Information processing device and information processing method

Abstract

To provide an information processing device and an information processing method capable of easily grasping a degree of interaction among users in a building.SOLUTION: An information processing device analyzes a usage status of a target apparatus in a building used by a plurality of users, and includes a processor. The processor specifies the usage status of the target apparatus in each of a plurality of periods, acquires evaluation results of an interaction degree of the plurality of users in the building in each of the plurality of periods, and specifies a correspondence relation between the usage status and the interaction degree based on the specification results of the usage status in each of the plurality of periods and the evaluation results of the interaction degree in each of the plurality of periods.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to an information processing device and an information processing method, and more particularly to an information processing device and an information processing method for analyzing the usage status of target devices in a building used by multiple users. [Background technology]

[0002] Technology for analyzing the usage of electrical devices and the like in buildings such as houses is sometimes used, for example, to determine the behavior of building users (specifically, whether they are at home or not) (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2018-117455 Summary of the Invention [Problem to be solved by the invention]

[0004] There is a need to make more effective use of the information obtained by analyzing the usage of devices in buildings. In particular, for buildings used by multiple people (e.g., residential buildings), analyzing the usage of devices in the building is expected to provide useful information for improving relationships between users, for example.

[0005] Therefore, the present invention has been made in consideration of the above-mentioned problems, and its purpose is to provide an information processing device and an information processing method that can increase the usefulness of analyzing equipment usage status within a building used by multiple users. [Means for solving the problem]

[0006] The above problem is solved by the information processing device of the present invention, which is equipped with a processor and analyzes the usage status of target devices within a building used by multiple users, wherein the processor identifies the usage status at each of multiple time periods, obtains evaluation results on the degree of interaction between the multiple users within the building at each of the multiple time periods, and identifies the correspondence between the usage status and the degree of interaction based on the identified results of the usage status at each of the multiple time periods and the evaluation results on the degree of interaction at each of the multiple time periods.

[0007] By using the information processing device configured as described above, it is possible to grasp the degree of interaction between a plurality of users using a building based on the usage status of target devices within the building.

[0008] In addition, in the information processing device of the present invention, the processor may predict usage conditions at a future time and estimate the degree of interaction at a future time based on the predicted usage conditions at the future time and the correspondence relationship. According to the above configuration, it is possible to predict future device usage and estimate the future interaction level based on the predicted usage level. The estimated interaction level can be used as reference information for improving the interaction level among multiple users in a building, for example.

[0009] The target devices may include first electric devices installed in each of a plurality of rooms in a building. In this case, in the information processing device of the present invention, the processor may identify, as the usage status, first times when the first electric device was used in two or more of the plurality of rooms in each of a plurality of time periods, and may identify, as the correspondence relationship, a correlation between the first times and the degree of interaction. According to the above configuration, the degree of interaction between multiple users of a building can be more easily understood based on the usage status of the first electrical device installed in each room (specifically, the time the first electrical device was used in two or more rooms).

[0010] The target devices may also include a second electric device installed in a space in a building shared by multiple users. In this case, in the information processing device of the present invention, the processor may identify, as the usage status, a second time period during which the second electric device was used in the building in each of multiple periods, and may identify, as the correspondence relationship, a correlation between the second time period and the degree of interaction. According to the above configuration, the degree of interaction between multiple users of a building can be more easily understood based on the usage status of a second electrical device installed in a shared space of the building (specifically, the time the second electrical device was used).

[0011] The target devices may include a first electrical device installed in each of a plurality of rooms in a building and a second electrical device installed in a space in the building shared by a plurality of users. In this case, in the information processing device of the present invention, the processor may identify, as the usage status, a first time period during which the first electrical device was used in two or more of the plurality of rooms in each of a plurality of time periods, and a second time period during which the second electrical device was used in the building in each of the plurality of time periods. The processor may also identify, as the correspondence relationship, an approximation formula for the degree of AC power, with the first time period and the second time period as variables. According to the above configuration, it is possible to more easily grasp the degree of interaction between a plurality of users of a building based on the usage status of the first electric device and the second electric device in the building.

[0012] In the information processing device of the present invention, the processor may acquire information regarding the use pattern of the building and set weights for each of the first and second times according to the use pattern. The processor may then specify, as the approximation formula, a polynomial including a term obtained by multiplying a first calculated value based on the first time by the weight for the first time, and a term obtained by multiplying a second calculated value based on the second time by the weight for the second time. According to the above configuration, when specifying an approximation formula for the degree of AC as a correspondence relationship between the usage status of the target devices (specifically, the first and second electric devices) and the degree of AC, it is possible to reflect the usage pattern of the building, thereby obtaining a more appropriate approximation formula.

[0013] In the information processing device of the present invention, the processor may obtain an evaluation result of the appropriateness of the amounts of time of the first time and the second time, and set a weight for each of the first time and the second time according to the appropriateness. The processor may then specify, as the approximation formula, a polynomial including a term obtained by multiplying a first calculated value based on the first time by the weight for the first time, and a term obtained by multiplying a second calculated value based on the second time by the weight for the second time. According to the above configuration, when specifying an approximation formula for the degree of AC as a correspondence relationship between the usage status of the target devices (specifically, the first and second electric devices) and the degree of AC, it is possible to reflect the appropriateness of the amount of time of the first time and the second time (in other words, the amount of time that multiple users spend in different spaces in a building), thereby obtaining a more appropriate approximation formula.

[0014] Furthermore, the above-mentioned problem is solved by the information processing method of the present invention, which is an information processing method for analyzing the usage status of target devices in a building used by multiple users, in which a processor identifies the usage status at each of multiple time periods, the processor obtains evaluation results on the degree of interaction between the multiple users in the building at each of the multiple time periods, and the processor identifies the correspondence between the usage status and the degree of interaction based on the identification results of the usage status at each of the multiple time periods and the evaluation results on the degree of interaction at each of the multiple time periods. According to the above information processing method, the information obtained by analyzing the device usage status within a building used by multiple users can be utilized more effectively, and specifically, the degree of interaction between multiple users within the building can be grasped based on the device usage status. [Effects of the Invention]

[0015] The information processing device and information processing method of the present invention can enhance the usefulness of analyzing device usage in a building used by multiple users. Specifically, the degree of interaction between multiple users in the building can be easily understood based on the device usage. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is an explanatory diagram of a building to which the present invention is applied; [Figure 2] 1 is a diagram showing a communication system including an information processing device according to an embodiment of the present invention. [Figure 3] FIG. 1 is a diagram showing an information processing flow according to an embodiment of the present invention (part 1). [Figure 4] FIG. 2 is a diagram showing an information processing flow according to an embodiment of the present invention (part 2). [Figure 5] 5 is an explanatory diagram of the procedure for identifying the usage status of a target device, where (a) in FIG. 5 shows a diagram when the target device is an air conditioner, (b) shows a diagram when the target device is a television, and (c) shows a diagram when the target device is a microwave oven. [Figure 6] FIG. 10 is a diagram showing the correlation between the usage status of the target device and the degree of interaction between multiple users in a building. [Figure 7] FIG. 10 is a diagram illustrating a procedure for estimating the degree of interaction in a future period. DETAILED DESCRIPTION OF THE INVENTION

[0017] <<About one embodiment of the present invention>> One embodiment of the present invention (hereinafter referred to as the present embodiment) will be described below with reference to the accompanying drawings. The present embodiment relates to an information processing technology for devices used in a building, and more specifically, to a technology for analyzing the usage status of target devices in a building used by multiple users.

[0018] In this specification, the concept of "device" includes a single device that performs a specific function, as well as a combination of multiple devices that are distributed and exist independently but work together (in cooperation) to perform a specific function.

[0019] Furthermore, the basic data processing technologies (communication / transmission technologies, data acquisition technologies, data recording technologies, data processing / analysis technologies, image processing technologies, visualization technologies, etc.) required to realize the contents of this embodiment are well-known technologies, and therefore explanations thereof will be omitted.

[0020] In addition, this embodiment will be described assuming that the "building" is a residence. Here, the residence may be a detached house or a single dwelling unit in an apartment building. However, buildings to which the present invention is applicable are not limited to residences, and the present invention can also be applied to buildings for various purposes other than residences, such as stores, offices, commercial facilities such as movie theaters and department stores, public facilities such as hospitals and schools, factories, or buildings.

[0021] <<Outline of this embodiment>> First, an overview of a communication system including an information processing device according to this embodiment will be described. Hereinafter, the information processing device according to this embodiment will be referred to as an "information processing device 10," and the communication system including the information processing device 10 will be referred to as an "interaction support system 100."

[0022] The interaction support system 100 is constructed for the purpose of grasping the degree of interaction within the house H among multiple users using the house H shown in FIG. 1 , i.e., the multiple residents living in the house H, and promoting interaction among the residents within the house H. The degree of interaction among the multiple residents within the house H refers to the degree to which, if the multiple residents are a family, the family members spend time together within the house H for family gatherings, etc., and more specifically, it is an index representing the amount of time or frequency that the family members spend time together in the same room, or the satisfaction level with these values. In this embodiment, the interaction support system 100 can quantify and quantitatively identify the degree of interaction among the multiple residents within the house H (hereinafter simply referred to as "degree of interaction").

[0023] The interaction support system 100 periodically or irregularly acquires the usage status of target devices used in the house H and the evaluation results of the degree of interaction. The target devices are devices whose usage status is analyzed by the information processing device 10, and in this embodiment, are electrical devices installed in the house H. The usage status of the target devices is the usage status of the electrical devices in the house H, and more specifically, the usage time of the electrical devices. More specifically, the target devices include first electrical devices installed in each of multiple rooms in the house H, and second electrical devices installed in a space in the house H that is shared by multiple residents.

[0024] The first electrical appliances are, for example, air conditioner C and television T shown in FIG. 1, and when multiple residents are in different rooms, each resident uses the first electrical appliance installed in the room in which that resident is located. In other words, when multiple residents each stay in their own room, first electrical appliances such as air conditioners and televisions will be used in two or more rooms. Conversely, when multiple residents stay in the same room, they will share the first electrical appliance installed in that room. The first electric appliance is not limited to the air conditioner C or the television T, but may be any appliance used in an individual room, and may include other electric appliances (for example, a vacuum cleaner).

[0025] The second electric appliance is, for example, an electric appliance installed in a shared space such as the kitchen shown in FIG. 1, and specifically corresponds to the microwave oven M, refrigerator, etc. For example, when multiple residents eat meals at different times in the house H, each resident uses the second electric appliance such as the microwave oven M at a different time, and therefore the usage time of the second electric appliance tends to be long. Conversely, when multiple residents eat meals together in the house H, the usage time of the second electric appliance such as the microwave oven M tends to be short because it is concentrated rather than dispersed. The second electric appliance is not limited to the microwave oven M or the refrigerator, but may include other electric appliances (for example, a rice cooker or a washing machine) that are used in a shared space such as a kitchen.

[0026] In this embodiment, the usage status of the target device is determined as the usage time of the first electric device, more specifically, the time (hereinafter referred to as the first time) when an air conditioner C or a television T is used in two or more rooms among the multiple rooms in the house H. Also, in this embodiment, the usage status of the target device is determined as the time (hereinafter referred to as the second time) when a second electric device is used in the house H. The first time and the second time are determined for each of multiple periods.

[0027] The above-mentioned multiple periods are set in advance as periods when the first time and the second time are specified, and can be set to any period. For example, each day in a specified period of n days, n weeks, or n months (n is a natural number), or days corresponding to specified days of the week, may be set as the multiple periods. Furthermore, the multiple periods may be set to the same time period on multiple days (for example, the time period from the evening to the night on each day). Furthermore, the multiple periods may be multiple dates and times specified randomly. The unit of "time" is not particularly limited and can be any of minutes, hours, days, weeks, months, and years, but the following explanation will be given assuming that the unit of time is one day.

[0028] The evaluation result of the interaction level is obtained by one or more residents evaluating the interaction level and inputting the evaluation result. Specifically, for example, a resident of house H scores the interaction level within a range of 0 to P (P is a natural number, for example, P=5) and inputs the score, thereby obtaining the evaluation result of the interaction level. The means and method for inputting the evaluation result of the interaction level are not particularly limited, and for example, the evaluation result of the interaction level may be input through a resident terminal 12, which will be described later. Furthermore, the person inputting the evaluation result of the interaction level may be someone other than a resident of house H. Furthermore, the interaction level may be input by a method other than inputting a score, for example, by selecting one of a list of words representing the interaction level (specifically, "satisfied," "average," "unsatisfied," etc.).

[0029] In this embodiment, the evaluation result of the interaction level is obtained for each of the multiple periods for which the first and second times are specified. That is, for example, if the first and second times are specified for Y month Z day of 20XX, the evaluation result of the interaction level for that day will be obtained.

[0030] Then, the interaction support system 100 identifies a correspondence between the usage status of the target device identified for each of the multiple time periods and the evaluation results of the interaction level acquired for each of the multiple time periods. Specifically, the system identifies a correlation between the first and second times identified for each time period and the evaluation results of the interaction level acquired for each of the time periods, and more specifically, derives an approximation formula for the interaction level using the first and second times as variables.

[0031] Furthermore, the interaction support system 100 can estimate the degree of interaction at a future time based on the identified correlation. The estimated degree of interaction is output to the resident of the house H and displayed, for example, on the display of the resident terminal 12. The resident may check the output estimation result of the degree of interaction at a future time, and use this as an opportunity to reconsider their behavior within the house H in order to improve the degree of interaction.

[0032] <<Example of a system configuration for supporting communication>> Next, a configuration example of the communication support system 100 will be described with reference to Fig. 2. As shown in Fig. 2, the communication support system 100 is configured by an information processing device 10, a resident terminal 12, a sensor group 14, and a database 16.

[0033] The information processing device 10 is made up of a computer, for example, a server computer, etc. The information processing device 10 may be made up of a single computer, or may be made up of multiple computers distributed in parallel. Furthermore, the server computer constituting the information processing device 10 may be a server computer for a cloud service, or may be a server computer for an ASP (Application Service Provider), SaaS (Software as a Service), PaaS (Platform as a Service), or IaaS (Infrastructure as a Service). In this case, when necessary information is input into a client terminal, the server computer performs various processes and calculations based on the input information, and the calculation results are output on the client terminal side. In other words, the functions of the server computer, which is the information processing device 10, can be used on the client terminal side. The server computer constituting the information processing device 10 may be a home server installed in the house H and capable of communicating with various communication devices within the house through a home network. Alternatively, the server computer may be installed outside the house H.

[0034] 2, the computer constituting the information processing device 10 includes a processor 21, a memory 22, a storage 23, and a communication interface 24. The processor 21 is configured by, for example, a CPU (Central Processing Unit), an MPU (Micro-Processing Unit), an MCU (Micro Controller Unit), a GPU (Graphics Processing Unit), a DSP (Digital Signal Processor), a TPU (Tensor Processing Unit), or an ASIC (Application Specific Integrated Circuit). The memory 22 is configured by semiconductor memories such as a ROM (Read Only Memory) and a RAM (Random Access Memory).

[0035] The storage 23 is configured by, for example, a flash memory, an HDD (Hard Disc Drive), an SSD (Solid State Drive), an FD (Flexible Disc), an MO disk (Magneto-Optical disc), a CD (Compact Disc), a DVD (Digital Versatile Disc), an SD card (Secure Digital card), or a USB memory (Universal Serial Bus memory), etc. The storage 23 may be built into the computer main body that configures the information processing device 10, or may be attached to the computer main body in an external format.

[0036] The communication interface 24 may be configured, for example, by a network interface card or a communication interface board. The computer that configures the information processing device 10 can communicate with each communication device connected to the communication network via the communication interface 24. Devices with which the information processing device 10 can communicate via the communication interface 24 include the resident terminal 12 and the sensor group 14.

[0037] Furthermore, a program for an operating system (OS) and an application program for data analysis are installed as software in the server computer constituting the information processing device 10. When these programs are read by the processor 21, the server computer constituting the information processing device 10 executes a series of processes required to grasp the degree of interaction within the house H. The application program for data analysis includes a program for identifying the first and second times for each of a plurality of periods, a program for identifying the correspondence between the first and second times and the degree of interaction, and a program for estimating the degree of interaction in a future period.

[0038] The resident terminal 12 is an information processing terminal operated by a resident of the house H, and is configured as a personal computer (PC), smartphone, mobile phone, tablet terminal, laptop computer, wearable terminal, or the like. The resident terminal 12 is equipped with input devices such as a keyboard, mouse, and touchpad, and a display device such as a display. The resident terminal 12 is also capable of communicating with the information processing device 10 via a communication network, transmitting information to the information processing device 10 and receiving information transmitted from the information processing device 10. The information transmitted by the resident terminal 12 to the information processing device 10 includes, for example, an evaluation result of the degree of interaction for each period input by the resident.

[0039] The display provided in the resident terminal 12 displays information transmitted from the information processing device 10. Specifically, for example, the correlation between the first time and the second time and the degree of interaction, and the estimated result of the degree of interaction in the future, etc. can be displayed on the display. The display may be a display provided in the resident terminal 12 itself, or may be a display connected by wire or wirelessly to the resident terminal 12. The display connected to the resident terminal 12 may include not only a typical stationary display, but also a head-mounted display (HMD) such as VR goggles, and a glasses-type display that allows images to be viewed through glasses such as smart glasses.

[0040] An application program (hereinafter, terminal-side application) for understanding the degree of interaction within the house H is installed in the resident terminal 12. When the terminal-side application is started on the resident terminal 12, an operation screen (user interface) for understanding the degree of interaction within the house H is displayed, and the resident performs the operations necessary to understand the degree of interaction within the house H through the operation screen. The operations by the resident include an operation for inputting the evaluation results of the degree of interaction for each period, and an operation for displaying information transmitted from the information processing device 10 on a display device. By performing these operations, the resident of the house H can confirm the degree of interaction within the house H, etc.

[0041] Furthermore, the residents of the house H can input information about their lifestyles in the house H through the resident terminal 12. The information about the lifestyles in the house H corresponds to information about the usage pattern of the house H, and specifically includes the number of residents living in the house H and how each resident spends their time (lifestyle) in the house H. The information about how to spend their time in the house H includes the content and tendencies of the residents' behaviors at each time of the day (lifestyle patterns), their locations within the house H, their behavioral preferences, and their routes of movement within the house H (traffic lines). The input information about the lifestyle is used in processing by the information processing device 10, and specifically, is reflected in an approximation formula for the degree of interaction within the house H.

[0042] The sensor group 14 is made up of a plurality of sensors that detect the usage status of electrical appliances in each of a plurality of rooms in the house H. Each sensor included in the sensor group 14 is configured as a power sensor with a communication function, specifically a measurement tap (more specifically, a smart tap) with a built-in communication module, and measures the power consumption of an electrical appliance installed in each room at each point in time. The measurement data is transmitted from the sensor to the information processing device 10 via a communication network as needed. The sensor in each room also measures the power consumption of each electrical appliance installed in the room, and transmits the measurement data, which includes information about the type of electrical appliance whose power consumption has been measured and its installation location, to the information processing device 10. As a result, based on the measurement data acquired from the sensors, the information processing device 10 can identify the point in time, the room in which the electrical appliance is installed, and the electrical appliance that consumed the power indicated by the measurement data.

[0043] The database 16 stores information and data required when a server computer constituting the information processing device 10 executes a series of processes. The database 16 may be constructed, for example, in a storage 23 of the server computer constituting the information processing device 10. Alternatively, the database 16 may be constructed in a database server communicatively connected to the server computer constituting the information processing device 10. The information and data stored in the database 16 include measurement data acquired from the sensor group 14, information on first and second times for multiple time periods obtained by analyzing the measurement data, and evaluation results of the degree of interaction input through the resident terminal 12. The database 16 may also include correlations between the first and second times and the degree of interaction, more specifically, an approximation formula for the degree of interaction using the first and second times as variables. The information processing device 10, more specifically, the processor 21 of the server computer constituting the information processing device 10, reads out information stored in the database 16 as appropriate when executing a process for grasping the degree of interaction within the house H.

[0044] <<Information processing by information processing device>> Next, the information processing by the information processing device 10, that is, a series of information processing for grasping the degree of interaction within the house H, will be described with reference to FIGS. As described above, a series of information processing for grasping the degree of interaction within the house H is executed by the information processing device 10. In detail, the processor 21 provided in the server computer constituting the information processing device 10 executes the series of information processing by reading a program (i.e., software) installed in the server computer.

[0045] The above series of information processing steps are divided into a processing flow shown in Fig. 3 (hereinafter referred to as the analysis flow) and a processing flow shown in Fig. 4 (hereinafter referred to as the estimation flow). Each processing flow employs the information processing method of the present invention. In other words, each step in the flow shown in Figs. 3 and 4 corresponds to each element constituting the information processing method of the present invention. The processing flows shown in FIGS. 3 and 4 are merely examples, and unnecessary steps may be deleted, new steps may be added, or the order in which steps are performed may be changed, without departing from the spirit of the present invention. The analysis flow and estimation flow will be explained below.

[0046] (Analysis flow) The analysis flow is executed for the purpose of analyzing the usage status of the target device within the house H and identifying the correspondence between the usage status and the degree of interaction within the house H, and proceeds according to the flow shown in Fig. 3. Specifically, in the analysis flow, first, the processor 21 of the server computer constituting the information processing device 10 (hereinafter simply referred to as the processor 21) identifies the usage status of the target device at each of a plurality of time periods (S001).

[0047] In step S001, the processor 21 receives measurement data sent from the sensor group 14 as needed, and identifies the daily usage status of the target devices based on the received measurement data. More specifically, if an air conditioner C and a television T are installed in each of multiple rooms (e.g., a living room, a children's room, a study, a bedroom, etc.) in a house H as shown in Fig. 1, the power consumption of the air conditioner C and the power consumption of the television T at each point in time in each room are measured by power sensors. The processor 21 receives the measurement data from the power sensors, and based on the received measurement data, identifies the first hour of each day for the air conditioner C and the television T as the usage status of the target devices. In addition, if only one of the air conditioners C and the televisions T is installed in multiple rooms, the first time of each day may be determined for the devices installed in the multiple rooms.

[0048] As shown in Figure 5(a), the first time for air conditioner C is the time during a day when air conditioner C is used simultaneously in two or more rooms among the multiple rooms in which air conditioner C is installed. In other words, it represents the amount of time multiple residents spend in different rooms. The first hour of TV T is the time during which TV T is used simultaneously in two or more rooms among the multiple rooms in which TV T is installed, as shown in (b) of Figure 5, in other words, it represents the amount of time preferred by each of the multiple residents.

[0049] Furthermore, if an electrical cooking appliance, for example, a microwave oven M, is installed in a kitchen shared by multiple residents of house H, the power consumption of the microwave oven M at each point in time is measured by a power sensor. Processor 21 receives the measurement data from the power sensor and, based on the received measurement data, identifies a second time period for the microwave oven M each day as the usage status of the target appliance. As shown in FIG. 5(c), the second time period for the microwave oven M is the time period for which the microwave oven M is used in house H each day, or in other words, represents the amount of time the residents spend cooking and eating. If a refrigerator is installed in the kitchen, processor 21 may identify the second refrigerator time for each day together with or instead of the second time of microwave oven M. The second refrigerator time is the time during which the refrigerator is used in house H in one day, or more precisely, the time during which the refrigerator's power consumption changes (increases) due to the refrigerator being opened or closed.

[0050] Next, processor 21 acquires an evaluation result of the degree of interaction for each of the multiple periods for which the first time and the second time have been identified (S002). More specifically, in step S002, first, a resident of house H evaluates the degree of interaction within house H on a daily basis and inputs the evaluation result using resident terminal 12. The input evaluation result data of the degree of interaction is transmitted from resident terminal 12 to information processing device 10. By receiving the data transmitted from resident terminal 12, processor 21 acquires an evaluation result of the degree of interaction within house H for each of the multiple periods, and in this embodiment, acquires an evaluation result of the degree of interaction for each day.

[0051] Next, processor 21 acquires information about the lifestyle at home H as information about the usage pattern of home H (S003). More specifically, in step S003, a resident of home H inputs information about their lifestyle using resident terminal 12. At this time, the method for inputting the information about their lifestyle is not particularly limited, and for example, two or more options about lifestyle may be displayed on the screen of resident terminal 12, and the resident may be prompted to select an option that matches their current lifestyle from the two or more displayed options, and touch or click on the option on the screen. The input lifestyle information is converted into data and transmitted from the resident terminal 12 to the information processing device 10. The processor 21 receives the data transmitted from the resident terminal 12 and thereby acquires the input lifestyle information.

[0052] After acquiring the lifestyle-related information, processor 21 sets weights according to the lifestyle for each of the first time period of air conditioner C, the first time period of television T, and the second time period of microwave oven M (S004). There are no particular limitations on the method for setting the weights, but, for example, weights for the first time period of air conditioner C, the first time period of television T, and the second time period of microwave oven M may be defined for each lifestyle, and the weights defined for each lifestyle may be stored as table data in database 16. In this case, based on the lifestyle-related information acquired in step S003, a weight corresponding to the lifestyle indicated by the information may be identified from the table data, and the identified weight may be used as the setting value.

[0053] It should be noted that steps S003 and S004 do not necessarily have to be performed, and if they are not required, these steps may be omitted and the process may proceed to step S005.

[0054] Next, processor 21 determines the correspondence between the usage status and the degree of interaction based on the results of identifying the usage status of the target device at each of the multiple periods obtained in step S001 and the evaluation results of the degree of interaction within house H at each of the multiple periods obtained in step S002 (S005).

[0055] Specifically, if in step S001 a first time period each day for air conditioner C and television T is identified as the usage status of the target devices, then in step S005 a correlation between the first time period and the degree of interaction within house H is identified. Also, if in step S001 a second time period each day for microwave oven M is identified as the usage status of the target devices, then in step S005 a correlation between the second time period and the degree of interaction within house H is identified.

[0056] In this embodiment, in step S001, the first time for each day of the air conditioner C and the television T, and the second time for each day of the microwave oven M are both identified. Therefore, in step S005, the correlation between the first time and the degree of interaction within the house H, and the correlation between the second time and the degree of interaction within the house H are each identified.

[0057] A known statistical analysis method such as regression analysis can be used to identify the correlation. Specifically, in this embodiment, the correlation is identified by applying linear approximation, as shown in Fig. 6. More specifically, a regression line showing the correlation with the AC level is obtained for the first time period of the air conditioner C, the first time period of the television T, and the second time period of the microwave oven M, and a correlation coefficient is calculated. 6 is a graph showing the correlation between the first time period specified in step S001 and the evaluation results of the degree of interaction acquired in step S002, with the horizontal axis representing the duration of the first time period and the vertical axis representing the evaluation results. Note that FIG. 6 is an illustration, and each plot in the figure is not actual data but fictitious data prepared to illustrate the above correlation in an easy-to-understand manner.

[0058] Then, in step S005, processor 21 identifies an approximation formula for the degree of AC based on the correlations, more specifically, the regression lines and correlation coefficients, between the degrees of AC identified for the first time period of air conditioner C, the first time period of television T, and the second time period of microwave oven M. At this time, if the first time period of air conditioner C, the first time period of television T, and the second time period of microwave oven M all have a strong correlation with the degree of AC (for example, if the correlation coefficient is equal to or greater than a reference value), processor 21 identifies an approximation formula for the degree of AC that uses these as variables.

[0059] More specifically, processor 21 identifies, as the approximation formula, a polynomial including a term representing the product of the first time t1a of air conditioner C and coefficient D1, a term representing the product of the first time t1b of television T and coefficient D2, and a term representing the product of the second time t2 of microwave oven M and coefficient D3. Here, coefficient D1 is a value corresponding to the slope of the regression line showing the correlation between the first time of air conditioner C and the degree of AC. Coefficient D2 is a value corresponding to the slope of the regression line showing the correlation between the first time of television T and the degree of AC. Coefficient D3 is a value corresponding to the slope of the regression line showing the correlation between the first time of television T and the degree of AC. The product of the first time t1a of the air conditioner C and the coefficient D1, and the product of the first time of the television T and the coefficient D2 correspond to a first calculated value based on the first time. The product of the second time of the microwave oven M and the coefficient D3 corresponds to a second calculated value based on the second time.

[0060] Furthermore, if the weight is set in step S004, in step S005, the processor 21 specifies the following polynomial as the approximation formula. E=(t1a×D1×w1)+(t1b×D2×w2)+(t2×D3×w3) In the above formula, E indicates the degree of interaction within the house H, and w1, w2, and w3 indicate the weights set in step S004. Here, on the right-hand side of the above equation, the first term is the product of the first time t1a of air conditioner C and coefficient D1 (i.e., the first calculated value) multiplied by the weight w1 for the first time t1a of air conditioner C. The second term is the product of the first time t1b of television T and coefficient D2 (i.e., the first calculated value) multiplied by the weight w2 for the first time t1b of television T. The third term is the product of the second time t2 of microwave oven M and coefficient D3 (i.e., the second calculated value) multiplied by the weight w3 for the second time t2 of microwave oven M.

[0061] The analysis flow ends when the series of processes described above, that is, steps S001 to S005, are all completed. 3, a step of outputting the correspondence relationship identified in step S005 to the resident of the house H may be further included. In this step, the processor 21 may display a graph showing the correlation between the usage status of the target devices (more specifically, the first time period for each of the air conditioner C and the television T, and the second time period for the microwave oven M) and the degree of interaction within the house H on the display of the resident terminal 12. This allows the analysis results of the analysis flow, i.e., the current degree of interaction within the house H, to be notified and fed back to the resident.

[0062] (Estimated flow) The estimation flow is executed for the purpose of estimating the degree of interaction within house H at a future time, and proceeds according to the flow shown in Fig. 4. Specifically, when a resident of house H starts up a terminal-side app on the resident terminal 12 and requests execution of the estimation flow, this triggers the start of the estimation flow.

[0063] In the estimation flow, first, the processor 21 predicts the usage status of the target devices in the house H in a future time period, specifically, a first time period for each of the air conditioner C and the television T, and a second time period for the microwave oven M (S011). The future time period is a time period for which the degree of interaction in the house H is to be estimated. The resident of the house H operates the resident terminal 12 to set the future time period. At this time, the future time period can be set to any time period, for example, one to several hours, one to several days, one to several weeks, one to several months, or one to several years.

[0064] The method and procedure for predicting the first and second hours in a future period are not particularly limited, and may be, for example, predictions based on past actual values. Specifically, as described above, measurement data on the power consumption of the air conditioner C, the television T, and the microwave oven M measured at each point in time in the past is stored in the database 16. The processor 21 may set a date corresponding to the future period to be predicted in response to a user's input operation, etc., read measurement data for the same month or day of the previous year for the set date from the database 16, and predict the usage time (i.e., the first and second hours) of each electrical appliance in the future period from the measurement data. Alternatively, machine learning may be performed using the measurement data of past power consumption stored in the database 16 to build a learning model for predicting the usage time of each electrical appliance at the time to be predicted, and the learning model may be used to predict the first and second hours in the future period.

[0065] Next, processor 21 acquires information relating to a lifestyle in house H at a future time (S012). In this step S012, first, a resident of house H imagines a lifestyle at a future time and inputs information relating to the imagined lifestyle using resident terminal 12. The input lifestyle information is converted into data and transmitted from resident terminal 12 to information processing device 10, and processor 21 receives the data from resident terminal 12 to acquire the input lifestyle information. It should be noted that step S012 does not necessarily have to be performed, and if unnecessary, it may be omitted.

[0066] When processor 21 acquires information about lifestyles in the future in step S012, it updates the approximation formula of the degree of interaction identified in the above-described analysis flow based on the acquired information (S013). Specifically, it resets the weights w1, w2, and w3 in the polynomial that forms the approximation formula of the degree of interaction based on the information about lifestyles acquired in step S012. The procedure for resetting the weights is the same as that in step S004, that is, the weights are set by referring to table data that defines the weights for each lifestyle. If the previous step S012 is omitted, step S013 may be omitted.

[0067] Next, processor 21 estimates the degree of AC power generation within house H at a future time based on the usage status of the target devices within house H at that future time predicted in step S011 and the approximate expression for the degree of AC power generation identified in the analysis flow described above (S014). Specifically, in step S013, the prediction results for the first hour of air conditioner C, the first hour of television T, and the second hour of microwave oven M are substituted into variables included in corresponding terms of the polynomial forming the approximate expression for the degree of AC power generation. At this time, if the approximate expression was updated in step S013, the prediction results for the first hour and the second hour are substituted into the updated approximate expression.

[0068] Then, processor 21 outputs the degree of interaction within house H estimated in step S014 to the resident of house H (S015). Specifically, processor 21 generates display data regarding the estimated result of the degree of interaction and transmits the display data to resident terminal 12. When resident terminal 12 receives the display data sent from information processing device 10, the display data is expanded. As a result, a screen showing the estimated result of the degree of interaction is displayed on the display of resident terminal 12. By looking at the display, the resident can confirm the estimated result of the degree of interaction within house H at a future time.

[0069] The inference flow ends when the series of processes described above, i.e., steps S011 to S015, are all completed. The inference flow is repeatedly executed every time a resident operates the resident terminal 12 to request execution of the inference flow.

[0070] <<Effectiveness of this embodiment>> As described above, according to this embodiment, the correlation between the usage status of the target devices in the house H and the degree of interaction within the house H is identified, specifically, the correlation between the usage times (i.e., the first and second hours) of the air conditioner C, television T, and microwave oven M and the degree of interaction is identified. As a result, if the usage status of the target devices is identified thereafter, the degree of interaction corresponding to that usage status can be calculated. In this way, according to this embodiment, the degree of interaction at a certain time can be determined from the usage status of the target devices at that time using a relatively simple procedure. In other words, in the past, to understand the degree of interaction (degree of togetherness) in a household, the current degree of interaction was evaluated using a survey or questionnaire, but this method required specialized knowledge to analyze the evaluation results.In contrast, in this embodiment, the degree of interaction can be identified from the usage status of the target device, so that the state of interaction and communication in a household can be understood even without specialized knowledge.

[0071] Furthermore, in this embodiment, the determined degree of interaction is output to the resident of the house H. This allows the resident to check the degree of interaction within the house H and use this as an opportunity to review their behavior within the house H in order to improve the degree of interaction.

[0072] Furthermore, in this embodiment, the usage status of the target devices in the future can be predicted, and the degree of interaction in the future can be estimated based on the predicted usage status. This allows the residents of the house H to understand the estimated result of the degree of interaction in the future. As a result, the residents can get an opportunity to review the content of their activities in the house H, in particular how they spend their time in the house H (more specifically, the rooms they use, the time periods they use, etc.), so that the degree of interaction in the future can be improved.

[0073] Furthermore, in this embodiment, an approximation formula for the degree of interaction is specified as the above correspondence relationship, with the first time and the second time as variables. By using this approximation formula, the degree of interaction within the house H can be more easily determined from the usage times of the air conditioner C, the television T, and the microwave oven M (i.e., the first time and the second time).

[0074] Furthermore, input information regarding the resident's lifestyle within the residence H can be reflected in the approximation formula. Specifically, weights according to the resident's lifestyle are set for each of the first time and the second time, which are variables in the approximation formula. The approximation formula is then specified (derived) as a polynomial including a term obtained by multiplying a first calculated value based on the first time by the weight for the first time, and a term obtained by multiplying a second calculated value based on the second time by the weight for the second time. This makes the approximation formula for the degree of interaction more appropriate because it is specified (derived) based on the resident's lifestyle.

[0075] If the resident's lifestyle within the residence H changes, the weights for the first time and the second time can be changed in accordance with the changed lifestyle. This allows the above approximation formula to be re-specified (updated) in accordance with changes in the resident's lifestyle.

[0076] <<Other embodiments>> Although one embodiment of the information processing device and information processing method of the present invention has been described above, the above embodiment is merely an example for facilitating understanding of the present invention and does not limit the present invention. In other words, the present invention can be modified and improved without departing from the spirit of the present invention. Furthermore, the present invention naturally includes equivalents thereof.

[0077] Furthermore, in the above embodiment, the information processing device 10 is configured by a server computer, but is not limited to the above configuration, and the information processing device of the present invention may also be constructed by a personal computer (PC) or workstation.

[0078] In the above embodiment, the resident terminal 12 is used as an input device for inputting the evaluation result of the degree of interaction within the house H, and is also used as an output device for outputting information from the information processing device 10. However, this is not limited to this, and the input device and the output device may each be configured as separate devices.

[0079] In the above embodiment, the usage times (i.e., the first hour and the second hour) of the first and second electric appliances are identified as the usage status of the target appliances in the house H. However, this is not limited to this, and the usage status of the target appliances may also be identified by identifying the amount of power consumed by each of the first and second electric appliances each day together with or instead of the usage times of the first and second electric appliances each day.

[0080] Furthermore, in the above embodiment, in identifying the correspondence between the first time and the second time and the degree of interaction within the house H, a weight is set for each of the first time and the second time, and each weight is set in advance according to the usage pattern of the house H. Here, the method for setting the weight is not limited to the method in the above embodiment, and other methods may be used. To be more specific, for example, for each of the first and second hours, a correlation between the appropriateness of the amount of time and the degree of interaction within the house H may be identified, and the correlation coefficient (a numerical value in the range of -1 to +1) may be set as the weight. The appropriateness of the amount of time is an index showing the length of the first and second hours, that is, whether the amount of time that family members spend separately within the house H is appropriate, and is evaluated by the residents of the house H. The evaluation results of the appropriateness by the residents can be obtained by inputting them through the resident terminal 12, similar to the evaluation results of the degree of interaction within the house H. As a method for inputting the appropriateness of the amount of time, the appropriateness may be evaluated using a score and the evaluation value may be input, or one of a choice of words expressing the appropriateness (for example, "too much" and "not enough") may be selected and input. In step S004 of the above-described analysis flow, the processor 21 of the server computer constituting the information processing device 10 acquires evaluation results of the appropriateness of the time amounts for the first time and the second time at multiple points in time. Then, the processor 21 identifies the correlation between the appropriateness and the degree of interaction within the house H, and sets weights according to the appropriateness for each of the first time and the second time based on the correlation (more specifically, the correlation coefficient). It should be noted that a known statistical analysis method may be used to identify the correlation and correlation coefficient between the appropriateness of the amount of time for each of the first and second hours and the degree of interaction within the residence H. Furthermore, since the appropriateness of the amount of time for the first and second hours may change depending on changes in the resident's lifestyle within the residence H, it is advisable to obtain the appropriateness in association with the lifestyle at each time point and set a weight according to the appropriateness at each time point.

[0081] Furthermore, in the above embodiment, the daily usage status of the target devices (specifically, the first hour for the first electrical device and the second hour for the second electrical device) is identified, and an evaluation result of the degree of interaction within the home H for each day is obtained. Then, in the above embodiment, the correspondence between the usage status of the target devices and the degree of interaction is identified based on the identification result of the daily usage status of the target devices and the evaluation result of the degree of interaction for each day. That is, in the above embodiment, the correspondence is identified using the daily usage status of the target devices and the evaluation result of the degree of interaction for each day, regardless of the day of the week or the season to which each day belongs. However, this is not limited thereto, and the usage status of the target devices and the evaluation result of the degree of interaction may be classified by day of the week, and the correspondence may be identified for each day of the week using the information classified by day of the week. Alternatively, the usage status of the target devices and the evaluation result of the degree of interaction may be classified by season, and the correspondence may be identified for each season using the information classified by season.

[0082] In the above embodiment, the target devices include first electrical devices such as an air conditioner C and a television T that are installed in multiple rooms, and second electrical devices such as a microwave oven M that is installed in a shared space in the house H, and the usage status of each electrical device is identified. However, the present invention is not limited to this, and the target device may be either the first electrical device or the second electrical device. [Explanation of symbols]

[0083] 10. Information processing equipment 12 Resident terminal 14 Sensor Group 16 Databases 21 processors 22 Memory 23 Storage 24 Communication Interface 100 Communication Support System C. Air Conditioner H. Residential (building) M microwave T TV

Claims

1. An information processing device that includes a processor and analyzes usage status of target devices in a building used by multiple users, the processor: Identifying the usage status at each of a plurality of time periods; acquiring an evaluation result regarding the degree of interaction of the plurality of users in the building for each of the plurality of time periods; An information processing device that identifies a correspondence between the usage status and the degree of interaction based on the identification result of the usage status for each of the plurality of time periods and the evaluation result of the degree of interaction for each of the plurality of time periods.

2. The processor: predicting said usage at a future time; The information processing device according to claim 1 , wherein the degree of interaction in the future time period is estimated based on the predicted usage state in the future time period and the correspondence relationship.

3. When the target devices include first electrical devices installed in each of a plurality of rooms in the building, the processor: identifying, as the usage status, a first time period during which the first electric device was used in two or more rooms among the plurality of rooms in each of the plurality of time periods; The information processing device according to claim 1 , wherein the correlation is determined to be a correlation between the first time period and the degree of interaction.

4. When the target device includes a second electrical device installed in a space in the building shared by the plurality of users, the processor: identifying, as the usage status, a second time period during which the second electrical device was used in the building in each of the plurality of time periods; The information processing device according to claim 1 , wherein the correlation is determined to be a correlation between the second time period and the degree of interaction.

5. When the target devices include a first electrical device installed in each of a plurality of rooms in the building and a second electrical device installed in a space in the building that is shared by the plurality of users, the processor: identifying, as the usage status, a first time period during which the first electric device was used in two or more rooms among the plurality of rooms in each of the plurality of time periods, and a second time period during which the second electric device was used in the building in each of the plurality of time periods; The information processing device according to claim 1 , further comprising: specifying, as the correspondence relationship, an approximation formula of the degree of interaction in which the first time period and the second time period are variables.

6. The processor: Acquire information about the use of the building; setting a weight for each of the first time period and the second time period according to the usage pattern; 6. The information processing device according to claim 5, wherein the approximation formula is a polynomial including a term obtained by multiplying a first calculated value based on the first time by the weight for the first time, and a term obtained by multiplying a second calculated value based on the second time by the weight for the second time.

7. The processor: obtaining an evaluation result of the appropriateness of the first time period and the second time period; setting a weight for each of the first time period and the second time period according to the appropriateness; 6. The information processing device according to claim 5, wherein the approximation formula is a polynomial including a term obtained by multiplying a first calculated value based on the first time by the weight for the first time, and a term obtained by multiplying a second calculated value based on the second time by the weight for the second time.

8. An information processing method for analyzing usage status of target devices in a building used by multiple users, comprising: a processor identifying the usage status at each of a plurality of time periods; a processor acquires an evaluation result regarding the degree of interaction of the plurality of users in the building for each of the plurality of time periods; An information processing method in which a processor identifies a correspondence between the usage status and the degree of interaction based on the results of identifying the usage status for each of the multiple periods and the evaluation results of the degree of interaction for each of the multiple periods.

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