Home appliance control information generation system

Abstract

A home appliance control information generating system is provided that generates control information that enables a home appliance to be operated more optimally in accordance with the environment in which it is installed. [Solution] A home appliance control information generating system 1 that generates control information for home appliances based on operation history information from multiple home appliances has a memory unit that stores acquired data and includes a server 31 that is an information processing unit that processes data. The operation history information includes location information that can identify the area where each of the multiple home appliances is installed, setting information, and power consumption, and the information processing unit acquires weather information for the location area where the multiple home appliances are installed based on the operation history information and location information from the multiple home appliances via a network, classifies the operation history information for the multiple home appliances belonging to the location area into regional operation history information, classifies the regional operation history information into multiple groups based on the magnitude of power consumption, analyzes the regional operation history information belonging to the same group, and outputs control information for the home appliances.

Description

[Technical field]

[0001] The present invention relates to a home appliance control information generating system, and more particularly to a system that classifies and analyzes information received from home appliances via a network by region, and generates information for controlling the home appliances. [Background technology]

[0002] In recent years, the need to improve the comfort of residential environments has been increasing due to the influence of changes in the external environment such as global warming. For example, the role of air conditioners, which are home appliances, in maintaining a comfortable thermal sensation for residents is becoming increasingly important. A comfort index called PMV (Predicted Mean Vote) has been proposed to achieve comfort. An air conditioning control system has been disclosed that monitors the PMV of users in an air-conditioned space and controls the air conditioner.

[0003] As an example of a conventional air conditioner, there is known one that performs control using PMV (Predicted Mean Vote, predicted thermal sensation declaration) as an index. PMV is calculated from a total of six elements consisting of four environmental elements, namely room temperature, radiant temperature, relative humidity, and wind speed, and two human body elements, namely the amount of clothing worn and the amount of activity. PMV is a parameter that indicates the degree of comfort regarding a person's thermal sensation. PMV can range from -3 to +3. PMV is judged according to seven levels of comfort, namely -3 (very cold), -2 (cold), -1 (slightly cold), 0 (neutral), +1 (slightly hot), +2 (hot), and +3 (very hot). In general, when a person feels comfortable, the PMV is -0.5 to +0.5.

[0004] When PMV is used as an index in controlling an air conditioner, the operation of the air conditioner is controlled so as to approach the PMV value when a person feels comfortable, based on the temperature, humidity, airflow (wind speed), and radiant temperature (wall temperature) of the indoor space measured as environmental information of the indoor space, and the behavior and amount of clothing of a target person in the room captured by a camera, etc. (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0005] [Patent Document 1] International Publication No. 2008 / 087959 Summary of the Invention [Problem to be solved by the invention]

[0006] In today's living environments, the insulation performance of tower apartments, detached houses, apartments, etc. can vary greatly, and the temperature and humidity can also vary greatly depending on the region. In this way, there was a problem that if control was based on a single index for air conditioning equipment that can be installed in a variety of environments, the control may not be suited to the environment in which it was installed.

[0007] For example, when PMV is used as in the control of an air conditioner disclosed in Patent Document 1, the thermal environment may be different even if the PMV is in the same numerical range. In other words, the PMV value may be the same for a windless environment at room temperature of 20°C and an environment with air blown at room temperature of 24°C. Therefore, even if the air conditioner is controlled using PMV as an index, it is not possible to clearly determine whether the room temperature should be set low or the wind speed should be increased to make the user in the installed environment comfortable. In other words, the optimal operating state of a home appliance varies depending on the installed environment and the user, and there was a problem that a lot of data was required to determine the optimal operating state.

[0008] An object of the present invention is to provide a home appliance control information generating system that generates control information that enables operation of a home appliance suited to the environment in which the appliance is installed. [Means for solving the problem]

[0009] The home appliance control information generation system of the present invention is a home appliance control information generation system that generates control information for home appliances based on operation history information from a plurality of home appliances, and is equipped with a memory unit that stores acquired data and an information processing unit that processes the data, and the operation history information includes location information that can identify the area in which each of the plurality of home appliances is installed, setting information, and power consumption. The information processing unit acquires location area weather information, which is weather information for the location area in which the plurality of home appliances are installed, based on the operation history information and the location information from the plurality of home appliances via a network, classifies the operation history information for the plurality of home appliances belonging to the location area into regional operation history information, classifies the regional operation history information into a plurality of groups based on the magnitude of the power consumption, analyzes the regional operation history information belonging to the same group among the plurality of groups, and outputs control information for the home appliances. Effect of the Invention

[0010] According to the above means, the home appliance control information generation system can collect operation history information from multiple home appliances, classify it by region, and analyze the data to extract operation history information that is suitable for the environment in which the appliances are installed in a particular region. [Brief description of the drawings]

[0011] [Figure 1] 1 is an explanatory diagram illustrating an example of a configuration of hardware included in a home appliance control information generation system 1 according to a first embodiment. [Diagram 2] 1 is a hardware configuration diagram of a probe device 11 according to the first embodiment. [Diagram 3] 2 is a hardware configuration diagram of a server 31 according to the first embodiment. FIG. [Figure 4] 2 is an explanatory diagram showing an example of information exchange between devices in the home appliance control information generation system 1 according to the first embodiment. FIG. [Diagram 5] 4 is an explanatory diagram showing an example of a data set transmitted from the probe device 11 to the server 31 according to the first embodiment. FIG. [Figure 6] 1 is an example of history comparison information displayed on the mobile terminal 21 according to the first embodiment. [Figure 7] 1 is a block diagram for illustrating an overview of functions of a home appliance control information generation system 1 according to a first embodiment. [Figure 8] 2 is a block diagram for explaining the flow of information processed in the home appliance control information generation system 1 according to the first embodiment. FIG. [Figure 9] 10 is a flowchart showing a process in which the server 31 of the home appliance control information generation system 1 according to the first embodiment stores the registration data R. [Figure 10] 13 is an example of a flowchart in which the server 31 of the home appliance control information generation system 1 according to the first embodiment classifies and analyzes the registration data R based on the power consumption amount Wv. [Figure 11] 13 is an example of two data sets included in registered data R in one group classified in the server 31 based on the power consumption Wv. [Figure 12] 13 is another example of a flowchart in which the server 31 of the home appliance control information generation system 1 according to the first embodiment classifies and analyzes the registration data R based on the power consumption amount Wv. [Figure 13] 3 is an explanatory diagram of an example of functions of an analysis unit 31d and a control information generation unit 31e of the server 31 according to the first embodiment. FIG. [Figure 14] 5 is a flowchart of an example of control of an air conditioner using control information generated by the server 31 according to the first embodiment. [Figure 15] 4 is a flowchart showing an example of generation of home appliance control information by the home appliance control information generation system 100 according to the first embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Preferred embodiments of the home appliance control information generating system of the present invention are described in detail below with reference to the drawings. Note that the embodiments described below are preferred specific examples of the present invention, and therefore various technically preferable limitations are attached, but the scope of the present invention is not limited to these aspects unless otherwise specified in the following description to the effect that the present invention is limited.

[0013] Embodiment 1 <System configuration> FIG. 1 is an explanatory diagram showing an example of a hardware configuration included in the home appliance control information generation system 1 according to the first embodiment. As shown in FIG. 1, the home appliance control information generation system 1 according to the first embodiment includes probe devices 11 and 12, a mobile terminal 21, and a server 31 (information processing unit). The probe device 11 is built in an air conditioner 41 (electrical appliance) installed in a house 1a. A remote control 51 for the air conditioner 41 and an in-home router 52 are arranged in the house 1a. In the first embodiment, an air conditioning device such as the air conditioner 41 installed in the house will be described as an example, but targets from which data is collected by the probe devices 11 and 12 and the mobile terminal 21 include general home appliances whose operation is affected by temperature, such as a refrigerator.

[0014] The operation of the probe device 12 will be described later. The home appliance control information generation system 1 may include multiple probe devices that are different from the probe devices 11 and 12 shown in FIG. 1 and have similar functions to the probe devices 11 and 12. In addition, the home appliance control information generation system 1 may include only one of the probe devices 11 and 12. The network 30 shown in FIG. 1 is the so-called Internet in which various public networks are interconnected. The server 31 and the home router 52 are connected to the network 30.

[0015] The air conditioner 41 is a home room air conditioner (air conditioning device) equipped with a heat pump unit (not shown). An outdoor unit constituting a part of the heat pump unit of the air conditioner 41 is omitted from the illustration. Power is supplied to the air conditioner 41 via a power line Cp (outlet cable) connected to an outlet (not shown) arranged in the house 1a.

[0016] A user can operate the air conditioner 41 using a remote control 51. Specifically, the remote control 51 includes, for example, an infrared emitting unit (not shown), and the air conditioner 41 includes an infrared receiving unit 43. The remote control 51 transmits an infrared signal from the infrared emitting unit in response to operation by the user. The air conditioner 41 operates in response to the infrared signal received by the infrared receiving unit 43. For example, the user can set (input) the set temperature Ts [°C] of the air conditioner 41 by operating the remote control 51.

[0017] FIG. 2 is a hardware configuration diagram of the probe device 11 according to the first embodiment. The probe device 11 can use a well-known small computer (microcomputer), and includes a CPU 61, a ROM 62, a RAM 63, a data communication unit 64, an input / output unit 65, a power meter 66, and a room temperature meter 67 as shown in FIG. 2. The CPU 61 sequentially executes a predetermined program (routine) to read data, perform numerical calculations, and output the calculation results. The ROM 62 stores the programs executed by the CPU 61 and maps (lookup tables) referenced by the CPU 61. A part or the whole of the ROM 62 may be configured by a flash memory capable of changing the stored data. The RAM 63 temporarily stores the data referenced by the CPU 61.

[0018] The data communication unit 64 provides a terminal (child device) function that complies with the Wi-Fi (registered trademark) or Bluetooth (registered trademark) standards. The data communication unit 64 controls data communication (reception and transmission of data) with various nodes including the server 31 via the home router 52 and the network 30. The input / output unit 65 performs input / output (I / O) of data with a control device (not shown) of the air conditioner 41.

[0019] The power meter 66 is installed on the power line Cp and detects the power consumption Wa [W] consumed by the air conditioner 41. The room temperature meter 67 detects the room temperature Tr [°C], which is the temperature of the air flowing into the air conditioner 41 (i.e., the temperature of the room in which the air conditioner 41 is installed). The light emitting device 68 is a light emitting diode element, and is disposed on the front side of the housing of the air conditioner 41 in a position visible to the user (see FIG. 1). The CPU 61 can control the lighting state of the light emitting device 68 (see FIG. 1) disposed on the air conditioner 41. Furthermore, the CPU 61 acquires the operating state of the air conditioner 41, including the set temperature Ts, via the input / output unit 65.

[0020] The home router 52 provides a base station (parent device) function that complies with the WiFi standard. For example, the probe device 11 and the mobile terminal 21 can use the base station function of the home router 52 and communicate with the server 31 (data communication based on the TCP / IPv4 standard in this embodiment) via the network 30. The data communication unit 64 communicates with the server 31 via the home router 52.

[0021] FIG. 3 is a hardware configuration diagram of the server 31 according to the first embodiment. The probe device 11 is a well-known small computer (microcomputer), and includes a CPU 71, a ROM 72, a RAM 73, a data communication unit 74, an input / output unit 65, and a storage device 75, as shown in FIG. 3. The CPU 71 sequentially executes a predetermined program (routine) to read data, perform numerical calculations, and output the calculation results. The ROM 72 stores the programs executed by the CPU 71 and maps (lookup tables) referenced by the CPU 71. A part or the whole of the ROM 72 may be configured by a flash memory capable of changing the stored data. The RAM 73 temporarily stores the data referenced by the CPU 71.

[0022] The data communication unit 74 receives meteorological observation data and the like from the probe device 11 via the network 30. The data acquired by the data communication unit 74 is processed by the CPU 71 or the like as necessary and stored in the storage device 75.

[0023] The storage device 75 is, for example, a non-volatile semiconductor memory such as a flash memory, an EPROM (Erasable Programmable ROM), an EEPROM (Electrically Erasable Programmable ROM), or an HDD (Hard disk drive), and serves as a so-called secondary storage device. In the first embodiment, the storage device 75 may be installed in a terminal, or may be a server connected via a network 90. ​​Note that the storage device 75 is not necessarily installed in the terminal, but may be installed on the network 30 so as to be able to communicate with the network 30, and the storage device may also include the network 30.

[0024] (Transmission of driving history information S) FIG. 4 is an explanatory diagram showing an example of information exchange of each device of the home appliance control information generating system 1 according to the first embodiment. FIG. 5 is an explanatory diagram showing an example of a data set transmitted from the probe device 11 according to the first embodiment to the server 31. As shown in FIG. 4(a), the probe device 11 transmits "operation history information S" to the server 31 via the home router 52 and the network 30 every time a predetermined transmission interval Ti elapses. In this embodiment, the operation history information S is transmitted from the probe device 11 to the server 31 using the POST method of the HTTP request. As shown in FIG. 4, the operation history information S includes identification information Id, the number of data Nd, an acquisition interval Tw, and a plurality of data sets Sa. The data set Sa is a combination of the power consumption amount Wv [Wh], the room temperature Tr, and the set temperature Ts. The probe device 11 acquires the data set Sa every time a predetermined acquisition interval Tw shorter than the transmission interval Ti elapses.

[0025] The identification information Id is a unique identifier (character string or numerical value) previously assigned to the probe device 11. The number of data Nd is the number of data sets Sa included in the operation history information S. In this embodiment, the transmission interval Ti is, for example, 30 minutes, and the acquisition interval Tw at which the probe device 11 acquires data from the air conditioner 41 in the house is 1 minute (=60 seconds). Therefore, the number of data Nd is "30". Note that each of the transmission interval Ti and the acquisition interval Tw can be changed as appropriate.

[0026] The probe device 11 acquires an integrated value of the power consumption Wa repeatedly acquired by the power meter 66 during the acquisition interval Tw (i.e., a value equivalent to a value obtained by integrating the power consumption Wa with respect to time, a power correlation amount) as the power consumption Wv for the acquisition interval Tw. In addition, the probe device 11 acquires the power consumption Wv, the room temperature Tr (detected by the room temperature meter 67) at the time when the power consumption Wv is acquired, and the set temperature Ts (acquired via the input / output unit 65) as a data set Sa.

[0027] Furthermore, when the number of data sets Sa equal to the number of data Nd is acquired (i.e., when the transmission interval Ti has elapsed), the probe device 11 transmits the data set Sa as the operation history information S to the server 31. Note that the indoor temperature Tr and the set temperature Ts included in the data set Sa may be the average values ​​of the indoor temperature Tr and the set temperature Ts repeatedly acquired during the acquisition interval Tw, respectively.

[0028] When the server 31 receives the operation history information S from the air conditioner 41 (specifically, the probe device 11), it acquires model information Mc, location area Lc, and outside temperature Te of the air conditioner 41, which will be described later. The server 31 stores the identification information Id included in the operation history information S, as well as the multiple power consumption amounts Wv, room temperatures Tr, and set temperatures Ts, together with the location area Lc, model information Mc, outside temperature Te, and time information Ta, in the storage device 75 as registration data R (see FIG. 8).

[0029] The model information Mc is an identifier representing the model (model information) of the air conditioner 41. The model information Mc of the air conditioner 41 is assigned in advance to each combination of a manufacturer (manufacturing company) and a model number assigned by the manufacturer. The server 31 stores the correspondence between the previously acquired identification information Id and the model information Mc in the storage device 75 as a "model DB". The server 31 acquires the model information Mc by applying the identification information Id of the operation history information S to the model DB.

[0030] In this embodiment, the location area Lc is an identifier representing an area divided by each of the observation stations of the "Regional Meteorological Observation System" (AMeDAS) installed by the Japan Meteorological Agency. The server 31 acquires the area (in this embodiment, a city, town, or village in Japan) in which the air conditioner 41 is installed based on the source address of the operation history information S (i.e., an IP address conforming to the IPv4 standard).

[0031] The outside air temperature Te in this embodiment is the air temperature observed at each of the observation stations published by the Japan Meteorological Agency. The server 31 stores in the storage device 75 the air temperature observed by the observation station corresponding to the location region Lc during the period during which the power consumption Wv included in the received operation history information S was obtained, as the outside air temperature Te. Note that if the outside air temperature Te has already been obtained for the observation station and period when the operation history information S is received from an air conditioner other than the air conditioner 41, the server 31 does not obtain new air temperature information from the Japan Meteorological Agency. Note that the server 31 may obtain the outside air temperature Te from the Japan Meteorological Agency when generating the history comparison information described later.

[0032] More specifically, the server 31 stores the previously acquired correspondence between IP addresses and municipalities as a "location DB" in the storage device 75. The server 31 acquires the location of the air conditioner 41 by applying the source IP address of the operation history information S to the location DB. That is, the server 31 acquires the location of the air conditioner 41 using well-known GeoIP technology. Next, the air conditioner 41 acquires an identifier representing the observation station closest to the acquired location as the location area Lc of the air conditioner 41. Note that the location information identifying the location is not limited to an IP address, and other information may be used.

[0033] The time information Ta indicates the time when information related to the data set Sa was acquired (specifically, the start of the acquisition interval Tw). The server 31 acquires (by calculating backwards) each piece of time information Ta (UNIX (registered trademark) time in Coordinated Universal Time (UTC) in this embodiment) of the data set Sa based on the time when the driving history information S was received and the acquisition interval Tw included in the driving history information S, and stores the information in the storage device 75.

[0034] (View historical comparison information) Fig. 6 is an example of history comparison information displayed on the mobile terminal 21 according to the first embodiment. When the user accesses the server 31 using the web browser of the mobile terminal 21 and performs a predetermined operation, the mobile terminal 21 transmits a "comparison information request" (specifically, an HTTP request) to the server 31, as shown in the upper part of Fig. 4. The comparison information request includes the identification information Id and a "comparison time period" specified by the user. The comparison time period is, for example, a period from a point six hours before the present time to the present time (as an example, the period from 3 pm to 9 pm on that day).

[0035] When the server 31 receives the comparison information request, it generates "history comparison information" and transmits it to the mobile terminal 21 as a response to the comparison information request (see the upper side of FIG. 4). The history comparison information received from the server 31 can also be displayed on the display 21a of the mobile terminal 21. For example, the mobile terminal 21 may display it using a Web browser.

[0036] The solid line L1 in Fig. 6 generally shows the change in the power consumption Wv of the air conditioner 41 in each of the comparison periods Pm obtained by dividing the comparison time zone at every predetermined comparison time Tc (that is, the length is equal to the comparison time Tc). Each of the solid lines L2 and L3 generally shows the change in the maximum value and the minimum value of the power consumption Wv related to the "similar products" and satisfying the "approximate conditions" (the first approximate condition) in each of the comparison periods Pm.

[0037] In this embodiment, the comparison time Tc is 10 minutes. As an example, the comparison period Pm is the period from 15:00 to 15:10 on the same day. The similar products are other air conditioners with the same model information Mc and location area Lc as the air conditioner 41 (that is, the air conditioner corresponding to the comparison information request, also referred to as the "specific product"). The approximate condition is a condition that holds when the operating status in the comparison period Pm is similar to that of the air conditioner 41.

[0038] More specifically, for the power history information of the similar products stored in the storage device 75, if the magnitude of the difference between each of the indoor temperature Tr, the set temperature Ts, and the outside air temperature Te related to the air conditioner 41 in the comparison period Pm (or at the start or end of the comparison period Pm) is smaller than a predetermined temperature threshold Th1, then the power history information satisfies the approximate condition.

[0039] In other words, if |Tr1 - Tr2| < Th1, |Ts1 - Ts2| < Th1, and |Te1 - Te2| < Th1, the approximate condition holds. Here, each of the indoor temperature Tr1, the set temperature Ts1, and the outside air temperature Te1 is the indoor temperature Tr, the set temperature Ts, and the outside air temperature Te related to the air conditioner 41. In addition, each of the indoor temperature Tr2, the set temperature Ts2, and the outside air temperature Te2 is the indoor temperature Tr, the set temperature Ts, and the outside air temperature Te related to the similar product. The fact that the magnitude of the difference between any of these temperatures related to the air conditioner 41 and the corresponding temperature related to the similar product is smaller than the temperature threshold Th1 is hereinafter simply referred to as (the temperature is) "approximate".

[0040] The server 31 extracts the power consumption Wv related to the power history information (specifically, the combination of the room temperature Tr, the set temperature Ts, and the outside temperature Te) related to the similar product and satisfying the similarity condition as the "comparison power correlation amount". In addition, the server 31 extracts the minimum and maximum values ​​from the (plurality of) comparison power correlation amounts (i.e., the power consumption Wv) extracted in a certain comparison period Pm. The server 31 executes a process of extracting the minimum and maximum values ​​of the comparison power correlation amount for each comparison period Pm included in the comparison time zone, and generates history comparison information.

[0041] For example, since the air conditioner 41 and the similar product are located in the same area Lc where the outdoor air temperature Te is acquired (observed), the outdoor air temperature Te related to the power history information of the air conditioner 41 in a certain comparison period Pm is equal to the outdoor air temperature Te related to the power history information of the similar product in that comparison period Pm. In other words, the outdoor air temperatures Te are close to each other. Furthermore, if the indoor temperature Tr and the set temperature Ts related to the similar product acquired in that comparison period Pm are close to the indoor temperature Tr and the set temperature Ts related to the air conditioner 41, respectively, the approximation condition is met.

[0042] On the other hand, even if the power history information is related to the power consumption Wv of a similar product acquired at a time other than the comparison period Pm, the outdoor temperature Te of the power history information may be approximate to the outdoor temperature Te of the power history information related to the power consumption Wv of the air conditioner 41 acquired during the comparison period Pm. In this case, if the room temperature Tr and the set temperature Ts are also approximate to each other, the approximation condition is met. In other words, the power consumption Wv of a similar product acquired at a time other than the comparison period Pm may be extracted as the comparison power correlation amount.

[0043] In this embodiment, the model information Mc is also referred to as "product attribute" for convenience. In other words, air conditioners with the same model information Mc have the same product attributes. In this embodiment, the temperature threshold Th1 is 1.5°C. However, the above-mentioned comparison time Tc and temperature threshold Th1 may each be changed as appropriate so as to clarify the difference in power consumption Wv (power correlation amount) between a specific product (i.e., an air conditioner corresponding to a comparison information request) and a similar product. For example, the temperature threshold Th1 may be set to a different value (temperature) for each of the room temperature Tr, the set temperature Ts, and the outdoor temperature Te.

[0044] (Distribution of notification information) As described above, the server 31 receives the operation history information S from the probe device 11 every time the transmission interval Ti elapses. When there is information to be notified to a user of the air conditioner 41 incorporating the probe device 11, the server 31 transmits "notification information" to the probe device 11 as a response to receiving the operation history information S, as shown in FIG. 4(a). In this embodiment, the notification information is transmitted from the server 31 to the probe device 11 as a response (HTTP response) to the HTTP request transmitted as the operation history information S. That is, the server 31 transmits the notification information to the probe device 11 via the TCP connection established for transmitting the operation history information S.

[0045] The notification information is issued, for example, by a person in charge at the manufacturer of the air conditioner 41 inputting model information Mc, which is the subject of the notification, to the server 31 as a "notification request" in a predetermined procedure. The notification request is input to the server 31, for example, by an HTTP request transmitted to the server 31. Alternatively, the notification request may be input by a maintenance person to a terminal of the server 31.

[0046] When the probe device 11 receives the notification information, it turns on the light-emitting device 68 of the air conditioner 41. A user who notices that the light-emitting device 68 is turned on can check detailed information, for example, by accessing the website of the manufacturer of the air conditioner 41. The notification information includes a predetermined reason code (numeric value), and the probe device 11 and the air conditioner 41 may be configured so that when the probe device 11 receives the notification information including the reason code, it plays a sound corresponding to the reason code on a speaker (not shown) built into the air conditioner 41.

[0047] As shown in FIG. 4(b), the driving history information S may be transmitted from the mobile terminal 21 (instead of the probe device 11) to the server 31. In this case, the probe device 11 and the mobile terminal 21 communicate with each other in accordance with the WiFi or Bluetooth standard. Specifically, the probe device 11 acquires and stores a data set Sa every time an acquisition interval Tw elapses. Meanwhile, the mobile terminal 21 transmits a "driving history information request" to the probe device 11 at a timing of the user's choice.

[0048] When the probe device 11 receives the driving history information request, it transmits a "driving history information response" to the mobile terminal 21. The driving history information response includes (a plurality of) data sets Sa acquired since the probe device 11 last received a driving history information request up to the present time. When the mobile terminal 21 receives the driving history information response, it transmits the driving history information S including the data sets Sa received from the probe device 11 to the server 31. When transmitting the driving history information S from the mobile terminal 21 to the server 31, the probe device 11 continues to hold the driving history information S for a certain period of time until it receives a history information acquisition request from the mobile terminal 21, but when the upper limit of the capacity to be held is reached, the oldest history is overwritten.

[0049] When a notification request related to the model information Mc of the air conditioner 41 is input, the server 31 transmits (responds) notification information to the mobile terminal when it receives the operation history information S from the mobile terminal 21. In this case, the mobile terminal 21 notifies the user that it has received the notification information. Alternatively, when a comparison information request is received before the operation history information S is received from the mobile terminal 21 after the notification request is input, the server 31 transmits the notification information together with the history comparison information.

[0050] (External probe device) Next, the operation of the probe device 12 will be described, focusing on the differences from the built-in probe device 11 described above. As shown in Fig. 1, the probe device 12 is disposed in a location where there is little temperature error with an air conditioner 42 installed in a house 1b. The probe device 12 is inserted into the power line Cp of the air conditioner 42. The probe device 12 and the air conditioner 42 are operated by power supplied from the power line Cp.

[0051] The probe device 12 is a well-known small computer like the probe device 11, and includes a CPU 61, a ROM 62, a RAM 63, and a light-emitting device 69 (see FIG. 1). The probe device 12 has a built-in power meter (not shown) that is disposed on the power line Cp and detects the power consumption Wa of the air conditioner 42. In addition, the probe device 12 has a built-in room temperature meter (not shown) that detects the temperature of the room in which the air conditioner 42 is installed as an indoor temperature Tr.

[0052] Since the probe device 12 cannot directly obtain the set temperature Ts, it sets an unrealistic value (e.g., 256°C) to the set temperature Ts included in the data set Sa. In this case, the server 31 estimates the actual set temperature Ts. Specifically, when the server 31 determines that a state (minimum power state) in which the power consumption Wa of the air conditioner 42 is close to the minimum value during operation has continued for a predetermined time based on the power consumption Wv included in the received data set Sa, it obtains (estimates) the room temperature Tr at that time as the set temperature Ts. For example, the server 31 treats the room temperature Tr when the minimum power state has continued for a predetermined time or more as the set temperature Ts for the period from when the power consumption Wa increases after the previous minimum power state has occurred until the minimum power state occurs again and continues for a predetermined time or more.

[0053] The probe device 12 transmits the driving history information S to the server 31 via the home router 52 installed in the house 1b and the network 30 at every transmission interval Ti. Naturally, the identification information Id given to the probe device 12 is different from the identification information Id of the probe device 11.

[0054] When the probe device 12 receives the notification information from the server 31, it lights up the light emitting device 69. In addition, similar to the example of the house 1a described above, when the user operates the mobile terminal 21 in the house 1b to transmit a comparison information request to the server 31, the server 31 transmits historical comparison information to the mobile terminal 21. As a result, a graph related to the historical comparison information (see the example in FIG. 6) is displayed on the display 21a.

[0055] (Modification of Transmission of Driving History Information S) A modified example (first modified example) of the first embodiment will be described. In the first embodiment described above, the server 31 extracted the power consumption Wv related to the power history information related to a similar product and satisfying the first approximation condition as the comparative power correlation amount. The similar product in the first embodiment was an air conditioner (other than the specific product) that has the same model information Mc and location area Lc as the specific product. In contrast, the similar product in the first modified example is an air conditioner (other than the specific product) that has the same "product group" and location area Lc as the specific product. The following description will focus on this difference.

[0056] The server 31 according to the first modified example stores a collection of model information Mc belonging to each of a plurality of product groups in the storage device 75 as a "product group DB." That is, when certain model information Mc is applied to the product group DB, a plurality of pieces of model information Mc included in the product group to which the model information Mc belongs is obtained. Each product group according to this modified example is a collection of model information Mc of air conditioners whose annual energy efficiency (APF) and usage environment guidelines (specifically, the size of the room in which it is used, expressed by, for example, the number of tatami mats in a Japanese-style room or the floor area of ​​a Western-style room) published by the manufacturer are similar to each other.

[0057] In other words, a product group is a collection of model information Mc of air conditioners whose power consumption Wa is likely to be similar to that of a specific product (e.g., air conditioner 41) when used in a similar manner. In this modified example, the product group also includes air conditioners whose model information Mc is the same as that of the specific product, but model information Mc that is the same as that of the specific product may be omitted. In this modified example, the product group is also referred to as "product attributes" for convenience. In other words, air conditioners included in the same product group have the same product attributes.

[0058] When the server 31 receives the comparison information request, the server 31 acquires model information Mc by applying the identification information Id included in the comparison information request to the model DB. In addition, the server 31 acquires the product group related to the comparison information request (i.e., a set of model information Mc corresponding to similar products in this modified example) by applying the model information Mc related to the comparison information request to the product group DB. Furthermore, the server 31 extracts the power consumption Wv (i.e., the comparison power correlation amount) related to the power history information related to the similar products and satisfying the first approximation condition. Next, the server 31 executes a process of extracting the minimum and maximum values ​​from the extracted comparison power correlation amounts for each comparison period Pm, and generates history comparison information.

[0059] (Data analysis using collected information) Fig. 7 is a block diagram for explaining an outline of the functions of the home appliance control information generation system 1 according to the embodiment 1. Fig. 8 is a block diagram for explaining the flow of information processed in the home appliance control information generation system 1 according to the embodiment 1. The server 31 is a device that not only collects information from the probe devices 11 and 12 or the mobile terminal 22 described above, but also processes the collected information and generates information for controlling air conditioning devices such as the air conditioners 41 and 42.

[0060] Usually, the air conditioners 41 and 42 are preset with respect to how to control the operation when the set temperature Ts is set for each product, or how to control the indoor temperature Tr, wind power, etc., in order to make the indoor condition comfortable when the automatic operation mode is selected. These controls are usually set individually according to the model of the air conditioners 41 and 42, for example, according to a comfort index such as PMV. However, the environments in which air conditioners such as the air conditioners 41 and 42 are installed are various. For example, since the climate differs from region to region even in Japan, the outdoor temperature Te and outdoor humidity Tf differ, and the clothes worn by the user indoors also differ. In addition, since the structure of the building in which the air conditioners are installed also differs, the comfort felt by the user differs depending on these factors. Therefore, the operation according to the control information preset in the air conditioners 41 and 42 may be comfortable in one region, but not comfortable in another region. The home appliance control information generating system 1 according to the first embodiment obtains operation history information S from a large number of air conditioners using a probe device 11 or the like, and analyzes the information to determine the optimal operating conditions for the air conditioners in a certain region.

[0061] The server 31 can determine in which area the probe devices 11, 12 and the mobile terminal 21 are located based on the source address (IP address) of the driving history information S, and can therefore obtain the area in which the air conditioners 41, 42, etc. are installed. Therefore, even if the server 31 obtains driving history information S from anywhere in the country, it can determine which location area Lc the driving history information S belongs to.

[0062] In addition, the server 31 can collect data from meteorological observation stations Wo in each region. Therefore, once it is determined which location region Lc the driving history information S belongs to, for example, the meteorological observation station Wo closest to the location region Lc can be selected, and the driving history information S can be associated with information such as the outside air temperature Te and the outside air humidity Tf published by the meteorological observation station Wo as a reference value. Note that the meteorological information of the meteorological observation station Wo in a certain location region Lc used to classify the driving history information S may be called "location region meteorological information." In addition, since the data published by the meteorological observation station Wo also includes information such as the altitude of the location, for example, if the altitude of the region where the air conditioners 41, 42, etc. are actually installed is different from the altitude of the meteorological observation station Wo, the reference values ​​of the outside air temperature Te and the outside air humidity Tf can be corrected according to the difference in altitude before being associated with the driving history information S.

[0063] 8, the acquired driving history information S is stored in the storage unit 31b in association with other information by the information processing unit 31a. The driving history information S is stored in the storage unit 31b as registered data R in association with, for example, time information Ta at the time of information acquisition detected by the timing unit 31c and weather information obtained from a weather observation station Wo. The server 31 stores the registered data R in the following procedure.

[0064] Fig. 9 is a flowchart showing a process in which the server 31 of the home appliance control information generation system 1 according to the first embodiment stores the registration data R. As shown in Fig. 7, the server 31 acquires driving history information S (data set Sa) from a plurality of location areas Lc via the network 30. At that time, the server 31 identifies the location area Lc from the IP address of the probe device (step A1).

[0065] Next, the server 31 identifies the weather observation station Wo closest to the location area Lc, and associates it with the driving history information S (step A2).

[0066] Next, the server 31 acquires meteorological information from the corresponding weather observation station Wo. The meteorological information includes, for example, the outside air temperature Te, the outside air humidity Tf, and the altitude. The server 31 extracts data from the meteorological information as necessary and associates it with the operation history information S as a reference value (step A3). The reference value is meteorological information that serves as the basis for the operation history information S in the location area Lc, and can also be used to classify data collected from a large number of air conditioning devices based on the reference value.

[0067] Next, the server 31 associates the driving history information S with the reference value and stores it in the storage unit 31b as registered data R (step A4). The driving history information S and the reference value are also associated with time information. Since the driving history information S is a set of multiple data sets (e.g., 30 data sets) collected by the probe device 11 for a certain period of time and transmitted collectively, the time when the driving history information S was collected by the probe device 11 may be estimated from the number of data sets Sa included in the multiple data sets Sa based on the time information given by the timer unit 31c at the time of acquisition and given to each data set Sa. The weather information is data released by the meteorological observation station Wo every 10 minutes, for example, and the data with the time information closest to the time information given to each data set Sa is associated with the data set Sa and stored in the storage unit 31b.

[0068] The server 31 analyzes the acquired registered data R and derives control information (operating conditions) for the air conditioner suitable for the location area Lc. The server 31 classifies the registered data R based on the power consumption Wv among the operating conditions of the air conditioner, and derives optimal control information from the classified registered data R. Specifically, the server 31 derives an optimal combination of environmental information, including the indoor temperature and indoor humidity of the environment in which the air conditioner is installed, and weather information, which are included in the registered data R, and control information, including the power consumption of the air conditioner and the outputs of the compressor, outdoor blower, and indoor blower. The procedure by which the server 31 classifies the registered data R based on the power consumption Wv is described below.

[0069] Specifically, the server 31 extracts region-specific operation history information Sr based on the location area Lc from the operation history information S included in the registration data R, and further extracts power consumption-specific operation history information from the region-specific operation history information Sr based on the power consumption Wv. The server 31 derives air conditioner control information that is optimal for environmental information and weather information from the extracted multiple pieces of power consumption-specific operation history information and their associated reference values ​​(data from a weather observation station).

[0070] 10 is an example of a flowchart in which the server 31 of the home appliance control information generation system 1 according to the embodiment 1 classifies and analyzes the registration data R based on the power consumption Wv. First, the server 31 extracts the maximum and minimum values ​​of the power consumption Wv from the registration data R of multiple air conditioners belonging to the same location region Lc (step B1).

[0071] From the extracted power consumption Wv, the server 31 obtains the difference ΔWv between the maximum and minimum values ​​of the power consumption Wv (step B2). Depending on the magnitude of the difference ΔWv, the server 31 creates multiple groups for classifying the power consumption Wv (step B3). For example, if the maximum value of the power consumption Wv is 10 kWh and the minimum value is 0 kWh, the server 31 creates 10 groups in which the power consumption Wv is greater than or equal to 0 kWh and less than 1 kWh, greater than or equal to 1 kWh and less than 2 kWh, ..., and greater than or equal to 9 kWh and less than 1 kWh. The number of multiple groups is not limited, and if the maximum value is 5 kWh and the minimum value is 0 kWh, the number of groups may be five or fewer.

[0072] Next, the server 31 analyzes the registered data R for each group (step B5). Since each group classifies the registered data R based on the power consumption Wv, for example, the registered data R included in the same group includes the transitions of the set temperature Ts and power consumption Wa, the indoor temperature Tr, and the outdoor temperature Te within a predetermined time period of multiple air conditioners operated at approximately the same output. From the registered data R classified based on the power consumption Wv, the server 31 extracts a combination of the set temperature Ts and power consumption Wa that is considered optimal. The extracted set temperature Ts and power consumption Wa are also associated with the indoor temperature Tr and outdoor temperature Te at that time, and are stored in the memory unit 31b as the optimal operating state under certain environmental information (indoor temperature Tr) and meteorological information (outdoor temperature Te). The server 31 derives control information for the air conditioner from the optimal operating state stored in the memory unit 31b.

[0073] In this manner, the server 31 classifies the registered data R based on the power consumption Wv, analyzes it, and derives optimal control information for the air conditioner. As an example, the derivation of the control information is performed based on the degree to which the setting information for the air conditioner changes within a specified period of time. An example of the derivation of the control information in the server 31 is described below.

[0074] Fig. 11 shows an example of two data sets included in the registered data R of a certain group classified in the server 31 based on the power consumption Wv. The data set shown in Fig. 11(a) is called data set S1, and the data set shown in Fig. 11(b) is called data set S2. Data sets S1 and S2 are temporal changes in the outdoor temperature Te, indoor temperature Tr, set temperature Ts, and power consumption Wa for a certain period in the same time zone. In Figs. 11(a) and (b), the horizontal axis represents time t, and the vertical axis represents temperature T [°C] and power W [W].

[0075] Although the data sets S1 and S2 differ in the way that power consumption fluctuates, they have approximately the same power consumption during the time period shown in Fig. 11. In addition, since the data sets S1 and S2 belong to the same location region Lc, the outdoor temperature Te is also the same. In Fig. 11, the air conditioner is in cooling operation.

[0076] Data set S1 shows a case where the initial set temperature Ts is set high, but the user lowers the set temperature Ts because the indoor temperature Tr is high. When the user lowers the set temperature Ts, the air conditioner increases its output, gradually causing the indoor temperature Tr to drop. When the indoor temperature Tr drops to the set temperature Ts, the air conditioner reduces its output. Then, the indoor temperature Tr rises. When the indoor temperature Tr exceeds the set temperature Ts by a specified temperature, the air conditioner increases its output again. Similar control is subsequently repeated in data set S1.

[0077] Like dataset S1, dataset S2 also shows a case where the initial set temperature Ts is set high, but the user lowers the set temperature Ts because the indoor temperature Tr is high. When the user lowers the set temperature Ts, the air conditioner increases its output, and the indoor temperature Tr gradually drops. At this point, the user feels that the indoor temperature Tr has dropped too low, so he raises the set temperature Ts, and the air conditioner also lowers its output. After a while, when the indoor temperature Tr rises, the user again lowers the set temperature, and the air conditioner increases its output. Thereafter, the user repeats the same actions, and the air conditioner also changes its output accordingly.

[0078] 11 are included in the groups classified by the magnitude of power consumption Wv, the server 31 extracts those with less frequent changes to the air conditioner settings in the analysis unit 31d, and derives optimal control information from the operation history information of those in the control information generation unit 31e. In other words, when there are data sets S1 and S2, the server 31 determines that data set S1, which has less fluctuation in the set temperature Ts, is the more ideal operating state, and derives control information from the operating state of data set S1.

[0079] Since the data set S1 indicates at least the relationship between the passage of time and the power consumption Wa, the server 31, for example, obtains the power consumption Wv for a predetermined time t1 shown in Fig. 11(a) and creates control information so that the air conditioner operates to achieve this power consumption Wv when it operates for the predetermined time t1. Alternatively, the server 31 may use the operating state according to the change in the power consumption Wa for the predetermined time t1 shown in Fig. 11(a) as the control information.

[0080] 11, the setting information for the air conditioner only shows the set temperature Ts, but it may also include other information such as wind power, wind direction, changes in operation mode, etc. If the setting information includes information such as wind power, these may also be included in the evaluation of the change frequency.

[0081] As described above, the process by which the server 31 derives the control information has been described using the example shown in Fig. 11. In reality, however, the registered data R includes many data sets, from which setting change frequency information is extracted, and the registered data R is classified based on the setting change frequency information. For example, a data set with a change frequency equal to or less than a predetermined frequency is extracted from the registered data R as low change frequency operation history information, assuming that the data represents a more ideal operating state, and the control information is derived based on the operating state of the air conditioner included in the low change frequency operation history information. When deriving the control information, the average outputs of the compressor, outdoor fan, and indoor fan may be obtained based on the average power consumption included in the extracted operating state of the air conditioner, or if the registered data R includes data on the outputs of the compressor, outdoor fan, and indoor fan, the average values ​​of these may be used as the control information.

[0082] Fig. 12 is another example of a flowchart in which the server 31 of the home appliance control information generation system 1 according to the first embodiment classifies and analyzes the registered data R based on the power consumption Wv. In the above, an example has been described in which the registered data R is classified based on Fig. 10, more ideal operating states are extracted from among those with similar power consumption Wv, and the extracted data is then analyzed. However, in the flow shown in Fig. 12, the server 31 extracts data sets with a predetermined change frequency or less from the registered data R, classifies the extracted data sets into a plurality of groups based on the power consumption Wv, and analyzes data for each group.

[0083] In the example shown in Fig. 12, before steps B1 to B5 shown in Fig. 10, a data set with a setting change frequency equal to or lower than a predetermined setting change frequency is extracted from the registered data R based on the setting change frequency information (step C1). The subsequent steps C2 to C6 have the same content as steps B1 to B5 shown in Fig. 10. By performing such processing, the server 31 can initially exclude data that is not necessary for generating control information for the air conditioner.

[0084] (Modification of analysis and control information generation by server 31) The server 31 extracts a data set from the registered data R based on the setting change frequency information, and derives control information for the air conditioner based on the operating state of the air conditioner in the extracted data set, but a learning model may be used to derive the control information. In this case, the analysis unit 31d of the server 31 generates a learning model, and the control information generation unit 31e inputs operation history information acquired from the probe device 11 or the like into the generated learning model, and outputs the control information.

[0085] Fig. 13 is an explanatory diagram of an example of the functions of the analysis unit 31d and the control information generation unit 31e of the server 31 according to the first embodiment. Operation history information S and weather information are input to the analysis unit 31d. Since the operation history information S is data including the passage of time and fluctuations in each parameter as shown in Fig. 11, setting change frequency information based on fluctuations in the set temperature Ts and power consumption Wa may be extracted in advance and input to the analysis unit 31d.

[0086] The analysis unit 31d generates a learning model based on the registered data R. In the case of unsupervised learning, the analysis unit 31d is designed to automatically identify patterns, relationships, anomalies, etc. of each data. For example, the analysis unit 31d can use clustering and principal component analysis (PCA) to identify driving states under different environmental information and weather information from the driving history information S, and generate a learning model that can realize an efficient driving state from among them. In the case of supervised learning, the analysis unit 31d generates a learning model using a data set of the set temperature, the driving state of the air conditioner (output of the air conditioner), the environmental information, and the weather information when the change frequency is less than a predetermined value as teacher data (labeled data). The analysis unit 31d learns every time new driving history information is acquired, and can generate a learning model that can output highly accurate driving states or control information that makes the user feel more comfortable.

[0087] The analysis unit 31d may also generate a learning model by reinforcement learning. For example, the analysis unit 31d generates a learning model in which the lower the frequency of setting changes, the higher the reward obtained, and the reward is maximized. The analysis unit 31d can generate a learning model that can handle a variety of situations by further setting the reward obtained to be higher when the power consumption Wv is low and when there is little fluctuation in the indoor temperature Tr, etc. The learning model takes environmental information and weather information as input, and takes the operating state or control information of the air conditioner as output.

[0088] (Example of control of air conditioner by server 31) 14 is a flowchart of an example of control of an air conditioner using control information generated by the server 31 according to embodiment 1. The server 31 identifies the location area Lc from the operation history information S acquired from the probe device 11 of the air conditioner to be controlled (step D1). Next, the server 31 identifies the weather observation station Wo closest to the location area Lc and associates it with the operation history information S (step D2). Furthermore, the server 31 acquires weather forecast data from the corresponding weather observation station Wo (step D3).

[0089] Next, the server 31 analyzes the weather forecast data, and here determines whether or not the forecast value of the outside air temperature Te will rise in the future (step D4). If the air conditioner is in heating operation, and it is determined that the outside air temperature Te will rise (yes in step D4), the server 31 transmits control information to the air conditioner to reduce output (step D5). If it is determined that the outside air temperature Te will not rise (no in step D4), the server 31 transmits control information for normal output to the air conditioner (step D6).

[0090] In steps D5 and D6, for example, the results obtained by inputting weather forecast data into the learning model in advance may be used as the control information. In this way, by creating control information based on weather forecast data, the air conditioner can operate more efficiently while ensuring the comfort of the user. For example, when an air conditioner is operating in cooling mode, the temperature is currently high, and the weather forecast data predicts that the temperature will gradually decrease in the coming time period, the server 31 generates control information that gradually reduces the output in accordance with the decreasing temperature in the coming time period. In this way, by gently controlling the operating state of the air conditioner in accordance with the temperature, the operation of the air conditioner becomes more efficient.

[0091] As described above, according to the home appliance control information generation system 1 according to the first embodiment, the operation history information S is acquired from air conditioners in different regions, and data is analyzed for each location region Lc based on the operation history information S. This makes it possible to obtain optimal control information for each region with a different climate. In addition, the home appliance control information generation system 1 stores and analyzes the operation history information S and meteorological information in chronological order, so that it is possible to obtain optimal control information in each case, even when the season or weather is different, for example. The home appliance control information generation system 1 can also generate control information by inputting weather forecast data into the learning model. In this case, the learning model outputs optimal air conditioner control information according to the weather forecast data, so that the determination shown in step D4 in FIG. 14 is not necessary. However, the server 31 may switch the learning model to be used according to the weather forecast data.

[0092] According to the home appliance control information generating system 1 according to the first embodiment, it becomes possible to output optimal control information each time the amount of registered data R increases. By using optimal control information suited to various installation environments generated by the home appliance control information generating system 1 instead of controlling the air conditioner based on conventional indices such as PMV, it becomes possible to operate the air conditioner in accordance with the latest environment (climate, region, living environment, etc.) at all times.

[0093] In the above, the home appliance control information generating system 1 has been described using an air conditioner as an example, but other home appliances for which control information is generated include refrigerators. For example, the power consumption Wa of a refrigerator may vary depending on the frequency of opening and closing the refrigerator, the outdoor air temperature Te, the set temperature Ts of an air conditioner installed in the room, and the room temperature Tr. Therefore, the server 31 may be configured to input the power consumption Wa of the refrigerator, the outdoor air temperature Te, the set temperature Ts of the air conditioner, and the room temperature Tr to the analysis unit 31d and analyze them. For example, the power consumption Wa of the refrigerator, the outdoor air temperature Te, the set temperature Ts of the air conditioner, and the room temperature Tr may be input to the analysis unit 31d to generate a learning model, and an optimal operating state or control information of the refrigerator according to the outdoor air temperature Te, the set temperature Ts of the air conditioner, and the room temperature Tr may be output. The learning model generated in the analysis unit 31d can output the optimal operating state or control information of the refrigerator by supervised / unsupervised learning, reinforcement learning, etc., as described in the case of the air conditioner above.

[0094] Fig. 15 is a flowchart showing an example of generation of home appliance control information by the home appliance control information generation system 100 according to the first embodiment. The power consumption Wa of a refrigerator is affected by the room temperature Tr and the operating state of the air conditioner. Therefore, in Fig. 15, the home appliance control information generation system 100 generates control information for the air conditioner and the refrigerator so that the power consumption Wv of the refrigerator is reduced and the indoor environment is made comfortable.

[0095] First, the server 31 acquires the set temperature Ts and the operation mode of the air conditioner (step E1). Next, the server 31 determines whether the air conditioner is in cooling operation or not (step E2). If the air conditioner is in cooling operation (yes in step E2), the server 31 calculates the amount of reduction in the refrigerator's power consumption when the indoor temperature Tr drops relative to a certain predetermined indoor temperature A (step E3). If the air conditioner is not in cooling operation (no in step E2), the server 31 calculates the amount of increase in the refrigerator's power consumption when the indoor temperature Tr rises relative to a certain predetermined indoor temperature A (step E4).

[0096] After the changes in the power consumption of these refrigerators are obtained, the server 31 analyzes the increase and decrease in the power consumption of the refrigerators and the operating conditions of the air conditioner, and obtains efficient operating conditions for the refrigerator and the air conditioner (step E5).

[0097] As described above, the home appliance control information generation system 100 according to the first embodiment can generate control information for a plurality of types of home appliances related to temperature control. In the above, the generation of control information relating to a refrigerator and an air conditioner has been described as an example, but control information may be generated similarly for other home appliances.

[0098] Although the present invention has been described above based on each embodiment, the present invention is not limited to the configuration of the above-mentioned embodiment. In each of the above embodiments, the home appliance control information generating system 1 is realized in a system including a client-server system of a network computer system, but the same function as the home appliance control information generating system 1 can also be realized in various computers such as personal computers that do not constitute a client-server system, and various communication terminals and mobile information terminals such as mobile terminals and tablets. In this case, it is also possible to realize at least a part of the function of the home appliance control information generating system 1 by implementing a computer program in various computers and various communication terminals and mobile information terminals. In other words, the present invention also includes a program for causing various computers to function as at least a part of the home appliance control information generating system 1. In addition, each of the above embodiments may be implemented in combination. It is to be noted that the scope of various modifications, applications, and uses made by those skilled in the art as necessary is also included in the gist (technical scope) of the present invention. [Explanation of symbols]

[0099] 1: Home appliance control information generation system 1a: House 1b: House 11: Probe device 12: Probe device 21: Mobile terminal 21a: Display 22: Mobile terminal 30: Network 31: Server 31a: Information processing section 31b: Storage section 31c: Timing section 31d: Analysis department 31e: Control information generation unit 40: Air conditioning equipment 41: Air conditioner 42: Air conditioner 43: Infrared receiver 51: Remote control 52: Home router 61: CPU 62 :ROM 63: RAM 64: Data Communications Department 65: Input / output section 66: Power meter 67: Room temperature meter 68: Light emitting device 69: Light emitting device 71: CPU 72 :ROM 73: RAM 74: Data Communications Department 75: Storage device 90: Network 100: Home appliance control information generation system Cp: ​​Power line Id : Identification information Lc:Location area Mc:Model information Nd: Number of data Pm: Comparison period R: Registration data S: Driving history information S1: Dataset S2: Dataset Sa : Dataset Sa : Dataset Sr: Regional driving history information T :Temperature Ta: Time information Tc: Comparison time Te: Outside air temperature Te1: Outside temperature Te2: Outside temperature Tf: Outside air humidity Th1: Temperature threshold Ti: Transmission interval Tr: Indoor temperature Tr1: Indoor temperature Tr2: Indoor temperature Ts: Set temperature Ts1: Set temperature Ts2: Set temperature Tw: Acquisition interval W: Power Wa: Power consumption Wo: Weather station Wv: Power consumption t1 : period ΔWv: Difference

Claims

1. A home appliance control information generating system that generates control information for home appliances based on operation history information from a plurality of home appliances, A storage unit that stores the acquired data; an information processing unit for processing the data; The driving history information is The information includes location information that can identify an area where each of the plurality of home appliances is installed, setting information, and power consumption amount, The information processing unit includes: acquire location area weather information, which is weather information for a location area in which the plurality of home appliances are installed, based on the operation history information and the location information from the plurality of home appliances via a network; The operation history information for the plurality of home appliances belonging to the location area is classified into area-specific operation history information; Classifying the regional operation history information into a plurality of groups based on the magnitude of the power consumption; A home appliance control information generating system that analyzes the regional operation history information belonging to the same group among the plurality of groups and outputs control information for home appliances.

2. The home appliance control information generating system according to claim 1, The information processing unit includes: Extracting setting change frequency information for each of the plurality of home appliances from the setting information included in the regional operation history information; A home appliance control information generating system that analyzes the location area weather information and the regional driving history information based on the setting change frequency information.

3. The home appliance control information generating system according to claim 2, The information processing unit includes: extracting the regional driving history information in which the frequency of setting changes within a predetermined time period included in the setting change frequency information is within a predetermined range, and setting the regional driving history information as low change frequency driving history information; Analyzing time information included in the low change frequency driving history information, the setting information in the time information, and the location area weather information in the time information; The home appliance control information generating system stores in the storage unit at least the setting information and the location area weather information included in the low change frequency operation history information in association with each other.

4. The home appliance control information generating system according to claim 3, The information processing unit includes: A home appliance control information generation system that inputs environmental information including the indoor temperature of the environment in which the multiple home appliances are installed and weather information for the location area, and generates a learning model that outputs control information for the home appliances.

5. The home appliance control information generating system according to claim 3, The information processing unit includes: The low-change-frequency driving history information and the location area weather information related to the low-change-frequency driving history information are used as teacher data, A home appliance control information generation system that uses the training data to input environmental information including the indoor temperature of the environment in which the multiple home appliances are installed and weather information for the location area, and generates a learning model that outputs control information for the home appliances.

6. The home appliance control information generating system according to claim 2, The information processing unit includes: A home appliance control information generation system that performs reinforcement learning based on the setting information included in the regional operation history information so that the less frequently the setting of each of the plurality of home appliances is changed, the more rewards can be obtained, and generates a learning model that inputs environmental information including at least the indoor temperature of the environment in which the plurality of home appliances are installed and weather information for the location area, and outputs control information for the home appliances.

7. The home appliance control information generating system according to any one of claims 4 to 6, The environmental information is A home appliance control information generating system including an indoor humidity of an environment in which the plurality of home appliances are installed.

8. The home appliance control information generating system according to claim 7, The plurality of home appliances include A plurality of air conditioning devices, The control information is A home appliance control information generating system including an output for at least one of a compressor, an outdoor fan, and an indoor fan provided in the plurality of air conditioning apparatuses.

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