. A user profile may include information such as, for example, the location of the user, the size of the user's home, the number of people living in the user's home, and the average time the user spends away from home. An exemplary embodiment of a user profile 400 is shown in FIG. 4. Utilization of a user profile allows the user to be presented with group utility consumption statistics corresponding to other users having similar living conditions as the user. For example, the water consumption of a user living alone in a small home will be different than the water consumption of a user living with a family in a larger home. Similarly, the water consumption of a user who is on the road and is often away from home will be different than the water consumption of a user who regularly spends time at home. The user's utility consumption can be compared with the group utility consumption statistics, allowing the user to modify his/her behavior and reduce his/her utility consumption. For example, the water consumption statistics presented to the user may indicate that an average user having similar living conditions consumes 30 gallons of water when using a sprinkler during lawn watering and only 25 gallons of water when using a washing machine. This information alerts the user that his/her sprinkler, which consumes 15 gallons of water, is running efficiently, but his/her washing machine consumes about twice the amount of water as an average user having similar living conditions. As a result, the user may decide to replace his/her washing machine to reduce his/her water consumption.

At block 206, suggestions of how to lower utility consumption are presented to the user. For example, the utility consumption disaggregation system may automatically compare the disaggregated utility consumption information from block 204 with the utility consumption statistics of other users from block 205 and suggest actions that can be taken by the user to reduce his/her utility consumption. For example, if a certain device, fixture or appliance is consuming more water than an equivalent device, fixture or appliance of an average user, a suggestion may be made to the user to replace the certain device, fixture or appliance. Similarly, if it is determined that the user is spending more time on a certain activity than an average user, a suggestion may be made to the user to modify the times spent on the certain activity.

In an exemplary embodiment of the present disclosure, data mining techniques may be utilized to automatically classify consumption into different categories. Each category may be associated with a certain activity, fixture, or appliance. In this embodiment, the user supplies training data (e.g., records labeled by the user) to the utility consumption disaggregation system. A classifier can then be generated based on the training data using techniques such as, for example, SVM or neural networks. Once the classifier is constructed, it may classify the real-time utility consumption so that decomposed consumption is automatically recognized. The classifier may make use of user-specified annotations to further guide the decomposition process.

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowcharts or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

More particularly, referring to FIG. 5, according to an exemplary embodiment of the present disclosure, a computer system 501 for utility consumption disaggregation can comprise, inter alia, a central processing unit (CPU) 502, a memory 503 and an input/output (I/O) interface 504. The computer system 501 is generally coupled through the I/O interface 504 to a display 505 and various input devices 506 such as a mouse and keyboard. The support circuits can include circuits such as cache, power supplies, clock circuits, and a communications bus. The memory 503 can include random access memory (RAM), read only memory (ROM), disk drive, tape drive, etc., or a combination thereof The present invention can be implemented as a routine 507 stored in memory 503 (e.g., a non-transitory computer-readable storage medium) and executed by the CPU 502 to process the signal from the signal source 508. As such, the computer system 501 is a general-purpose computer system that becomes a specific purpose computer system when executing the routine 507 of the present invention.

The computer platform 501 also includes an operating system and micro-instruction code. The various processes and functions described herein may either be part of the micro-instruction code or part of the application program (or a combination thereof) which is executed via the operating system. In addition, various other peripheral devices may be connected to the computer platform such as an additional data storage device and a printing device.

Having described embodiments for a system and method for utility consumption disaggregation, it is noted that modifications and variations can be made by persons skilled in the art in light of the above teachings. It is therefore to be understood that changes may be made in exemplary embodiments of the disclosure, which are within the scope and spirit of the invention as defined by the appended claims. Having thus described the invention with the details and particularity required by the patent laws, what is claimed and desired protected by Letters Patent is set forth in the appended claims.

Claims

1. A computer readable storage medium embodying instructions executed by a processor to perform a method for utility consumption disaggregation, comprising: measuring a total utility consumption of a consumer during a specified time period;generating a first disaggregated utility consumption segment and a second disaggregated utility consumption segment, based on the total utility consumption of the consumer; andproviding the consumer with disaggregated consumer utility consumption statistics based on at least one of the first and second disaggregated utility consumption segments.

2. The computer readable storage medium of claim 1, further comprising modifying behavior of the consumer based on the disaggregated consumer utility consumption statistics.

3. The computer readable storage medium of claim 2, further comprising generating group utility consumption statistics corresponding to a group of consumers similar to the consumer, wherein the group utility consumption statistics are generated based on a consumer profile corresponding to the consumer.

4. The computer readable storage medium of claim 3, wherein modifying the behavior of the consumer comprises comparing the disaggregated consumer utility consumption statistics with the group utility consumption statistics.

5. The computer readable storage medium of claim 1, further comprising generating a suggestion for modifying behavior of the consumer based on a comparison of the disaggregated consumer utility consumption statistics and the group utility consumption statistics.

6. The computer readable storage medium of claim 1, wherein the total utility consumption includes one of water consumption or energy consumption.

7. The computer readable storage medium of claim 1, wherein the consumer includes a user.

8. The computer readable storage medium of claim 7, further comprising generating group utility consumption statistics corresponding to a group of users similar to the user, wherein the group utility consumption statistics are generated based on a user profile corresponding to the user, and the user profile includes at least one of a location of the user, a size of a home of the user, or a number of people living in the user's home.

9. The computer readable storage medium of claim 7, further comprising: generating a first category corresponding to the first disaggregated utility consumption segment, wherein the first category comprises first activity information, first fixture information, and first consumption information; andgenerating a second category corresponding to the second disaggregated utility consumption segment, wherein the second category comprises second activity information, second fixture information, and second consumption information,wherein the first and second categories are generated in response to additional information received from the user.

10. The computer readable medium of claim 7, further comprising visually presenting the disaggregated consumer utility consumption statistics to the user.

11. The computer readable storage medium of claim 10, wherein the disaggregated consumer utility consumption statistics are visually presented using a chart, graph or outline.

12. A utility consumption disaggregation system, comprising: a utility consumption recording component configured to measure a total utility consumption of a consumer during a specified period;a utility consumption disaggregation component configured to generate a first disaggregated utility consumption segment and a second disaggregated utility consumption segment, based on the total utility consumption of the consumer;a utility consumption statistics component configured to generate group utility consumption statistics corresponding to a group of consumers similar to the consumer, wherein the utility consumption statistics are generated based on a consumer profile corresponding to the consumer; anda utility consumption recommendation component configured to generate a suggestion for modifying behavior of the consumer, based on a comparison of at least one of the first and second disaggregated utility consumption segments and the group utility consumption statistics.