Home appliance system

Abstract

The present application provides a home appliance system capable of achieving improvement in convenience. The home appliance system of an embodiment has a determination section and a control section. The determination section determines an action setting of a home appliance corresponding to a user based on information indicating an action of the user different from a case where the action setting of the home appliance is changed. The control section controls the home appliance or reports to the user a proposal to change the action setting of the home appliance based on the action setting of the home appliance determined by the determination section.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to a home appliance system. BACKGROUND

[0002] There are home appliances that are capable of performing various functions according to user settings by various mode settings and the like.

[0003] On the other hand, there are cases where the user is unaware of the existence of a mode or the content of the mode, and cases where the user is not able to utilize the functions that can be set.

[0004] Patent Literature 1: Japanese Patent Application Publication No. 2016-206851 SUMMARY

[0005] The present application has been made to solve the problem of providing a home appliance system that enables an improvement in convenience.

[0006] The home appliance system of the embodiment has a determination section and a control section. The determination section determines an action setting of a home appliance corresponding to a user based on information indicating an action of the user that is different from a case where the action setting of the home appliance is changed. The control section controls the home appliance based on the action setting of the home appliance determined by the determination section, or reports a proposal to change the action setting of the home appliance to the user.

[0007] According to the above-described home appliance system, an improvement in convenience can be achieved. BRIEF DESCRIPTION OF DRAWINGS

[0008] Figure 1 is a view that shows a configuration example of a home appliance system to which the first embodiment relates.

[0009] Figure 2 is a view that shows an example of input and output of a learning model to which the first embodiment relates.

[0010] Figure 3 is a view that shows an example of functions that a user terminal device to which the first embodiment relates is capable of performing through an application.

[0011] Figure 4 is a view that shows an example of items of input data that is input to a learning model to which the first embodiment relates.

[0012] Figure 5 is a view that shows an example of steps of a process in which a refrigerator to which the first embodiment relates provides a recommended setting to a user.

[0013] Figure 6 is a view that shows an example of steps of a process in which a refrigerator to which the first embodiment relates reflects a reaction of a user to a recommended setting in a learning result.

[0014] Figure 7 is a view showing a configuration example of a home appliance system according to a second embodiment.

[0015] Figure 8 is a view showing an example of steps of a process in which a learning server device according to the second embodiment provides a recommended setting to a user. DETAILED DESCRIPTION

[0016] Hereinafter, a home appliance system according to an embodiment will be described with reference to the drawings. In the following embodiment, a case in which a home appliance device is a refrigerator will be described as an example, but the home appliance device as an object of the home appliance system according to the embodiment is not limited to a specific device. A home appliance device capable of selecting an action setting from among a plurality of candidates of action settings can be an object of the home appliance system according to the embodiment. "User setting" in the following description is a setting based on a user operation.

[0017] In the following description, the same reference numerals are assigned to configurations having the same or similar functions. Also, sometimes, repeated description of these configurations is omitted. In this specification, "based on XX" means "based on at least XX", including a case where another element is used in addition to XX. In addition, "based on XX" is not limited to a case where XX is used directly, but also includes a case where a result obtained by performing an operation or processing on XX is used. In this specification, "XX or YY" is not limited to a case where only "XX" is used, or a case where only "YY" is used, but also includes a case where both "XX" and "YY" are used. The same applies to a case where the number of selection elements is three or more. "XX" and "YY" are arbitrary elements (for example, arbitrary information).

[0018] (First Embodiment)

[0019] Figure 1 is a view showing a configuration example of a home appliance system 1 according to the first embodiment. The home appliance system 1 includes a refrigerator 100, a user terminal device 200, a user information server device 300, and an application server device 400. In addition, the refrigerator 100, the user terminal device 200, the user information server device 300, and the application server device 400 are communicatively connected to a communication network 900. The refrigerator 100 includes a refrigerator main body 110, a communication module 120, a sensor group 130, an information device 140, a state value acquisition unit 151, a determination unit 152, a control unit 153, and a storage unit 160.

[0020] Any one or two or more of the user terminal device 200, the user information server device 300, the application server device 400, and the communication network 900 can also be a configuration external to the home appliance system 1.

[0021] Alternatively, the determination unit 152 can be configured as a device independent of the refrigerator 100, or the refrigerator 100 can be composed of two or more such devices. For example, as described later, the determination unit 152 can be installed in a learning server device 500 independent of the refrigerator 100 (see reference). Figure 7 The learning server device 500 can be configured as a cloud server.

[0022] The appliance system 1 provides the user with the recommended settings in the refrigerator 100 that correspond to the user's settings. In particular, the appliance system 1 determines and provides the recommended settings in the refrigerator 100 to the user based on the user's actions, which differ from those of changing the operating settings of the refrigerator 100.

[0023] The recommended setting mentioned here refers to the operation setting of the refrigerator 100, which the determining unit 152 determines as the operation setting to be provided to the user. The appliance system 1 can provide the recommended setting to the user by automatically setting the recommended setting for the refrigerator 100. Alternatively, the appliance system 1 can provide the recommended setting to the user by prompting the user with information indicating the recommended setting. For example, the user terminal device 200 can display the information indicating the recommended setting.

[0024] Here, it is possible to reproduce, for example, previously performed action settings based on user actions that change the action settings of the refrigerator 100, such as user operations on the refrigerator 100. However, in this case, it is not possible to provide action settings that the user did not perform.

[0025] Alternatively, one could consider randomly proposing action settings for the refrigerator 100, but given the high probability of proposing actions that the user does not want, the user is unlikely to benefit.

[0026] In contrast, the home appliance system 1 proposes recommended settings based on actions that differ from those of the refrigerator 100, enabling it to suggest settings for actions that the user has not performed. Furthermore, by proposing recommended settings based on the user's actions, the home appliance system 1 is expected to suggest action settings that meet the user's requirements or preferences.

[0027] Refrigerator 100 provides the user with the function of a refrigerator through the refrigerator body 110. In addition, refrigerator 100 performs recommended settings.

[0028] The refrigerator main body 110 is a portion that performs a function as a refrigerator in the refrigerator 100. For example, the refrigerator main body 110 includes each compartment such as a refrigerating compartment, a freezing compartment, a vegetable compartment, and an ice making compartment, and each portion for performing a cooling function as a refrigerator such as a compressor, a heat exchanger, a refrigerant tank, and a pipe. The refrigerator main body 110 is operated in accordance with the control of the control portion 153, and provides a function as a refrigerator to a user.

[0029] The communication module 120 communicates with other devices. For example, the communication module 120 receives user information including history record information of a user's action from the user information server device 300. The user information is used for the refrigerator 100 to make a recommended setting. Alternatively, the communication module 120 can receive history record information of a user's operation with respect to the user terminal device 200 or the like from the user terminal device 200, acquire user information from other devices in addition to the user information server device 300, or acquire user information from other devices instead of the user information server device 300.

[0030] In addition, the communication module 120 can transmit information on a user's action with respect to the refrigerator 100 such as a history record of opening and closing of a door of the refrigerator 100 to the user information server device 300 or the user terminal device 200. The information can be displayed on the user terminal device 200 for the user to confirm a usage state of his or her refrigerator 100.

[0031] The sensor group 130 includes various sensors for detecting a state of the refrigerator 100 or its surroundings. The sensor mentioned here is not limited to a specific kind of sensor. For example, a switch that outputs a binary value such as a door switch that detects opening and closing of a door is included in the sensor group 130. The sensor group 130 also includes a detection portion that detects a current value of a current flowing in an electrical component included in the refrigerator main body 110 such as a compressor, or the like.

[0032] The information device 140 is used as a user interface in the refrigerator 100. For example, the information device 140 can have either one or both of a display screen and a speaker, and report various messages with respect to the refrigerator main body 110 such as that water in an ice making tank is used up to a user. In addition, the information device 140 can reproduce a recipe (information on a method of making a dish), an animation, or the like, and provide various information to a user.

[0033] In addition, the display screen of the information device 140 can be configured as a touch panel, or have a microphone to perform voice recognition, or the like, so that the information device 140 accepts various user operations. For example, the information device 140 can accept a user operation with respect to the refrigerator main body 110 and a user operation with respect to the information device 140 itself.

[0034] The state value acquisition unit 151 acquires a state value quantitatively indicating a state of the refrigerator 100. For example, the state value acquisition unit 151 can acquire a measured value of the sensor group 130 as the state value. The state value acquired by the state value acquisition unit 151 is used, for example, for the determination of whether to switch the mode of the refrigerator 100.

[0035] The determination unit 152 determines a recommended setting (a setting suitable for the user) in the refrigerator 100 corresponding to the user. As described above with respect to the home electric system 1, the determination unit 152 determines the recommended setting based on information indicating an action of the user different from a case where the action setting of the refrigerator 100 is changed. The "action of the user different from a case where the action setting of the refrigerator 100 is changed" refers to an action different from an action of a user who directly changes the action setting of the refrigerator 100 (for example, an action of a user who directly specifies the set temperature, the action mode of the refrigerator 100 after the change).

[0036] The determination unit 152 can also directly determine the recommended setting.

[0037] As described above with respect to the home electric system 1, the determination unit 152 can automatically set the determined recommended setting in the refrigerator 100. Alternatively, the determination unit 152 can present the determined recommended setting to the user by causing the determined recommended setting to be displayed on the user terminal device 200 or the information device 140, without automatic setting.

[0038] Alternatively, the determination unit 152 can also change the determination condition of the setting switching. For example, in a case where the action of the user corresponds to an action decided in advance as an action indicating interest in power saving, the determination unit 152 can change the determination condition (the transition condition to the power saving mode) of the switching of the normal mode and the power saving mode of the refrigerator 100 to be easy to become the power saving mode.

[0039] The determination unit 152 can reflect the reaction of the user to the recommended setting in the determination of the recommended setting thereafter. For example, in a case where the recommended setting is changed by the user operation with respect to the recommended setting determined by the determination unit 152, or the like, it can be considered that the user does not like the recommended setting. In this case, the determination unit 152 can learn the determination method of the recommended setting so as not to determine the same recommended setting again, or to make it difficult to determine the same recommended setting again.

[0040] Alternatively, the determination unit 152 can provide the determined recommended setting to the user at a different time period or a different day of the week, or the like, from the timing at which the recommended setting is provided in a case where the recommended setting is changed by the user. After the recommended setting is also changed by the user in this case, the determination method of the recommended setting can also be learned so as not to determine the same recommended setting again by the determination unit 152, or to make it difficult to determine the same recommended setting again.

[0041] The control section 153 controls each section of the refrigerator 100. In particular, the control section 153 controls the refrigerator main body 110.

[0042] The control section 153 controls the refrigerator 100 according to the operation setting of the refrigerator 100 determined by the determination section 152 or the user operation. Thereby, the control section 153 controls the refrigerator 100 based on the operation setting (recommended setting) of the refrigerator 100 determined by the determination section 152. For example, in a case where the determination section 152 automatically sets the recommended setting to the refrigerator 100, the control section 153 controls the refrigerator 100 according to the setting made by the determination section 152. In a case where the determination section 152 proposes the recommended setting to the user, and the recommended setting is set to the refrigerator 100 by the user operation, the control section 153 also controls the refrigerator 100 according to the setting.

[0043] For the setting showing the judgment condition of the setting switching, the control section 153 decides the operation setting according to the judgment condition, and controls the refrigerator 100 according to the decided setting. In a case where the determination section 152 changes the judgment condition as described above, the control section 153 controls the refrigerator 100 according to the changed judgment condition.

[0044] The storage section 160 stores various information. The storage section 160 can store a learning model (learned model) used for the determination section 152 to determine the recommended setting. The determination section 152 can determine the recommended setting by calculation using the learning model. For example, the determination section 152 can input information of the user's operation or the like to the learning model, and adopt the operation setting output from the learning model as the recommended setting.

[0045] The functions of the state value acquisition section 151, the determination section 152, and the control section 153 can be executed by one or more hardware processors such as a CPU executing a program (software). Alternatively, all or a part of these functional sections can be realized by a circuit section (hardware) such as an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), or an FPGA (Field Programmable Gate Array), or can be realized by a cooperation of software and hardware. The storage section 160 can be realized by a RAM (Random Access Memory), a ROM (Read Only Memory), an HDD (Hard Disk Drive), a flash memory, or a combination of a plurality of these, or the like.

[0046] The user terminal device 200 is a device that receives a user operation. The operation history information of the user with respect to the user terminal device 200 can be used as information for the determination unit 152 to determine the user's action for determining the recommended setting.

[0047] Hereinafter, a case where the user terminal device 200 is a smartphone of the user will be described as an example. For example, the user can use an application that provides information on the opening and closing history of the door of the refrigerator 100 and the like, and the refrigerator 100. Also, the information viewing history information in the user terminal device 200 can be used as information for the determination unit 152 to determine the user's action for determining the recommended setting.

[0048] However, the configuration of the user terminal device 200 is not limited to a specific configuration. Various devices that receive a user operation can be used as the user terminal device 200. For example, the user terminal device 200 can be configured using a personal computer (PC) or a tablet terminal device, or the like.

[0049] The information for the determination unit 152 to determine the user's action for determining the recommended setting can be any one of information indicating the user's action with respect to the refrigerator 100, information indicating the user's action (operation) with respect to the information device 140, or information indicating the user's action (operation) with respect to the user terminal device 200, or a combination of these information. However, the information for the determination unit 152 to determine the user's action for determining the recommended setting is not limited to these. For example, as the information for the determination unit 152 to determine the user's action for determining the recommended setting, information indicating the user's action using a device other than the refrigerator 100, the information device 140, or the user terminal device 200, such as the user's utterance to a smart speaker, can be used.

[0050] In addition, as the information for the determination unit 152 to determine the user's action for determining the recommended setting, information indicating an action other than the action using a device by the user, such as the user's shopping information (for example, information indicating that the user has made a bulk purchase), can be used. For example, the refrigerator 100 can be provided with a camera to capture an image of the user's shopping, and the user's shopping information can be acquired by image analysis.

[0051] The user information server device 300 stores user information. The user information server device 300 can be configured using a computer such as a personal computer or a workstation, for example.

[0052] As described above, the user information stored in the user information server apparatus 300 can include history information of the user's action. This history information of the user's action can be used as information of the user's action for the determination unit 152 to determine the recommended setting. In addition, the user information stored in the user information server apparatus 300 can be transmitted to the user terminal apparatus 200, and the user uses the user terminal apparatus 200 to view the user information.

[0053] As described above, the user information server apparatus 300 can collect information of the user's action from either or both of the refrigerator 100 and the user terminal apparatus 200, and store it as (a part of) the user information.

[0054] The application server apparatus 400 provides an application program used in the user terminal apparatus 200. For example, the application server apparatus 400 can provide an application program for viewing information about the refrigerator 100, such as the opening / closing history information of the door of the refrigerator 100. The application program is also simply referred to as an application.

[0055] The application server apparatus 400 can be constituted, for example, of a computer such as a personal computer or a workstation.

[0056] The communication network 900 is not limited to a specific communication network as long as it can provide a communication route between apparatuses. For example, the communication network 900 can be constituted to include a combination of the Internet and a mobile phone network, but is not limited thereto. The mobile phone network is a wireless communication network provided by a communication company for mobile terminal apparatuses such as smartphones.

[0057] Figure 2 is a diagram showing an example of input and output of the learning model stored in the storage unit 160. As described above, the learning model is used for the determination unit 152 to determine the recommended setting.

[0058] In the example of Figure 2 , the learning model accepts input of the user action information, the current time information, and the refrigerator operation state information, and outputs the recommended setting information.

[0059] The recommended setting information is information indicating the recommended setting.

[0060] The user action information is the above-described information of the user's action. For example, in a case where the user action information indicates that the user frequently views the opening / closing history of the door of the refrigerator 100, it can be considered that the user's interest in the energy consumption (power consumption) of the refrigerator 100 is high. In this case, the determination unit 152 can determine, as the recommended setting, the setting of the power saving mode or the setting of a mode determination condition that easily becomes the power saving mode, using the learning model.

[0061] The current time information is information indicating the current date and time. For example, it can be considered that the opening / closing frequency of the door of the refrigerator 100 differs between daytime and nighttime, and the like, the usage status of the refrigerator 100, or the state of the refrigerator 100 differs according to time elements such as time zone, day of the week, and season. In view of this, the determination unit 152 can determine the recommended setting corresponding to the current date and time using the learning model.

[0062] The refrigerator operation state information is information indicating the state of the refrigerator 100. The refrigerator operation state information, for example, includes the operation mode (operation status) of the refrigerator 100, the air temperature in the cabinet, the temperature of the cooler, and the like. For example, it can be considered that the appropriate operation setting differs according to the state of the refrigerator 100 such as the amount of food stored in the refrigerating chamber. In view of this, the determination unit 152 can determine the recommended setting corresponding to the state of the refrigerator 100 using the learning model.

[0063] Here, the information input to the learning model can include only the information of the user's operation, and is not limited to a specific information. For example, either or both of the current time information and the refrigerator operation state information can not be input to the learning model. Alternatively, the learning model can accept an input of information other than the information illustrated in the drawing, or the like, on the basis of the current time information and the refrigerator operation state information, or instead of accepting an input of the information. Figure 2

[0064] For example, the learning of the learning model can be performed using learning data in which teaching data indicating an operation setting considered appropriate by a person in charge of learning (for example, a technician of the manufacturer of the refrigerator 100) is associated with input data such as user operation information, current time information, and refrigerator operation state information. The learned learning model can be installed in the refrigerator 100. The refrigerator 100 can not have a learning function for updating the learning model.

[0065] Alternatively, the determination unit 152 can update the learning model according to the user's reaction to the recommended setting. As described above, in a case where the recommended setting is changed by the user operation such as canceling the recommended setting, the determination unit 152 can update the learning model so as not to determine the same recommended setting again or so as to make it difficult to determine the same recommended setting again. The determination unit 152 can perform this change, for example, by machine learning using learning data obtained by associating data indicating the operation setting after the change by the user with data input to the learning model for determining the recommended setting by the determination unit 152 itself.

[0066] ​The configuration of the learning model is not limited to a specific configuration. For example, the learning model can be configured using a neural network (NN), a support vector machine (SVM), a random forest, or a regression model, or a combination of these. In addition, the learning model is not limited to a software model stored in the storage 160, and can be configured using hardware.

[0067] Also, the determination unit 152 can determine the recommended setting or the like using an inference rule decided by the designer of the refrigerator 100, or using a determination method decided by a method other than machine learning.

[0068] Figure 3 is an example of functions that the user terminal device 200 can execute by the application. The determination unit 152 can input the execution history of these functions as user action information to the learning model.

[0069] The remote operation function is a function of performing operation on the refrigerator 100, such as setting of the refrigerator 100, via a server device for remote operation from the user terminal device 200. In the example of the refrigerator 100, the user can perform change of the set temperature of the refrigerating chamber, change of the set temperature of the freezing chamber, switching of the chilled mode (quick cooling mode, change to a special chilled mode, and the like) of the chilled chamber, switching of the ice making mode (change to a quick ice making mode, and the like) of the ice making chamber, switching of the freezing mode of the freezing chamber, and switching of the automatic power saving mode, by remote operation. Figure 3

[0070] In a case where the user uses the remote operation function frequently, it can be considered that the user is interested in the setting of the operation of the refrigerator 100. In this case, the determination unit 152 can determine the recommended setting more frequently.

[0071] The determination unit 152 can determine the recommended setting based on the use history of the remote operation function. For example, in a case where the determination unit 152 easily selects a frequently used operation setting as the recommended setting, it is desirable to easily determine an operation setting that meets the user's requirements or preferences. Alternatively, in a case where the determination unit 152 easily selects a less frequently used operation setting as the recommended setting, it is desirable to be able to propose to the user an operation setting that the user has not used or is not used to using as the recommended setting.

[0072] ​The determination section 152 can use a threshold to make a determination of the amount of whether the frequency with which the user uses the remote operation function is high. For example, as a determination of whether it corresponds to the "case where the frequency with which the user uses the remote operation function is high" described above, the determination section 152 can determine whether the frequency with which the user uses the remote operation function is high to a prescribed threshold or more.

[0073] The same applies to the determination of the amount other than the "case where the frequency with which the user uses the remote operation function is high".

[0074] The door opening / closing history recording function is a function with which the user determines the opening / closing history of the door of the refrigerator 100. In the example of Fig. 1, the user can select either the history for 1 day or the history for 1 week to cause the user terminal device 200 to display. Figure 3

[0075] As described above, in the case where the user confirms the door opening / closing history at a high frequency, it can be considered that the concern for the power consumption of the refrigerator 100 is high. In this case, the determination section 152 can determine the setting of the power saving mode or the setting of the mode determination condition that easily becomes the power saving mode as the recommended setting. In this way, the determination section 152 can determine the setting corresponding to the user with respect to the power consumption of the refrigerator 100 as the recommended setting on the basis of information indicating the confirmation action of the user who confirms the opening / closing history of the door of the refrigerator 100 (for example, information indicating the number of times of the confirmation action of the user).

[0076] In the case where the determination section 152 determines the setting of the mode determination condition that easily becomes the power saving mode, it can determine either or both of the temperature threshold value or the time threshold value with respect to the temperature in the interior of the refrigerator 100. For example, the determination condition of the switching from the mode other than the power saving mode (for example, the normal mode) to the power saving mode can be a state where the temperature in the interior of the refrigerator 100 is in a prescribed range (for example, a state where it is stable in the prescribed range) for a prescribed time or more. In this case, the determination section 152 can determine the temperature threshold value in such a manner that the lower limit of the range of the temperature in the interior of the refrigerator 100 is lowered, or the upper limit of the range of the temperature in the interior of the refrigerator 100 is raised, or both. In addition, the determination section 152 can determine the time threshold value in such a manner that the prescribed time is shortened.

[0077] In the power saving mode, the control section 153 can perform any one or a combination of the reduction of the frequency of the operation of the compressor of the refrigerator 100, the reduction of the number of rotations of the fan, the extension of the time interval of the defrosting process in the refrigerator 100, and the reduction of the illuminance of the illumination in the interior of the refrigerator 100.

[0078] The gaze function is a function that, in the case where a prescribed condition is satisfied, notifies the user terminal device 200 of the case. In the example of Fig. 1, the user can select the "gaze" function to cause the user terminal device 200 to notify the user of the case where the user gazes at the refrigerator 100 for a prescribed time or more. Figure 3 ​In the example of FIG. 9, the user can select one or more of the case in which the door is not opened and closed during a specified period, the case in which the door is opened and closed during a specified period, and the case in which the temperature near the refrigerator is high as a condition for accepting the notification.

[0079] For example, in the case where the selection frequency of the condition of making the notification when the door is opened and closed during a specified period is high, it can be assumed that the notification is accepted in anticipation of the opening and closing of the door outside the period in which the opening and closing of the door does not occur due to the user's going out or bedtime, and the like. There is a case where the temperature in the case is maintained due to the non-occurrence of the opening and closing of the door, and power saving is possible. In view of this, the determination unit 152 can determine the setting of the power saving mode or the setting of the mode determination condition that easily becomes the power saving mode as the recommended setting for the period for which the condition is specified with a high frequency.

[0080] The food management function is a function for allowing the user to confirm the kind, amount, and shelf life of the food stored in the refrigerator 100, and the like. For example, the user terminal device 200 can list display the information of the kind, amount, and shelf life of the food, and the like for each storage compartment such as the freezer compartment and the refrigerating compartment. The shelf life referred to here can also be the expiration date. The information of the food used for the food management function is also referred to as food management information.

[0081] The determination unit 152 can determine the recommended setting based on the shelf life indicated by the food management information. For example, in the case where the number of foods that are close to the shelf life increases, the determination unit 152 can determine the automatic lowering of the temperature in the case, the entry into the quick cooling mode, the use of the bacteria removal function, or the use of the odor removal function, or a combination thereof as the recommended setting. Thereby, it is expected that the freshness of the food is maintained for a longer period of time.

[0082] In addition, in the case where the frequency of the increase in the number of foods that are close to the shelf life is high, the determination unit 152 can determine the setting of the temperature in the case to a temperature that is lower than the standard temperature as the recommended setting.

[0083] The determination unit 152 can also determine the recommended setting based on the input condition of the information of the shelf life. For example, in the case where the number of times of input of the shelf life of all the foods registered in the food management function by the user is large, it can be considered that the user is concerned about the freshness of the food. In this case, the determination unit 152 can also determine the setting of the temperature in the case to be lower than the standard temperature, and the like for maintaining the freshness of the food for a longer period of time as the recommended setting.

[0084] The determination section 152 can also determine the recommendation setting based on information indicating a tendency of an action related to the user's purchase. For example, when there is a tendency of the user to make bulk purchases, it can be considered that time will be taken until the purchased food material is used up. In this case, the determination section 152 can also determine, as the recommendation setting, a setting in which the temperature in the box is set lower than the standard temperature, or a setting in which the bulk-purchased food material is rapidly cooled by the rapid cooling function, or the like, for maintaining the freshness of the food material for a longer period of time.

[0085] As described above, for example, the refrigerator 100 can also be provided with a camera to take an image of the user's shopping, and can acquire the tendency of the action related to the user's purchase by image analysis. Alternatively, the determination section 152 can also grasp the tendency of the action related to the user's purchase from the food material management information registered by the user in the food material management function.

[0086] In addition, the determination section 152 can determine the recommendation setting based on the nutritional component determined from the kind of the food material. For example, when there is a food material in the food materials stored in the refrigerator 100 whose nutritional component increases when the temperature is high, the determination section 152 can determine, as the recommendation setting, a setting in which the temperature in the box is increased for a prescribed period of time.

[0087] Further, the food material is also referred to as food here. That is, the term "food material" and the term "food" are not distinguished, and are used as a term that generally refers to food.

[0088] The determination section 152 can determine the recommendation setting based on information of the user's action related to confirmation of the nutritional information. For example, when the user confirms the nutrition of the food material by accessing a website that provides information on the nutritional component of food, or the like, via the Internet, it can be considered that the concern for nutrition is high. In this case, the determination section 152 can determine, as the recommendation setting, a setting in which the temperature in the box is increased for a prescribed period of time in order to increase the nutritional component of the food material.

[0089] In addition, the determination section 152 can determine the recommendation setting based on the number of times the user confirms the food management information for each storage compartment (storage section), and / or the number of times the door of the storage compartment is opened and closed, and the like. For example, when the user confirms the food management information for a specific storage compartment (refrigerating compartment, freezing compartment, or vegetable compartment) more than a prescribed proportion of the number of times for other storage compartments, it can be considered that the user has a high concern for the storage compartment. In this case, the determination section 152 can determine, as the recommendation setting, an action setting related to the storage compartment to be easy. Alternatively, the determination section 152 can determine, as the recommendation setting, a setting in which the storage compartment is preferentially cooled.

[0090] The recipe function is a function for the user to refer to a recipe. For example, the user terminal device 200 can display a search screen of a recipe or a list of recipes, and display a recipe designated by the user.

[0091] The determination section 152 can determine the recommended setting based on the user's action of referring to the recipe. For example, in a case where the user refers to the recipe and actually performs cooking, it can be considered that the user takes out the ingredients by opening the door of the refrigerator 100. In view of this, the determination section 152 determines the recommended setting in a manner that the temperature inside the box is reduced at a timing at which the user refers to the recipe.

[0092] The consumed power display function is a function for allowing the user to confirm the consumed power of the refrigerator 100. In the consumed power display function, the user terminal device 200 can display a history of the consumed power of the refrigerator 100 or an average value of the consumed power of the refrigerator 100 for a recent prescribed period.

[0093] In a case where the frequency at which the user confirms the consumed power of the refrigerator 100 is high, it can be considered that the concern for the consumed power of the refrigerator 100 is high. In this case, the determination section 152 can confirm the setting of the power saving mode or the setting of the mode determination condition that easily becomes the power saving mode as the recommended setting. In this way, the determination section 152 can determine the action setting related to the consumed power of the refrigerator 100 corresponding to the user as the recommended setting based on information indicating the confirmation action of the user who confirms the consumed power of the refrigerator 100 (for example, the number of times of the confirmation action of the user who confirms the consumed power).

[0094] Figure 4 is an example of a project indicating input data input to a learning model. In Figure 4 In the example of

[0095] Each project of the application operation history corresponds to an example of a project of user action information input to the learning model. The determination section 152 can input, to the learning model, the number of times of display of a screen, the display time of the screen, the operation time, and the number of times of selection of a function in each application program of the remote operation, the door opening / closing history, and the like, as the user action information. In addition to this, the determination section 152 can input the history information of each project of each function (each application program) and the history information of each setting as the user action information. Figure 3

[0096] Each project of the refrigerator operation state corresponds to an example of a project of refrigerator operation state information input to the learning model. By Figure 4 The state of the refrigerator 100 is indicated by sensor data of the sensor class such as the refrigerating chamber door opening / closing, the vegetable compartment door opening / closing, and the like, exemplified by ​​

[0097] The determination section 152 can perform image display and sound output in the information device 140, or either of these, with respect to a user action that is considered to be an action in which the user is in front of the refrigerator 100. For example, the determination section 152 can perform image display and sound output in the information device 140, or either of these, by executing an application. The execution of the application in this case can correspond to an example of implementation of the recommendation setting, or can be a form other than the recommendation setting, such as reproduction of an entertainment animation.

[0098] Examples of a user action that is considered to be an action in which the user is in front of the refrigerator 100 include an action of taking out a food material from the refrigerator 100, an action of referring to a recipe prompted by the information device 140, and an opening and closing action of a door of the refrigerator 100, but are not limited to these.

[0099] As a result, it is expected that the determination section 152 can influence the user at an appropriate timing when the user is in front of the refrigerator 100.

[0100] The determination section 152 can store in advance a timing at which the user puts a food material into the refrigerator 100, and determine the recommendation setting in such a manner that the temperature in the cabinet is lowered at the same timing (for example, the temperature in the cabinet is lowered in advance, or a defrosting action is performed in advance so that cooling can be performed at the timing), such as at the same time of day on the same day of the week.

[0101] As a result, in a case where the user goes shopping at the same time period on the same day of the week, or in a case where a food material is put into the refrigerator 100 at the same timing, it is expected that the newly stored food material can be cooled quickly, and that the freshness of the food material can be ensured.

[0102] The determination section 152 can detect a timing at which the user puts a food material into the refrigerator 100 with reference to information registered in a food material management application (an application that provides a function for managing food materials). Alternatively, the determination section 152 can detect a timing at which the user puts a food material into the refrigerator 100 by performing image recognition processing with respect to an image of the camera in the cabinet.

[0103] The determination section 152 can determine a setting that lowers the temperature in the cabinet, such as a quick cooling mode, as the recommendation setting with respect to an action in which the user puts a food material with a relatively high temperature into the refrigerator 100.

[0104] As a result, it is expected that the newly stored food material can be cooled quickly, and that the freshness of the food material can be ensured. In addition, the temperature in the cabinet is ensured to be a relatively low temperature, and it is expected that the freshness of food materials other than the newly stored food material can also be ensured.

[0105] As an example of a method by which the determination section 152 detects the user's action of putting a food material with a relatively high temperature into the refrigerator 100, there can be mentioned a method of detecting the user's shopping by detecting the operation of a shopping application (for example, a connection to a mail-order website, or a payment of electronic money, and the like), detecting the opening and closing of the door of the refrigerator 100, detecting the rise in the temperature in the box, and the like. In addition, as an example of a method by which the determination section 152 detects the user's action of putting a food material with a relatively high temperature into the refrigerator 100, there can be mentioned a method of detecting the user's cooking by detecting the user's action of referring to a recipe, detecting the opening and closing of the door of the refrigerator 100, detecting the rise in the temperature in the box, and the like. However, the method by which the determination section 152 detects the user's action of putting a food material with a relatively high temperature into the refrigerator 100 is not limited to these methods.

[0106] The determination section 152 can determine the action related to ice making corresponding to the user to be the recommended setting on the basis of the information indicating the user's action of acknowledging the notification that the water for the ice-making tank is used up.

[0107] For example, in a case where the user does not acknowledge the notification that the water for the ice-making tank is used up, or even if the user acknowledges the notification, the user does not replenish the water, it can be considered that the user does not require ice making. In this case, the determination section 152 can determine the setting of not performing automatic ice making to be the recommended setting.

[0108] Alternatively, in a case where the user replenishes the water immediately (within a prescribed time) after the notification that the water for the ice-making tank is used up, it can be considered that the user wants a lot of ice. In this case, the determination section 152 can determine the setting of increasing the ice-making speed to be the recommended setting.

[0109] Figure 5 is an example of a step indicating the process by which the refrigerator 100 provides the recommended setting to the user. The refrigerator 100 repeatedly performs the process of Figure 5 every certain time, for example.

[0110] In the process of Figure 5 , the determination section 152 acquires input data to the learning model (step S111). For example, the determination section 152 acquires the user action information, the current time information, and the refrigerator operation state information exemplified in Figure 2 as the input data to the learning model.

[0111] Next, the determination section 152 determines the recommended setting (step S112). Specifically, the determination section 152 inputs the data obtained in step S111 to the learning model, and determines the action setting output from the learning model to be the recommended setting.

[0112] Next, the determination section 152 determines whether the recommended setting is valid (step S113). For example, in a case where the action setting determined in step S112 has become the current action setting of the refrigerator 100, the determination section 152 determines that the determined recommended setting is not valid. Alternatively, there is also a case where the learning model does not output the recommended setting. In a case where the learning model does not output the recommended setting, the determination section 152 determines that the recommended setting is not valid.

[0113] In a case where the determination section 152 determines that the recommended setting is not valid (step S113: No), the refrigerator 100 ends the processing. Figure 5

[0114] On the other hand, in a case where it is determined that the recommended setting is valid (step S113: Yes), the determination section 152 automatically sets the determined recommended setting to the refrigerator 100 (step S114). Alternatively, the determination section 152 can not perform the automatic setting, but can instead present the user with the determined recommended setting by causing the user terminal device 200 to display the determined recommended setting. The user can preselect whether the recommended setting is automatically set to the refrigerator 100 by the determination section 152.

[0115] Next, the determination section 152 reports to the user that the recommended setting is automatically set to the refrigerator 100 (step S115). For example, the determination section 152 reports by causing the user terminal device 200 to display a message that the recommended setting is automatically set to the refrigerator 100 via the communication module 120.

[0116] After step S115, the refrigerator 100 ends the processing. Figure 5

[0117] Figure 6 is an example of a step indicating the processing of the refrigerator 100 reflecting the user's reaction to the recommended setting in the learning result. For example, after a predetermined time elapses after the recommended setting is automatically set to the refrigerator 100 in step S114 of Figure 5 , the refrigerator 100 performs the processing of Figure 6 .

[0118] In the processing of Figure 6 , the determination section 152 acquires refrigerator operation information (step S121). The refrigerator operation information here includes information indicating the current action setting of the refrigerator 100.

[0119] Next, the determination section 152 determines whether a setting change is made from the recommended setting (step S122). For example, the determination section 152 determines whether the current action setting of the refrigerator 100 indicated by the refrigerator operation information is different from or the same as the recommended setting.

[0120] ​​In a case where the determination section 152 determines that the setting change from the recommended setting has not been made (step S122: No), the refrigerator 100 ends the processing. Figure 6

[0121] On the other hand, in a case where it is determined that the setting change from the recommended setting has been made (step S122: Yes), the determination section 152 feeds back the result that the recommended setting has not been adopted to the learning model (step S123). As described above, the determination section 152 updates the learning model so as not to determine the same recommended setting again, or so as to make it difficult to determine the same recommended setting again. As described above, the determination section 152 can make this change by machine learning.

[0122] After step S123, the refrigerator 100 ends the processing. Figure 6

[0123] As described above, the determination section 152 determines the action setting of the home electric appliance corresponding to the user on the basis of information indicating the action of the user different from the case where the action setting of the home electric appliance (for example, the refrigerator main body 110) is changed. The control section 153 controls the home electric appliance on the basis of the action setting of the home electric appliance determined by the determination section 152, or reports the proposal of the change of the action setting of the home electric appliance to the user.

[0124] Thereby, the home electric system 1 can assist the use of the function settable by the user.

[0125] Here, although it can be considered to reproduce, for example, the action setting performed in the past in accordance with the action of the user who changes the action setting of the home electric appliance in accordance with the user operation or the like with respect to the home electric appliance, in this case, it is not possible to propose the action setting which the user has not performed.

[0126] In addition, it can also be considered to propose, for example, the action setting with respect to the home electric appliance at random, but in this case, the possibility that the user is not benefited is high in terms of the possibility that the action setting which the user does not want is proposed.

[0127] In contrast to this, the home electric system 1 can propose the action setting which the user has not performed by proposing the recommended setting in accordance with the action different from the case where the action setting of the home electric appliance is changed. Furthermore, the home electric system 1 can be expected to be able to propose the action setting in accordance with the requirement or the preference of the user even in a case where the user is not aware of the existence of the mode or the content of the mode by proposing the recommended setting in accordance with the action of the user. Thereby, the improvement of convenience can be achieved.

[0128] ​​Further, the state value acquisition section 151 acquires a state value quantitatively indicating a state of the home electric appliance. The determination section 152 determines a threshold value for control of the home electric appliance corresponding to the user, based on the information indicating the user's action. The control section 153 controls the home electric appliance based on the state value acquired by the state value acquisition section 151 and the threshold value determined by the determination section 152.

[0129] Thus, by the determination section 152 determining the threshold value instead of directly determining the action setting, the control section 153 is able to control the home electric appliance with the action setting corresponding to the state value acquired by the state value acquisition section 151, such as the temperature in the cabinet. According to the home electric system 1, it is expected that the home electric appliance can be appropriately controlled according to the state of the home electric appliance at this point.

[0130] Further, the determination section 152 can determine (change) only the threshold value already set for control of the home electric appliance. At this point, the change of the existing control logic for the determination of the determination section 152 to be reflected in the control of the home electric appliance can be small.

[0131] Further, in a case where a setting change based on the user's operation is made to the action setting determined by the determination section 152, the determination section 152 suppresses redetermination of the action setting before the change.

[0132] In a case where the user makes a setting change to the action setting determined by the determination section 152, it can be considered that the user does not want the action setting determined by the determination section 152. By the determination section 152 suppressing redetermination of the action setting in this case, it is expected that the action setting in accordance with the user's request or preference can be determined.

[0133] The determination section 152 determines the action setting related to the power consumption of the refrigerator 100 corresponding to the user, based on information indicating the user's confirmation action of confirming the opening / closing history of the door of the refrigerator 100 (e.g., the number of times of the user's confirmation action of confirming the opening / closing history of the door).

[0134] In a case where the number of times of the user's confirmation action of confirming the opening / closing history of the door of the refrigerator 100 is large, it can be considered that the user is highly interested in the power consumption of the refrigerator 100. In this case, by the determination section 152 determining an action setting such that the power consumption of the refrigerator 100 is reduced, for example, it is expected that the action setting in accordance with the user's request or preference can be determined.

[0135] Further, the determination section 152 determines at least any one of a temperature threshold value or a time threshold value related to the temperature in the cabinet of the refrigerator 100 as the action setting related to the power consumption of the refrigerator. The control section 153 controls the refrigerator 100 based on at least any one of the temperature threshold value or the time threshold value determined by the determination section 152.

[0136] Thus, by the determination section 152 determining the temperature threshold value or the time threshold value instead of directly determining the operation setting of the refrigerator 100, the control section 153 is able to control the refrigerator 100, for example, by the operation setting based on the temperature in the box or the stabilization time of the temperature in the box. At this point, the control section 153 is able to control the refrigerator 100 by the operation setting corresponding to the state of the refrigerator 100. According to the home electric system 1, at this point, it is expected that the refrigerator 100 is able to be appropriately controlled according to the state of the refrigerator 100.

[0137] In addition, the determination section 152 can determine only the threshold value that has been set in the control of the refrigerator 100. At this point, the change of the existing control logic for reflecting the determination of the determination section 152 to the control of the refrigerator 100 can be small.

[0138] In addition, the determination section 152 determines the operation setting corresponding to the user related to the consumption power of the refrigerator 100 based on information indicating the confirmation operation of the user confirming the consumption power of the refrigerator 100 (for example, the number of times of the confirmation operation of the user confirming the consumption power). In the case where the number of times of the confirmation operation of the user confirming the consumption power of the refrigerator 100 is large, it is considered that the user is interested in the consumption power of the refrigerator 100. In this case, by the determination section 152 determining the operation setting such as reducing the consumption power of the refrigerator 100, it is expected that the operation setting corresponding to the request or the preference of the user is able to be determined.

[0139] In addition, the determination section 152 determines the operation setting corresponding to the user related to the temperature management of the refrigerator 100 based on the operation of the user inputting the shelf life of the food stored in the box.

[0140] For example, in the case where the number of times of inputting the shelf life or the like of all the food registered in the food management function by the user is large, it is considered that the user is interested in the freshness of the food. In this case, by the determination section 152 determining the setting for long-term securing of the freshness of the food such as setting the temperature in the box lower than the standard temperature, it is expected that the operation setting corresponding to the request or the preference of the user is able to be determined.

[0141] In addition, the determination section 152 determines the operation setting corresponding to the user related to the temperature management of the refrigerator 100 based on information indicating the tendency of the operation related to the purchase of the user.

[0142] For example, in a case where the user has a tendency to make bulk purchases, it can be considered that it takes time to finish the purchased food ingredients. In this case, by determining the setting for the temperature in the box to be lower than the standard temperature or by rapidly cooling the bulk-purchased food ingredients with the rapid cooling function, or the like, for a setting that ensures the freshness of the food ingredients for a longer period, the determination unit 152 can be expected to be able to determine the action setting that corresponds to the user's requirements or preferences.

[0143] In addition, the determination unit 152 determines the action setting related to the temperature management of the refrigerator corresponding to the user based on information indicating the user's confirmation action related to the nutrition of the food ingredients (for example, the number of times of the user's confirmation action related to the nutrition of the food ingredients).

[0144] In this case, it can be considered that the user's concern for the nutrition of the food ingredients is high. By determining the action setting related to the temperature management of the refrigerator, the determination unit 152 can be expected to be able to determine the action setting that corresponds to the user's requirements or preferences.

[0145] For example, when there is a food ingredient among the food ingredients accommodated in the refrigerator 100 whose temperature increase causes an increase in the nutritional content, the determination unit 152 can determine a setting that causes the temperature in the box to rise for a prescribed time as the recommended setting.

[0146] In addition, the determination unit 152 determines the action setting related to the temperature management of the refrigerator 100 corresponding to the user based on information indicating the user's action related to a specific storage part included in the refrigerator 100 (for example, the number of times of the user's opening and closing action for the specific storage part).

[0147] In a case where the number of times of the user's confirmation action for the specific storage part is large, it can be considered that the user's concern for the storage part is high (the storage part is frequently used). By determining the action setting based on the information indicating the number of times of the user's confirmation action related to the specific storage part, the determination unit 152 can be expected to be able to determine the action setting, such as a setting that gives priority to cooling the storage part, in accordance with the user's concern.

[0148] In addition, the determination unit 152 determines the action setting related to the temperature management of the refrigerator 100 in a specific time period corresponding to the user based on information indicating the user's action of putting food into the box in the specific time period.

[0149] Thus, the home electric appliance system 1 can appropriately perform the temperature management of the refrigerator 100 in accordance with the timing at which the user puts the food ingredients into the refrigerator 100, and can be expected to be able to ensure the freshness of the food ingredients.

[0150] For example, the determination unit 152 stores in advance the timing at which the user puts the food ingredients into the refrigerator 100, and can determine the recommended setting, for example, in a manner that reduces the temperature in the box at the same timing on the same day of the week, or the like.

[0151] Thus, when the user goes shopping at the same time period of the same day of the week, and so on, and puts in food into the refrigerator 100 at the same time, the newly stored food can be rapidly cooled, and it is expected that the freshness of the food can be ensured.

[0152] Further, the determination section 152 determines the operation setting related to ice making corresponding to the user based on the information indicating the operation of the user who acknowledges the notification of the water running out of the ice making tank.

[0153] Thus, it is expected that the determination section 152 can determine the operation setting related to ice making that corresponds to the requirement or preference of the user.

[0154] For example, in a case where the user does not acknowledge the notification of the water running out of the ice making tank or does not supplement the water even if acknowledging the notification, it can be considered that the user does not require ice making. In this case, the determination section 152 can determine the setting of not performing automatic ice making as the recommended setting.

[0155] Or, in a case where the user supplements the water immediately (within a prescribed period) after the notification of the water running out of the ice making tank, it can be considered that the user wants a lot of ice. In this case, the determination section 15 can determine the setting of increasing the ice making speed as the recommended setting.

[0156] (Second Embodiment)

[0157] Figure 7 is a diagram indicating a configuration example of the home appliance system 2 of the second embodiment. The home appliance system 2 is provided with the refrigerator 100, the user terminal device 200, the user information server device 300, the application server device 400, and the learning server device 500. Further, the refrigerator 100, the user terminal device 200, the user information server device 300, the application server device 400, and the learning server device 500 are communicatively connected with the communication network 900. The refrigerator 100 is provided with the refrigerator main body 110, the communication module 120, the sensor group 130, the information device 140, the state value acquisition section 151, the control section 153, and the storage section 160. The learning server device 500 is provided with the determination section 152, the communication module 510, and the storage section 520.

[0158] The same reference numerals (100, 110, 120, 130, 141, 142, 143, 150, 200, 300, 400, 900) are given to the portions having the same functions in the respective sections of Figure 7 corresponding to the respective sections of Figure 1 the same reference numerals (100, 110, 120, 130, 141, 142, 143, 150, 200, 300, 400, 900) are given to the portions having the same functions in the respective sections of

[0159] In Figure 7In the example shown, the refrigerator 100 does not have the determination section 152 but is provided with the learning server apparatus 500 which has the determination section 152, and the learning model is stored by the learning server apparatus 500 instead of the refrigerator 100, unlike the case of Figure 1 . As for points other than this, Figure 7 , the example shown is the same as Figure 1 .

[0160] The communication module 510 communicates with other apparatuses. For example, the communication module 510 receives, from the refrigerator 100, the communication module 510, and the user information server apparatus 300, or a part of these apparatuses, information for determining the recommended setting, and information for feeding back the user's reaction to the recommended setting to the learning model. In addition, the communication module 510 transmits, to the refrigerator 100, information indicating the recommended setting determined by the determination section 152.

[0161] The information for determining the recommended setting can be Figure 2 the user action information, the current time information, and the refrigerator operation state information exemplified. The information for feeding back the user's reaction to the recommended setting to the learning model can be information indicating the action setting of the refrigerator 100 after a prescribed time elapses from when the learning server apparatus 500 transmits the recommended setting to the refrigerator 100 and the refrigerator 100 itself performs automatic setting.

[0162] The storage section 520 stores various information. In particular, the storage section 520 stores the learning model. However, as described in the first embodiment, the learning model is not limited to a specific kind of model, and can be constituted by hardware.

[0163] The function of the determination section 152 can be executed by one or more hardware processors such as a CPU executing a program (software). Alternatively, all or a part of the function of the determination section 152 can be realized by a circuit section (hardware) such as an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), or an FPGA (Field Programmable Gate Array), and can be realized by cooperation of software and hardware. The storage section 520 can be realized by a RAM (Random Access Memory), a ROM (Read Only Memory), an HDD (Hard Disk Drive), a flash memory, or a combination of a plurality of these.

[0164] As described above, the communication network 900 is configured to include the Internet. The learning server apparatus 500 can be configured as a cloud server on the Internet.

[0165] Figure 8 is a diagram showing an example of steps of the process in which the learning server apparatus 500 provides the recommendation setting to the user. The learning server apparatus 500 repeatedly executes the process of Figure 8 , for example, at every certain time.

[0166] Figure 8 Steps S211 to S213 of Figure 5 are the same as steps S111 to S113 of

[0167] When the determination section 152 determines that the recommendation setting is not valid in step S213 (step S213: No), the learning server apparatus 500 ends the process of Figure 8 . This point is the same as that of Figure 5 .

[0168] When the determination section 152 determines that the recommendation setting is valid in step S213 (step S213: Yes), the determination section 152 transmits the determined recommendation setting to the refrigerator 100 and the user terminal apparatus 200 (step S214).

[0169] After step S214, the learning server apparatus 500 ends the process of Figure 8 .

[0170] In the process shown in Figure 8 , the determination section 152 does not directly automatically set the recommendation setting to the refrigerator 100, but transmits the recommendation setting to the refrigerator 100 (and the user terminal apparatus 200) via the communication module 510, which is different from the case of Figure 5 . As for other points, Figure 8 the process shown in Figure 5 is the same as that of .

[0171] The process in which the determination section 152 causes the refrigerator 100 to reflect the user's reaction to the recommendation setting in the learning result is the same as that of Figure 6 .

[0172] Thus, even in the configuration in which the determination section 152 is provided on the cloud server, the recommendation setting can be provided to the user as in the case in which the determination section 152 is provided to the refrigerator 100.

[0173] According to at least one embodiment described above, by having: a determination section 152 that determines an action setting of an electric appliance corresponding to a user on the basis of information representing an action of the user that is different from a case in which an action setting of the electric appliance is changed; and a control section 153 that controls the electric appliance on the basis of the action setting of the electric appliance determined by the determination section 152 or reports a proposal to change the action setting of the electric appliance to the user, it is possible to achieve an improvement in convenience.

[0174] Several embodiments of the present application are described, but these embodiments are only examples and are not intended to limit the scope of the application. These embodiments can be implemented in other various ways, and various omissions, substitutions, and changes can be made without departing from the scope of the application. These embodiments and their modifications, as well as the application including the scope and spirit of the application, are included in the technical scope described in the claims and the equivalents thereof.

[0175] Explanation of Reference Signs:

[0176] 1…home appliance system, 2…home appliance system, 100…refrigerator, 110…refrigerator main body, 120…communication module, 130…sensor group, 140…information device, 151…state value acquisition unit, 152…determination unit, 153…control unit, 160…storage unit, 200…user terminal device, 300…user information server device, 400…application server device, 500…learning server device, 510…communication module, 520…storage unit, 900…communication network.

Claims

1. A home appliance system, characterized by, Possessing: a determination section that determines, as a recommended setting, an action setting related to consumption power of a refrigerator corresponding to a user based on information indicating a confirmation action of the user who confirms a history of opening and closing of a door of the refrigerator; and a control section that has a function of controlling a function of the refrigerator based on the action setting of the refrigerator determined by the determination section and a function of reporting a proposal to change the action setting of the refrigerator to the user based on the action setting of the refrigerator determined by the determination section. Possessing:

2. A home appliance system characterized by, a determination section that determines, as a recommended setting, an action setting related to consumption power of a refrigerator corresponding to a user based on information indicating a confirmation action of the user who confirms the consumption power of the refrigerator; and a control section that has a function of controlling a function of the refrigerator based on the action setting of the refrigerator determined by the determination section and a function of reporting a proposal to change the action setting of the refrigerator to the user based on the action setting of the refrigerator determined by the determination section. Possessing: a determination section that determines, as a recommended setting, an action setting related to temperature management of a refrigerator corresponding to a user based on information indicating a confirmation action of the user related to nutrition of a food material; and 3. A home appliance system characterized by comprising: a control section that has a function of controlling a function of the refrigerator based on the action setting of the refrigerator determined by the determination section and a function of reporting a proposal to change the action setting of the refrigerator to the user based on the action setting of the refrigerator determined by the determination section. Possessing: a determination section that determines, as a recommended setting, an action setting of increasing ice-making speed of a refrigerator or an action setting of not performing automatic ice making of the refrigerator corresponding to a user based on information indicating an action of the user who receives a notification of water running out of an ice-making tank of the refrigerator; and a control section that has a function of controlling a function of the refrigerator based on the action setting of the refrigerator determined by the determination section and a function of reporting a proposal to change the action setting of the refrigerator to the user based on the action setting of the refrigerator determined by the determination section.

4. A home appliance system characterized by comprising:

5. The home appliance system according to any one of claims 1 to 4, further comprising a state value acquisition section that acquires a state value that quantitatively indicates a state of the refrigerator, the determination section determines a threshold value for controlling the refrigerator corresponding to the user based on the information indicating the action of the user, the control section controls the refrigerator based on the state value acquired by the state value acquisition section and the threshold value determined by the determination section.

6. The home appliance system according to any one of claims 1 to 4, wherein in a case where a setting change based on an operation of the user is made to the action setting determined by the determination section, the determination section suppresses redetermination of the action setting before the change.

7. The home appliance system according to claim 1, wherein the determination section determines at least any one of a temperature threshold value or a time threshold value related to an in-box temperature of the refrigerator as a setting related to consumption power of the refrigerator, ​ ​ ​ ​ ​ The control section controls the refrigerator based on at least any one of the temperature threshold or the time threshold determined by the determination section.

8. The home appliance system according to any one of claims 1 to 4, wherein The determination section determines, as the recommended setting, the action setting corresponding to the user in relation to the temperature management of the refrigerator based on an action of the user inputting a shelf life of food stored in the box.

9. The home appliance system according to any one of claims 1 to 4, wherein The determination section determines, as the recommended setting, the action setting corresponding to the user in relation to the temperature management of the refrigerator based on information indicating a tendency of an action related to a purchase of the user.

10. The home appliance system according to any one of claims 1 to 4, wherein The determination section determines, as the recommended setting, the action setting corresponding to the user in relation to the temperature management of the refrigerator based on information indicating an action of the user in relation to a specific storage section included in the refrigerator.

11. The home appliance system according to any one of claims 1 to 4, wherein The determination section determines, as the recommended setting, the action setting corresponding to the user in relation to the temperature management of the refrigerator in a specific time period based on information indicating an action of the user in putting food into the box in the specific time period.

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