Air conditioning control system

Abstract

This air-conditioning control system (1) comprises an air-conditioner (100) having: a first discomfort index calculation unit for calculating an indoor first discomfort index by using information about an indoor temperature detected by an indoor temperature sensor and information about an indoor humidity detected by an indoor humidity sensor; and a control unit for controlling operation of the air-conditioner (100) on the basis of the indoor discomfort index. The air-conditioning control system (1) comprises a server (200) having a second discomfort index calculation unit for calculating a second discomfort index on the basis of: user information, which includes user characteristic information indicating characteristics of a user when the air-conditioner (100) is in use and discomfort index information constituted by a report of the user's sense of indoor warmth when the air-conditioner (100) is in use; and environmental information indicating the environment in which the air-conditioner (100) is used. The control unit controls the operation of the air-conditioner (100) on the basis of at least the first discomfort index.

Description

Technical Field

[0001] The present disclosure relates to an air conditioning control system that automatically controls the indoor environment to be comfortable for the occupants. Mu

Background Art

[0002] Conventionally, in air conditioners, in order to achieve the comfort of the thermal sensation of the human beings living there, a comfort index called Predicted Mean Vote (PMV), which represents how people feel the thermal sensation, has been proposed. As a device that controls an air conditioner based on the PMV index, Patent Document 1 describes an air conditioner that can allow a user to input the current temperature sensation, can confirm the operation by the user himself / herself, and can perform accurate correction desired by the user based on the PMV value to control heating and cooling.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the air conditioner of Patent Document 1 described above, since it is necessary to input the temperature sensation of the user, there is a problem that the correction control of the heating and cooling control does not operate when there is no input of the temperature sensation information by the user.

[0005] The present disclosure has been made in view of the above, and an object thereof is to obtain an air conditioning control system capable of making the indoor environment comfortable without input of the temperature sensation by the user.

Means for Solving the Problems

[0006] ​To solve the above-mentioned problems and achieve the objective, the air conditioning control system according to this disclosure is an air conditioning control system comprising an air conditioner and a server capable of communicating with the air conditioner. The air conditioning control system comprises an air conditioner having an indoor temperature sensor for detecting the temperature of the room which is the area to be air-conditioned by the air conditioner, an indoor humidity sensor for detecting the humidity of the room, a first discomfort index calculation unit that calculates a first discomfort index of the room using the indoor temperature information detected by the indoor temperature sensor and the indoor humidity information detected by the indoor humidity sensor, and a control unit that controls the operation of the air conditioner based on the indoor discomfort index. The air conditioning control system comprises a server having a second discomfort index calculation unit that calculates a second discomfort index based on user information including user characteristic information indicating the characteristics of the user when using the air conditioner and discomfort index information reporting the temperature sensation of the room felt by the user when using the air conditioner, and environmental information which is information indicating the operating environment of the air conditioner. The control unit controls the operation of the air conditioner based on at least the first discomfort index. The system controls the operation of the air conditioner based on the discomfort index that has the largest difference between the first discomfort index and the target discomfort index information, which is information about the discomfort index that users perceive as comfortable in the indoor environment. [Effects of the Invention]

[0007] The air conditioning control system described herein has the effect of enabling air conditioning control that makes the indoor environment comfortable even without user input of temperature preferences. [Brief explanation of the drawing]

[0008] [Figure 1] Block diagram showing the system configuration of the air conditioning control system according to Embodiment 1. [Figure 2] Block diagram showing the configuration of the indoor unit of the air conditioner according to Embodiment 1 [Figure 3] Block diagram showing the configuration of the outdoor unit of the air conditioner according to Embodiment 1. [Figure 4] Block diagram showing the configuration of the remote controller for the air conditioner according to Embodiment 1. [Figure 5] Block diagram showing the server configuration according to Embodiment 1 [Figure 6] Block diagram showing the functional configuration of the external control terminal according to Embodiment 1 [Figure 7] A flowchart illustrating the procedure for operating the air conditioning control system according to Embodiment 1. [Figure 8] A flowchart illustrating the procedure for determining discomfort index information in the server of the air conditioning control system according to Embodiment 1. [Figure 9] Flowchart showing the procedure for correcting discomfort index information in the air conditioning control system according to Embodiment 1 [Figure 10] Diagram showing the configuration of the learning device according to Embodiment 1. [Figure 11] Flowchart showing the processing procedure of the learning process by the learning device according to Embodiment 1 [Figure 12] This figure shows the configuration of the neural network used in the learning device according to Embodiment 1. [Figure 13] Diagram showing the configuration of the inference device according to Embodiment 1. [Figure 14] Flowchart showing the processing procedure of inference processing by the inference device according to Embodiment 1 [Figure 15] This diagram shows the configuration in which each function of the control unit according to Embodiment 1 is implemented in hardware. [Figure 16] This diagram shows the configuration in which each function of the control unit according to Embodiment 1 is implemented in software. [Modes for carrying out the invention]

[0009] The following describes the air conditioning control system according to the embodiment. Mu I will explain in detail based on the drawings.

[0010] Embodiment 1. FIG. 1 is a block diagram showing the system configuration of the air conditioning control system 1 according to Embodiment 1. The air conditioning control system 1 according to Embodiment 1 is a system that can automatically perform air conditioning control in order to realize the comfort of the thermal sensation of the human beings living therein. The air conditioning control system 1 according to Embodiment 1 includes an air conditioner 100, a server 200, and an external control terminal 300.

[0011] The air conditioner 100 has a function of automatically performing air conditioning control so that the indoor environment, which is the air conditioning target area of the air conditioner 100, becomes comfortable for the occupants based on the discomfort index information. The discomfort index information is information representing how a person feels the thermal sensation, and PMV can be used.

[0012] The air conditioner 100 includes an indoor unit 110 installed indoors, an outdoor unit 120 installed outdoors, and a remote controller 130. The indoor unit 110 is communicable with the outdoor unit 120 via a communication line (not shown). The remote controller 130 is an operation device for the user to set a control instruction command for the air conditioner 100 in order to control the air conditioner 100, and transmits the control instruction command operated by the user to the outdoor unit 120. Hereinafter, the remote controller may be referred to as a remote control.

[0013] The air conditioner 100, the server 200, and the external control terminal 300 are communicably connected to each other via a network such as the Internet 400, which is a global information communication network. That is, the air conditioner 100, the server 200, and the external control terminal 300 are connected to the network and can transmit and receive information to and from each other. Note that each of the air conditioner 100, the server 200, and the external control terminal 300 may directly communicate with other devices in the air conditioning control system 1 without going through the Internet 400.

[0014] The air conditioner 100 forms a complete refrigeration cycle with an indoor unit 110 and an outdoor unit 120. The air conditioner 100 uses a refrigerant that circulates between the indoor unit 110 and the outdoor unit 120 through refrigerant pipes (not shown) to transfer heat between the indoor air, which is the area to be air-conditioned, and the outdoor air, which is the outside air, thereby achieving air conditioning for the room.

[0015] Figure 2 is a block diagram showing the configuration of the indoor unit 110 of the air conditioner 100 according to Embodiment 1. As shown in Figure 2, the indoor unit 110 includes an indoor unit sensor 111, an indoor unit storage unit 112, an indoor unit communication unit 113, and an indoor unit control unit 114. Each component of the indoor unit 110 is capable of exchanging information with each other.

[0016] The indoor unit sensor 111 is a detector that detects the status of the air conditioner 100 and the operating environment of the air conditioner 100 in order to control the air conditioner 100. Examples of indoor unit sensors 111 include an indoor temperature sensor 1111 that detects the indoor temperature, an indoor humidity sensor 1112 that detects the indoor humidity, and various other sensors.

[0017] The indoor unit memory unit 112 is a memory unit that stores various control setting values ​​and control programs for controlling the air conditioner 100. The indoor unit memory unit 112 is a non-volatile memory unit and is composed of a semiconductor memory medium such as flash memory.

[0018] The indoor unit communication unit 113 communicates with external devices of the indoor unit 110. Specifically, the indoor unit communication unit 113 communicates with the communication units of external devices of the indoor unit 110, such as the remote control communication unit 134 of the remote control 130 (described later), the outdoor unit communication unit 123 of the outdoor unit 120 (described later), and the server communication unit 210 of the server 200 (described later). The indoor unit communication unit 113 transmits information received from the communication units of external devices of the indoor unit 110 to the indoor unit control unit 114. The indoor unit communication unit 113 transmits information received from the indoor unit control unit 114 to the communication units of external devices of the indoor unit 110.

[0019] The communication method between the communication unit of the external device and the indoor unit communication unit 113 may be wired communication, or it may be wireless communication using infrared communication, Wi-Fi (registered trademark) (Wireless Fidelity), or Bluetooth (registered trademark).

[0020] The indoor unit control unit 114 is a control unit that controls the overall operation of the indoor unit 110, and controls the operation of the indoor unit 110 and the outdoor unit 120 to control the operation of the air conditioner 100. The indoor unit control unit 114 works in conjunction with the outdoor unit control unit 126 of the outdoor unit 120, which will be described later, to control the operation of the air conditioner 100 through automatic air conditioning control, which automatically controls the air conditioning so that the indoor environment becomes comfortable according to the value of the discomfort index information determined in the air conditioning control system 1, and normal air conditioning control, which controls the air conditioning based on operating conditions set by the user from the remote control 130 or the like. The indoor unit control unit 114 controls the operation of the air conditioner 100 based on at least the first discomfort index, which will be described later.

[0021] Figure 3 is a block diagram showing the configuration of the outdoor unit 120 of the air conditioner 100 according to Embodiment 1. As shown in Figure 3, the outdoor unit 120 includes an outdoor unit sensor 121, an outdoor unit storage unit 122, an outdoor unit communication unit 123, an acquisition unit 124, an outdoor unit discomfort index calculation unit 125, and an outdoor unit control unit 126. Each component of the outdoor unit 120 can exchange information with each other.

[0022] The outdoor unit sensor 121 is a detector that detects the status of the air conditioner 100 and the operating environment of the air conditioner 100 in order to control the air conditioner 100. Examples of outdoor unit sensors 121 include an outdoor temperature sensor (not shown) that detects the temperature of the outside air, and an outdoor humidity sensor (not shown) that detects the humidity of the outside air.

[0023] The outdoor unit memory unit 122 is a memory unit that stores various control setting values ​​and control programs for controlling the air conditioner 100. The outdoor unit memory unit 122 is a non-volatile memory unit and is composed of a semiconductor memory medium such as flash memory. The outdoor unit memory unit 122 stores the air conditioner-calculated discomfort index information calculated by the outdoor unit discomfort index calculation unit 125 and the discomfort index information finally determined by the outdoor unit discomfort index calculation unit 125.

[0024] The outdoor unit communication unit 123 communicates with external devices of the outdoor unit 120. Specifically, the outdoor unit communication unit 123 communicates with the communication units of external devices of the outdoor unit 120, such as the remote control communication unit 134 of the remote control 130 (described later), the indoor unit communication unit 113 of the indoor unit 110, and the server communication unit 210 of the server 200 (described later). The outdoor unit communication unit 123 transmits the information received from the communication units of the external devices of the outdoor unit 120 to the outdoor unit control unit 126. The outdoor unit communication unit 123 transmits the information received from the outdoor unit control unit 126 to the communication units of external devices of the outdoor unit 120.

[0025] The communication method between the communication unit of the external device and the outdoor unit communication unit 123 may be wired communication, or it may be wireless communication using infrared communication, Wi-Fi, or Bluetooth.

[0026] The acquisition unit 124 acquires and stores the server-calculated discomfort index information, which is the discomfort index information calculated by the server 200, from the server 200. The server-calculated discomfort index information is the second discomfort index information in the air conditioning control system 1. The acquisition unit 124 transmits the server-calculated discomfort index information acquired from the server 200 to the outdoor unit discomfort index calculation unit 125.

[0027] The outdoor unit discomfort index calculation unit 125 acquires indoor temperature information detected by the indoor temperature sensor 1111 and indoor humidity information detected by the indoor humidity sensor 1112 from the indoor unit 110, and uses the acquired indoor temperature information and indoor humidity information to calculate the indoor discomfort index, i.e., indoor discomfort index information.

[0028] The outdoor unit discomfort index calculation unit 125 is the first discomfort index calculation unit in the air conditioning control system 1. The discomfort index calculated by the outdoor unit discomfort index calculation unit 125 is the air conditioner-calculated discomfort index and is the first discomfort index in the air conditioning control system 1. The information of the air conditioner-calculated discomfort index is the air conditioner-calculated discomfort index information. The information of the first discomfort index is the first discomfort index information.

[0029] The outdoor unit discomfort index calculation unit 125 calculates the discomfort index using, for example, the following formula (1). This allows the outdoor unit discomfort index calculation unit 125 to obtain discomfort index information, which is information about the discomfort index. The discomfort index calculated by the outdoor unit discomfort index calculation unit 125 is the air conditioner-calculated discomfort index calculated by the air conditioner 100. In formula (1), T is the indoor temperature (°C) and H is the indoor humidity (%).

[0030] 0.81T+0.01H(0.99T-14.3)+46.3 (1)

[0031] The outdoor unit discomfort index calculation unit 125 stores the calculated unit discomfort index information and the finally determined discomfort index information in the outdoor unit storage unit 122.

[0032] The outdoor unit control unit 126 is a control unit that controls the overall operation of the outdoor unit 120, and controls the operation of the air conditioner 100 by controlling the operation of the outdoor unit 120. The outdoor unit control unit 126 works in conjunction with the indoor unit control unit 114 to control the operation of the air conditioner 100 through automatic air conditioning control, which automatically controls the air conditioning so that the indoor environment becomes comfortable according to the discomfort index information value determined in the air conditioning control system 1, and normal air conditioning control, which controls the air conditioning based on operating conditions set by the user from the remote control 130 or the like. The outdoor unit control unit 126 performs control to transmit the finally determined discomfort index information to the indoor unit control unit 114 of the indoor unit 110. The outdoor unit control unit 126 controls the operation of the air conditioner 100 based on at least the first discomfort index.

[0033] Figure 4 is a block diagram showing the configuration of the remote controller 130 of the air conditioner 100 according to Embodiment 1. As shown in Figure 4, the remote control 130 includes a remote controller operation unit 131, a remote controller display unit 132, a remote controller storage unit 133, a remote controller communication unit 134, and a remote controller control unit 135. Each component of the remote control 130 can exchange information with each other.

[0034] The remote control unit 131 receives setting operations related to the air conditioning of the air conditioner 100 requested by the user. In other words, the remote control unit 131 is an interface for remotely controlling the operation of the air conditioner 100 and receives operations related to the operation of the air conditioner 100 from the user. When the remote control unit 131 receives an operation from the user, it transmits information corresponding to the user's operation as operation information to the remote control control unit 135.

[0035] The remote control unit 131 is configured to allow the user to arbitrarily select various functions related to the operation of the air conditioner 100, such as starting the air conditioner 100, stopping the air conditioner 100, selecting the operating mode of the air conditioner 100, changing the set temperature, changing the set humidity, setting the airflow volume, setting the airflow direction, and changing the settings for prohibited operations.

[0036] The remote control display unit 132 is a display unit that displays various information, including the set temperature and operating mode of the air conditioner 100, as well as information and status necessary for air conditioning by the air conditioner 100, and switches and displays screens corresponding to operations on the remote control operation unit 131.

[0037] The remote control memory unit 133 stores various information necessary for air conditioning processing in the air conditioner 100, and temporarily or permanently stores information such as settings to be displayed on the remote control display unit 132 and image data related to those settings.

[0038] The remote control communication unit 134 is capable of bidirectional communication of information with the indoor unit communication unit 113 of the indoor unit 110. The communication method between the indoor unit communication unit 113 and the remote control communication unit 134 may be wired communication, or wireless communication using infrared communication, Wi-Fi, or Bluetooth.

[0039] The remote control unit 135 controls the operation of the entire remote control 130. The remote control unit 135 controls the remote control 130 based on the operation information transmitted from the remote control operation unit 131. The remote control unit 135 also transmits the operation information transmitted from the remote control operation unit 131 to the indoor unit communication unit 113 of the indoor unit 110.

[0040] Server 200 acquires user information, environmental information, and user setting information from the external control terminal 300 and stores them in the server storage unit 220. Then, based on the data stored in the server storage unit 220, Server 200 calculates a discomfort index using machine learning.

[0041] User information includes the user's gender, age, clothing, and discomfort index information reported by the user when using the air conditioner 100. Therefore, more specifically, user information includes user characteristic information that indicates the user's characteristics such as gender, age, and clothing, and discomfort index information reported by the user.

[0042] The discomfort index information reported by the user is information about the discomfort index that the user reported regarding the indoor temperature when using the air conditioner 100. For example, the discomfort index information reported by the user can use PMV, which quantifies temperature sensations such as hot, slightly warm, comfortable, slightly cool, and cool.

[0043] Environmental information refers to information indicating the operating environment of the air conditioner 100, such as the weather, season, and time of day when the air conditioner 100 is in use.

[0044] User setting information is information about the operating conditions of the air conditioner 100 that the user sets in order to control the operation of the air conditioner 100.

[0045] Figure 5 is a block diagram showing the configuration of the server 200 according to Embodiment 1. The server 200 comprises a server communication unit 210, a server storage unit 220, a server discomfort index calculation unit 230, and a server control unit 240. Information can be exchanged between the various components of the server 20.

[0046] The server communication unit 210 is capable of communicating with the indoor unit communication unit 113 of the indoor unit 110 and the outdoor unit communication unit 123 of the outdoor unit 120. The indoor unit communication unit 113 and the outdoor unit communication unit 123 can communicate with the server communication unit 210, for example, via the internet 400. The server communication unit 210 receives information transmitted from the indoor unit communication unit 113 or the outdoor unit communication unit 123 via the internet 400. The server communication unit 210 transmits the received information to the server control unit 240. The server communication unit 210 also transmits information transmitted from the server control unit 240 to the indoor unit communication unit 113 or the outdoor unit communication unit 123.

[0047] The server communication unit 210 is capable of communicating with the terminal communication unit 340 of the external control terminal 300, which will be described later. The terminal communication unit 340 of the external control terminal 300 and the server communication unit 210 are capable of communicating, for example, via the internet 400. The server communication unit 210 transmits the information sent from the server control unit 240 to the terminal communication unit 340 of the external control terminal 300 via the internet 400.

[0048] The server storage unit 220 stores various types of information used to control the server 200. The server storage unit 220 also has a storage unit 221 that stores and accumulates information acquired from the external control terminal 300, such as environmental information, user information, and user setting information, as well as server-calculated discomfort index information. The storage unit 221 stores user information and environmental information transmitted from multiple external control terminals 300, grouping similar information together. This improves the accuracy of the server-calculated discomfort index information when calculating the server-calculated discomfort index information using machine learning, as described later, by combining multiple pieces of information with similar characteristics.

[0049] The server discomfort index calculation unit 230 includes a machine learning device 270 having a learning device 250 and an inference device 260, and calculates the indoor discomfort index, i.e., indoor discomfort index information, by machine learning. Details of the learning device 250 and the inference device 260 will be described later.

[0050] The server discomfort index calculation unit 230 is the second discomfort index calculation unit in the air conditioning control system 1. The discomfort index calculated by the server discomfort index calculation unit 230 is the server-calculated discomfort index and is the second discomfort index in the air conditioning control system 1. The server-calculated discomfort index information is the server-calculated discomfort index information. The second discomfort index information is the second discomfort index information.

[0051] The server control unit 240 controls the overall processing of the server 200. The server control unit 240 receives environmental information from the external control terminal 300 via the server communication unit 210 and stores the received environmental information in the server storage unit 220. This allows the server 200 to acquire the environmental information. The server control unit 240 also receives user information from the external control terminal 300 via the server communication unit 210 and stores the received user information in the server storage unit 220. This allows the server 200 to acquire the user information.

[0052] The external control terminal 300 has the function of remotely operating the setting and control of the operating conditions of the air conditioner 100 via the server 200, and remotely controlling the operation of the air conditioner 100. The external control terminal 300 also has the function of receiving various information from the user, such as user information, user setting information, and environmental information, and transmitting it to the server 200.

[0053] Figure 6 is a block diagram showing the functional configuration of an external control terminal 300 according to Embodiment 1. The external control terminal 300 comprises a terminal operation unit 310, a terminal display unit 320, a terminal storage unit 330, a terminal communication unit 340, and a terminal control unit 350. Information can be exchanged between the various components of the external control terminal 300.

[0054] The terminal operation unit 310 is an operation reception unit that receives user operations, that is, operations from the user. The terminal operation unit 310 receives various operations from the user. When the terminal operation unit 310 receives an operation from the user, it transmits operation information, which is information corresponding to that operation, to the terminal control unit 350. The terminal operation unit 310 is composed of input devices such as a keyboard, mouse, and touch panel display with touch panel functionality, and operations on the external control terminal 300 are performed by the user.

[0055] The terminal display unit 320 is a display unit that displays various information from within the external control terminal 300. The terminal display unit 320 also displays various information acquired from the air conditioner 100 and the server 200, and presents this information to the user.

[0056] The terminal storage unit 330 is a storage unit that stores various information from within the external control terminal 300. The terminal storage unit 330 stores various information such as user information, user setting information, and environment information.

[0057] The terminal communication unit 340 connects to the internet 400 and communicates with the server 200. The terminal communication unit 340 transmits various information sent from the server 200 to the terminal control unit 350. The terminal communication unit 340 transmits various information sent from the terminal control unit 350 to the server 200.

[0058] The terminal control unit 350 controls the overall processing of the external control terminal 300. The terminal control unit 350 also controls the transmission of various information, such as user information, user settings information, and environment information, to the server 200 based on user operations.

[0059] Furthermore, the terminal control unit 350 controls the display of various information acquired from the server 200 on the terminal display unit 320 based on user operations. In other words, the terminal control unit 350 functions as a display control unit that controls the display of information on the terminal display unit 320.

[0060] Next, the operation of the air conditioning control system 1 will be described. Figure 7 is a flowchart showing the procedure for the operation of the air conditioning control system 1 according to Embodiment 1.

[0061] First, in step S110, the air conditioner 100 acquires indoor temperature and humidity information. Specifically, the indoor temperature sensor 1111 of the indoor unit 110 of the air conditioner 100 detects the indoor temperature as indoor temperature and humidity information. In addition, the indoor humidity sensor 1112 of the indoor unit 110 of the air conditioner 100 detects the indoor humidity as indoor temperature and humidity information. Then, the process proceeds to step S120.

[0062] In step S120, the discomfort index is calculated in the outdoor unit discomfort index calculation unit 125 of the outdoor unit 120 of the air conditioner 100. Specifically, the outdoor unit discomfort index calculation unit 125 acquires information on the indoor temperature detected by the indoor temperature sensor 1111 and information on the indoor humidity detected by the indoor humidity sensor 1112, and uses the acquired indoor temperature information and indoor humidity information to calculate the discomfort index using the above-mentioned formula (1). The discomfort index calculated in step S120 by the outdoor unit discomfort index calculation unit 125 is the air conditioner-calculated discomfort index calculated by the air conditioner 100. Then, the process proceeds to step S130.

[0063] In step S130, it is determined whether or not server-calculated discomfort index information, which is information on the discomfort index calculated by the server 200, exists. Specifically, the outdoor unit discomfort index calculation unit 125 determines whether or not server-calculated discomfort index information exists.

[0064] When the acquisition unit 124 of the outdoor unit 120 receives server-calculated discomfort index information from the server 200 via the outdoor unit communication unit 123, it stores the received server-calculated discomfort index information. The server-calculated discomfort index information is always updated to the latest information. The acquisition unit 124 may also store the discomfort index information acquired from the server 200 in the outdoor unit storage unit 122.

[0065] The outdoor unit discomfort index calculation unit 125 determines that server-calculated discomfort index information exists if server-calculated discomfort index information acquired and stored by the acquisition unit 124 within a predetermined time range is stored in the acquisition unit 124. The outdoor unit discomfort index calculation unit 125 determines that server-calculated discomfort index information does not exist if server-calculated discomfort index information acquired and stored by the acquisition unit 124 within a predetermined time range is not stored in the acquisition unit 124.

[0066] If it is determined that server-calculated discomfort index information exists, the answer in step S130 is Yes, and the process proceeds to step S140. If it is determined that server-calculated discomfort index information does not exist, the answer in step S130 is No, and the process proceeds to step S160.

[0067] In step S140, the outdoor unit discomfort index calculation unit 125 acquires the server-calculated discomfort index information. Specifically, the outdoor unit discomfort index calculation unit 125 acquires the server-calculated discomfort index information from the acquisition unit 124. After that, the process proceeds to step S150.

[0068] In step S150, the discomfort index is corrected. Specifically, the outdoor unit discomfort index calculation unit 125 corrects the discomfort index based on the server-calculated discomfort index information obtained from the acquisition unit 124 and the harmonizer-calculated discomfort index information calculated in step S120. Details of the discomfort index correction process will be described later. After that, the process proceeds to step S160.

[0069] In step S160, the discomfort index information is determined. Specifically, the outdoor unit discomfort index calculation unit 125 determines the discomfort index, thereby determining the discomfort index information. If the outdoor unit discomfort index calculation unit 125 determines in step S130 that server-calculated discomfort index information exists, it determines the discomfort index corrected in step S150 as the discomfort index. If the outdoor unit discomfort index calculation unit 125 determines in step S130 that server-calculated discomfort index information does not exist, it determines the harmonizer-calculated discomfort index calculated by the outdoor unit discomfort index calculation unit 125 in step S120 as the discomfort index. As a result, the outdoor unit discomfort index calculation unit 125 determines the determined discomfort index information as the discomfort index information. After that, the process proceeds to step S170.

[0070] In step S170, the air conditioner 100 is controlled. Specifically, the indoor unit control unit 114 of the indoor unit 110 and the outdoor unit control unit 126 of the outdoor unit 120 of the air conditioner 100 perform air conditioning control of the air conditioner 100 based on the discomfort index information determined in step S160. The indoor unit control unit 114 of the indoor unit 110 and the outdoor unit control unit 126 of the outdoor unit 120 perform air conditioning control of the air conditioner 100 so that the discomfort index indicated in the discomfort index information determined in step S160 satisfies the target discomfort index information. In other words, the indoor unit control unit 114 of the indoor unit 110 and the outdoor unit control unit 126 of the outdoor unit 120 automatically perform air conditioning control based on the discomfort index information so that the indoor environment is comfortable for the occupants.

[0071] The target discomfort index information is information about the discomfort index that makes the indoor environment comfortable for the user, that is, information about the discomfort index set so that the indoor environment is comfortable for the occupants. The target discomfort index information may be information about a range of discomfort indices, or it may be a single value for the discomfort index. The target discomfort index information is predetermined and stored in the outdoor unit storage unit 122. The target discomfort index information can be changed from the remote control 130 or the external control terminal 300.

[0072] Next, the calculation of discomfort index information in server 200 will be explained. Figure 8 is a flowchart showing the procedure for determining discomfort index information in server 200 of the air conditioning control system 1 according to Embodiment 1.

[0073] First, in step S210, environmental information is acquired by the server 200. Specifically, the server control unit 240 of the server 200 receives environmental information from the external control terminal 300 via the server communication unit 210 and stores the received environmental information in the server storage unit 220. This allows the server 200 to acquire environmental information. After that, the process proceeds to step S220.

[0074] In step S220, user information is acquired. Specifically, the server control unit 240 receives user information from the external control terminal 300 via the server communication unit 210 and stores the received user information in the server storage unit 220 of the server 200. As a result, user information is acquired in the server 200. That is, in step S220, user information acquired includes user characteristic information indicating the user's characteristics such as age and clothing, and discomfort index information reported by the user. The process then proceeds to step S230.

[0075] In step S230, it is determined whether or not there is learned information regarding the discomfort index. Specifically, the server discomfort index calculation unit 230 determines whether or not it has learned information regarding the discomfort index. The learned information regarding the discomfort index is the trained model 283, which will be described later. If it is determined that there is learned information regarding the discomfort index, the result in step S230 is Yes, and the process proceeds to step S240. If it is determined that there is no learned information regarding the discomfort index, the result in step S230 is No, and the process proceeds to step S270.

[0076] In step S240, the discomfort index is calculated by applying the learned information regarding the discomfort index. Specifically, the server discomfort index calculation unit 230 uses machine learning to calculate the server-calculated discomfort index using the environmental information acquired in step S210, the user information acquired in step S220, and the trained model 283 described later. The discomfort index calculated in step S240 is the server-calculated discomfort index. The process then proceeds to step S250.

[0077] In step S250, discomfort index information is presented to the outdoor unit 120. Specifically, the server discomfort index calculation unit 230 transmits the server-calculated discomfort index information calculated in step S240 to the acquisition unit 124 of the outdoor unit 120.

[0078] When the acquisition unit 124 receives server-calculated discomfort index information from the server discomfort index calculation unit 230, it stores the server-calculated discomfort index information. Then, the process proceeds to step S260.

[0079] In step S260, the learning information regarding the discomfort index is updated. Specifically, the learning device 250, described later, learns the learning information regarding the discomfort index using the environmental information acquired in step S210, the user information acquired in step S220, and the server-calculated discomfort index calculated in step S240, and updates the trained model 283.

[0080] In step S270, learning information regarding the discomfort index is created. Specifically, the learning device 250, described later, learns the discomfort index and creates learning information regarding the discomfort index. After that, the process proceeds to step S240. When proceeding from step S230 to step S270 and then to step S240, the server discomfort index calculation unit 230 does not create learning information regarding the discomfort index until the learning information regarding the discomfort index has been created.

[0081] Next, the processing for correcting discomfort index information in step S150 described above will be explained. Figure 9 is a flowchart showing the procedure for correcting discomfort index information in the air conditioning control system 1 according to Embodiment 1. The processing described below is the processing performed in step S150 described above.

[0082] First, in step S310, discomfort index information with a large difference between the discomfort index information calculated by the harmonizer and the discomfort index information calculated by the server is determined. Specifically, the outdoor unit discomfort index calculation unit 125 compares the discomfort index information calculated by the harmonizer in step S120 with the discomfort index information obtained by the server in step S140 to determine the discomfort index information with a large difference from the target discomfort index information. In other words, the outdoor unit discomfort index calculation unit 125 compares the discomfort index shown in the discomfort index calculated by the harmonizer with the discomfort index shown in the discomfort index information calculated by the server to determine the discomfort index information with a large difference from the discomfort index shown in the target discomfort index information. After that, the process proceeds to step S320.

[0083] In step S320, the discomfort index information is determined. Specifically, the outdoor unit discomfort index calculation unit 125 determines the discomfort index information that was determined in step S310 to have a large difference between the comfort index information calculated by the harmonizer and the discomfort index information calculated by the server and is the discomfort index information for the correction process.

[0084] Subsequently, the air conditioner 100 performs air conditioning control based on the discomfort index information determined in the correction process in step S320.

[0085] However, if the discomfort index information reported by the user in the user information indicates that the user does not find the indoor environment uncomfortable, the air conditioner 100 will maintain its current air conditioning control. If the user does not find the indoor environment uncomfortable, there is no need to change the air conditioning control of the air conditioner 100.

[0086] Next, the calculation of the discomfort index using machine learning by the server discomfort index calculation unit 230 in step S240 described above will be explained. The server discomfort index calculation unit 230 calculates the discomfort index, that is, calculates discomfort index information, using a machine learning device 270 which includes a learning device 250 and an inference device 260. The configuration of the learning device 250 and the inference device 260 will be described below.

[0087] Figure 10 shows the configuration of the learning device 250 according to Embodiment 1. The learning device 250 comprises a data acquisition unit 251, a model generation unit 252, and a learned model storage unit 253. The data acquisition unit 251 is the first data acquisition unit in the air conditioning control system 1. The learned model storage unit 253 may be located outside the learning device 250, or it may be provided in the server storage unit 220 of the server 200.

[0088] The learning device 250 learns the discomfort index, i.e., learns discomfort index information, based on training data. The learning device 250 learns discomfort index information based on training data for multiple users that is input to the learning device 250. As a result, the learning device 250 can learn discomfort index information by taking into account training data for multiple users.

[0089] The data acquisition unit 251 acquires input information 281 and discomfort index information 282 corresponding to the state indicated in the input information 281 as training data. The input information 281 includes environmental information and user information. The discomfort index information 282 is discomfort index information corresponding to the state indicated in the input information 281. Here, the training data is data that associates the input information 281 and the discomfort index information 282 with each other. The data acquisition unit 251 acquires the training data from the server control unit 240 of the server 200. Alternatively, the training data may be input to the data acquisition unit 251 from an external device of the server 200. The data acquisition unit 251 generates training data by associating the input information 281 and the discomfort index information 282.

[0090] The model generation unit 252 learns discomfort index information based on training data created from the combination of input information 281 and discomfort index information 282 sent from the data acquisition unit 251. The model generation unit 252 has a learning function that generates a trained model 283 for inferring appropriate discomfort index information corresponding to the combination of environmental information and user information from the input information 281 and discomfort index information 282.

[0091] Next, the processing procedure of the learning device 250 will be explained using Figure 11. Figure 11 is a flowchart showing the processing procedure of the learning device 250 according to Embodiment 1.

[0092] In step S410, the data acquisition unit 251 acquires training data. Specifically, the data acquisition unit 251 acquires input information 281 and discomfort index information 282 as training data. The data acquisition unit 251 may acquire the input information 281 and discomfort index information 282 at the same time, or at different times. In other words, as long as the input information 281 and discomfort index information 282 can be associated, the data acquisition unit 251 may acquire the input information 281 and discomfort index information 282 at any time.

[0093] In step S420, the model generation unit 252 performs a learning process according to the training data, which is a combination of input information 281 and discomfort index information 282 acquired by the data acquisition unit 251. The model generation unit 252 generates a trained model 283, for example, according to the training data, using so-called supervised learning.

[0094] In step S430, the trained model storage unit 253 stores the trained model 283. That is, the model generation unit 252 causes the generated trained model 283 to be stored in the trained model storage unit 253.

[0095] The model generation unit 252 can use any known learning algorithm, such as supervised learning, unsupervised learning, or reinforcement learning. As an example, we will describe the case where the model generation unit 252 performs supervised learning using a neural network.

[0096] The model generation unit 252 learns discomfort index information, for example, by supervised learning according to a neural network model. Here, supervised learning is a method in which a learning device is given pairs of input and result (label) data, learns features in that training data, and infers the result from the input.

[0097] A neural network consists of an input layer made up of multiple neurons, a hidden layer (intermediate layer) also made up of multiple neurons, and an output layer also made up of multiple neurons. The hidden layer can be one or more layers.

[0098] Figure 12 shows the configuration of the neural network used by the learning device 250 according to Embodiment 1. For example, in a three-layer neural network as shown in Figure 12, when multiple data are input to the input layers X1 to X3, these values ​​are multiplied by weights w11 to w16 and input to the hidden layers Y1 to Y2, and the result is further multiplied by weights w21 to w26 and output from the output layers Z1 to Z3. This output result varies depending on the values ​​of the weights w11 to w16 and the weights w21 to w26.

[0099] In Embodiment 1, the neural network learns the discomfort index information by so-called supervised learning, according to training data (dataset) created based on the combination of input information 281 acquired by the data acquisition unit 251 and discomfort index information 282.

[0100] In other words, the neural network learns by inputting input information 281 into input layers X1 to X3 and adjusting the weights w11 to w16 and w21 to w26 so that the output from output layers Z1 to Z3 approaches the discomfort index information 282.

[0101] The model generation unit 252 generates and outputs a trained model 283 by performing the training described above.

[0102] The trained model storage unit 253 stores the trained model 283 output from the model generation unit 252.

[0103] Figure 13 shows the configuration of the inference device 260 according to Embodiment 1. The inference device 260 comprises a data acquisition unit 261 and an inference unit 262. The data acquisition unit 261 is the second data acquisition unit in the air conditioning control system 1. The inference unit 262 is connected to the trained model storage unit 253.

[0104] The environmental information of input information 281 is input from the server control unit 240 of the server 200 to the data acquisition unit 261. The user information of input information 281 is input from the server control unit 240 to the data acquisition unit 261. The inference unit 262 uses the trained model 283 obtained by the learning device 250 to output server-calculated discomfort index information, which is server-calculated discomfort index information, as discomfort index information.

[0105] The data acquisition unit 261 acquires environmental information and user information as inference data. The inference data is input from the server control unit 240 to the data acquisition unit 261.

[0106] The inference unit 262 outputs discomfort index information using the obtained trained model 283. The inference unit 262 reads the trained model 283 from the trained model storage unit 253. The inference unit 262 inputs the input information 281 to the trained model 283. As a result, the inference unit 262 infers discomfort index information. That is, the inference unit 262 can output discomfort index information inferred from the input information 281 by inputting the input information 281, which was acquired by the data acquisition unit 261, into the trained model 283 for inferring discomfort index information.

[0107] Next, the processing procedure of the inference process by the inference device 260 will be explained using Figure 14. Figure 14 is a flowchart showing the processing procedure of the inference process by the inference device 260 according to Embodiment 1.

[0108] In step S510, the data acquisition unit 261 acquires inference data. Specifically, the data acquisition unit 261 acquires environmental information and user information as inference data.

[0109] In step S520, the inference unit 262 inputs environmental information and user information, which are inference data acquired by the data acquisition unit 261, into the trained model 283 stored in the trained model storage unit 253, and obtains discomfort index information corresponding to the input information as an inference result obtained by the trained model 283.

[0110] In step S530, the inference result obtained by the trained model 283 is output to the outdoor unit 120. Specifically, the inference unit 262 transmits the inference result obtained by the trained model 283 to the server control unit 240. The server control unit 240 transmits the inference result to the outdoor unit control unit 126 of the outdoor unit 120.

[0111] The inference results obtained by the trained model 283 are discomfort index information corresponding to the inference data acquired by the data acquisition unit 261.

[0112] In step S540, the outdoor unit 120 uses the inference result to correct the discomfort index in step S150 described above to determine the discomfort index information, and controls the air conditioner 100 based on the determined discomfort index information.

[0113] Thus, since the inference unit 262 uses the trained model 283, it can easily infer discomfort index information. As a result, the air conditioner 100 can perform air conditioning control using the discomfort index information calculated by the air conditioner 100 and the server 200.

[0114] Furthermore, although the learning device 250 and the inference device 260 are used to learn discomfort index information, the learning device 250 and the inference device 260 may be separate devices from the server 200, for example, connected to the server 200 via a network such as the Internet. Also, at least one of the learning device 250 and the inference device 260 may be connected to the server 200 via a network, for example. Also, at least one of the learning device 250 and the inference device 260 may be separate devices from the server 200. In addition, at least one of the learning device 250 and the inference device 260 may reside on a cloud server. Also, at least one of the learning device 250 and the inference device 260 may be built into the server 200. Also, at least one of the learning device 250 and the inference device 260 may be built into the external control terminal 300.

[0115] Furthermore, although Embodiment 1 was described as outputting discomfort index information using a trained model 283 learned by the model generation unit 252 of server 200, it is also possible to obtain a trained model from an external device such as another server 200 and output discomfort index information based on this trained model.

[0116] Furthermore, while Embodiment 1 described a case where supervised learning is applied to the learning algorithm used by the model generation unit 252, it is not limited to this. In addition to supervised learning, reinforcement learning, unsupervised learning, or semi-supervised learning can also be applied to the learning algorithm.

[0117] Furthermore, the model generation unit 252 may learn discomfort index information according to training data created for multiple external control terminals 300. The model generation unit 252 may acquire training data from multiple external control terminals 300 used in the same area, or it may learn discomfort index information using training data collected from multiple external control terminals 300 operating independently in different areas. It is also possible to add or remove external control terminals 300 that collect training data as targets during the process. Moreover, a learning device that has learned discomfort index information for one external control terminal 300 may be applied to another external control terminal 300, and the discomfort index information for that other external control terminal 300 may be relearned and updated.

[0118] Furthermore, the learning algorithm used in the model generation unit 252 can be deep learning, which learns to extract the features themselves, or machine learning can be performed according to other known methods, such as support vector machines.

[0119] According to the first embodiment of the air conditioning control system described above, the air conditioning control system comprises an air conditioner and a server capable of communicating with the air conditioner, and includes an air conditioner having an indoor temperature sensor for detecting the temperature of a room which is the area to be air-conditioned by the air conditioner, an indoor humidity sensor for detecting the humidity of a room, a first discomfort index calculation unit that calculates a first discomfort index of the room using the indoor temperature information detected by the indoor temperature sensor and the indoor humidity information detected by the indoor humidity sensor, and a control unit that controls the operation of the air conditioner based on the indoor discomfort index, and a server having a second discomfort index calculation unit that calculates a second discomfort index based on user characteristics information indicating the characteristics of the user when using the air conditioner and discomfort index information reporting the temperature sensation of the room felt by the user when using the air conditioner, and environmental information which is information indicating the operating environment of the air conditioner, and the control unit controls the operation of the air conditioner based on at least the first discomfort index.

[0120] Furthermore, in the air conditioning control system 1 according to Embodiment 1, a learning device is realized that includes a first data acquisition unit that acquires learning data including user information, which includes user characteristic information indicating the characteristics of the user when using the air conditioner and discomfort index information reporting the temperature sensation in the room felt by the user when using the air conditioner; environmental information, which is information indicating the operating environment of the air conditioner; and discomfort index information corresponding to the state of the environmental information and user information; and a model generation unit that generates a trained model for inferring discomfort index information corresponding to the combination of environmental information and user information using the learning data.

[0121] Furthermore, in the air conditioning control system 1 according to Embodiment 1, an inference device is realized that includes a second data acquisition unit that acquires user information including user characteristic information indicating the characteristics of the user when using the air conditioner and discomfort index information reporting the indoor temperature sensation felt by the user when using the air conditioner, and environmental information which is information indicating the operating environment of the air conditioner, and an inference unit that outputs discomfort index information from the environmental information and user information using a trained model for inferring discomfort index information corresponding to the combination of environmental information and user information.

[0122] The air conditioning control system 1 according to the above-described embodiment 1 is configured to calculate the discomfort index in both the air conditioner 100 and the server 200 to obtain discomfort index information. Therefore, the discomfort index can be calculated and discomfort index information can be obtained even without inputting user information such as user information. As a result, the air conditioning control system 1 can perform heating and cooling control in the air conditioner 100 even without inputting user information such as user information.

[0123] In other words, the air conditioning control system 1 can calculate the discomfort index using the indoor temperature information detected by the indoor temperature sensor 1111 and the indoor humidity information detected by the indoor humidity sensor 1112, through the outdoor unit discomfort index calculation unit 125 of the outdoor unit 120 of the air conditioner 100. That is, the air conditioning control system 1 calculates the air conditioner's discomfort index as the discomfort index in the air conditioner 100 using only the information obtained by the air conditioner 100, without using information from the user. As a result, the air conditioning control system 1 can obtain discomfort index information from the air conditioner 100 alone without using information from the user, and based on this discomfort index information, can automatically control the air conditioning of the air conditioner 100 so that the indoor environment becomes comfortable according to the value of the discomfort index information.

[0124] As a result, the air conditioning control system 1 eliminates the inconvenience of users having to frequently input user information and other data in order to obtain a comfortable indoor environment, thereby reducing the burden on users and improving user comfort.

[0125] Furthermore, since the air conditioning control system 1 is configured to calculate discomfort index information on the server 200 based on environmental information and user information, it can implement air conditioning control that is more comfortable for the user. In addition, since the server 200 is configured to calculate discomfort index information using machine learning, it can calculate more accurate discomfort index information, and thus implement air conditioning control that is more comfortable for the user.

[0126] Next, the hardware configuration of each component of the control unit 80 according to Embodiment 1 will be described. The control unit 80 according to Embodiment 1 corresponds to the indoor unit control unit 114 of the indoor unit 110 of the air conditioner 100, the outdoor unit control unit 126 of the outdoor unit 120 of the air conditioner 100, the remote control control unit 135 of the remote control unit 130, the server control unit 240 of the server 200, and the terminal control unit 350 of the external control terminal 300, according to Embodiment 1. Each function of the control unit 80 according to Embodiment 1 is realized by a processing circuit. The processing circuit may be dedicated hardware, or it may be a processing unit that executes a program stored in a memory device.

[0127] When the processing circuit is dedicated hardware, the processing circuit may be a single circuit, a complex circuit, a programmed processor, a parallel programmed processor, an application-specific integrated circuit, a field-programmable gate array, or a combination thereof. Figure 15 shows a configuration in which each function of the control unit 80 according to Embodiment 1 is realized in hardware. The processing circuit 81 incorporates a logic circuit 81a that realizes the functions of the control unit 80.

[0128] If the processing circuit 81 is a processing unit, the functions of the control unit 80 are realized by software, firmware, or a combination of software and firmware.

[0129] Figure 16 shows a configuration in which each function of the control unit 80 according to Embodiment 1 is implemented by software. The processing circuit 81 includes a processor 811 that executes program 81b, a random access memory 812 used by the processor 811 as a work area, and a storage device 813 that stores program 81b. The processor 811 loads program 81b stored in the storage device 813 onto the random access memory 812 and executes it, thereby realizing the functions of the control unit 80. The software or firmware is written in a programming language and stored in the storage device 813. The processor 811 can be a central processing unit, but is not limited to this. The storage device 813 can be a semiconductor memory such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), or EEPROM (Electrically Erasable Programmable Read Only Memory). The semiconductor memory may be non-volatile memory or volatile memory. Furthermore, the storage device 813 can be a magnetic disk, flexible disk, optical disk, compact disk, minidisc, or DVD (Digital Versatile Disc) in addition to semiconductor memory. The processor 811 may output data such as calculation results to the storage device 813 for storage, or it may store such data in an auxiliary storage device (not shown) via the random access memory 812. By integrating the processor 811, random access memory 812, and storage device 813 onto a single chip, the functions of the control unit 80 can be realized by a microcomputer.

[0130] The processing circuit 81 realizes the functions of the control unit 80 by reading and executing the program 81b stored in the memory device 813. The program 81b can also be described as instructing the computer to execute the procedures and methods for realizing the functions of the control unit 80.

[0131] Furthermore, the processing circuit 81 may implement some of the functions of the control unit 80 using dedicated hardware, and some of the functions of the control unit 80 using software or firmware.

[0132] Thus, the processing circuit 81 can realize each of the above-mentioned functions through hardware, software, firmware, or a combination thereof.

[0133] The configurations shown in the above embodiments are merely examples, and it is possible to combine them with other known technologies, combine different embodiments, and omit or modify parts of the configuration without departing from the gist of the invention. [Explanation of Symbols]

[0134] 1 Air conditioning control system, 80 Control unit, 81 Processing circuit, 81a Logic circuit, 81b Program, 100 Air conditioner, 110 Indoor unit, 111 Indoor unit sensor, 112 Indoor unit memory unit, 113 Indoor unit communication unit, 114 Indoor unit control unit, 120 Outdoor unit, 121 Outdoor unit sensor, 122 Outdoor unit memory unit, 123 Outdoor unit communication unit, 124 Acquisition unit, 125 Outdoor unit discomfort index calculation unit, 126 Outdoor unit control unit, 130 Remote controller, 131 Remote controller operation unit, 132 Remote controller display unit, 133 Remote controller memory unit, 134 Remote controller communication unit, 135 Remote controller control unit, 200 Server, 210 Server communication unit, 220 Server memory unit, 221 Storage unit, 230 Server discomfort index calculation unit, 240 Server control unit, 250 Learning device, 251, 261 Data acquisition unit, 252 Model generation unit, 253 Trained model storage unit, 260 Inference device, 262 Inference unit, 270 Machine learning device, 281 Input information, 282 Discomfort index information, 283 Trained model, 300 External control terminal, 310 Terminal operation unit, 320 Terminal display unit, 330 Terminal storage unit, 340 Terminal communication unit, 350 Terminal control unit, 400 Internet, 811 Processor, 812 Random access memory, 813 Storage device, 1111 Indoor temperature sensor, 1112 Indoor humidity sensor.

Claims

1. An air conditioning control system comprising an air conditioner and a server capable of communicating with the air conditioner, An indoor temperature sensor for detecting the temperature of the room, which is the area to be air-conditioned by the air conditioner, An indoor humidity sensor for detecting the humidity in the room, A first discomfort index calculation unit calculates a first discomfort index for the room using the indoor temperature information detected by the indoor temperature sensor and the indoor humidity information detected by the indoor humidity sensor. A control unit that controls the operation of the air conditioner based on the indoor discomfort index, An air conditioner having, A server having a second discomfort index calculation unit that calculates a second discomfort index based on user information including user characteristic information indicating the characteristics of the user when using the air conditioner and discomfort index information reporting the indoor temperature sensation felt by the user when using the air conditioner, and environmental information which is information indicating the operating environment of the air conditioner. Equipped with, The control unit, The operation of the air conditioner is controlled based at least on the first discomfort index, The operation of the air conditioner is controlled based on the discomfort index that has the largest difference between the first discomfort index and the second discomfort index, which is the discomfort index information that the user perceives as the indoor environment to be comfortable. Air conditioning control system.

2. The control unit controls the operation of the air conditioner based on the first discomfort index and the second discomfort index. The air conditioning control system according to claim 1.

3. The user characteristics information includes the user's gender, age, and clothing when using the air conditioner. The air conditioning control system according to claim 1 or 2.

4. The aforementioned environmental information includes the weather, season, and time of day when the air conditioner is in use. The air conditioning control system according to claim 1.

5. The server stores user information and environmental information transmitted from multiple external control terminals that remotely operate the setting and control of the operating conditions of the air conditioner via the server, grouped by similar information. The air conditioning control system according to claim 1.

6. The aforementioned server, A first data acquisition unit acquires learning data including the user information, the environmental information, and the discomfort index information corresponding to the state of the environmental information and the user information. A model generation unit generates a trained model for inferring discomfort index information corresponding to a combination of environmental information and user information using the aforementioned training data. A learning device having The air conditioning control system according to claim 1.

7. The aforementioned server, A second data acquisition unit that acquires the user information and the environment information, An inference unit that outputs the discomfort index information from the environmental information and the user information using a trained model for inferring the discomfort index information corresponding to the combination of the environmental information and the user information, Having an inference device equipped with, The air conditioning control system according to claim 1.

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