Information processing device, proposed method, program, and storage medium

Abstract

An information processing device, a proposal method, a program, and a storage medium are provided that propose air conditioning operation of an air conditioner. [Solution] The information processing device includes a communication unit capable of acquiring weather information related to the temperature at the location of the air conditioner, a memory unit that accumulates the acquired weather information, and a control unit that controls the communication unit and the memory unit. The control unit acquires a first temperature feature value that represents a temperature trend over a predetermined past period based on the accumulated weather information, acquires a second temperature feature value that represents a predicted maximum temperature or minimum temperature for a target time period, and determines at least one of a proposed mode related to the operating mode of the air conditioning operation of the air conditioner and a proposed temperature related to the set temperature of the proposed mode for the target time period based on the first temperature feature value and the second temperature feature value, and presents at least one of the proposed mode and the proposed temperature.

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device, a proposal method, a program, and a storage medium that propose air conditioning operation of an air conditioner. [Background technology]

[0002] An air conditioner can operate in multiple operating modes, such as heating mode and cooling mode, and at a set temperature. Conventionally, as described in Patent Document 1, a technology has been researched and developed that suggests a set temperature based on the operating mode set by the user. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6908441 Specification Summary of the Invention [Problem to be solved by the invention]

[0004] With the device described in Patent Document 1, it is difficult to make an appropriate suggestion regarding at least one of the operating mode and set temperature of the air conditioning control.

[0005] An object of the present disclosure is to provide an information processing device, a suggestion method, a program, and a storage medium that can provide appropriate suggestions for at least one of the operating mode and set temperature of air conditioning control. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems, the present disclosure provides an information processing device, a proposed method, a program, and a storage medium.

[0007] According to one aspect of the present disclosure, an information processing device that suggests air conditioning operation of an air conditioner includes a communication unit capable of acquiring weather information related to the temperature at the location of the air conditioner, a memory unit that accumulates the acquired weather information, and a control unit that controls the communication unit and the memory unit. The control unit acquires a first temperature feature value that represents a temperature trend over a predetermined past period based on the accumulated weather information, acquires a second temperature feature value that represents a predicted maximum temperature or a predicted minimum temperature for a target time period, and determines at least one of a proposed mode related to the operating mode of the air conditioning operation of the air conditioner and a proposed temperature related to the set temperature of the proposed mode for the target time period based on the first temperature feature value and the second temperature feature value, and presents at least one of the proposed mode and the proposed temperature.

[0008] In another aspect of the present disclosure, a method for proposing air conditioning operation of an air conditioner includes the steps of acquiring a first temperature characteristic value representing the temperature trend over a predetermined period of time in the past based on weather information related to the temperature at the location of the air conditioner, acquiring a second temperature characteristic value representing the predicted maximum temperature or the predicted minimum temperature for a target time period, determining at least one of a proposed mode related to the operating mode of the air conditioning operation of the air conditioner and a proposed temperature related to the set temperature of the proposed mode for the target time period based on the first temperature characteristic value and the second temperature characteristic value, and presenting at least one of the proposed mode and the proposed temperature.

[0009] Furthermore, a program according to another aspect of the present disclosure causes an information processing device to execute the proposed method.

[0010] Another aspect of the present disclosure is a storage medium that is non-transitory and computer-readable and stores a computer program, which, when executed by a processor, realizes the proposed method. [Effects of the Invention]

[0011] According to the present disclosure, the information processing device, the proposed method, the program, and the storage medium can provide an appropriate proposal for at least one of the operation mode and the set temperature of the air conditioning control. [Brief explanation of the drawings]

[0012] [Figure 1A] 1 is a block diagram illustrating an example of an information processing device according to a first embodiment. [Figure 1B] 1 is a block diagram illustrating an example of an information processing device according to a first embodiment. [Figure 1C] 1 is a block diagram illustrating an example of an information processing device according to a first embodiment. [Figure 2] 1 is a flowchart illustrating an example of a proposed method according to the first embodiment. [Figure 3] An example of a user interface (UI) that presents a suggested mode and a suggested temperature according to the first embodiment. [Figure 4] Another example of a UI presenting a suggested mode and a suggested temperature in the first embodiment [Figure 5] 1 is a flowchart illustrating an example of a proposed method according to the first embodiment. [Figure 6] An example of weather information in the first embodiment [Figure 7A] Example of a comparison table in the second embodiment [Figure 7B] Another example of the comparison table in the second embodiment [Figure 8] An example of a trained model in the third embodiment [Figure 9] Examples of the first trained model and the second trained model in the third embodiment [Figure 10] Flowchart of an example of a proposed method according to the fourth embodiment [Figure 11A] An example of a UI for acquiring clothing information in the fourth embodiment [Figure 11B] An example of a UI for acquiring clothing information in the fourth embodiment [Figure 11C] An example of a UI for acquiring clothing information in the fourth embodiment [Figure 12] Flowchart of an example of a proposed method according to the fifth embodiment [Figure 13] 10 is an example of a UI for obtaining user feedback in the fifth embodiment. [Figure 14] 10 is an example of a UI for obtaining user feedback in the fifth embodiment. [Figure 15A] 10 is a flowchart illustrating an example of step S430 according to the fifth embodiment. [Figure 15B] 13 is a flowchart showing an example of a part of step S430 in the fifth embodiment. [Figure 15C] 13 is a flowchart showing an example of a part of step S430 in the fifth embodiment. [Figure 15D] 13 is a flowchart showing an example of a part of step S430 in the fifth embodiment. [Figure 15E] 13 is a flowchart showing an example of a part of step S430 in the fifth embodiment. [Figure 16] Flowchart of an example of correction of proposed mode in the sixth embodiment [Figure 17A] Example of a comparison table in the sixth embodiment [Figure 17B] Another example of the comparison table in the sixth embodiment [Figure 18] Flowchart of an example of a proposed method according to the seventh embodiment [Figure 19A] 13 is an example of a UI that presents a notification related to the first temperature characteristic value or the second temperature characteristic value in the seventh embodiment. [Figure 19B] Another example of a UI presenting a notification related to the first temperature characteristic value or the second temperature characteristic value in the seventh embodiment DETAILED DESCRIPTION OF THE INVENTION

[0013] 《Technical concept》 Before describing specific embodiments of the information processing device, proposed method, program, and storage medium according to the present disclosure, the technical concept described in the present disclosure will be explained using an example. In this example, a server connected to an air conditioner via the Internet for communication functions as an information processing device that proposes air conditioning operation for the air conditioner.

[0014] Conventional devices such as those described in Patent Document 1 suggest a set temperature for an air conditioner to a user based on the operating mode set by the user, information about the location of the building in which the air conditioner is installed, and information about the current season. However, conventional devices have difficulty in appropriately determining the operating mode and set temperature when the temperature transition trend differs from normal or when the temperature suddenly becomes hotter or colder within the same season.

[0015] In response to this, the information processing device disclosed herein can determine an appropriate suggested mode and suggested temperature. The information processing device includes a communication unit capable of acquiring weather information related to the temperature at the location of the air conditioner, a memory unit that accumulates the acquired weather information, and a control unit that controls the communication unit and the memory unit. The control unit acquires a first temperature feature value that represents the temperature trend over a predetermined period of time in the past based on the accumulated weather information, and acquires a second temperature feature value that represents the predicted maximum temperature or minimum temperature for a target time period. For example, the control unit calculates the average maximum temperature over the previous month and acquires it as the first temperature feature value, and acquires the predicted maximum temperature for the target time period as the second temperature feature value.

[0016] Based on the first temperature feature value and the second temperature feature value, the control unit of the information processing device determines, for the target time period, at least one of a proposed mode related to the operating mode of the air conditioning operation of the air conditioner and a proposed temperature related to the set temperature of the proposed mode. For example, the control unit inputs the first temperature feature value and the second temperature feature value into a trained model for proposal, and the results output by the trained model are the proposed mode and the proposed temperature. Finally, the control unit presents the determined proposed mode and proposed temperature to the user.

[0017] By using the first temperature feature value, even if the recent trend in temperature changes is different from normal, it is possible to make appropriate suggestions taking into account the recent temperature changes. By using the second temperature feature value, even if the temperature suddenly rises or falls over a period of time, it is possible to make appropriate suggestions taking into account the temperatures over the period of time. In other words, by using temperature information such as the actual measured temperature and predicted temperature via the first temperature feature value and the second temperature feature value, the information processing device can determine appropriate suggestions even if there is a seasonal trend that is different from normal or a sudden temperature change within a season.

[0018] Although the information processing device does not actually determine changes in temperature transition trends using the first temperature characteristic value or the second temperature characteristic value, by using the first temperature characteristic value and the second temperature characteristic value as described above, it can provide appropriate suggested modes and suggested temperatures even when the temperature transition trends or predicted temperatures are different from normal. Furthermore, by using the first temperature characteristic value and the second temperature characteristic value, it is possible to determine suggested modes and suggested temperatures that are comfortable for the user in winter, summer, or in intermediate periods that are neither winter nor summer (for example, April, May, and October).

[0019] In this disclosure, "air temperature" refers to the outdoor air temperature at the location of the air conditioner. For example, the Japan Meteorological Agency's standard practice for temperature observations is to use an electric thermometer at a height of 1.5 meters above the lawn in a well-ventilated and sunny location. The electric thermometer is stored inside a ventilation duct to avoid exposure to direct sunlight. However, the air temperature may be detected under other observation conditions or at other observation locations, such as by an outdoor air temperature sensor in the air conditioner.

[0020] Each of the embodiments described below represents an example of the present disclosure. The numerical values, shapes, configurations, steps, and step orders shown in each of the following embodiments are examples and do not limit the present disclosure. Among the components in the following embodiment 1, components that are not described in the independent claims that represent the highest concept are described as optional components.

[0021] In each of the embodiments described below, certain elements may be modified, and other elements may be appropriately combined with any configuration, and the combined configurations will provide the respective effects. In the embodiments, the respective combinations of the respective modified configurations will provide the respective effects of the respective modified configurations.

[0022] In the following detailed description, terms such as "first," "second," etc. are used for descriptive purposes only and should not be understood as expressing or implying the relative importance or ranking of technical features. Features qualified as "first" and "second" expressly or imply the inclusion of one or more of that feature.

[0023] First Embodiment Hereinafter, a first embodiment of an information processing device, a proposed method, a program, and a storage medium according to the present disclosure will be described in detail with reference to the accompanying drawings as appropriate.

[0024] The information processing device of the present disclosure can make suggestions regarding the air conditioning operation of an air conditioner. Fig. 1A is a block diagram of an example of an information processing device according to Embodiment 1, and Figs. 1B and 1C are block diagrams of other examples of the information processing device.

[0025] 1A, a server 10 that is communicatively connected to an air conditioner 20 via the Internet is implemented as an information processing device that makes suggestions about the air conditioning operation of the air conditioner 20. The server 10 as an information processing device includes a communication unit 11, a storage unit 12, and a control unit 13.

[0026] The server 10 can be connected to the air conditioner 20 and / or the terminal device 30 via the communication unit 11. The server 10 as an information processing device can cause the air conditioner 20 and / or the terminal device 30 to present suggested modes and suggested temperatures related to the air conditioning operation of the air conditioner 20. The terminal device 30 can be connected to the air conditioner 20 and can control the air conditioner 20 or obtain information related to air conditioning operation from the air conditioner 20 via an associated application 36. The server 10 or the terminal device 30 can further connect to an external information source 40 and obtain meteorological information related to the temperature at the location of the air conditioner 20 from the external information source 40. Furthermore, if the air conditioner 20 includes an outdoor air temperature sensor, the server 10, the air conditioner 20, or the terminal device 30 can obtain meteorological information via the outdoor air temperature sensor.

[0027] Below, an overview of each component will be explained.

[0028] <Server 10> The server 10 is a server for managing at least one air conditioner 20, but may also be used for other purposes. For example, the server 10 may be a management server of the manufacturer of the air conditioner 20, or may be an application server for managing related applications 36 executed on the terminal device 30.

[0029] <Communications Department 11> The communication unit 11 can also communicate with the air conditioner 20, the terminal device 30, and the external information source 40, and can also send and receive internet packets, for example. The communication unit 11 can obtain meteorological information related to the temperature at the location of the air conditioner 20 from the air conditioner 20 or the external information source 40 via the internet. The control unit 13 may cooperate with the air conditioner 20 and / or the terminal device 30 via the communication unit 11 to control the air conditioning of the air conditioner 20. The communication unit 11 may communicate and send and receive data between the server 10, the air conditioner 20, and the terminal device 30 in accordance with standards such as Wi-Fi (registered trademark), IEEE802.2, IEEE802.3, 3G, and LTE. The communication unit 11 may communicate via the internet, an intranet, an extranet, a LAN, ISDN, a VAN, a CATV communication network, a virtual private network, a telephone line network, a mobile communication network, a satellite communication network, infrared light, or Bluetooth (registered trademark).

[0030] <Storage section 12> The storage unit 12 is a recording medium that records various information and control programs, and may be a memory that functions as a work area for the control unit 13. The storage unit 12 is realized, for example, by a flash memory, a RAM (Random Access Memory), a ROM (Read Only Memory), or other storage device, or by an appropriate combination of these.

[0031] The storage unit 12 stores information for making suggestions about air conditioning control, criteria, thresholds, and contrasts. The memory unit 12 may store a table, a trained model, and the like. For example, the memory unit 12 may store the location of at least one air conditioner 20. The memory unit 12 accumulates meteorological information related to the temperature at the location of the air conditioner 20, acquired by the communication unit 11. For example, the memory unit 12 may accumulate the temperature at the location of the air conditioner 20 every three hours for a certain period of time in the past. The memory unit 12 may also store or accumulate user input or user feedback entered by a user via the terminal device 30. These data can be read out by the control unit 13 when the proposed method is executed.

[0032] The storage unit 12 may also store a computer program for causing the control unit 13 to execute the proposed method. That is, the storage unit 12 may be a non-transitory computer-readable storage medium in which the computer program is stored. When the computer program is executed by the processor of the control unit 13, the proposed method is realized.

[0033] <Control unit 13> The control unit 13 of the server 10 as an information processing device executes the proposed method of the present disclosure. The control unit 13 is a controller that controls at least some of the functions of the server 10. The control unit 13 includes a general-purpose processor such as a CPU, MPU, MCU, FPGA, DSP, or ASIC that executes a program to realize a predetermined function. The control unit 13 can realize various controls in the server 10 by calling and executing a control program stored in the storage unit 12. The control unit 13 can also read and write data stored in the storage unit 12 in cooperation with the storage unit 12. The control unit 13 is not limited to a device that realizes a predetermined function through cooperation between hardware and software, and may be a hardware circuit designed specifically to realize the predetermined function.

[0034] The control unit 13 can communicate with the air conditioner 20 and an external information source 40 via the communication unit 11. Similarly, the control unit 13 can receive various commands and setting values ​​from the user (for example, a command to start automatic operation of the air conditioner 20) from the air conditioner 20 or the terminal device 30 via the communication unit 11.

[0035] <Air conditioner 20> The air conditioner 20 controls the air conditioning of, for example, the interior space of a room in a home or office. The air conditioner 20 has, for example, a cooling function, a heating function, and / or an air cleaning function. The air conditioner 20 may include a ventilation device that introduces outdoor air from outside the controlled space into the controlled space. Operation modes for air conditioning include at least a cooling mode and a heating mode. Furthermore, the air conditioner 20 may have operation modes such as a dehumidification mode, a humidification mode, a fan mode, and a ventilation mode, and these functions / operation modes can be freely combined (for example, a heating and humidification function, a cooling and ventilation mode, etc.).

[0036] <Terminal device 30> The terminal device 30 is a device related to the air conditioner 20. The terminal device 30 can perform data communication with the server 10 or the air conditioner 20. In one example, the terminal device 30 is an information terminal that connects to the air conditioner 20 via the Internet or the server 10. For example, the terminal device 30 may be a smartphone, a mobile phone, a tablet, a wearable device, a computer, or the like, that has a dedicated associated application 36 installed. In another example, the terminal device 30 is a remote controller that connects to the air conditioner 20 via infrared or Bluetooth. For example, the terminal device 30 may be a remote controller that manages and controls only the air conditioner 20, or a remote controller that can manage and control multiple types of home appliances simultaneously.

[0037] The terminal device 30 can acquire user input or user feedback entered by the user and transfer it to the server 10 or the air conditioner 20. The terminal device 30 can also acquire a suggested mode and a suggested temperature from the server 10 or the air conditioner 20 and present them to the user.

[0038] The air conditioner 20 or the terminal device 30 may include a display, a speaker, or a buzzer for displaying visual or audio information to the user. The air conditioner 20 or the terminal device 30 can present at least one of the suggested mode and suggested temperature received from the server 10 to the user via the display or speaker.

[0039] <External information source 40> The external information source 40 is an information source that provides information about services that are not directly related to the air conditioner 20, such as weather information or information about the temperature in a specific region. For example, the external information source 40 may be the website of the Japan Meteorological Agency, or a website that publishes weather forecasts. The server 10 may transfer the weather information obtained from the external information source 40 to the air conditioner 20 or the terminal device 30.

[0040] 1A, the server 10 is implemented as an information processing device that makes suggestions about the air conditioning operation of the air conditioner 20. That is, the server 10 as an information processing device executes the proposal method of the present disclosure. Note that when the server 10 executes the proposal method and presents a proposed mode or proposed temperature to the terminal device 30, the server 10 and the terminal device 30 do not need to be connected to the air conditioner 20.

[0041] On the other hand, in the embodiment of FIG. 1B, the terminal device 30 is implemented as an information processing device that proposes air conditioning operation of the air conditioner 20. In other words, the terminal device 30 as an information processing device executes the proposal method of the present disclosure. The terminal device 30 in the embodiment of FIG. 1B includes a communication unit 31, a storage unit 32, and a control unit 33. The communication unit 31, storage unit 32, and control unit 33 of the terminal device 30 may have the same configuration as the communication unit 11, storage unit 12, and control unit 13 of the server 10 described above, or may have lower performance than the communication unit 11, storage unit 12, and control unit 13.

[0042] The terminal device 30 may further include a presentation unit 34 for presenting at least one of the suggested mode and suggested temperature determined by the control unit 33. The presentation unit 34 may include a display, a speaker, a speaker microphone, a speakerphone, or a buzzer for displaying visual or audio information to the user.

[0043] The terminal device 30 may further include an input unit 35 for obtaining user input or user feedback from a user. If the terminal device 30 is a smartphone, a tablet, a wearable device, a computer, or the like, it may include an associated application 36.

[0044] The terminal device 30 may acquire weather information by directly connecting to the air conditioner 20 or the external information source 40. The terminal device 30 may acquire weather information by indirectly connecting to the air conditioner 20 or the external information source 40 via the server 10 or the air conditioner 20. The control unit 33 of the terminal device 30 can execute the proposed method using the acquired weather information. Note that when the terminal device 30 executes the proposed method and presents the proposed mode or proposed temperature to the presentation unit 34, the server 10 and the terminal device 30 do not need to be connected to the air conditioner 20.

[0045] In the embodiment of FIG. 1B, the control unit 33 of the terminal device 30 has a program used to execute the notification method described above. The program causes the control unit 33 of the terminal device 30 to execute the notification method. The storage unit 32 of the terminal device 30 may store a computer program for causing the control unit 33 to execute the proposed method. That is, the storage unit 32 may be a non-transitory computer-readable storage medium on which the computer program is stored. When the computer program is executed by the processor of the control unit 33, the proposed method is realized.

[0046] In the embodiment of FIG. 1C , the air conditioner 20 is implemented as an information processing device that makes suggestions about the air conditioning operation of the air conditioner 20. That is, the air conditioner 20 as an information processing device executes the proposal method of the present disclosure. The air conditioner 20 in the embodiment of FIG. 1C includes a communication unit 21, a memory unit 22, and a control unit 23. The communication unit 21, memory unit 22, and control unit 23 of the air conditioner 20 may have the same configuration as the communication unit 11, memory unit 12, and control unit 13 of the server 10 described above, or may have lower performance than the communication unit 11, memory unit 12, and control unit 13. Note that when the air conditioner 20 executes the proposal method and presents a proposed mode or proposed temperature to the terminal device 30, the air conditioner 20 does not need to be connected to the server 10.

[0047] The air conditioner 20 may further include a presentation unit 24 for presenting at least one of the suggested mode and suggested temperature determined by the control unit 23. The presentation unit 24 may include a display, a speaker, a speaker microphone, a speakerphone, or a buzzer for displaying visual or auditory information to the user. The air conditioner 20 may further include an input unit 25 for obtaining user input or user feedback from the user.

[0048] The air conditioner 20 further includes an air conditioning unit 26 for performing air conditioning functions such as cooling and heating. The air conditioning unit 26 includes components such as a heat exchanger, a compressor, a fan, and refrigerant piping to perform the air conditioning function.

[0049] Furthermore, in order to perform its air conditioning function, the air conditioner 20 may include various sensors. For example, the air conditioner 20 may include an indoor temperature sensor that detects the temperature inside the room in which the air conditioner 20 is installed (i.e., the controlled space for air conditioning control), and an outdoor temperature sensor that detects the outdoor air temperature outside the controlled space. Information detected by the sensors is input and stored in the memory unit 22, and can later be used by the control unit 23 or transmitted to the server 10 or the terminal device 30.

[0050] The air conditioner 20 may acquire weather information by directly connecting to the external information source 40, or may acquire weather information by indirectly connecting from the external information source 40 via the server 10 or the terminal device 30. Furthermore, if the air conditioner 20 includes an outdoor air temperature sensor, the control unit 23 can acquire weather information via the outdoor air temperature sensor. The control unit 23 of the air conditioner 20 can execute the proposed method using the acquired weather information.

[0051] In the embodiment of FIG. 1C , the control unit 23 of the air conditioner 20 has a program used to execute the notification method described above. The program causes the control unit 23 of the air conditioner 20 to execute the notification method. The storage unit 22 of the air conditioner 20 may store a computer program for causing the control unit 23 to execute the proposed method. That is, the storage unit 22 may be a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by the processor of the control unit 23, the proposed method is realized.

[0052] Up to this point, we have provided a brief description of the configuration of the information processing device. The information processing device executes the proposal method and can provide appropriate proposals for at least one of the operating mode and set temperature of air conditioning control. Below, we will explain the features of the proposal method, program, and storage medium according to this embodiment using an example (FIG. 1A) in which the server 10 is the information processing device.

[0053] <Proposed method> The proposed method of the present disclosure proposes air conditioning operation of the air conditioner 20 for a target time period that includes a future point in time. Specifically, the proposed method proposes at least one of a proposed mode related to the operating mode of the air conditioning operation of the air conditioner 20 and a proposed temperature related to the set temperature of the proposed mode. Figure 2 is a flowchart of an example of the proposed method according to the first embodiment, and in this example, the proposed method includes steps S110 to S140.

[0054] In one embodiment, the control unit 13 of the server 10 as an information processing device periodically executes the proposed method. For example, the control unit 13 may execute the proposed method at 10:00 PM every night, at 10:00 PM every Sunday, or at 9:00 AM, 12:00 PM, and 9:00 PM every day.

[0055] In the proposed method, first, the control unit 13 acquires a first temperature feature value based on accumulated weather information (step S110). The accumulated weather information may include the temperature at the location of the air conditioner 20 at regular intervals, or may include past predicted values ​​for the location of the air conditioner 20 at regular intervals. The temperature at the location of the air conditioner 20 may be, for example, the temperature measured at the location of the air conditioner 20 (i.e., the actual measured value). The regular interval may be, for example, every 20 minutes, every 30 minutes, every hour, every 2 hours, every 3 hours, every 6 hours, every 12 hours, or every 24 hours.

[0056] The first temperature characteristic value obtained based on accumulated weather information represents a trend in temperature over a predetermined period of time in the past. In one embodiment, the first temperature characteristic value is a statistical value calculated based on the maximum or minimum temperatures for each of multiple days in the predetermined period. The statistical value may be, for example, the mean, median, average, variance, mode, maximum, minimum, or quartile. For example, the first temperature characteristic value may be the average maximum temperature for the previous month. The predetermined period may be, for example, one week, two weeks, one month, two months, or three months. The predetermined period of time in the past may be, for example, the previous predetermined period, a predetermined period from several days ago, or an intermittent period within a certain period.

[0057] In one example, the first temperature characteristic value is a statistical value of the maximum or minimum temperature for each of multiple days in a predetermined period. For example, the first temperature characteristic value is a statistical value of the maximum or minimum temperature for each of all days or some days in the predetermined period. The control unit 13 calculates the statistical value of the maximum or minimum temperature for each of multiple days in the predetermined period and sets the calculation result as the first temperature characteristic value. In this disclosure, the average value of the maximum temperature for each of all days in the predetermined period is often described as an example of the first temperature characteristic value, but the first temperature characteristic value is not limited to this.

[0058] In another example, the first temperature characteristic value is a statistical value of the maximum or minimum temperature for each target time period on multiple days during a predetermined period. For example, the target time period is from 9:00 PM on the current day to 6:00 AM the next day. The control unit 13 calculates the average maximum temperature for the time period from 9:00 PM to 6:00 AM the next day in the location of the air conditioner 20 every day for the previous month, and sets this as the first temperature characteristic value.

[0059] In another example, the control unit 13 uses a first temperature characteristic value that differs depending on the current season. Therefore, the criteria for determining whether to perform air conditioning control differ depending on the season. In this example, if it is currently winter, the first temperature characteristic value is a statistical value of the minimum temperature in each target time slot on multiple days during a predetermined period. In winter, if the indoor temperature is too low, it can be harmful to health, so the control unit 13 suggests air conditioning control based on the first temperature characteristic value related to the minimum temperature. On the other hand, if it is not currently winter, the first temperature characteristic value is a statistical value of the maximum temperature in each target time slot on multiple days during a predetermined period. In summer or in intermediate periods that are neither winter nor summer (e.g., April, May, and October), if the indoor temperature is too high, the risk of heatstroke increases, so the control unit 13 suggests air conditioning control based on the first temperature characteristic value related to the maximum temperature.

[0060] The control unit 13 may use the first temperature feature value associated with the highest temperature throughout the year, or may use the first temperature feature value associated with the lowest temperature throughout the year. In this way, it is possible to make proposals using the same criteria throughout the year, including during the intermediate seasons (for example, a comparison table or trained model for proposals, which will be described later). For example, if the air conditioner 20 is located in a polar region, the first temperature feature value associated with the lowest temperature may be used, and if the air conditioner 20 is not located in a polar region, the first temperature feature value associated with the highest temperature may be used.

[0061] Returning to the flowchart of FIG. 2, the control unit 13 acquires a second temperature characteristic value (step S120). The second temperature characteristic value represents the predicted maximum temperature or minimum temperature for the target time period. The target time period is a time period that includes a future time point. For example, the target time period may be a time period after the current time point on the current day, excluding the current time point, or may be a time period that includes both the current time point and a future time point. The control unit 13 sets the minimum or maximum value of the predicted temperature over the target time period as the second temperature characteristic value.

[0062] In one example, the second temperature characteristic value is adjusted to the first temperature characteristic value. If the first temperature characteristic value is a statistical value of the maximum temperature for each of multiple days in a specified period, the second temperature characteristic value is a predicted maximum temperature for the target time period. On the other hand, if the first temperature characteristic value is a statistical value of the minimum temperature for each of multiple days in a specified period, the second temperature characteristic value is a predicted minimum temperature for the target time period. For example, if the first temperature characteristic value is an average value of the maximum temperature for each of the multiple days in a specified period, the second temperature characteristic value is a predicted maximum temperature for the target time period.

[0063] In another example, the control unit 13 uses a second temperature characteristic value that differs depending on the current season. For example, if it is not currently winter, the second temperature characteristic value is the predicted maximum temperature for the target time period, and if it is currently winter, the second temperature characteristic value is the predicted minimum temperature for the target time period.

[0064] In another example, the second temperature characteristic value is set independently of the first temperature characteristic value. For example, the first temperature characteristic value may be the average maximum temperature for a predetermined period, and the second temperature characteristic value may be the predicted minimum temperature for a target time period.

[0065] Next, the control unit 13 determines at least one of a proposed mode related to the operating mode of the air conditioning operation of the air conditioner 20 and a proposed temperature related to the set temperature of the proposed mode for the target time period based on the first temperature characteristic value and the second temperature characteristic value (step S130).The control unit 13 then presents at least one of the determined proposed mode and proposed temperature to the user (step S140).

[0066] The control unit 13 may determine and present one of the suggested mode and the suggested temperature, or may determine and present both the suggested mode and the suggested temperature. Examples of the suggested mode include, but are not limited to, a heating mode, a cooling mode, or operation off.

[0067] In one example of step S130, the control unit 13 determines the proposed mode and the proposed temperature by comparing the first temperature feature value and the second temperature feature value with at least one predetermined threshold. In another example, the control unit 13 determines the proposed mode and the proposed temperature by checking the first temperature feature value and the second temperature feature value against a lookup table stored in the memory unit 12. In yet another example, the control unit 13 determines the proposed mode and the proposed temperature by machine learning technology, for example, by inputting the first temperature feature value and the second temperature feature value into a trained model.

[0068] When presenting a suggested mode or suggested temperature, if the server 10 is an information processing device, the control unit 13 of the server 10 causes the presentation unit 24 of the air conditioner 20 or the presentation unit 34 of the terminal device 30 to present the suggested mode or suggested temperature via the communication unit 11. If the air conditioner 20 is an information processing device, the control unit 23 of the air conditioner 20 may cause the presentation unit 24 of the air conditioner 20 to present the suggested mode or suggested temperature, or may cause another device, such as the presentation unit 34, to present the suggested mode or suggested temperature via the communication unit 21 of the air conditioner 20. Similarly, if the terminal device 30 is an information processing device, the control unit 33 of the terminal device 30 may cause the presentation unit 34 of the terminal device 30 to present the suggested mode or suggested temperature, or may cause another device, such as the presentation unit 24, to present the suggested mode or suggested temperature via the communication unit 31 of the terminal device 30.

[0069] The control unit 13 can display numbers, letters, images, videos, etc., representing the proposed mode or proposed temperature on the display of the presentation unit 24, 34. The control unit 13 can also play audio based on the numbers or letters representing the proposed mode or proposed temperature from the speaker of the presentation unit 24, 34.

[0070] 3 is an example of a UI that presents a suggested mode and a suggested temperature in the first embodiment. In the example shown in FIG. 3, the suggested mode and the suggested temperature are presented on the UI of the related application 36 via the presentation unit 34 of the terminal device 30. In area R1 of the screen SC1 in FIG. 3, a suggested mode of "cooling" and a suggested temperature of "27°C" for a target time period in the evening (for example, from 9:00 PM to 6:00 AM the next morning) are presented. In addition to the suggested mode and the suggested temperature, the target time period and the location of the air conditioner 20 can also be presented to the user.

[0071] In one example, the control unit 13 further causes the UI to present a button for starting air conditioning operation as proposed. FIG. 4 shows another example of a UI presenting a proposed mode and a proposed temperature in embodiment 1. A button "Start sleep" is presented in area R2 of the screen SC2 shown in FIG. 4. When this button is pressed by the user, the air conditioner 20 is caused to operate in the proposed target time period (from 9:00 PM to 6:00 AM the next morning) with the proposed mode (cooling) as the operation mode and the proposed temperature (27°C) as the set temperature. Note that when causing the air conditioner 20 to operate air conditioning operation as proposed, the control unit 13 may store the operation time, the proposed mode, and the proposed temperature in the memory unit 12.

[0072] As described above, the information processing device can make suggestions for air conditioning operation based on the first temperature feature value, which represents the temperature trend over a predetermined period of time in the past, and the second temperature feature value, which represents the predicted temperature for a target time period. This suggestion method can provide appropriate suggestions for at least one of the air conditioning control operating mode and set temperature. Furthermore, by using these first temperature feature value and second temperature feature value, it is possible to automatically determine a suggested mode and suggested temperature that are comfortable for the user in winter, summer, or an intermediate period that is neither winter nor summer (e.g., April, May, and October).

[0073] In one embodiment, the control unit 13 also suggests the air volume and humidity for the air conditioning operation of the air conditioner 20. For example, the memory unit 12 stores a comparison table showing the relationship between the first temperature feature value, the second temperature feature value, and the air volume and humidity for the air conditioning operation, or a trained model that has learned this relationship. The control unit 13 can use this comparison table or trained model to determine a suggested air volume or suggested humidity and present it to the user. Furthermore, when the user presses a button to start the air conditioning operation as suggested, the control unit 13 can operate the air conditioner 20 according to the suggested air volume or suggested humidity.

[0074] In one embodiment, the control unit 13 acquires weather information before step S110. For example, as shown in Fig. 5, the control unit 13 may execute steps S210 to S230 before step S110.

[0075] To obtain weather information, the control unit 13 obtains identification information for identifying the air conditioner 20 or the user (step S210), and determines the location of the air conditioner 20 based on the identification information (step S220). The identification information may be, for example, the user's identification number, the identification number of the air conditioner 20, the identification number of the terminal device 30, the telephone number of the terminal device 30, etc. The identification information is associated with the location of the corresponding air conditioner 20 and stored in the memory unit 12.

[0076] Generally, the territory of a country or a country-like organization can be hierarchically divided into multiple regions administratively, geographically, or meteorologically. For example, the territory of Japan is administratively divided into 47 large regions called "prefectures," and each "prefecture" is further divided into multiple smaller regions called "cities, towns, and villages." In this disclosure, a location may be a region including one "prefecture," one "city, town, and village," or multiple "cities, towns, and villages." The location of the air conditioner 20 may be expressed by the place name of the region, at least part of the address, the area code used by meteorological stations, a postal code, or the like.

[0077] After determining the location, the control unit 13 acquires weather information including the temperature at the location and the predicted temperature for the location from the air conditioner 20 or the external information source 40 (step S230). For example, the control unit 13 acquires weather information from a meteorological station, which is the external information source 40, via the communication unit 11.

[0078] Figure 6 is an example of weather information in embodiment 1. The weather information shown in Figure 6 includes at least one area name, area code, temperature measured in the area, and time of measurement. For example, the weather information includes a temperature of "34°C" measured at 12:00 on July 24, 2023 in an area whose name is "Kyoto" and whose area code is "61286" (hereinafter referred to as "Kyoto").

[0079] Suppose the control unit 13 determines, based on the user's identification number, that the area code for the location of the air conditioner 20 is "61286." By matching the area code "61286" with weather information, the control unit 13 can obtain temperatures measured at various times in the area "Kyoto." For example, in step S110, the control unit 13 can extract the maximum temperature for each day of the previous month from the weather information using the area code. Then, based on the extracted data, the control unit 13 calculates the average value of the maximum temperatures for each day of the previous month, and sets this as the first temperature feature value.

[0080] Similarly, the weather information further includes a predicted temperature for the location. For example, the weather information may include a predicted temperature for the area "Kyoto" at 9:00 p.m. on July 24, 2024 (not shown). In step S120, the control unit 13 extracts predicted temperatures for the target time period by comparing the weather information with the area code or area name, and sets the minimum or maximum value of the extracted predicted temperatures as the second temperature characteristic value.

[0081] It should be noted that if previously acquired weather information such as the previous temperature can be acquired from the storage unit 12, it is not necessary to acquire it again from the external information source 40.

[0082] In this way, the weather information used in the proposed method can be obtained from an external information source 40 or the like.

[0083] Second Embodiment <Comparison table for proposals> In the second embodiment, the information processing device can determine at least one of the proposed mode and the proposed temperature using the lookup table.

[0084] In the second embodiment, the storage unit 12 of the server 10 as an information processing device stores a comparison table showing the relationship between the first temperature feature value, the second temperature feature value, and the operating mode and set temperature of the air conditioning operation. In step S130, the control unit 13 of the server 10 as an information processing device reads out this comparison table from the storage unit 12 and collates it.

[0085] More specifically, in step S130, the control unit 13 can determine, as the proposed mode, an operation mode corresponding to a combination of the first temperature feature value and the second temperature feature value by comparing the first temperature feature value and the second temperature feature value with the lookup table. Also, the control unit 13 can determine, as the proposed temperature, a set temperature corresponding to a combination of the first temperature feature value and the second temperature feature value by comparing the first temperature feature value and the second temperature feature value with the lookup table.

[0086] Fig. 7A is an example of a comparison table in embodiment 2. In the example of Fig. 7A, the first temperature characteristic value and the second temperature characteristic value are each divided into multiple ranges using the same threshold. For example, the second temperature characteristic value is divided into five ranges: "less than 0°C," "0°C or more and less than 10°C," "10°C or more and less than 20°C," "20°C or more and less than 30°C," and "30°C or more."

[0087] In the comparison table, each combination of the range to which the first temperature feature value belongs and the range to which the second temperature feature value belongs corresponds to a preset proposed mode and proposed temperature. For example, the combination of a first temperature feature value less than 0°C and a second temperature feature value between 0°C and 10°C corresponds to the proposed mode "heating mode" and the proposed temperature "T21." Furthermore, the combination of a first temperature feature value between 10°C and 20°C and a second temperature feature value between 10°C and 20°C corresponds to the proposed mode "operation off." Although a set temperature is not required when operation is off, a set temperature can also be set for the proposed mode "operation off."

[0088] 7B is another example of a comparison table in the second embodiment. In the example of FIG. 7B, the second temperature feature value is divided into multiple ranges using different thresholds for different first temperature feature values. For example, for a first temperature feature value A1 below 0°C, the second temperature feature value A2 is divided into multiple ranges using six thresholds: B11, B21, B31, B41, B51, and B61. On the other hand, for a first temperature feature value A1 between 0°C and 10°C, the second temperature feature value A2 is divided into multiple ranges using six thresholds: B12, B22, B32, B42, B52, and B62.

[0089] In the comparison table of FIG. 7B, the combination of a first temperature feature value of 10°C or more and less than 15°C and a second temperature feature value of less than B14 corresponds to the proposed mode "heating mode" and the proposed temperature "T14." The combination of a first temperature feature value of 10°C or more and less than 15°C and a second temperature feature value of B34 or more and less than B44 corresponds to the proposed mode "operation off." The combination of a first temperature feature value of 30°C or more and a second temperature feature value of B38 or more and less than B48 corresponds to the proposed mode "cooling mode" and the proposed temperature "T48."

[0090] 7B, the first temperature feature value can also be divided into multiple ranges using different thresholds for different second temperature feature values, allowing for more detailed settings of the proposed modes and proposed temperatures.

[0091] In one embodiment, the control unit 13 divides a day into multiple target time periods of equal length. For example, a day may be divided into four target time periods: from midnight to 6:00, from 6:00 to 12:00, from 12:00 to 18:00, and from 18:00 to 24:00. Alternatively, a day may be divided into different time periods. For example, a day may be divided into five target time periods: from 6:00 to 11:00 (morning), from 11:00 to 13:00 (daytime), from 13:00 to 18:00 (afternoon), from 18:00 to 21:00 (night), and from 21:00 to 6:00 the next day (sleep time). In this embodiment, the memory unit 12 stores a comparison table for suggesting air conditioning operation corresponding to each target time period. That is, each of the multiple comparison tables represents the relationship between the first and second temperature feature values ​​and the operating mode and set temperature of the air conditioning operation for a different target time period. In step S130, the control unit 13 reads and uses the corresponding comparison table from the memory unit 12 based on the target time period to be suggested.

[0092] By using the above-described comparison table, the control unit 13 can determine the proposed mode and proposed temperature corresponding to the combination based on the first temperature characteristic value and the second temperature characteristic value.

[0093] Third Embodiment <Pre-trained model for proposals> In the third embodiment, the information processing device can determine at least one of the proposed mode and the proposed temperature using machine learning techniques and a trained model.

[0094] In the third embodiment, the memory unit 12 of the server 10 serving as an information processing device stores at least one trained model for making suggestions regarding air conditioning operation. The trained model has learned the relationship between the first temperature feature value, the second temperature feature value, and at least one of the operating mode and set temperature of the air conditioning operation. In step S130, the control unit 13 of the server 10 serving as an information processing device can determine, as the proposed mode, the operating mode estimated by the trained model based on the first temperature feature value and the second temperature feature value. Furthermore, in step S130, the control unit 13 can determine, as the proposed temperature, the set temperature estimated by the trained model based on the first temperature feature value and the second temperature feature value.

[0095] Fig. 8 is an example of a trained model in the third embodiment. In the example shown in Fig. 8, the trained model has learned the relationship between the first temperature feature value, the second temperature feature value, and the operating mode and set temperature of the air conditioning operation. By using such a trained model, it is possible to obtain both the proposed mode and the proposed temperature in one trained model.

[0096] In one example, the trained model M is a multi-output neural network. This multi-output neural network learns the relationship between the first temperature feature values, the second temperature feature values, the operation modes, and the set temperatures using input data (teaching data) including a plurality of different first temperature feature values, a plurality of different second temperature feature values, operation modes of air conditioning operation corresponding to a plurality of different combinations of the first temperature feature values ​​and the second temperature feature values, and set temperatures corresponding to each of the plurality of different combinations. In step S130, the trained model M can simultaneously estimate the proposed mode and the proposed temperature based on the first temperature feature values ​​and the second temperature feature values.

[0097] In one embodiment, the information processing device executes the proposal method using multiple trained models. FIG. 9 shows an example of a first trained model and a second trained model in embodiment 3. In the example of FIG. 9, the storage unit 12 stores a first trained model M1 for proposing a proposed mode and a second trained model M2 for proposing a proposed temperature.

[0098] The first trained model M1 is a classification model that learns the relationship between the first temperature feature values, the second temperature feature values, and the operation modes using input data (teacher data) including a plurality of different first temperature feature values, a plurality of different second temperature feature values, and operation modes of air conditioning operation corresponding to each of a plurality of different combinations of the first temperature feature values ​​and the second temperature feature values. In step S130, the first trained model M1 estimates the proposed mode based on the first temperature feature values ​​and the second temperature feature values.

[0099] The second trained model M2 is a regression model that learns the relationship between the first temperature feature values, the second temperature feature values, and the set temperature using input data (teacher data) including a plurality of different first temperature feature values, a plurality of different second temperature feature values, and set temperatures corresponding to each of a plurality of different combinations of the first temperature feature values ​​and the second temperature feature values. In step S130, the second trained model M2 estimates the proposed mode based on the first temperature feature values ​​and the second temperature feature values. Note that in step S130, the first temperature feature values ​​and the second temperature feature values ​​input to the first trained model M1 are the same as the first temperature feature values ​​and the second temperature feature values ​​input to the second trained model M2.

[0100] The training data used to train the trained model M, the first trained model M1, and the second trained model M2 may include the average temperature for a certain period in the past, the maximum or minimum temperature for a specific time period after that certain period, and the operating mode and set temperature set for that specific time period. Furthermore, the training data may include not only past actual measured values ​​and set values, but also artificially set periods, average temperatures, time periods, maximum or minimum temperatures, and operating modes and set temperatures.

[0101] In one embodiment, a day is divided into multiple target time periods, and the memory unit 12 stores a trained model for proposing air conditioning operation corresponding to each target time period. In this case, each trained model has learned the relationship between the first temperature feature value, the second temperature feature value, and the air conditioning operation mode and / or set temperature for a different target time period. In step S130, the control unit 13 selects a trained model corresponding to the target time period to be proposed, and determines the proposed mode and proposed temperature using the selected trained model.

[0102] By using the trained model described above, the control unit 13 can determine the proposed mode and proposed temperature based on the first temperature feature value and the second temperature feature value through machine learning.

[0103] The input data used to train the trained model may include data related to air conditioning operation in addition to the first temperature feature value, second temperature feature value, operation mode, and set temperature described above. For example, the server may generate the trained model using input data including indoor humidity, outdoor humidity, weather information, data related to the amount of clothing the user is wearing, bedding used, etc. The trained model generated in this manner has learned the relationship between the first temperature feature value, the second temperature feature value, and humidity, weather information, etc. The information processing device can use the trained model generated in this manner to determine the set mode or set temperature taking into account humidity, weather information, etc.

[0104] Fourth Embodiment <Proposal and modification based on user's thermal insulation information> In the fourth embodiment, the information processing device can modify the suggested temperature based on heat retention information including the amount of clothing the user is wearing, and can provide a more appropriate suggested temperature. For example, if the user is wearing thick clothing in winter, the user is likely to feel relatively hot, so the information processing device lowers the suggested temperature.

[0105] In the fourth embodiment, the information processing device uses the CLo value (also called the CLo value) as the amount of clothing worn to correct the suggested temperature, but other definitions or standards for the amount of clothing worn may also be used. Generally, the CLo value is defined as the amount of insulation required to maintain the skin temperature of a person sitting in a chair at 33°C in a room with a temperature of 21°C, a relative humidity of 50% or less, and a wind speed of 5 cm / s. Here, insulation includes not only clothing but also bedding, etc., and therefore the amount of clothing worn in the present disclosure also takes into account the influence of bedding, etc.

[0106] Fig. 10 is a flowchart of an example of a suggestion method according to embodiment 4. In the example of Fig. 10, control unit 13 of server 10 as an information processing device executes steps S310 to S330 before presenting a suggested temperature (step S140).

[0107] In the proposed method, the control unit 13 acquires a user input including thermal insulation information related to at least one of the user's clothing and bedding (step S310). For example, the user input including the thermal insulation information can be acquired via the UI of the related application 36 of the terminal device 30.

[0108] FIG. 11A shows an example of a UI for acquiring thermal information in the fourth embodiment. In area R3 of screen SC3 shown in FIG. 11A, a "Bedding Settings" button and a "Clothing Settings" button for acquiring thermal information are displayed. When the "Bedding Settings" button is pressed, the UI transitions from screen SC3 to screen SC4 shown in FIG. 11B. Via the UI shown on screen SC4, the user can input thermal information such as the type of mattress bedding to be used, the type of comforter bedding, and the number of comforters. In other words, the thermal information includes at least one of the type of mattress bedding, the type of comforter bedding, and the number of comforters. For example, the thermal information may include "mattress pad (cotton, linen)" or "one duvet."

[0109] When the "Clothing Settings" button shown on screen SC3 is pressed, the UI transitions from screen SC3 to screen SC5 shown in FIG. 11C. Through the UI shown on screen SC5, the user can input the type of clothing they are wearing. For example, the thermal insulation information may include "T-shirt (short sleeves)" and "jersey (long pants)."

[0110] When the terminal device 30 acquires a user input including thermal insulation information via the UI of the related application 36, the terminal device 30 transmits the user input to the server 10 as an information processing device. Then, the control unit 13 calculates the amount of clothing worn by the user based on the thermal insulation information acquired from the terminal device 30 (step S320).

[0111] In one embodiment, the storage unit 12 stores a Claw value corresponding to each item of thermal insulation information. For example, the storage unit 12 stores a comparison table of various thermal insulation information and the Claw value corresponding to each item of thermal insulation information. The control unit 13 calculates the sum of the Claw values ​​corresponding to the acquired thermal insulation information as the amount of clothing worn by the user.

[0112] Next, the control unit 13 modifies the suggested temperature based on the calculated amount of clothing worn (step S330). Generally, when the amount of clothing worn is high for the same indoor temperature, for example, when the user wears thick clothes or a duvet, the user tends to feel relatively hot. Therefore, the control unit 13 modifies the suggested temperature determined in step S130 so that the suggested temperature decreases as the amount of clothing worn increases. In one example, the control unit 13 modifies the suggested temperature using a mathematical formula or a comparison table that expresses the relationship between the amount of clothing worn and the amount of modification to the suggested temperature (e.g., +0.5°C, -1°C). Then, in step S140, the control unit 13 presents the modified suggested temperature.

[0113] Note that steps S310 and S320 may be performed before steps S330 and S140, and may be performed, for example, before step S130 or step S110.

[0114] This completes the process of correcting the suggested temperature based on the user's clothing and bedding, making it possible to present a more appropriate suggested temperature.

[0115] Furthermore, if the above-mentioned comparison table for suggestions or trained model has already been generated taking into account thermal insulation information, a suggested temperature that takes into account the user's thermal insulation information can be presented to the user without performing steps S310 to S330.

[0116] Fifth Embodiment <Updated based on user feedback> In the fifth embodiment, the information processing device can acquire user feedback regarding the air conditioning operation performed, and update the comparison table for proposals or the trained model based on the acquired user feedback.

[0117] 12 is a flowchart of an example of a proposal method in embodiment 5. When a proposed mode or proposed temperature is presented and operation is to be performed as proposed, control unit 13 of server 10 as an information processing device further performs steps S410 to S430 after step S140.

[0118] After presenting the proposal, the control unit 13 performs air conditioning operation according to the proposed mode and proposed temperature during the target time period (step S410). For example, when the "Start sleep" button shown in Fig. 4 is pressed, the control unit 13 causes the air conditioner 20 to perform air conditioning operation according to the proposed mode (cooling) and proposed temperature (27°C) during the target time period. In one example, the server 10 as an information processing device or the air conditioner 20 stores the proposed mode and proposed temperature that were operated in the memory unit 12 or the memory unit 22.

[0119] The control unit 13 acquires user feedback including thermal sensation information regarding the thermal sensation felt by the user for the proposed operating mode and proposed temperature (step S420). The thermal sensation information is information that represents the thermal sensation felt by the user who is or was in the controlled space of air conditioning operation. For example, the thermal sensation information may be expressed in three levels, such as "hot," "just right," and "cold," or in five levels, such as "hot," "slightly hot," "just right," "slightly cold," and "cold." Alternatively, the thermal sensation information may be expressed in two options, such as "comfortable" and "uncomfortable."

[0120] In one embodiment, during or after the proposed air conditioning operation, the control unit 13 obtains user feedback about the air conditioning operation via the UI of the associated application 36 of the terminal device 30. For example, the day after the air conditioner 20 performs air conditioning operation in the evening according to the proposed mode and proposed temperature, the control unit 13 causes the terminal device 30 to present a UI to prompt the user to input feedback.

[0121] FIG. 13 shows an example of a UI for acquiring user feedback in the fifth embodiment. A UI for inputting details of the air conditioning operation performed during the target time period (e.g., a proposed mode and a proposed temperature) is presented in area R4 of screen SC6 shown in FIG. 13. A UI for inputting user feedback of thermal sensation information is presented in area R5 of screen SC6. In this example, when user feedback is input via the UI, the terminal device 30 transmits the input details of the air conditioning operation and the user feedback to the server 10. Note that when the radio button "No air conditioning" in area R4 is selected, the control unit 13 determines that the air conditioning operation was not performed during the target time period and processes this as a proposed mode of "operation off."

[0122] In one embodiment, the control unit 13 acquires the details of the air conditioning operation performed by means other than user input. For example, when the control unit 13 causes the air conditioner 20 to perform air conditioning operation as proposed, the control unit 13 may store the operation time, the proposed mode, and the proposed temperature in the storage unit 12. Alternatively, the control unit 13 may acquire the operating mode and set temperature (i.e., the proposed mode or proposed temperature) performed by inquiring of the air conditioner 20 or the terminal device 30. In such a case, it is not necessary for the user to input the details of the air conditioning operation performed.

[0123] 14 shows an example of a UI for obtaining user feedback in embodiment 5. A UI for inputting details of the air conditioning operation performed is presented in area R6 of screen SC7 shown in FIG. 14. When the radio button "Performed as suggested" in area R6 is selected, the control unit 13 obtains the suggested details from the memory unit 12, the air conditioner 20, or the terminal device 30.

[0124] In one embodiment, the terminal device 30 is a wearable device worn by the user and includes sensors capable of measuring the user's body temperature and heart rate. The control unit 13 acquires the user's body temperature and heart rate from the terminal device 30 and can automatically estimate the thermal sensation felt by the user based on the user's body temperature and heart rate. Furthermore, when the user is wearing a wearable device other than the terminal device 30, the terminal device 30 can receive the user's body temperature and heart rate from the wearable device and transfer them to the server 10. In this way, the control unit 13 can acquire user feedback including thermal sensation information without the user having to input feedback.

[0125] For example, normal ranges are provided for the user's body temperature and heart rate. When the control unit 13 determines that both the user's body temperature and heart rate are higher than the normal ranges, it infers that the user feels hot and sets the thermal sensation information to "hot." When the control unit 13 determines that both the user's body temperature and heart rate are within the normal ranges, it infers that the user feels neither hot nor cold and sets the thermal sensation information to "just right." When the control unit 13 determines that the user's body temperature is lower than the normal ranges and the heart rate is higher than the normal ranges, it infers that the user feels cold and sets the thermal sensation information to "cold."

[0126] Next, the control unit 13 updates the comparison table or trained model used to determine at least one of the proposed operating mode and the proposed temperature based on the thermal sensation information (step S430). For example, if the thermal sensation information is "hot," the control unit 13 updates the comparison table or trained model for proposal to lower the proposed temperature. On the other hand, if the thermal sensation information is "cold," the control unit 13 updates the comparison table or trained model for proposal to raise the proposed temperature. The updating of the comparison table and trained model will be described in more detail below.

[0127] <Update of comparison table based on user feedback> When the control unit 13 determines the content of the suggestion using a comparison table, it can update the comparison table based on the thermal sensation information in step S430. Fig. 15A is an overall flowchart of an example of step S430 for updating the comparison table, and Figs. 15B to 15E are flowcharts of an example of part of step S430 in the fifth embodiment.

[0128] 15A to 15E, the thermal sensation information is "hot," "just right," or "cold," but is not limited to these items. Even if thermal sensation information with a different definition is used, the comparison table can be updated in a similar manner.

[0129] As shown in Fig. 15B, in step S430, the control unit 13 first determines the proposed mode in which the air conditioner was operated (step S431). If the proposed mode in which the air conditioner was operated is the "heating mode," the control unit 13 performs steps S432 to S438 shown in Fig. 15C. If the proposed mode in which the air conditioner was operated is the "cooling mode," the control unit 13 performs steps S435 and S439 to S444 shown in Fig. 15D. If the proposed mode in which the air conditioner was operated is the "operation off," the control unit 13 performs steps S435 and S445 to S447 shown in Fig. 15E.

[0130] 15C, after determining that the proposed mode operated is the heating mode, the control unit 13 further determines the thermal sensation information included in the user feedback (step S432). If the thermal sensation information is "just right," it is considered that the proposed mode and the proposed temperature already match the user's preferences, and therefore the update process is terminated.

[0131] If the thermal sensation information is "hot", the control unit 13 further determines whether the proposed temperature is within a settable range (step S433). The settable range is set to a range of temperatures that can be set during normal use of the air conditioner 20, and can be set separately for the heating mode and the cooling mode. For example, the settable range for the heating mode may be 15°C to 30°C, 17°C to 29°C, or 18°C ​​to 27°C.

[0132] If the proposed temperature is within the settable range for heating, the control unit 13 lowers the proposed temperature based on the first and second temperature characteristic values ​​(step S434). For example, the control unit 13 lowers the proposed temperature by 0.5°C or 1°C each time step S434 is performed.

[0133] Then, the control unit 13 determines the part in the lookup table that needs to be updated (hereinafter referred to as the "update part"), and updates the lookup table so as to rewrite the proposed temperature corresponding to the update part to the proposed temperature lowered in step S434 (step S435). That is, when the proposed operating mode is the heating mode and the thermal sensation information indicates hot, the control unit 13 updates the lookup table so as to lower the proposed temperature for the target time period based on the first temperature feature value and the second temperature feature value within the settable range.

[0134] As described above, the comparison table sets a suggested mode corresponding to each combination of the first temperature feature value and the second temperature feature value. If the corresponding suggested mode is a "heating mode" or a "cooling mode," a suggested temperature is also set. When updating the comparison table, it is not necessary to update the entire table; it is sufficient to update at least the portion related to user feedback during processing. For example, the control unit 13 may update the portion corresponding to the combination of the first temperature feature value and the second temperature feature value that is the basis for determining the suggested mode or suggested temperature.

[0135] In one example, the first and second temperature feature values ​​that serve as the basis for the proposed mode and proposed temperature are stored in memory unit 12, memory unit 22, or memory unit 32. In step S430, control unit 13 acquires the first and second temperature feature values ​​from these memories and identifies the part to be updated. In another example, information indicating the combination of the first and second temperature feature values ​​that serve as the basis, such as the identification number of a cell in a lookup table, is stored along with the proposed mode and proposed temperature. In step S430, control unit 13 acquires the cell identification number, etc., and identifies the part to be updated.

[0136] On the other hand, if the proposed mode is the heating mode and the thermal sensation information is "hot," but the proposed temperature is outside the settable range, it is considered that the room temperature is sufficiently warm without heating operation. Therefore, in this case, the control unit 13 changes the proposed mode from the heating mode to operation off (step S436). Then, in step S435, the control unit 13 updates the comparison table so that the proposed mode corresponding to the updated part is rewritten to operation off.

[0137] If the proposed operating mode is the heating mode and the thermal sensation information is "cold," the control unit 13 further determines whether the proposed temperature is within the settable range (step S437). If the proposed temperature is within the settable range, the control unit 13 increases the proposed temperature based on the first temperature characteristic value and the second temperature characteristic value (step S438). As in step S434, the control unit 13 may increase the proposed temperature by 0.5°C or 1°C each time step S438 is performed.

[0138] Then, in step S435, the control unit 13 updates the comparison table so as to rewrite the proposed temperature corresponding to the updated portion to the proposed temperature increased in step S438. That is, when the proposed operating mode is the heating mode and the thermal sensation information indicates cold, the control unit 13 updates the comparison table so as to increase the proposed temperature for the target time period based on the first temperature feature value and the second temperature feature value within the settable range.

[0139] On the other hand, if the proposed temperature is already the upper limit of the settable range for the heating mode ("NO" in step S437), the control unit 13 ends the process without updating the lookup table.

[0140] 15D, after determining that the proposed mode operated is the cooling mode, the control unit 13 further determines the thermal sensation information included in the user feedback (step S439). If the thermal sensation information is "just right," it is considered that the proposed mode and the proposed temperature already match the user's preferences, and therefore the update process is terminated.

[0141] If the thermal sensation information is "cold", the control unit 13 further determines whether the proposed temperature is within a settable range (step S440). The settable range for the cooling mode may be, for example, 15°C to 30°C, 17°C to 29°C, or 18°C ​​to 27°C. Note that the settable range for the cooling mode and the settable range for the heating mode may be the same or different.

[0142] If the proposed temperature is within the settable range for cooling, the control unit 13 raises the proposed temperature based on the first temperature feature value and the second temperature feature value (step S441). Then, in step S435, the control unit 13 updates the comparison table so as to rewrite the proposed temperature corresponding to the updated location to the proposed temperature raised in step S441. That is, if the proposed operating mode is cooling mode and the thermal sensation information indicates cold, the control unit 13 updates the comparison table so as to raise the proposed temperature for the target time period based on the first temperature feature value and the second temperature feature value within the settable range.

[0143] On the other hand, if the thermal sensation information is "cold" but the suggested temperature is not within the settable range, it is considered that the room temperature is cool enough without performing cooling operation. Therefore, in this case, the control unit 13 corrects the suggested mode from cooling mode to operation off (step S442). Then, in step S435, the control unit 13 updates the comparison table so that the suggested mode corresponding to the updated part is rewritten to operation off.

[0144] If the proposed mode operated is the cooling mode and the thermal sensation information is "hot," the control unit 13 further determines whether the proposed temperature is within the settable range (step S443). If the proposed temperature is within the settable range, the control unit 13 lowers the proposed temperature based on the first temperature characteristic value and the second temperature characteristic value (step S444). Then, in step S435, the control unit 13 updates the comparison table so as to rewrite the proposed temperature corresponding to the updated location to the proposed temperature lowered in step S444. In other words, if the proposed mode operated is the cooling mode and the thermal sensation information indicates "hot," the control unit 13 updates the comparison table so as to lower the proposed temperature for the target time period based on the first temperature characteristic value and the second temperature characteristic value within the settable range.

[0145] On the other hand, if the proposed temperature is already at the lower limit of the settable range for the cooling mode ("NO" in step S443), the control unit 13 ends the process without updating the lookup table.

[0146] 15E, after determining that the proposed mode operated is operation off, the control unit 13 further determines the thermal sensation information included in the user feedback (step S445). If the thermal sensation information is "just right," it is considered that the proposed mode and the proposed temperature already match the user's preferences, and therefore the update process is terminated.

[0147] If the thermal sensation information is "hot", the control unit 13 corrects the proposed mode to the cooling mode (step S446) and updates the comparison table so as to rewrite the proposed mode corresponding to the updated part to the cooling mode (step S435). That is, if the operated proposed mode is operation off and the thermal sensation information indicates hot, the control unit 13 updates the comparison table so as to correct the proposed mode for the target time period based on the first temperature feature value and the second temperature feature value to the cooling mode.

[0148] On the other hand, if the thermal sensation information is "cold", the control unit 13 corrects the proposed mode to the heating mode (step S447) and updates the comparison table so as to rewrite the proposed mode corresponding to the updated part to the heating mode (step S435). That is, if the operated proposed mode is operation off and the thermal sensation information indicates cold, the control unit 13 updates the comparison table so as to correct the proposed mode for the target time period based on the first temperature feature value and the second temperature feature value to the heating mode.

[0149] Note that when the proposed mode is corrected to the cooling mode in step S446, the control unit 13 may further set the proposed temperature to a default set temperature for the cooling mode. The default set temperature for the cooling mode may be, for example, 29°C, 28°C, or 27°C. Similarly, when the proposed mode is corrected to the heating mode in step S447, the control unit 13 may further set the proposed temperature to a default set temperature for the heating mode. The default set temperature for the heating mode may be, for example, 16°C, 18°C, or 21°C.

[0150] In this way, the suggestion table can be updated based on user feedback and user preferences can be learned.

[0151] <Updating trained models based on user feedback> When the control unit 13 determines the content of the proposal using machine learning technology and a trained model, it can update the trained model based on the thermal sensation information in step S430. In one embodiment, the control unit 13 generates new input data based on user feedback and re-trains the trained model using the new input data, thereby updating the trained model. Regarding the re-training, the control unit 13 may perform offline re-training after accumulating a certain amount of user feedback, or may perform online re-training each time at least one piece of user feedback is obtained.

[0152] In one embodiment, the control unit 13 updates the trained model by performing reinforcement learning on the trained model using user feedback. For example, the control unit 13 can optimize the trained model using techniques such as Q-learning and DQN (Deep Q-Network). When using Q-learning or DQN, the control unit 13 constructs a default value function by simulating a selection pattern of ideal behavior (proposed mode or proposed temperature). The control unit 13 then updates the value function by linking the comfort / discomfort of the user feedback (e.g., thermal sensation information such as "just right" / "hot" or "cold") to a reward. Furthermore, the control unit 13 can bias the value function when updating it to direct the user feedback of "hot" or "cold." In this way, the next time a suggestion is made, it can be more in line with the user feedback.

[0153] In this way, the trained model for suggestions can be updated based on user feedback and learn user preferences.

[0154] This completes the process of obtaining user feedback about the air conditioning operation and updating the suggestion table or trained model based on the user feedback. This allows the system to learn user preferences from user feedback and provide suggested modes or suggested temperatures that better suit the user's preferences.

[0155] Sixth Embodiment <Adjusting the proposed mode based on the outdoor air environment> In the sixth embodiment, the information processing device can modify the proposed mode based on the outdoor air environment. As described in the fifth embodiment, the information processing device can learn the user's preferences. However, depending on the user's preferences, an inappropriate proposed mode may be presented, such as cooling mode in winter or heating mode in summer. For example, even for a user who is sensitive to heat or prefers cold environments, a room temperature that is too low may be harmful to their health. The World Health Organization (WHO) strongly recommends that the minimum room temperature in winter be set to 18 degrees Celsius or higher to prevent health damage caused by the cold. Similarly, an environment that is too hot may be harmful to health. In the sixth embodiment, the information processing device learns the user's preferences while making suggestions that take the user's health into consideration. For example, the information processing device can modify the proposed mode using a second temperature feature value that represents the extreme value of the predicted temperature for the target time period.

[0156] 16 is a flowchart of an example of correcting a proposed mode in embodiment 6. Before presenting a proposed mode (step S140), the control unit 13 of the server 10 as an information processing device checks whether the proposed mode is appropriate, and executes steps S510 to S560 to correct an inappropriate proposal.

[0157] After determining the suggested mode or suggested temperature (step S130), the control unit 13 determines whether the second temperature characteristic value is equal to or greater than a first temperature threshold (step S510). The first temperature threshold is a reference value for determining whether the outdoor environment is hot enough to cause health problems, and may be, for example, 28°C, 29°C, or 30°C.

[0158] If the second temperature characteristic value is equal to or greater than the first temperature threshold, the cooling mode should be operated to prevent heat-related health hazards throughout the target time period. If the second temperature characteristic value is equal to or greater than the first temperature threshold, the control unit 13 further determines whether the proposed mode is cooling (step S520). If the second temperature characteristic value is equal to or greater than the first temperature threshold and the proposed mode is not cooling, the control unit 13 modifies the proposed mode to cooling mode (step S530). The control unit 13 may also set the proposed temperature to a default setting temperature for the cooling mode. For example, in step S530, the control unit 13 may set the proposed temperature to 29°C, 28°C, or 27°C.

[0159] On the other hand, if the second temperature characteristic value is equal to or greater than the first temperature threshold and the proposed mode is cooling, the control unit 13 presents the proposed mode to the user without modifying it.

[0160] If the second temperature characteristic value is lower than the first temperature threshold, the control unit 13 further determines whether the second temperature characteristic value is equal to or lower than the second temperature threshold (step S540). The second temperature threshold is lower than the first temperature threshold. The second temperature threshold is a reference value for determining whether the outside air environment is cold enough to be harmful to health, and may be, for example, 10°C, 5°C, or 0°C.

[0161] If the second temperature characteristic value is equal to or less than the second temperature threshold, the heating mode should be operated to prevent health damage due to the cold throughout the target time period. If the second temperature characteristic value is equal to or less than the second temperature threshold, the control unit 13 further determines whether the proposed mode is heating (step S550). If the second temperature characteristic value is equal to or less than the second temperature threshold and the proposed mode is not heating, the control unit 13 corrects the proposed mode to heating mode (step S550). The control unit 13 may also further set the proposed temperature to a default setting temperature for the heating mode. For example, in step S550, the control unit 13 may set the proposed temperature to 16°C, 18°C, or 21°C.

[0162] On the other hand, if the second temperature characteristic value is equal to or less than the second temperature threshold value and the proposed mode is heating, the control unit 13 presents the proposed mode to the user without modifying it.

[0163] Note that the control unit 13 can modify the proposed mode using a first temperature characteristic value that indicates a trend in past temperatures instead of or in addition to the second temperature characteristic value. For example, a third temperature threshold for determining whether the outdoor environment will be hot enough to cause health problems and a fourth temperature threshold for determining whether the outdoor environment will be cold enough to cause health problems may be set for the first temperature characteristic value.

[0164] FIG. 17A is an example of a comparison table in the sixth embodiment. In the comparison table, area R7 is an area where the proposed mode is fixed to heating mode, and area R8 is an area where the proposed mode is fixed to cooling mode. For example, when both the first temperature feature value and the second temperature feature value are less than 0°C, the proposed mode is fixed to heating mode. On the other hand, when both the first temperature feature value and the second temperature feature value are 30°C or higher, the proposed mode is fixed to cooling mode. Areas R7 and R8 can be defined by setting thresholds for the first temperature feature value and the second temperature feature value.

[0165] 17B is another example of a comparison table in the sixth embodiment. Similarly, in the comparison table, area R7 is an area where the proposed mode is fixed to heating mode, and area R8 is an area where the proposed mode is fixed to cooling mode. Areas R7 and R8 can be defined by setting thresholds for the first temperature feature value and the second temperature feature value. In this example, the second temperature feature value is divided into multiple ranges with different thresholds for different first temperature feature values, allowing for more detailed settings for the proposed mode and proposed temperature.

[0166] When the proposed mode is determined using a comparison table, the control unit 13 may update the comparison table so as to rewrite it with the modified proposed mode in step S530 or step S560. When the proposed mode is determined using a trained model, the control unit 13 may update the trained model by performing re-learning or reinforcement learning using the modified proposed mode in step S530 or step S560.

[0167] This completes the process of correcting the proposed mode based on the outdoor air environment. In this way, it is possible to learn the user's preferences while making suggestions that take the user's health into consideration. In addition, the corrected proposed mode can be used to update the suggestion comparison table or the trained model.

[0168] Seventh Embodiment <Presentation of the basis for the proposal> In the seventh embodiment, the information processing device also presents a notification regarding the first temperature characteristic value or the second temperature characteristic value. The first temperature characteristic value and the second temperature characteristic value can be considered as the basis for determining the proposed mode or the proposed temperature. By presenting the first temperature characteristic value or the second temperature characteristic value that serves as the basis for the proposal, the user's trust in the proposal can be increased.

[0169] FIG. 18 is a flowchart of an example of a proposal method according to the seventh embodiment. In the example of FIG. 18, the control unit 13 of the server 10 serving as an information processing device presents a notification related to at least one of the first temperature feature value and the second temperature feature value (step S610). For example, the control unit 13 presents the first temperature feature value or the second temperature feature value on the UI of the associated application 36 of the terminal device 30 via the communication unit 11 of the server 10. The first temperature feature value or the second temperature feature value may be presented together with the proposed mode or the proposed temperature, or may be presented on a different screen. The notification may further include meteorological information represented by the first temperature feature value or the second temperature feature value in addition to the numerical value of the first temperature feature value or the second temperature feature value.

[0170] 19A is an example of a UI that presents a notification related to the first temperature feature value or the second temperature feature value in the seventh embodiment. In area R4 of screen SC8 shown in FIG. 19A, a notification related to the second temperature feature value, "Tonight's predicted temperature is expected to be between 22°C and 24°C," is presented. Furthermore, if the proposed mode determined by control unit 13 based on the second temperature feature value is "driving off," a notification related to the proposed mode, "turning off the air conditioner and opening the windows might be just right!" is also presented on screen SC8.

[0171] 19B is another example of a UI presenting a notification related to the first or second temperature characteristic value in embodiment 7. Area R5 of screen SC9 shown in FIG. 19B presents the second temperature characteristic value, which is the predicted maximum temperature, and a notification related to the fact that the predicted maximum temperature is an unseasonable temperature. By presenting such a notification, the user realizes that the predicted temperature for the target time period is different from usual, increasing the likelihood that they will agree with the proposed mode or proposed temperature.

[0172] This completes the process of presenting a notification related to at least one of the first temperature characteristic value and the second temperature characteristic value. This can increase the user's confidence in the suggestion. Also, presenting the first temperature characteristic value or the second temperature characteristic value can make the user aware of unusual or unseasonable temperatures.

[0173] (Other embodiments) (Addendum) The above description of the embodiments discloses the following techniques.

[0174] (Technology 1) An information processing device that suggests air conditioning operation of an air conditioner includes a communication unit capable of acquiring weather information related to the temperature at the location of the air conditioner, a memory unit that accumulates the acquired weather information, and a control unit that controls the communication unit and the memory unit. The control unit acquires a first temperature feature value that represents a temperature trend over a predetermined past period based on the accumulated weather information, acquires a second temperature feature value that represents a predicted maximum temperature or a predicted minimum temperature for a target time period, and determines at least one of a proposed mode related to the operating mode of the air conditioning operation of the air conditioner and a proposed temperature related to the set temperature of the proposed mode for the target time period based on the first temperature feature value and the second temperature feature value, and presents at least one of the proposed mode and the proposed temperature.

[0175] Such an information processing device can provide an appropriate suggestion for at least one of the operating mode and temperature setting of air conditioning control.

[0176] (Technology 2) The information processing device according to Technology 1, wherein the first temperature characteristic value is a statistical value calculated based on the highest or lowest temperature for each of a plurality of days in the predetermined period.

[0177] Such a first temperature characteristic value makes it possible to more appropriately suggest at least one of the operating mode and temperature setting of the air conditioning control.

[0178] (Technology 3) The information processing device according to Technology 2, wherein the first temperature feature value is a statistical value related to the maximum temperature or minimum temperature in the target time period for each of a plurality of days in the predetermined period.

[0179] Such a first temperature characteristic value makes it possible to more appropriately suggest at least one of the operating mode and temperature setting of the air conditioning control.

[0180] (Technology 4) An information processing device according to Technology 3, wherein, when it is not currently winter, the first temperature characteristic value is a statistical value of the highest temperature in the target time period for each of a plurality of days in the specified period, and when it is currently winter, the first temperature characteristic value is a statistical value of the lowest temperature in the target time period for each of a plurality of days in the specified period.

[0181] Such a first temperature characteristic value makes it possible to more appropriately suggest at least one of the operating mode and temperature setting of the air conditioning control.

[0182] (Technology 5) The information processing device described in any one of Technologies 1 to 4, wherein the accumulated weather information includes the temperature at the location at regular intervals, and the control unit further calculates a statistical value of the highest temperature for each of the target time slots on multiple days in the specified period based on the accumulated weather information, and sets the calculation result as the first temperature feature value, or calculates a statistical value of the lowest temperature for each of the target time slots on multiple days in the specified period based on the accumulated weather information, and sets the calculation result as the first temperature feature value.

[0183] Such a first temperature characteristic value makes it possible to more appropriately suggest at least one of the operating mode and temperature setting of the air conditioning control.

[0184] (Technology 6) An information processing device described in any one of Technologies 1 to 5, wherein when the first temperature characteristic value is a statistical value of the highest temperature for each of multiple days in the specified period, the second temperature characteristic value is a predicted highest temperature for the target time period, and when the first temperature characteristic value is a statistical value of the lowest temperature for each of multiple days in the specified period, the second temperature characteristic value is a predicted lowest temperature for the target time period.

[0185] Such a second temperature characteristic value makes it possible to more appropriately suggest at least one of the operating mode and temperature setting of the air conditioning control.

[0186] (Technology 7) An information processing device described in any one of techniques 1 to 6, wherein if it is not currently winter, the second temperature feature value is the predicted maximum temperature for the target time period, and if it is currently winter, the second temperature feature value is the predicted minimum temperature for the target time period.

[0187] Such a second temperature characteristic value makes it possible to more appropriately suggest at least one of the operating mode and temperature setting of the air conditioning control.

[0188] (Technology 8) An information processing device described in any one of Technologies 1 to 7, wherein the control unit further acquires identification information for identifying the air conditioner or the user, determines the location of the air conditioner based on the identification information, and acquires the weather information including the temperature at the location and the predicted temperature for the location.

[0189] Such an information processing device can acquire accurate weather information regarding the air conditioner to be proposed.

[0190] (Technical 9) The storage unit stores a comparison table showing the relationship between the first temperature characteristic value, the second temperature characteristic value, and the operating mode and set temperature of the air conditioning operation, The information processing device described in any one of techniques 1 to 8, wherein the control unit determines an operating mode corresponding to a combination of the first temperature feature value and the second temperature feature value as the proposed mode by comparing the first temperature feature value and the second temperature feature value with the comparison table, or determines a set temperature corresponding to the combination as the proposed temperature.

[0191] According to such an information processing device, at least one of the proposed mode and the proposed temperature can be determined using the lookup table.

[0192] (Technology 10) The information processing device described in any one of Technologies 1 to 9, wherein the memory unit stores at least one trained model for making suggestions regarding air conditioning operation, the trained model having learned the relationship between the first temperature feature value, the second temperature feature value, and the operating mode and set temperature of air conditioning operation, and the control unit determines the operating mode estimated by the trained model based on the first temperature feature value and the second temperature feature value as the proposed mode, or determines the set temperature estimated by the trained model based on the first temperature feature value and the second temperature feature value as the proposed temperature.

[0193] According to such an information processing device, at least one of the proposed mode and the proposed temperature can be determined by the trained model.

[0194] (Technology 11) The information processing device described in Technology 10, wherein the memory unit stores a first trained model for proposing the proposed mode and a second trained model for proposing the proposed temperature, the first trained model is a classification model that learns the relationship between the first temperature feature value, the second temperature feature value, and the operating mode using input data including different first temperature feature values, different second temperature feature values, and air conditioning operation modes corresponding to different combinations of the first temperature feature value and the second temperature feature value, and the second trained model is a regression model that learns the relationship between the first temperature feature value, the second temperature feature value, and the set temperature using input data including different first temperature feature values, different second temperature feature values, and set temperatures corresponding to different combinations of the first temperature feature value and the second temperature feature value.

[0195] According to such an information processing device, the proposed mode and proposed temperature can be determined respectively using multiple trained models.

[0196] (Technology 12) The information processing device described in Technology 10, wherein the trained model is a multi-output neural network that learns the relationship between the first temperature feature value, the second temperature feature value, the operating mode, and the set temperature using input data including different first temperature feature values, different second temperature feature values, operating modes of air conditioning operation corresponding to different combinations of the first temperature feature value and the second temperature feature value, and set temperatures corresponding to the different combinations.

[0197] According to such an information processing device, the proposed mode and the proposed temperature can be determined using one trained model.

[0198] (Technology 13) The information processing device described in any one of technologies 10 to 12, wherein the control unit divides a day into a plurality of target time periods, the memory unit stores a comparison table or a learned model for making suggestions about air conditioning operation corresponding to each target time period, each of the comparison tables representing the relationship between the first temperature feature value and the second temperature feature value and the operating mode and set temperature of air conditioning operation for a different target time period, and each of the learned models learning the relationship between the first temperature feature value and the second temperature feature value and the operating mode and set temperature of air conditioning operation for a different target time period.

[0199] Such a trained model can more appropriately suggest at least one of the operating mode and set temperature of the air conditioning control.

[0200] (Technology 14) The control unit further acquires user input including thermal insulation information regarding at least one of the user's clothing and bedding, calculates the amount of clothing the user is wearing based on the thermal insulation information, and modifies the suggested temperature based on the amount of clothing, in an information processing device described in any one of Technologies 1 to 13.

[0201] According to such an information processing device, the suggested temperature can be corrected based on the clothing or bedding of the user, and a more appropriate suggested temperature can be provided.

[0202] (Technology 15) An information processing device described in any one of Technologies 1 to 14, wherein the memory unit stores at least one comparison table or trained model for suggesting air conditioning operation, and the control unit further performs air conditioning operation according to the proposed mode and the proposed temperature during the target time period, obtains user feedback including thermal sensation information regarding the thermal sensation felt by the user for the proposed mode and the proposed temperature operated, and updates the comparison table or trained model used to determine at least one of the proposed mode and the proposed temperature operated based on the thermal sensation information.

[0203] Such an information processing device can learn user preferences from user feedback, and can provide suggested modes or suggested temperatures that better suit the user's preferences.

[0204] (Technology 16) The control unit further updates the comparison table so as to lower the proposed temperature for the target time period based on the first temperature feature value and the second temperature feature value within a settable range when the proposed mode operated is a cooling mode or a heating mode and the thermal sensation information indicates that it is hot, or updates the comparison table so as to raise the proposed temperature for the target time period based on the first temperature feature value and the second temperature feature value within the settable range when the proposed mode operated is a cooling mode or a heating mode and the thermal sensation information indicates that it is cold.

[0205] According to such an information processing device, the comparison table for proposals can be updated based on feedback from the user.

[0206] (Technology 17) The control unit further updates the comparison table to correct the proposed mode for the target time period based on the first temperature feature value and the second temperature feature value to operation off when the proposed mode operated is a heating mode, the thermal sensation information indicates hot, and the proposed temperature operated is outside the settable range, or updates the comparison table to correct the proposed mode for the target time period based on the first temperature feature value and the second temperature feature value to operation off when the proposed mode operated is a cooling mode, the thermal sensation information indicates cold, and the proposed temperature operated is outside the settable range.

[0207] According to such an information processing device, the comparison table for proposals can be updated based on feedback from the user.

[0208] (Technology 18) The control unit further updates the comparison table so that, if the proposed mode operated is operation off and the thermal sensation information indicates hot, the proposed mode for the target time period based on the first temperature feature value and the second temperature feature value is corrected to cooling mode, or, if the proposed mode operated is operation off and the thermal sensation information indicates cold, the control unit updates the comparison table so that the proposed mode for the target time period based on the first temperature feature value and the second temperature feature value is corrected to heating mode. (Technology 18) The information processing device described in any one of Technologies 15 to 17.

[0209] According to such an information processing device, the comparison table for proposals can be updated based on feedback from the user.

[0210] (Technology 19) The information processing device described in Technology 15, wherein the control unit further generates new input data based on the user feedback and updates the trained model by re-learning the trained model using the new input data, or updates the trained model by performing reinforcement learning on the trained model using the user feedback.

[0211] According to such an information processing device, the trained model for proposal can be updated based on feedback from the user.

[0212] (Technology 20) The control unit further corrects the proposed mode to cooling mode when the second temperature characteristic value is greater than or equal to a first temperature threshold and the proposed mode is not cooling, or corrects the proposed mode to heating mode when the second temperature characteristic value is less than or equal to a second temperature threshold and the proposed mode is not heating, and the second temperature threshold is lower than the first temperature threshold. An information processing device described in any one of Technologies 1 to 19.

[0213] According to such an information processing device, the proposed mode can be determined more appropriately.

[0214] (Technology 21) The information processing device according to any one of Techniques 1 to 20, wherein the control unit further presents a notification related to at least one of the first temperature characteristic value and the second temperature characteristic value.

[0215] According to such an information processing device, the basis for the suggestion can be presented, thereby increasing the user's confidence in the suggestion.

[0216] (Technology 22) A method for proposing air conditioning operation of an air conditioner includes the steps of: acquiring a first temperature characteristic value that represents a temperature trend over a predetermined period of time in the past based on meteorological information related to the temperature at the location of the air conditioner; acquiring a second temperature characteristic value that represents a predicted maximum temperature or a predicted minimum temperature for a target time period; determining at least one of a proposed mode related to the operating mode of the air conditioning operation of the air conditioner and a proposed temperature related to the set temperature of the proposed mode for the target time period based on the first temperature characteristic value and the second temperature characteristic value; and presenting at least one of the proposed mode and the proposed temperature.

[0217] According to this suggestion method, it is possible to provide an appropriate suggestion for at least one of the operation mode and temperature setting of the air conditioning control.

[0218] (Technology 23) A program that causes an information processing device to execute the proposed method described in Technology 22.

[0219] Such a program can provide an appropriate suggestion for at least one of the operating mode and temperature setting of the air conditioning control.

[0220] (Technology 24) A non-transitory computer-readable storage medium on which a computer program is stored, wherein, when the computer program is executed by a processor, the proposed method described in Technology 22 is realized.

[0221] Such a storage medium can provide appropriate suggestions for at least one of the operating mode and temperature setting of the air conditioning control.

[0222] The above are merely specific embodiments of the present disclosure, and the scope of protection of the present disclosure is not limited thereto. The present disclosure includes the contents described above in the drawings and the specific embodiments described above, but the present disclosure is not limited thereto. Various disclosed embodiments or examples can be combined without departing from the scope or spirit of the present disclosure. Modifications that do not depart from the functional and structural principles of the present disclosure are within the scope of the claims. [Explanation of symbols]

[0223] 10 Servers 11 Communications Department 12 Storage section 13 Control Unit 14 Presentation part 15 Input section 20 Air conditioner 21 Communications Department 22 Memory section 23 Control Unit 24 Presentation section 25 Input section 26 Air Conditioning Section 30 Terminal Equipment 31 Communications Department 32 Storage section 33 Control Unit 34 Presentation part 35 Input section 36 Related Applications 40 External information sources SC1~SC9 screens R1~R8 area

Claims

1. An information processing device that proposes air conditioning operation of an air conditioner, a communication unit capable of acquiring meteorological information relating to the temperature at the location of the air conditioner; a storage unit that stores the acquired weather information; a control unit that controls the communication unit and the storage unit; Including, The control unit obtaining a first temperature characteristic value representing a trend of temperature over a predetermined period of time in the past based on the accumulated weather information; obtaining a second temperature feature value representing a predicted maximum temperature or a predicted minimum temperature for the target time period; determining, for the target time period, at least one of a proposed mode related to an operating mode of an air conditioning operation of the air conditioner and a proposed temperature related to a set temperature of the proposed mode based on the first temperature characteristic value and the second temperature characteristic value; presenting at least one of the suggested mode and the suggested temperature; Information processing device.

2. The accumulated weather information includes the temperature at the location for each fixed time period, The control unit further includes: Calculating a statistical value related to the maximum temperature in the target time slot for each of a plurality of days in the predetermined period based on the accumulated weather information, and setting the calculation result as the first temperature characteristic value; or Calculating a statistical value related to the minimum temperature in the target time slot for each of a plurality of days in the predetermined period based on the accumulated weather information, and setting the calculation result as the first temperature characteristic value; The second temperature characteristic value is a predicted maximum temperature or a predicted minimum temperature for the target time period. The information processing device according to claim 1 .

3. The control unit further includes: acquiring identification information for identifying the air conditioner or the user; determining the location of the air conditioner based on the identification information; obtaining the weather information including a temperature at the location and a predicted temperature for the location; The information processing device according to claim 1 .

4. the storage unit stores a comparison table showing the relationship between the first temperature characteristic value, the second temperature characteristic value, and an operation mode and a set temperature of an air conditioning operation; the control unit determines an operation mode corresponding to a combination of the first air temperature characteristic value and the second air temperature characteristic value as the proposed mode by comparing the first air temperature characteristic value and the second air temperature characteristic value with the lookup table, or determines a set temperature corresponding to the combination as the proposed temperature. The information processing device according to claim 1 .

5. The storage unit stores at least one trained model for making suggestions regarding air conditioning operation, The trained model has learned the relationship between the first temperature feature value, the second temperature feature value, and the operation mode and set temperature of the air conditioning operation, The control unit determines, as the proposed mode, an operation mode estimated by the trained model based on the first temperature feature value and the second temperature feature value, or determines, as the proposed temperature, a set temperature estimated by the trained model based on the first temperature feature value and the second temperature feature value. The information processing device according to claim 1 .

6. The control unit divides a day into a plurality of target time periods, The storage unit stores a comparison table or a learned model for proposing air conditioning operation corresponding to each target time period, each of the comparison tables represents a relationship between the first temperature characteristic value and the second temperature characteristic value and an operation mode and a set temperature of an air conditioning operation for a different target time period; Each of the trained models has learned the relationship between the first temperature feature value, the second temperature feature value, and the operating mode and set temperature of the air conditioning operation for different target time periods. The information processing device according to claim 5 .

7. The control unit further includes: obtaining user input including thermal information regarding at least one of the user's clothing and bedding; Calculating the amount of clothing worn by the user based on the heat retention information; modifying the suggested temperature based on the amount of clothing worn; The information processing device according to claim 1 .

8. The storage unit stores at least one comparison table or trained model for making suggestions regarding air conditioning operation, The control unit further includes: performing air conditioning operation in accordance with the proposed mode and the proposed temperature during the target time period; acquiring user feedback including thermal sensation information regarding the thermal sensation felt by the user for the proposed mode and the proposed temperature operated; updating a comparison table or a trained model used to determine at least one of the proposed operating mode and the proposed temperature based on the thermal sensation information; The information processing device according to claim 1 .

9. The control unit further includes: If the proposed mode operated is a cooling mode or a heating mode and the thermal sensation information indicates hot, the comparison table is updated so as to lower the proposed temperature for the target time period within a settable range based on the first temperature characteristic value and the second temperature characteristic value, or to correct the proposed mode for the target time period to operation off; If the proposed mode operated is a cooling mode or a heating mode and the thermal sensation information indicates cold, the comparison table is updated so as to increase the proposed temperature for the target time period within the settable range based on the first air temperature characteristic value and the second air temperature characteristic value, or to correct the proposed mode for the target time period to operation off; If the proposed mode operated is operation off and the thermal sensation information indicates hot, update the comparison table so as to correct the proposed mode for the target time period based on the first temperature characteristic value and the second temperature characteristic value to a cooling mode; or When the proposed mode operated is operation off and the thermal sensation information indicates cold, the comparison table is updated so as to correct the proposed mode for the target time period based on the first air temperature characteristic value and the second air temperature characteristic value to a heating mode. The information processing device according to claim 8 .

10. The control unit further includes: updating the trained model by generating new input data based on the user feedback and retraining the trained model using the new input data; or updating the trained model by performing reinforcement learning on the trained model using the user feedback; The information processing device according to claim 8 .

11. The control unit further includes: If the second temperature characteristic value is greater than or equal to a first temperature threshold and the proposed mode is not cooling, modify the proposed mode to a cooling mode; or If the second temperature characteristic value is equal to or less than a second temperature threshold and the proposed mode is not heating, modify the proposed mode to a heating mode; the second temperature threshold is lower than the first temperature threshold; The information processing device according to claim 1 .

12. The control unit further includes: presenting a notification associated with at least one of the first temperature characteristic value and the second temperature characteristic value; The information processing device according to claim 1 .

13. A method for proposing air conditioning operation of an air conditioner, acquiring a first temperature characteristic value that represents a trend in temperature over a predetermined period of time in the past based on meteorological information related to the temperature at the location of the air conditioner; acquiring a second temperature characteristic value representing a predicted maximum temperature or a predicted minimum temperature for a target time period; determining, for the target time period, at least one of a proposed mode related to an operating mode of the air conditioning operation of the air conditioner and a proposed temperature related to a set temperature of the proposed mode based on the first temperature characteristic value and the second temperature characteristic value; presenting at least one of the suggested mode and the suggested temperature; Including, Proposal method.

14. A program that causes an information processing device to execute the proposal method according to claim 13.

15. A non-transitory computer-readable storage medium on which a computer program is stored, When the computer program is executed by a processor, the proposed method according to claim 13 is realized. A non-transitory computer-readable storage medium.

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