Information processing method, program, information processing device, and information processing system

Abstract

To provide a method for processing information which can efficiently output information on health measures of a user on the basis of the usage amount of gas, electricity, and water.SOLUTION: The method for processing information includes: acquiring information on a usage time zone and user identification information for identifying a user to usage amount data formed by relating the usage amount of electricity, gas, and water of the user; deriving information on actions at home of the user on the basis of the acquired usage amount data; and outputting advice information on health measures of the user on the basis of the derived information on actions at home of the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an information processing method, a program, an information processing device, and an information processing system. [Background technology]

[0002] An energy database system is known that allows a management system operating company, which is different from a utility supply company such as gas, electricity, or water, to monitor meters without handling personal information (for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2018-173691 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the system described in Patent Document 1 does not take into consideration the derivation of information regarding health measures for consumers who use gas, electricity, and water based on the amounts of gas, electricity, and water used.

[0005] The present invention has been made in consideration of the above circumstances, and aims to provide an information processing method, etc. that efficiently outputs information regarding health measures for consumers based on gas, electricity, and water usage. [Means for solving the problem]

[0006] An information processing method according to one aspect of the present disclosure acquires usage data that associates a consumer's electricity usage, gas usage, and tap water usage with information about the time of usage and consumer identification information that identifies the consumer, derives information about the consumer's in-home behavior based on the acquired usage data, and outputs advice information about the consumer's health measures based on the derived information about the in-home behavior.

[0007] A program according to one aspect of the present disclosure causes a computer to acquire usage data that associates a consumer's electricity usage, gas usage, and tap water usage with information regarding the time of usage and consumer identification information that identifies the consumer, derive information regarding the consumer's in-home behavior based on the acquired usage data, and output advice information regarding the consumer's health measures based on the derived information regarding the in-home behavior.

[0008] An information processing device according to one aspect of the present disclosure includes an acquisition unit that acquires usage data that associates a consumer's electricity usage, gas usage, and tap water usage with information regarding the time of usage and consumer identification information that identifies the consumer, a derivation unit that derives information regarding the consumer's in-home behavior based on the acquired usage data, and an output unit that outputs advice information regarding the consumer's health measures based on the derived information regarding the in-home behavior.

[0009] An information processing system according to one aspect of the present disclosure is an information processing system including an electricity smart meter that outputs electricity usage by a consumer, a gas smart meter that outputs gas usage by the consumer, a tap water smart meter that outputs tap water usage by the consumer, and an information processing device that is communicatively connected to the electricity smart meter, the gas smart meter, and the tap water smart meter, wherein the information processing device acquires the electricity usage from the electricity smart meter, acquires the gas usage from the gas smart meter, acquires the tap water usage from the tap water smart meter, and stores usage data in a memory area accessible from the information processing device, associating the acquired electricity usage, gas usage, and tap water usage with information regarding the time of use and consumer identification information that identifies the consumer, and derives information regarding the consumer's indoor behavior based on the usage data stored in the memory area, and outputs advice information regarding the consumer's health measures based on the derived information regarding the indoor behavior. [Effects of the Invention]

[0010] According to one aspect of the present disclosure, it is possible to provide an information processing method, etc., that efficiently outputs information regarding health measures for consumers based on gas, electricity, and water usage. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 1 is an explanatory diagram illustrating an overview of an information processing system according to a first embodiment. [Figure 2] FIG. 1 is a block diagram showing a configuration example of an information processing device, etc. [Figure 3] FIG. 2 is an explanatory diagram illustrating an example of the data layout of a consumer master table. [Figure 4] FIG. 10 is an explanatory diagram illustrating an example of the data layout of a usage amount table. [Figure 5] 2 is a functional block diagram illustrating functional units included in a control unit of the information processing device. FIG. [Figure 6] FIG. 1 is an explanatory diagram regarding the generation process of a learning model (in-home behavior model). [Figure 7] 10 is a flowchart illustrating an example of a processing procedure performed by a control unit of the information processing device. [Figure 8] FIG. 10 is an explanatory diagram showing an overview of an information processing system according to a second embodiment (health equipment information). [Figure 9] 2 is a functional block diagram illustrating functional units included in a control unit of the information processing device. FIG. [Figure 10] FIG. 10 is an explanatory diagram illustrating an example of the data layout of an advice table. [Figure 11] 10 is a flowchart illustrating an example of a processing procedure performed by a control unit of the information processing device. [Figure 12] FIG. 10 is a diagram illustrating an example of an advice screen including advice information and the like. DETAILED DESCRIPTION OF THE INVENTION

[0012] The present invention will be specifically described with reference to drawings showing embodiments thereof. An information processing device 1 according to an embodiment of the present disclosure will be described below with reference to the drawings. Note that the present invention is not limited to these examples, but is defined by the claims, and all modifications within the meaning and scope equivalent to the claims are intended to be included.

[0013] (Embodiment 1) The present disclosure will be described in detail below with reference to the drawings illustrating embodiments. Fig. 1 is an explanatory diagram illustrating an overview of an information processing system S according to embodiment 1. Fig. 2 is a block diagram illustrating an example configuration of an information processing device 1 and the like. The information processing system S includes an electricity smart meter H1 (E smart meter), a gas smart meter H2 (G smart meter), and a tap water smart meter H3 (A smart meter) installed in a consumer's building H, and an information processing device 1 that acquires and stores usage data including the amount of electricity usage, the amount of gas usage, and the amount of tap water usage output from these smart meters.

[0014] The information processing device 1 is communicably connected to, for example, a terminal device (facility manager side terminal device T2) of a facility manager (management company) that manages the consumer's building H, and a terminal device (consumer side terminal device T1) of the consumer, via an external network N such as the Internet, and information output from the information processing device 1 is displayed on the display units (not shown) of these terminal devices. For each energy company that provides usage data (electricity usage, gas usage, and tap water usage), each consumer sets whether or not they have permission to use the consumer's usage data.

[0015] The usage data output from the electricity smart meter H1, gas smart meter H2, and tap water smart meter H3 installed in the building H for each of multiple consumers includes or is associated with identification information (consumer ID) for identifying the consumer. Therefore, the information processing device 1 can register the usage data, including the electricity usage, gas usage, and tap water usage output from these smart meters, in a database (usage table 32) stored in the memory unit 3 of the information processing device 1, based on the consumer ID associated with the usage data.

[0016] The information processing device 1 derives information about the consumer's behavior in the home (home behavior information) based on the acquired usage data, and generates advice information for taking health measures, including measures to combat frailty, for the consumer, according to the derived home behavior information. The information processing device 1 outputs the home behavior information and advice information to the facility manager's terminal device T2, the consumer's terminal device T1, or both terminal devices. As will be described in detail later, the home behavior information includes at least one of information about the consumer's presence at home, sleeping, bathing, cooking, and toilet use in the building or facility where the consumer lives or occupies.

[0017] The information processing device 1 acquires information (license data) relating to the license to use usage data from a consumer who is a resident of the building H, from the consumer-side terminal device T1 of the consumer, or from the facility manager-side terminal device T2 of the manager of the building H, and registers the information in a database (consumer master table 31) stored in the storage unit 3 of the information processing device 1. The details of the consumer master table 31 will be described later, but based on the presence or absence of a license from each consumer, the information processing device 1 may process the usage data acquired from each smart meter in each consumer's building H by distinguishing or differentiating between the usage data of consumers with a license and the usage data of consumers without a license.

[0018] The information processing device 1 is not limited to acquiring the amounts of electricity, gas, and tap water consumption directly from the electricity smart meter H1, gas smart meter H2, and tap water smart meter H3, for example, via base station K, but may also acquire one or more of the amounts of electricity, gas, and tap water consumption via a data server at each of the electricity, gas, and tap water supply companies.

[0019] The building H is, for example, a structure such as a consumer's detached house or apartment building. Alternatively, the building H may be a nursing home, a care home, a home for active seniors, or a facility managed by a facility manager (facility management company). The electricity smart meter H1 is an electricity meter that measures electricity usage and has wireless or wired communication capabilities, and detects and outputs the amount of electricity usage in the consumer's building H. The gas smart meter H2 is a gas meter that measures gas usage and has wireless or wired communication capabilities, and detects and outputs the amount of gas usage in the consumer's building H. The tap water smart meter H3 is a tap water meter that measures tap water usage and has wireless or wired communication capabilities, and detects and outputs the amount of tap water usage in the consumer's building H.

[0020] The electricity smart meter H1, the gas smart meter H2, and the tap water smart meter H3 are not limited to being configured as separate devices. The electricity smart meter H1 may be communicably connected to a gas usage detection device such as a gas meter and a tap water usage detection device such as a water meter via wired or wireless communication, and the electricity smart meter H1 may acquire the gas usage and tap water usage output from the gas usage detection device and the tap water usage detection device, associate the electricity usage, gas usage, and tap water usage with an identifier such as a consumer ID, and output (transmit) the amounts. The electricity smart meter H1, the gas smart meter H2, and the tap water smart meter H3 may output the electricity usage, gas usage, and tap water usage amounts by associating each amount with the time period during which they were used.

[0021] The demander side terminal device T1 is configured by a mobile terminal device such as a personal computer, tablet PC, or smartphone. The demander side terminal device T1 has a control unit, a memory unit, and a communication unit, similar to the information processing device 1, and further has a display unit T14 such as a display. The demander side terminal device T1 is configured to be able to communicate with the information processing device 1 via the communication unit. The display unit T14 of the demander side terminal device T1 displays the in-home behavior information output from the information processing device 1.

[0022] The facility manager side terminal device T2 is configured by a mobile terminal device such as a personal computer, tablet PC, or smartphone. Similar to the consumer side terminal device T1, the facility manager side terminal device T2 is equipped with a control unit, a memory unit, a communication unit, and a display unit. The facility manager side terminal device T2 is configured to be able to communicate with the information processing device 1 via the communication unit. The display unit of the facility manager side terminal device T2 displays the in-home behavior information output from the information processing device 1.

[0023] The information processing device 1 is a computer capable of various information processing and sending and receiving information, such as a server device or a personal computer. The server device includes not only a single server device but also a cloud server device or a virtual server device configured by multiple computers. The information processing device 1 includes a control unit 2, a communication unit 4, and a storage unit 3.

[0024] The control unit 2 has an arithmetic processing device equipped with a timing function such as one or more CPUs (Central Processing Units), MPUs (Micro-Processing Units), GPUs (Graphics Processing Units), etc., and performs various information processing, control processing, etc. related to the information processing device 1 by reading and executing a program P (program product) stored in the memory unit 3.

[0025] The storage unit 3 includes a volatile storage area such as a static random access memory (SRAM), a dynamic random access memory (DRAM), or a flash memory, and a non-volatile storage area such as an EEPROM or a hard disk. The storage unit 3 pre-stores a program P (program product) and data referenced during processing. The program P (program product) stored in the storage unit 3 may be a program P (program product) read from a recording medium 300 readable by the information processing device 1. Alternatively, the program P (program product) may be downloaded from an external computer (not shown) connected to a communication network (not shown) and stored in the storage unit 3. The storage unit 3 stores databases (a consumer master table 31, a usage table 32) that save and manage usage data, etc. The storage unit 3 stores entity files that constitute a trained model. The entity files may be configured as part of the program P (program product).

[0026] The communication unit 4 is a communication module or communication interface for communicating with each smart meter, the consumer side terminal device T1, or the facility manager side terminal device T2 by wire or wirelessly, and is, for example, a short-range wireless communication module such as Wi-Fi (registered trademark) or Bluetooth (registered trademark), or a wide-area wireless communication module such as 4G or 5G. The control unit 2 communicates with each smart meter, the consumer side terminal device T1, and the facility manager side terminal device T2 via the communication unit 4, for example, through an external network N such as the Internet.

[0027] The information processing device 1 configured as described above stores the electricity consumption, gas consumption, and tap water consumption output (transmitted) from the electricity smart meter H1, gas smart meter H2, and tap water smart meter H3 in association with identifiers such as consumer IDs. In other words, the information processing device 1 functions as a database server that stores and manages this usage data, thereby enabling the establishment of an information bank or the like in the energy management field centered around the database server, or performing part of the functions of the information bank. The information processing device 1 may also function as a business intelligence (BI) server and analyze acquired usage data using drill-down, slicing, dicing, and other functions included in the BI server. In this embodiment, the information processing device 1 includes an information bank that stores usage data, but is not limited to this. The information bank that stores usage data may be hosted by another server device, and the information processing device 1 may acquire usage data from the other server device with the consumer's permission to use the data.

[0028] Fig. 3 is an explanatory diagram illustrating an example of the data layout of the consumer master table 31. Fig. 4 is an explanatory diagram illustrating an example of the data layout of the usage table 32. The consumer master table 31 and the usage table 32 are stored in the storage unit 3 of the information processing device 1, and are configured by database management software such as an RDBMS (Relational Database Management System) implemented in the information processing device 1.

[0029] The types of items (metadata) managed in the consumer master table 31 include, for example, consumer ID, name, address, family composition, building classification, electricity contract number, gas contract number, water contract number, and facility manager (facility manager).

[0030] The consumer ID item (field) stores an identification number for identifying the consumer. The name item (field) stores the consumer's name. The address item (field) stores the location of the consumer's building H. The family composition item (field) stores the number of family members. Furthermore, the family composition item (field) may store age composition, gender ratio, nationality, classification of care status, disability support classification, etc.

[0031] The building classification item (field) stores the consumer's building classification. The building classification includes information indicating the type of building H, such as a detached house, an apartment building, a two-generation house, reinforced concrete, wood construction, a condominium, or a rental. Alternatively, if the building H in which the consumer resides or moves into is a facility such as a home or facility for active seniors, a nursing home, or a care home, the building classification includes information indicating the type of facility.

[0032] The electricity contract number field stores the contract number with the electricity retailer that the consumer has a contract with. The gas contract number field stores the contract number with the gas retailer that the consumer has a contract with. The water contract number field stores the contract number with the water supplier that the consumer has a contract with. By managing these contract numbers in association with the consumer ID, it is possible to efficiently associate the amounts of electricity, gas, and tap water used output from each smart meter and store the usage data.

[0033] The facility manager item (field) stores information indicating the manager (facility manager) of the facility in which the consumer resides. This information may include, for example, the name, address, and email address of the facility manager, or the URL of the server owned or operated by the facility manager.

[0034] The types of items (metadata) managed in the usage table 32 include, for example, consumer ID, usage period, electricity usage, gas usage, and water usage. As with the consumer master table 31, the consumer ID item (field) stores an identification number for identifying the consumer, and the usage table 32 is normalized by the consumer ID.

[0035] The "usage period" item (field) stores time information indicating a time period of a unit time determined for measuring the amount of electricity, gas, and tap water used. The unit time is set, for example, in 30-minute increments, thereby defining 48 time periods in a day. As illustrated in the present embodiment, the "usage period" item may include a sub-item for the year, month, and day, and a sub-item for the time period.

[0036] The electricity usage item (field) stores the total amount of electricity used during each usage period. The gas usage item (field) stores the total amount of gas used during each usage period. The water usage item (field) stores the total amount of tap water used during each usage period. By storing the amounts of electricity, gas, and tap water used during each unit time period in this way, it is possible to store, search, and extract these amounts for each consumer during a specified period in matrix format (vertical axis: time period, horizontal axis: each amount used) according to the time period for each unit time included in the specified period.

[0037] 5 is a functional block diagram illustrating functional units included in the control unit 2 of the information processing device 1. The control unit 2 of the information processing device 1 executes a program P stored in the memory unit 3 to function as a registration functional unit that registers data in the consumer master table 31 or the usage table 32. The registration functional unit includes a usage data acquisition unit 201 and a usage permission data acquisition unit 202.

[0038] The usage data acquisition unit 201 acquires usage data output from the electricity smart meter H1, gas smart meter H2, and tap water smart meter H3 installed in the consumer's building H, and stores the acquired usage data in each field of the usage table 32 stored in the storage unit 3 based on the consumer ID included in or associated with the usage data. The consumer's building H is, for example, a home or facility for active seniors where the consumer resides, a facility such as a nursing home or care home, an apartment complex, or a detached house, and is provided with the electricity smart meter H1, gas smart meter H2, and tap water smart meter H3 so that the usage data of each consumer can be acquired.

[0039] The license data acquisition unit 202 acquires license data transmitted, for example, from the consumer side terminal device T1 or the facility manager side terminal device T2, and stores and manages information (license data) regarding the license for each consumer ID stored in the consumer master table 31 based on the consumer ID included in or associated with the license data.

[0040] The control unit 2 of the information processing device 1 functions as an output system function unit that outputs advice information, etc. to the consumer side terminal device T1 or the facility manager side terminal device T2 by executing the program P stored in the memory unit 3. The output system function unit includes a target consumer identification unit 203, a usage data extraction unit 204, and an advice generation unit 206, and further functions as a learning model 205 (in-home behavior model) that derives in-home behavior based on the usage data.

[0041] The target consumer identification unit 203 generates and outputs information (target consumer information) for identifying the consumer who is the target of the in-home behavior information to be output, for example, based on the request content transmitted from the facility manager's terminal device T2. The information for identifying the consumer who is the target of the in-home behavior information includes, for example, a consumer ID for pinpointing the consumer, and a building classification indicating a specific facility such as a facility for active seniors, a nursing home, or a care home. Furthermore, when identifying the consumer, the target period may be attached to the target consumer information.

[0042] The usage data extraction unit 204 searches the consumer master table 31 and the usage table 32 based on the target consumer information output from the target consumer identification unit 203, and extracts usage data corresponding to the target consumer information. The usage data extraction unit 204 outputs the extracted usage data to the learning model 205.

[0043] The learning model 205 functions as an indoor behavior model that outputs information about indoor behavior of the target consumer (indoor behavior information) based on the usage data extracted by the usage data extraction unit 204. The information about indoor behavior (indoor behavior information), which is response data output by or used for learning by the learning model 205 (indoor behavior model), includes, for example, information about being at home or going out, information about sleeping, information about using the toilet, information about bathing, and information about cooking at home.

[0044] Information about being at home or out includes, for example, the time periods when the consumer is at home or out each day. Information about sleep includes, for example, the consumer's bedtime, wake-up time, or sleeping time periods each day. Information about toileting includes, for example, the number of times the consumer uses the toilet each day, the time required to use the toilet, or the time periods when the consumer uses the toilet each day. Information about bathing includes, for example, the number of times the consumer bathes each day, the time required to bathe, or the time periods when the consumer uses the toilet each day. Information about cooking at home includes, for example, the number of times the consumer cooks at home each day, the time required to cook at home, or the time periods when the consumer cooks at home.

[0045] FIG. 6 is an explanatory diagram of the generation process of the learning model 205 (in-home behavior model). The information processing device 1 generates the learning model 205 (in-home behavior model) using acquired usage data, i.e., electricity usage, gas usage, and tap water usage, as question data and in-home behavior information as answer data, by training a neural network based on training data. This training data can be created by combining electricity, gas, and tap water usage data from a large number of consumers with the in-home behavior information of those consumers. The dataset of question data and answer data included in the training data for learning the learning model 205 is synonymous with the dataset of input data and output data when the learning model 205 is used. Therefore, if it is defined in one dataset, it naturally applies to the other dataset as well.

[0046] The neural network (learning model 205) trained using the training data is expected to be used as a program module that is part of artificial intelligence software. The learning model 205 is used in the information processing device 1 that includes the control unit 2 (CPU, etc.) and storage unit 3 as described above, and when executed by the information processing device 1 that has such calculation processing capabilities, a neural network system is configured. That is, the control unit 2 of the information processing device 1 performs calculations to extract features of the usage amount data input to the input layer in accordance with instructions from the learning model 205 stored in the storage unit 3, and operates to output indoor behavior information from the output layer.

[0047] The usage data input to the input layer may be, for example, matrix-format data with the vertical axis representing time, i.e., multiple times or points in time indicating the time periods when electricity, gas, and tap water were used, and the horizontal axis representing the amounts of electricity, gas, and tap water used. By converting the usage data into matrix-format data representing the amounts of electricity, gas, and tap water used over a predetermined period, such as one day, including multiple points in time, a convolution neural network (CNN) can be used as the neural network. For example, a neural network using a CNN has an input layer that accepts input of matrix-format usage data, an output layer that outputs information about household behavior, and an intermediate layer that extracts features from the usage data.

[0048] The input layer has a plurality of neurons that receive input of each usage value included in the usage data and passes the input values ​​to the intermediate layer. The intermediate layer includes, for example, a convolution layer and a pooling layer, has a plurality of neurons that extract features of each usage amount, and passes the extracted features to the output layer. The output layer is, for example, composed of a fully connected layer, and outputs indoor activity information based on the features output from the intermediate layer.

[0049] In this embodiment, the learning model 205 is described as a CNN, but the learning model 205 is not limited to a CNN and may be a neural network other than a CNN, a deep neural network (DNN), a recurrent neural network (RNN), a long-short term model (LSTM), a support vector machine (SVM), a Bayesian network, a regression tree, or another learning model constructed with another learning algorithm. The learning model 205 may be one that is learned by unsupervised learning or reinforcement learning.

[0050] In the present embodiment, the learning model 205 outputs information about the consumer's indoor behavior based on the usage data. However, this is not limited to this. The learning model 205 may output a determination result of whether the consumer is frail or not based on the usage data. The determination result may include a determination result in accordance with frailty assessment criteria for the consumer. The frailty assessment criteria may include, for example, criteria related to weight loss, subjective fatigue, reduced daily activity, decreased physical ability such as walking speed, and decreased muscle strength such as grip strength. The learning model 205 functioning as a frailty assessment model may output a determination value for each of these criteria. In this case, the frailty assessment model (learning model 205), like the above-described indoor behavior model, is trained based on training data in which usage data (electricity usage, gas usage, and tap water usage) are used as question data and the determination value for each item of the frailty assessment criteria is used as answer data. Alternatively, the learning model 205 may output the consumer's behavior type based on the usage data, where the behavior type is a type classified based on a combination of the consumer's time-series in-home behavior, and may include, for example, a night-owl behavior type, a non-home-cooking type, a no-bath type, etc., or a composite type that combines multiple of these types.Learning model 205, which functions as a behavior type classification model in this way, learns based on training data in which usage data (electricity usage, gas usage, and tap water usage) are used as question data and the consumer's behavior type is used as answer data, similar to the above-mentioned in-home behavior model.

[0051] The advice generation unit 206 generates advice information regarding frailty countermeasures for a consumer based on information (in-home behavior information) regarding the consumer's in-home behavior output by the learning model 205 (in-home behavior model). The advice generation unit 206 may acquire daily in-home behavior information for a predetermined period, such as one week or one month, from the learning model 205 (in-home behavior model). The advice generation unit 206 may derive a rate of change or a trend of change in the in-home behavior information over multiple days based on the acquired daily in-home behavior information, and generate advice information based on the rate of change, etc. In this case, the advice generation unit 206 may generate advice information recommending a visit to a clinic if the number of toilet visits this week has increased by more than a predetermined value compared to last week. Alternatively, the advice generation unit 206 may generate advice information based on behavioral information with continuity in the in-home behavior information over multiple days. In this case, the advice generation unit 206 may generate advice information recommending going out if the consumer has not gone out for three or more consecutive days. Furthermore, the advice generating unit 206 may generate advice information recommending cooking at home if no cooking has been done for three or more consecutive days. Furthermore, the advice generating unit 206 may generate advice information recommending taking a bath if no bathing has been done for three or more consecutive days. Such advice information is used not only as a measure against frailty, but also as a health measure that contributes to the promotion of the consumer's health.

[0052] In this way, the advice generating unit 206 may generate advice information for each item of the home activity information output by the learning model 205 (home activity model). As described above, the home activity information includes, for example, information (items) related to being at home / out, sleeping, using the toilet, taking a bath, and cooking, and advice information may be generated corresponding to each individual item.

[0053] The advice generation unit 206 may generate advice information for each item by, for example, referring to an advice table 33 (see FIG. 10 ) that indicates the correspondence between in-home behavior information and advice information. The advice generation unit 206 generates screen data including the generated advice information, etc., and outputs the screen data to the consumer-side terminal device T1 or the facility manager-side terminal device T2. The advice table 33 and the screen data will be described later. When the learning model 205 functions as a frailty assessment model, the advice generation unit 206 may generate advice information regarding frailty countermeasures based on the assessment result in accordance with the frailty assessment criteria output by the frailty assessment model. When the learning model 205 functions as a behavior type classification model, the advice generation unit 206 may generate advice information regarding frailty countermeasures based on the consumer's behavior type output by the behavior type classification model.

[0054] 7 is a flowchart showing an example of a processing procedure by the control unit 2 of the information processing device 1. The control unit 2 of the information processing device 1 starts the processing of the flowchart based on, for example, the request content transmitted from the demander side terminal device T1 or the facility manager side terminal device T2 communicably connected to the information processing device 1.

[0055] The control unit 2 of the information processing device 1 acquires target consumer information (S101). The control unit 2 of the information processing device 1 acquires target consumer information, such as a name that identifies the consumer or a building classification of the facility where the consumer is located, from the consumer side terminal device T1 or the facility manager side terminal device T2.

[0056] The control unit 2 of the information processing device 1 acquires the usage data of the target consumer (S102). The control unit 2 of the information processing device 1 searches the consumer master table 31 and the usage table 32 stored in the memory unit 3 based on the target consumer information, and acquires the usage data of the target consumer information. If the target consumer information includes information regarding the usage period, the control unit 2 of the information processing device 1 may acquire the usage data for that usage period. The consumer master table 31 and the usage table 32 are not limited to being stored in the memory unit 3 of the information processing device 1 itself, but may also be stored in a storage server or the like accessible from the information processing device 1, and the information processing device 1 may access the storage server to refer to the consumer master table 31 and the usage table 32.

[0057] The control unit 2 of the information processing device 1 derives information regarding the target consumer's in-home behavior (S103). The control unit 2 of the information processing device 1 derives (acquires) information regarding the target consumer's in-home behavior (in-home behavior information) by, for example, inputting the acquired usage data of the target consumer into the learning model 205 (in-home behavior model). The control unit 2 of the information processing device 1 may derive (acquire) multiple pieces of in-home behavior information on a daily basis by, for example, inputting multiple pieces of daily usage data into the learning model 205 (in-home behavior model).

[0058] The control unit 2 of the information processing device 1 outputs advice information for frailty countermeasures based on the home behavior of the target consumer (S104). The control unit 2 of the information processing device 1 outputs the advice information for frailty countermeasures based on the derived home behavior information of the target consumer on a daily basis, for example, in accordance with a determination result such as whether a predetermined home behavior, such as staying at home (without going out), has continued for a predetermined period or more, or whether the rate of change in the number of home behaviors, such as using the toilet, cooking, or bathing, has exceeded a threshold. In this case, the control unit 2 of the information processing device 1 may output the advice information by referring to an advice table 33 (see FIG. 10 ) stored in the memory 3. Alternatively, the control unit 2 of the information processing device 1 may output the advice information for frailty countermeasures based on a determination result conforming to a frailty evaluation criterion based on the derived home behavior information of the target consumer on a daily basis. The output destination of the advice information is not limited to the consumer-side terminal device T1 or the facility manager-side terminal device T2, but may be a terminal device used by a person designated by the consumer. The person designated by the consumer may be, for example, a relative such as the consumer's family, an acquaintance, or a friend, who watches over or manages the consumer's health condition, and may refer to a person who has been registered in advance in the consumer master table 31, etc. as a recipient of advice (notification).

[0059] According to this embodiment, the storage unit 3 of the information processing device 1 accumulates usage data (electricity usage, gas usage, and tap water usage) of a consumer in a building H such as a house (home) or facility where the consumer resides, and the control unit 2 of the information processing device 1 derives information on in-home behavior from the usage data. The information on in-home behavior includes, for example, on a daily basis (day by day), the number of times and the time periods when the consumer bathes, cooks, and uses the toilet in the building H such as a home. Furthermore, the information on in-home behavior may include, for example, on a daily basis (day by day), the time periods when the consumer is in the building H such as a home (at-home time periods). Furthermore, the information on in-home behavior may include the time periods when the consumer is sleeping. Based on the information on in-home behavior, the control unit 2 of the information processing device 1 outputs advice information on measures to combat frailty in accordance with the determination result of whether the consumer is frail (a state between healthy and requiring care). By using usage data that associates the amounts of electricity, gas, and tap water used according to the consumer's daily living activities (activities of daily living) in the home with the time periods of use, it is possible to derive information about the consumer's activities in the home without imposing an excessive burden on the consumer. By using the information about the consumer's activities in the home derived in this way, the control unit 2 of the information processing device 1 can efficiently output advice information about the consumer's frailty countermeasures and provide useful information to the consumer or a person related to the consumer.

[0060] According to this embodiment, the control unit 2 of the information processing device 1 derives information about the in-home behavior of the consumer who is the subject of the usage data by inputting the acquired usage data into the learning model 205 (in-home behavior model) that has been trained to output in-home behavior when the amounts of electricity usage, gas usage, and tap water usage associated with a usage time period are input. In this way, by using the learning model 205 (in-home behavior model), the control unit 2 of the information processing device 1 can efficiently acquire information about the in-home behavior of the consumer based on the amounts of electricity usage, gas usage, and tap water usage for each consumer included in the usage data.

[0061] According to this embodiment, the storage unit 3 of the information processing device 1 stores daily life data and information about home activities derived from the life data for each consumer. For example, if the frequency of deriving information about home activities is daily, the information about home activities is derived based on the daily life data, i.e., the total daily values ​​of electricity consumption, gas consumption, and tap water consumption, and the time periods of use. As a result, the storage unit 3 of the information processing device 1 stores (accumulates) information about home activities based on the aggregation results of the daily life data as a daily history. The control unit 2 of the information processing device 1 derives change information, including the rate of change or change trend of the information about home activities over a predetermined period, such as one week or one month, and outputs advice information about frailty countermeasures for the consumer based on the change information. By using changes in the home activities of the consumer in this way (change information), appropriate advice information can be efficiently output based on a relative evaluation of each consumer based on factors over time.

[0062] (Embodiment 2) 8 is an explanatory diagram showing an overview of an information processing system S according to embodiment 2 (health device information). The information processing device 1, which is the main device constituting the information processing system S, is further connected to a health device KK used by a consumer so as to be able to communicate directly or indirectly, and acquires physical information (vital information) of the consumer measured by the health device KK as health device information.

[0063] The health devices KK are devices that measure physical information (vital information) of consumers, and include, for example, a weight scale, a body fat percentage meter, a BMI measuring device, a basal metabolic rate measuring device, a muscle mass measuring device, a bone mass estimator, a body water percentage measuring device, a blood pressure monitor, a pedometer, and a heart rate monitor. The health devices KK are worn by consumers who are targets of frailty prevention, and data (vital information) measured by the health devices KK may be transmitted to the information processing device 1 via, for example, the consumer-side terminal device T1. Alternatively, the health devices KK themselves may have a communication function and transmit continuous data (vital information) directly to the information processing device 1. Alternatively, these health devices KK may be functional units included in the consumer-side terminal device T1, such as a blood pressure monitor app or a pedometer app installed in the consumer-side terminal device T1.

[0064] The information processing device 1 acquires vital information (health device information) of a consumer measured by a health device KK, associates the acquired vital information with the measurement date and time of the vital information and the consumer ID, and stores the information in the storage unit 3. This allows the vital information (health device information) and usage data for each consumer to be stored and managed in association with each other.

[0065] 9 is a functional block diagram illustrating functional units included in the control unit 2 of the information processing device 1. As in the first embodiment, the control unit 2 of the information processing device 1 functions as a target consumer identification unit 203, a usage data extraction unit 204, a learning model 205 (in-home behavior model), and an advice generation unit 206, and further functions as a health device information acquisition unit 207.

[0066] The health equipment information acquisition unit 207 acquires vital information (health equipment information) of the target consumer measured by the health equipment KK, associates the acquired vital information with the measurement date and time of the vital information and the consumer ID, and stores the information in the memory unit 3.

[0067] The advice generation unit 206 acquires the in-home behavior information output from the learning model 205 (in-home behavior model) as in the first embodiment, and further acquires vital information (health device information) of each consumer from the health device information acquisition unit 207. The advice generation unit 206 generates advice information regarding frailty countermeasures based on the acquired in-home behavior information and vital information (health device information). When generating the advice information, the advice generation unit 206 may refer to the advice table 33 stored in the storage unit 3.

[0068] 10 is an explanatory diagram illustrating an example of the data layout of the advice table 33. Information indicating the correspondence between indoor activity information and advice information is stored, for example, in a table format (advice table 33) in the storage unit 3 of the information processing device 1. Items (fields) managed in the advice table 33 include activity type, activity content, health device information, advice information, etc.

[0069] The activity type item includes items indicating the type of home activity, such as at home / out, sleeping, using the toilet, taking a bath, or cooking at home. The activity content item stores values ​​or information output by the learning model 205 (home activity model) based on usage data (electricity usage, gas usage, and tap water usage) for each corresponding activity type. The activity content includes, for example, the consumer's time of day when they are at home, their bedtime, their wake-up time, the number of times they use the toilet, the number of times they take a bath, and the number of times they cook at home. In this way, the activity content item stores the results of analysis or classification of the usage data using the learning model 205 (home activity model).

[0070] The health device information item stores the consumer's physical information (vital information) measured by the health device KK. The vital information includes, for example, a weight scale, a body fat percentage meter, a BMI measuring device, a basal metabolic rate measuring device, a muscle mass measuring device, a bone mass estimator, a body water percentage measuring device, a blood pressure monitor, a pedometer, and a heart rate monitor, and is determined according to the corresponding activity type.

[0071] The advice information item stores advice information corresponding to a combination of the activity content and the health device information content (vital values ​​such as heart rate and blood pressure) for each activity type. The advice information in this embodiment is an example, and includes multiple pieces of advice information corresponding to the number of combinations of the home activity information and the health device information (vital information).

[0072] The advice generation unit 206 generates advice information based on a combination of the home behavior information output by the learning model 205 (home behavior model) and the health device information (vital information) measured by the health device KK by referring to the advice table 33. The advice generation unit 206 may generate screen data for displaying an advice screen including the advice information, and output the screen data to the demander side terminal device T1 or the facility manager side terminal device T2.

[0073] When the learning model 205 functions as a frailty assessment model, the advice generation unit 206 may generate advice information regarding frailty countermeasures based on a combination of the assessment result in accordance with the frailty assessment criteria output by the frailty assessment model and health device information (vital information) measured by the health device KK. When the learning model 205 functions as a behavioral type classification model, the advice generation unit 206 may generate advice information regarding frailty countermeasures based on a combination of the consumer's behavioral type output by the behavioral type classification model and health device information (vital information) measured by the health device KK.

[0074] 11 is a flowchart showing an example of a processing procedure by the control unit 2 of the information processing device 1. As in the first embodiment, the control unit 2 of the information processing device 1 starts the processing of the flowchart based on, for example, the request content transmitted from the demander-side terminal device T1 or the facility manager-side terminal device T2 communicably connected to the information processing device 1.

[0075] The control unit 2 of the information processing device 1 acquires target consumer information (S201). The control unit 2 of the information processing device 1 acquires usage data of the target consumer (S202). The control unit 2 of the information processing device 1 derives information regarding the target consumer's in-home behavior (S203). The control unit 2 of the information processing device 1 performs the processes from S201 to S203, similar to the processes from S101 to S103 in the first embodiment.

[0076] The control unit 2 of the information processing device 1 acquires the health device information of the target consumer (S204). The control unit 2 of the information processing device 1 acquires the vital information (health device information) of the target consumer measured by the health device KK, associates the acquired vital information with the measurement date and time of the vital information and the consumer ID, and stores the associated information in the memory unit 3. The vital information (health device information) includes, for example, the target consumer's weighing scale, body fat percentage meter, BMI measuring device, basal metabolic rate measuring device, muscle mass measuring device, bone mass estimator, body water percentage measuring device, blood pressure monitor, pedometer, and heart rate monitor.

[0077] The control unit 2 of the information processing device 1 outputs advice information for frailty countermeasures based on the home behavior and health device information (S205). The control unit 2 of the information processing device 1 outputs the advice information for frailty countermeasures based on the home behavior and health device information, for example, by referring to an advice table 33 stored in the storage unit 3. The control unit 2 of the information processing device 1 may generate advice information for frailty countermeasures by referring to the advice table 33 to identify advice information corresponding to a combination of the behavior content indicated in the home behavior information and the content (value) of the health device information. The control unit 2 of the information processing device 1 generates an advice screen (screen data) including the advice information and outputs the screen data to the consumer-side terminal device T1, the facility manager-side terminal device T2, or a terminal device used by a person designated by the consumer (such as a family member), thereby displaying the advice screen on the consumer-side terminal device T1, the facility manager-side terminal device T2, or a terminal device used by a person designated by the consumer (such as a family member). The advice information may be output to all of these terminal devices.

[0078] 12 is a diagram illustrating an example of an advice screen including advice information, etc. The control unit 2 of the information processing device 1 generates screen data for displaying the advice screen including the advice information, and outputs the screen data to the consumer-side terminal device T1 or the facility-management-side terminal device T2. The consumer-side terminal device T1 or the facility-management-side terminal device T2, which has acquired the screen data, displays the advice screen on a display unit connected to or provided with the device. This makes it possible to efficiently notify the consumer, who is a target for frailty prevention, of advice regarding frailty countermeasures for the consumer, as well as the usage data (electricity usage, gas usage, and tap water usage) on which the advice is based, or the like, to the consumer himself / herself, who is a target of frailty prevention, or to the facility manager of the housing or facility for active seniors in which the consumer resides.

[0079] The advice screen includes a consumer information display area, a usage data display area, an in-home behavior information display area, a health equipment information display area, and an advice display area.

[0080] The consumer information display area displays bibliographic information about the consumer, such as consumer ID, name, address, and building classification. The displayed consumer ID, name, etc. correspond to the consumer ID, name, etc. of the consumer who logged in to the information processing device 1 from the consumer-side terminal device T1. Alternatively, when a facility manager of a facility for active seniors logs in to the information processing device 1 using the facility manager-side terminal device T2, the consumer ID, etc. of the consumer residing in the facility for active seniors may be displayed.

[0081] The usage data display area displays electricity, gas, and tap water usage data for the building H where the consumer resides. As an illustrated example of this embodiment, subtotal values ​​of daily usage data (electricity usage, gas usage, and tap water usage) for a predetermined period of one week, based on the current time point, and the average value for the week are displayed. Furthermore, the rate of change, for example, the rate of change compared to the previous week, is displayed.

[0082] The home activity information display area displays home activity information output by the learning model 205 (home activity model) based on daily usage data. The home activity information is displayed in list format, with values ​​(contents) for each category, such as at home / out, sleeping, using the toilet, taking a bath, and cooking. The average value for one week displays information obtained by averaging these values ​​(contents). Alternatively, by aggregating the daily values ​​(contents) for one week, for example, if a certain activity continues for multiple days, the number of days that activity has continued may be displayed. Furthermore, the rate of change, for example, the rate of change compared to the previous week, is displayed.

[0083] The health device information display area displays the user's daily physical information (vital information) in list format. The average value for one week displays information obtained by averaging these values ​​(contents). Furthermore, the rate of change, for example, compared to the previous week, is displayed.

[0084] As described above, the advice display area displays advice information related to measures against frailty generated by the advice generating unit 206 (control unit 2).

[0085] According to this embodiment, the control unit 2 of the information processing device 1 outputs advice information regarding measures to combat frailty for the consumer based on health equipment information obtained from the health equipment KK used by the consumer and information regarding home behavior, thereby improving the accuracy or appropriateness of the advice information.

[0086] The embodiments disclosed herein are to be considered in all respects as illustrative and not restrictive. The scope of the present invention is defined by the claims, not by the above meaning, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0087] S Information Processing System H building H1 Electricity Smart Meter H2 gas smart meter H3 Tap Water Smart Meter N External Network K base station KK health equipment T1 customer terminal equipment T2 Facility manager's terminal device 1. Information processing equipment 2. Control section 201 Usage data acquisition unit 202 License Data Acquisition Unit 203 Target Consumer Identification Department 204 Usage data extraction unit 205 Learning Model (In-Home Behavior Model) 206 Advice Generation Unit 207 Health equipment information acquisition department 3 Storage section 31 Consumer Master Table 32 Usage Table 33 Advice Table P Program (Program Product) 300 Recording Media 4. Communications Department

Claims

1. A computer, Acquire usage data in which the amount of electricity, gas, and tap water used by the consumer is associated with information on the time period of use and consumer identification information that identifies the consumer; deriving information about the consumer's behavior in the home based on the acquired usage data; outputting advice information regarding health measures for the consumer based on the derived information regarding the in-home behavior; deriving information about the indoor behavior from the acquired usage data using a learning model that has been trained to output the indoor behavior when usage data is input; deriving a plurality of pieces of information relating to the consumer's in-home behavior based on the plurality of pieces of usage data acquired within a predetermined period; deriving change information regarding a change in the indoor behavior based on the derived information regarding the plurality of indoor behaviors; Based on the derived change information, advice information regarding health measures for the consumer is output. An information processing method for executing processing.

2. A computer, Acquire usage data in which the amount of electricity, gas, and tap water used by the consumer is associated with information on the time period of use and consumer identification information that identifies the consumer; deriving information about the consumer's behavior in the home based on the acquired usage data; outputting advice information regarding health measures for the consumer based on the derived information regarding the in-home behavior; deriving information about the indoor behavior from the acquired usage data using a learning model that has been trained to output the indoor behavior when usage data is input; Acquire health device information from the health device used by the consumer; Based on the acquired health device information and the information on the home behavior, advice information regarding health measures for the consumer is output. An information processing method for executing processing.

3. generating screen data including information on the consumer's in-home behavior and the health device information; Output the generated screen data The information processing method according to claim 2 .

4. The advice information regarding health measures includes advice information regarding frailty measures. The information processing method according to any one of claims 1 to 3.

5. The advice information regarding the consumer's health measures is output to the consumer or a person designated by the consumer. The information processing method according to any one of claims 1 to 4.

6. The home behavior includes the consumer's behavior related to bathing, cooking, and using the toilet in their home. The information processing method according to any one of claims 1 to 5.

7. The in-home behavior of the consumer is behavior in a residence for the elderly in which the consumer resides, Outputting advice information regarding health measures for the consumer to the manager of the residence for the elderly The information processing method according to any one of claims 1 to 6.

8. On the computer, Acquire usage data in which the amount of electricity, gas, and tap water used by the consumer is associated with information on the time period of use and consumer identification information that identifies the consumer; deriving information about the consumer's behavior in the home based on the acquired usage data; outputting advice information regarding health measures for the consumer based on the derived information regarding the in-home behavior; deriving information about the indoor behavior from the acquired usage data using a learning model that has been trained to output the indoor behavior when usage data is input; deriving a plurality of pieces of information relating to the consumer's in-home behavior based on the plurality of pieces of usage data acquired within a predetermined period; deriving change information regarding a change in the indoor behavior based on the derived information regarding the plurality of indoor behaviors; Based on the derived change information, advice information regarding health measures for the consumer is output. A program that executes a process.

9. To a computer Acquire usage data in which the amount of electricity, gas, and tap water used by the consumer is associated with information on the time period of use and consumer identification information that identifies the consumer; deriving information about the consumer's behavior in the home based on the acquired usage data; outputting advice information regarding health measures for the consumer based on the derived information regarding the in-home behavior; deriving information about the indoor behavior from the acquired usage data using a learning model that has been trained to output the indoor behavior when usage data is input; Acquire health device information from the health device used by the consumer; Based on the acquired health device information and the information on the home behavior, advice information regarding health measures for the consumer is output. A program that executes a process.

10. an acquisition unit that acquires usage data in which the amounts of electricity, gas, and tap water used by a consumer are associated with information on the time period of use and consumer identification information that identifies the consumer; a derivation unit that derives information regarding the consumer's behavior in the home based on the acquired usage data; an output unit that outputs advice information regarding health measures for the consumer based on the derived information regarding the indoor behavior, deriving information about the indoor behavior from the acquired usage data using a learning model that has been trained to output the indoor behavior when usage data is input; deriving a plurality of pieces of information relating to the consumer's in-home behavior based on the plurality of pieces of usage data acquired within a predetermined period; deriving change information regarding a change in the indoor behavior based on the derived information regarding the plurality of indoor behaviors; Based on the derived change information, advice information regarding health measures for the consumer is output. Information processing device.

11. An acquisition unit that acquires usage data that associates information about the time of use and consumer identification information that identifies the consumer with the amount of electricity, gas, and tap water used by the consumer; a derivation unit that derives information regarding the consumer's behavior in the home based on the acquired usage data; an output unit that outputs advice information regarding health measures for the consumer based on the derived information regarding the indoor behavior, deriving information about the indoor behavior from the acquired usage data using a learning model that has been trained to output the indoor behavior when usage data is input; Acquire health device information from the health device used by the consumer; Based on the acquired health device information and the information on the home behavior, advice information regarding health measures for the consumer is output. Information processing device.

12. an electricity smart meter that outputs the amount of electricity used by a consumer; a gas smart meter that outputs the amount of gas used by the consumer; a tap water smart meter that outputs the amount of tap water used by the consumer; an information processing device communicably connected to the electricity smart meter, the gas smart meter, and the tap water smart meter; An information processing system comprising: The information processing device includes: acquiring the amount of power usage from the power smart meter; Acquire the gas usage amount from the gas smart meter; Acquire the amount of tap water used from the tap water smart meter; storing usage data in which the acquired amounts of electricity usage, gas usage, and tap water usage are associated with information on a usage time period and consumer identification information that identifies the consumer in a storage area accessible from the device itself; deriving information on the consumer's in-home behavior based on the usage data stored in the storage area; outputting advice information regarding health measures for the consumer based on the derived information regarding the in-home behavior; deriving information about the indoor behavior from the acquired usage data using a learning model that has been trained to output the indoor behavior when usage data is input; deriving a plurality of pieces of information relating to the consumer's in-home behavior based on the plurality of pieces of usage data acquired within a predetermined period; deriving change information regarding a change in the indoor behavior based on the derived information regarding the plurality of indoor behaviors; Based on the derived change information, advice information regarding health measures for the consumer is output. Information processing system.

13. An electricity smart meter that outputs the amount of electricity used by a consumer; a gas smart meter that outputs the amount of gas used by the consumer; a tap water smart meter that outputs the amount of tap water used by the consumer; an information processing device communicably connected to the electricity smart meter, the gas smart meter, and the tap water smart meter; An information processing system comprising: The information processing device includes: acquiring the amount of power usage from the power smart meter; Acquire the gas usage amount from the gas smart meter; Acquire the amount of tap water used from the tap water smart meter; storing usage data in which the acquired amounts of electricity usage, gas usage, and tap water usage are associated with information on a usage time period and consumer identification information that identifies the consumer in a storage area accessible from the device itself; deriving information on the consumer's in-home behavior based on the usage data stored in the storage area; outputting advice information regarding health measures for the consumer based on the derived information regarding the in-home behavior; deriving information about the indoor behavior from the acquired usage data using a learning model that has been trained to output the indoor behavior when usage data is input; Acquire health device information from the health device used by the consumer; Based on the acquired health device information and the information on the home behavior, advice information regarding health measures for the consumer is output. Information processing system.

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