Air conditioner control method and device, electronic equipment and computer readable storage medium

Abstract

The embodiment of the invention discloses an air conditioner control method and device, electronic equipment and a computer readable storage medium. The method comprises the steps that environment information of a space where an air conditioner is located is obtained, and a thermal imaging image of a user in the space is obtained; determining a target feature vector according to the environment information and the thermal imaging image; performing thermal comfort prediction on the target feature vector to obtain a thermal comfort value; and a target operation strategy is determined according to the thermal comfort degree value, and the target operation strategy is an operation strategy for air conditioner control under the thermal comfort degree value. According to the air conditioner control method provided by the embodiment of the invention, the air conditioner can be controlled according to the current thermal comfort value of the user, so that the sensible temperature of the user is closer to the set temperature.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of air conditioning technology, and specifically to an air conditioning control method, device, electronic device, and computer-readable storage medium. Background Art

[0002] The air conditioning system is an indispensable part of modern buildings. It provides occupants with a comfortable living environment by regulating indoor temperature, humidity and air flow. However, the air conditioning system also has some problems and shortcomings.

[0003] In the prior art, the air conditioner only adjusts its operating mode or operating strategy according to the indoor temperature. However, there is a certain difference between the user's perceived temperature and the indoor temperature, resulting in the air conditioner being unable to adjust to a temperature that satisfies the user during operation, thereby reducing the user's experience.

[0004] Therefore, simply relying on indoor temperature to control the air conditioner cannot meet user needs. For this reason, the air conditioning system needs to be controlled more intelligently. Summary of the invention

[0005] The embodiments of the present application provide an air conditioning control method, device, electronic device and computer-readable storage medium, which can control the air conditioning according to the user's current thermal comfort value to make the user's perceived temperature closer to the set temperature, thereby achieving the technical effect of accurately formulating operating strategies according to the thermal comfort value and improving the user experience.

[0006] In a first aspect, an embodiment of the present application provides an air conditioning control method, which is applied to an air conditioner, and the method includes:

[0007] Acquiring environmental information of a space where the air conditioner is located, and acquiring thermal imaging images of users in the space;

[0008] Determine a target feature vector according to the environmental information and the thermal imaging image;

[0009] Performing thermal comfort prediction on the target feature vector to obtain a thermal comfort value;

[0010] A target operating strategy is determined according to the thermal comfort value, wherein the target operating strategy is an operating strategy for performing air conditioning control under the thermal comfort value.

[0011] Optionally, in some embodiments of the present application, determining a target feature vector according to the environmental information and the thermal imaging image includes:

[0012] Determine a first feature vector according to the environmental information, wherein the environmental information includes at least one of the following: a temperature value, a humidity value, and a wind speed;

[0013] Encoding the thermal imaging image to determine a second eigenvector, wherein the second eigenvector is used to characterize the color intensity of the thermal imaging image;

[0014] The target feature vector is obtained by fusing the first feature vector and the second feature vector.

[0015] Optionally, in some embodiments of the present application, encoding the thermal imaging image to determine the second feature vector includes:

[0016] Dividing the thermal imaging image into a plurality of sub-images;

[0017] Determine the color intensity of each sub-image in the plurality of sub-images to obtain a plurality of color intensity values, wherein one sub-image corresponds to one color intensity value;

[0018] The second feature vector is determined based on the plurality of color intensity values.

[0019] Optionally, in some embodiments of the present application, determining a target operation strategy according to the thermal comfort value includes:

[0020] Determining a change in compressor frequency of the air conditioner and a change in fan speed of the air conditioner corresponding to the thermal comfort value;

[0021] The target operation strategy is determined according to the compressor frequency change, the fan speed change and the thermal comfort value.

[0022] Optionally, in some embodiments of the present application, determining the target operation strategy according to the compressor frequency change, the fan speed change and the thermal comfort value includes:

[0023] Determining an operating mode of the air conditioner, wherein the operating mode includes at least one of the following: a cooling mode and a heating mode;

[0024] In the case where the working mode is the cooling mode, if the thermal comfort value is greater than or equal to a preset value, determining that the target operation strategy is that the compressor frequency is increased according to the compressor frequency change amount, and the fan is increased according to the fan speed change amount;

[0025] In the case where the working mode is the cooling mode, if the thermal comfort value is less than the preset value, determining the target operation strategy as the compressor frequency reduction according to the compressor frequency change amount, and the fan downshifting according to the fan speed change amount;

[0026] In the case where the working mode is the heating mode, if the thermal comfort value is greater than or equal to a preset value, determining that the target operation strategy is to reduce the frequency of the compressor according to the compressor frequency change amount, and to reduce the speed of the fan according to the fan speed change amount;

[0027] When the working mode is the heating mode, if the thermal comfort value is less than the preset value, the target operation strategy is determined as the compressor frequency is increased according to the compressor frequency change, and the fan is increased according to the fan speed change.

[0028] Optionally, in some embodiments of the present application, after determining the target operation strategy according to the thermal comfort value, the method further includes:

[0029] If the first compressor frequency of the compressor after frequency reduction according to the compressor frequency change amount is less than the first preset frequency, controlling the compressor to stop;

[0030] If the second compressor frequency of the compressor after the frequency is increased according to the compressor frequency change amount is greater than the second preset frequency, controlling the compressor to operate according to the second preset frequency;

[0031] If the first fan speed of the fan after downshifting according to the fan speed change is less than the first preset speed, controlling the fan to stop;

[0032] If the second fan speed of the fan after the fan is shifted up according to the fan speed change is greater than a second preset speed, the fan is controlled to operate according to the second preset speed.

[0033] Optionally, in some embodiments of the present application, determining a target operation strategy according to the thermal comfort value further includes:

[0034] Obtaining a thermal comfort evaluation of the user;

[0035] The target operation strategy is determined according to the thermal comfort value and the thermal comfort evaluation, wherein the thermal comfort evaluation is a real-time thermal comfort evaluation of the user.

[0036] In a second aspect, an embodiment of the present application further provides an air conditioning control device, which is applied to an air conditioner, and the device includes:

[0037] An acquisition module, used to acquire environmental information of a space where the air conditioner is located, and to acquire thermal imaging images of users in the space;

[0038] A processing module, used for determining a target feature vector according to the environmental information and the thermal imaging image;

[0039] The processing module is further used to perform thermal comfort prediction on the target feature vector to obtain a thermal comfort value;

[0040] The processing module is further used to determine a target operation strategy according to the thermal comfort value, wherein the target operation strategy is an operation strategy for performing air conditioning control under the thermal comfort value.

[0041] Optionally, in some embodiments of the present application, the processing module is used to:

[0042] Determine a first feature vector according to the environmental information, wherein the environmental information includes at least one of the following: a temperature value, a humidity value, and a wind speed;

[0043] Encoding the thermal imaging image to determine a second eigenvector, wherein the second eigenvector is used to characterize the color intensity of the thermal imaging image;

[0044] The target feature vector is obtained by fusing the first feature vector and the second feature vector.

[0045] Optionally, in some embodiments of the present application, the processing module is further used to:

[0046] Dividing the thermal imaging image into a plurality of sub-images;

[0047] Determine the color intensity of each sub-image in the plurality of sub-images to obtain a plurality of color intensity values, wherein one sub-image corresponds to one color intensity value;

[0048] The second feature vector is determined based on the plurality of color intensity values.

[0049] Optionally, in some embodiments of the present application, the processing module is further used to:

[0050] Determining a change in compressor frequency of the air conditioner and a change in fan speed of the air conditioner corresponding to the thermal comfort value;

[0051] The target operation strategy is determined according to the compressor frequency change, the fan speed change and the thermal comfort value.

[0052] Optionally, in some embodiments of the present application, the processing module is further used to:

[0053] Determining an operating mode of the air conditioner, wherein the operating mode includes at least one of the following: a cooling mode and a heating mode;

[0054] In the case where the working mode is the cooling mode, if the thermal comfort value is greater than or equal to a preset value, determining that the target operation strategy is that the compressor frequency is increased according to the compressor frequency change amount, and the fan is increased according to the fan speed change amount;

[0055] In the case where the working mode is the cooling mode, if the thermal comfort value is less than the preset value, determining the target operation strategy as the compressor frequency reduction according to the compressor frequency change amount, and the fan downshifting according to the fan speed change amount;

[0056] In the case where the working mode is the heating mode, if the thermal comfort value is greater than or equal to a preset value, determining that the target operation strategy is to reduce the frequency of the compressor according to the compressor frequency change amount, and to reduce the speed of the fan according to the fan speed change amount;

[0057] When the working mode is the heating mode, if the thermal comfort value is less than the preset value, the target operation strategy is determined as the compressor frequency is increased according to the compressor frequency change, and the fan is increased according to the fan speed change.

[0058] Optionally, in some embodiments of the present application, the processing module is further used to:

[0059] If the first compressor frequency of the compressor after frequency reduction according to the compressor frequency change amount is less than the first preset frequency, controlling the compressor to stop;

[0060] If the second compressor frequency of the compressor after the frequency is increased according to the compressor frequency change amount is greater than the second preset frequency, controlling the compressor to operate according to the second preset frequency;

[0061] If the first fan speed of the fan after downshifting according to the fan speed change is less than the first preset speed, controlling the fan to stop;

[0062] If the second fan speed of the fan after the fan is shifted up according to the fan speed change is greater than a second preset speed, the fan is controlled to operate according to the second preset speed.

[0063] Optionally, in some embodiments of the present application, the processing module is further used to:

[0064] Obtaining a thermal comfort evaluation of the user;

[0065] The target operation strategy is determined according to the thermal comfort value and the thermal comfort evaluation, wherein the thermal comfort evaluation is a real-time thermal comfort evaluation of the user.

[0066] In a third aspect, an embodiment of the present application further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps in the above-mentioned air conditioning control method when executed by the processor.

[0067] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps in the above-mentioned air conditioning control method are implemented.

[0068] In a fifth aspect, the embodiments of the present application further provide a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. The processor of the computer device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the method provided in various optional implementations described in the embodiments of the present application.

[0069] In summary, the embodiments of the present application obtain environmental information of the space where the air conditioner is located, and obtain a thermal imaging image of the user in the space; determine a target feature vector based on the environmental information and the thermal imaging image; perform thermal comfort prediction on the target feature vector to obtain a thermal comfort value; determine a target operation strategy based on the thermal comfort value, wherein the target operation strategy is a technical solution for an operation strategy for controlling the air conditioner under the thermal comfort value, and can formulate a target operation strategy based on the user's current thermal comfort value, and control the air conditioner based on the target operation strategy, thereby achieving the technical effect of accurately controlling the operation of the air conditioner based on the thermal comfort value, making the user's perceived temperature closer to the set temperature, and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the technical solutions in the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0071] Figure 1 A schematic diagram of a scenario of an air conditioning control method provided in an embodiment of the present application;

[0072] Figure 2 is a schematic diagram of a scenario in which an air conditioner according to an embodiment of the present application executes the air conditioner control method;

[0073] Figure 3 is a schematic diagram of a dual-flow model structure corresponding to the air-conditioning control method provided in an embodiment of the present application;

[0074] Figure 4 It is a schematic diagram of a process of determining a target feature vector through a dual-stream model provided in an embodiment of the present application;

[0075] Figure 5 is a schematic diagram of a single-flow model structure corresponding to the air-conditioning control method provided in an embodiment of the present application;

[0076] Figure 6 It is a schematic diagram of a process of determining a target feature vector through a single stream model provided in an embodiment of the present application;

[0077] Figure 7 It is a schematic diagram of the data collection and multimodal learning model establishment process provided by the embodiment of the present application;

[0078] Figure 8 It is a schematic diagram of the BP neural network structure provided in the embodiment of the present application;

[0079] Fig. 9 It is a schematic diagram of the target operation strategy generation process provided by the embodiment of the present application;

[0080] Fig.10 This is a schematic diagram of a process flow for controlling air-conditioning operation according to a target operation strategy provided by an embodiment of the present application;

[0081] Fig.11 is a structural schematic diagram of an air conditioning control device provided in an embodiment of the present application;

[0082] Fig.12 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0083] The following will be combined with the drawings in this application to clearly and completely describe the technical solutions in this application. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments in the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0084] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the above features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0085] In this application, the word "exemplary" is used to mean "serving as an example, illustration, or illustration." Any embodiment described in this application as "exemplary" is not necessarily to be construed as being preferred or advantageous over other embodiments. The following description is given to enable any person skilled in the art to implement and use the invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the invention can be implemented without using these specific details. In other instances, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in this application.

[0086] First, the terms involved in this application are explained:

[0087] Thermal sensation index: Predicted Mean Vote, PMV, is the average value of the group's evaluation of 7 levels of thermal sensation based on the thermal balance of the human body, including: hot (+3), warm (+2), slightly warm (+1), moderate (0), slightly cool (-1), cool (-2), cold (-3). In the 1970s, Danish Professor Fanger comprehensively considered the influence of 10 parameters related to human thermal comfort, including human metabolism, effective mechanical power, clothing thermal resistance, clothing surface area coefficient, air temperature, etc., in order to quantify the thermal sensation comfort of the human body.

[0088] Thermal Sensation Vote (TSV) is one of the most widely used indicators in thermal comfort research. The seven scales of sensation voting are usually based on the ASHRAE 7-point scale system, including: hot (+3), warm (+2), slightly warm (+1), moderate (0), slightly cool (-1), cool (-2), and cold (-3).

[0089] Multimodal Learning: Multimodal Learning refers to a machine learning method that uses multiple different perceptual modalities (such as images, text, audio, etc.) for learning and reasoning. Traditional machine learning methods usually only use a single input modality for learning and prediction, while multimodal learning can integrate information from multiple modalities to obtain more comprehensive and accurate results.

[0090] The embodiments of the present application provide an air conditioning control method, device, electronic device, and computer-readable storage medium. Specifically, the embodiments of the present application provide an air conditioning control device applicable to the air conditioning control method, the air conditioning control device includes an air conditioning and a main control device of the air conditioning, and the air conditioning can be a wall-mounted air conditioning, a cabinet air conditioning, a window air conditioning, a ceiling air conditioning, an embedded air conditioning, etc.

[0091] In the prior art, the control strategies of air conditioners are becoming more and more diverse. During the operation of the air conditioner, the operation strategy of the air conditioner can be adjusted according to the collected information such as temperature, humidity, wind speed, etc.

[0092] For example, the air conditioning equipment obtains indoor temperature information based on its own temperature sensor. At the same time, it uses a humidity sensor to obtain indoor humidity information, as well as the fan speed during its own operation. It controls its own operating state based on the above information obtained to adjust the indoor temperature.

[0093] However, the existing air conditioning control method cannot accurately adjust the indoor temperature to a satisfactory result for the user. For example, during cooling in summer, the human body may feel too cold due to the blowing of air. At this time, the indoor temperature cannot well reflect the indoor thermal comfort, but may cause energy loss in order to maintain the current temperature. Correspondingly, when the air conditioner is in heating operation, since hot air is lighter than cold air, hot air will rise during heating, causing the temperature in the upper half of the room to be higher than that in the lower half. At the same time, since the temperature sensor of the air conditioner indoor unit is located in the upper part of the room, the temperature detected by the room temperature probe of the air conditioner indoor unit is higher than that in the lower half of the room. In addition, the temperature receptors of the human body are unevenly distributed, and there are more cold receptors on the feet. Therefore, it is easy to feel cold feet in winter. However, because the temperature information obtained by the temperature sensor reaches the set temperature value, the air conditioner can only maintain the current temperature, resulting in a poor user experience.

[0094] Therefore, the air conditioning control method in the prior art has the problem of being unable to meet the thermal comfort of users.

[0095] The embodiment of the present application provides an air conditioning control method, device, electronic device and computer-readable storage medium. The method adopts the following technical solutions: obtaining environmental information of the space where the air conditioner is located, and obtaining thermal imaging images of users in the space; determining a target feature vector according to the environmental information and the thermal imaging image; predicting thermal comfort of the target feature vector to obtain a thermal comfort value; and determining a target operation strategy according to the thermal comfort value, wherein the target operation strategy is an operation strategy for air conditioning control under the thermal comfort value.

[0096] In summary, the air conditioning control method in the embodiment of the present application can control the air conditioning according to the user's current thermal comfort value, so that the user's perceived temperature is closer to the set temperature, thereby achieving the technical effect of accurately formulating operating strategies according to the thermal comfort value and improving the user experience.

[0097] It should be noted that the order of description of the following embodiments is not intended to limit the priority order of the embodiments.

[0098] See also Figure 1 , Figure 1 The scene diagram of the air conditioning control method provided in the embodiment of the present application, the air conditioning control system may include an air conditioner 100, a main control device 200 and a shooting module 300, the air conditioner 100, the main control device 200 and the shooting module 300 may be connected to each other by any means, including but not limited to signal communication through electronic circuits, communication through wireless signals, the wireless signal may be a computer network communication of the TCP / IP protocol suite (TCP / IP Protocol Suite, TCP / IP), the user datagram protocol (User Datagram Protocol, UDP), etc. The air conditioner 100 may receive a control signal from a remote control or a control panel, the air conditioner 100 may also receive a command message sent by the main control device 200, the air conditioner 100 may perform a corresponding operation according to the corresponding command message, and accordingly, the shooting module 300 may also receive a control signal from a remote control or a control panel, the shooting module 300 may also receive a command message sent by the main control device 200, the shooting module 300 may perform a corresponding operation according to the corresponding command message, such as the air conditioning control method in the present application.

[0099] In the embodiment of the present application, the air conditioner 100 includes but is not limited to a wall-mounted air conditioner, a cabinet air conditioner, a window air conditioner, a ceiling air conditioner, an embedded air conditioner, etc.

[0100] Those skilled in the art will understand that Figure 1The application environment shown in the figure is only one application scenario of the present application solution and does not constitute a limitation on the application scenario of the present application solution. Other application environments may also include Figure 1 More or less air conditioning as shown in Figure 1 Only one air conditioner is shown, and the specific details are not limited here.

[0101] In addition, if Figure 1 As shown, the main control device 200 may include any hardware device capable of data processing and command sending, such as a CPU or a single-chip microcomputer embedded in the air conditioner, and the specific details are not limited here.

[0102] In addition, if Figure 1 As shown, the shooting module 300 may include any hardware device capable of acquiring images, such as a camera embedded inside the air conditioner, and the specific details are not limited here.

[0103] It should be noted that Figure 1 The scene diagram of the air-conditioning control system shown is only an example. The air-conditioning control system and scene described in the embodiment of the present application are intended to more clearly illustrate the technical solution of the embodiment of the present application, and do not constitute a limitation on the technical solution provided in the embodiment of the present application. A person of ordinary skill in the art can know that with the evolution of the air-conditioning control system and the emergence of new business scenarios, the technical solution provided in the embodiment of the present application is also applicable to similar technical problems.

[0104] For details, please refer to Figure 2 , Figure 2 : is a schematic diagram of a scenario in which an air conditioner according to an embodiment of the present application executes the air conditioner control method, wherein the specific execution process of the air conditioner executing the air conditioner control method is as follows:

[0105] S201: Acquire environmental information of a space where the air conditioner is located, and acquire thermal imaging images of users in the space;

[0106] In an embodiment of the present application, in order to control the air conditioner according to the thermal comfort of the human body indoors, indoor environmental parameters can be collected through indoor temperature sensors, humidity sensors, wind speed sensors and other sensing devices to obtain environmental information; at the same time, thermal imaging images of the human body can be obtained through thermal imagers or other image capture devices to obtain the surface temperature of the human body.

[0107] Optionally, the air conditioner can be controlled by calculating the thermal comfort value (PMV value) based on the acquired temperature data, humidity data, wind speed data and human body temperature data obtained from the thermal imaging image using the PMV formula in the prior art.

[0108] However, the existing PMV formula also needs to consider parameters such as human metabolic rate, human work power, water vapor partial pressure in the ambient air, air temperature around the human body, average radiation temperature, ratio of clothed area to naked area, clothing outer surface temperature, surface heat transfer coefficient, etc. The above parameters are difficult to obtain or calculate, resulting in poor accuracy of the thermal comfort value calculated according to the PMV formula. Accordingly, the air conditioning control effect cannot meet user needs.

[0109] In the embodiments of the present application, a thermal comfort prediction model is constructed through multimodal learning, and a thermal comfort value is obtained after predicting and processing the environmental information and thermal imaging images, and the air conditioner is controlled according to the thermal comfort value, thereby achieving the technical effect of accurately formulating operating strategies and improving user experience.

[0110] S202: determining a target feature vector according to environmental information and the thermal imaging image;

[0111] In an embodiment of the present application, first, the acquired data (such as text, images, etc.) is encoded to obtain a representation vector; secondly, these vectors are fused, and a representation vector, that is, a target feature vector, is output based on the single modal data and the fused data.

[0112] It should be noted that some external knowledge can also be integrated in the process of vector fusion, such as knowledge graphs, language models, computer vision models, etc. Single-modal data refers to the text data corresponding to environmental information and the image data corresponding to thermal imaging images; fused data refers to the feature vector data after feature extraction and fusion of text data and image data.

[0113] Optionally, the air conditioning control method provided in the embodiment of the present application also includes: determining a first eigenvector based on environmental information, wherein the environmental information includes at least one of the following: temperature value, humidity value and wind speed; encoding the thermal imaging image to determine a second eigenvector, wherein the second eigenvector is used to characterize the color intensity of the thermal imaging image; and obtaining a target eigenvector by fusing the first eigenvector and the second eigenvector.

[0114] In the embodiment of the present application, a single-stream model and / or a dual-stream model may be used to determine the target feature vector.

[0115] Alternatively, if Figure 3 The schematic diagram of the dual-stream model structure shown in the figure first determines the first eigenvector based on the environmental information, and then determines the second eigenvector based on the thermal imaging image, and the first eigenvector and the second eigenvector are fused to obtain the target eigenvector.

[0116] Specifically, Figure 4As shown in the figure, a flow chart of determining the target feature vector through the dual-stream model is shown. Since the text information of the environmental information is relatively simple and all of it is digital information, all of this information can be directly extracted. This part of the data is one-dimensional data, such as [abc]. A row of data represents temperature, humidity, and wind speed data respectively, and this one-dimensional data is used as the first feature vector.

[0117] Optionally, the air conditioning control method provided in the embodiment of the present application also includes: dividing the thermal imaging image into multiple sub-images; determining the color intensity of each sub-image in the multiple sub-images to obtain multiple color intensity values, wherein one sub-image corresponds to one color intensity value; and determining a second eigenvector based on the multiple color intensity values.

[0118] Optionally, the image data can be directly divided into n rows and m columns, where n and m can be the same or different, to obtain n*m sub-images, and the three-dimensional graphic data can be converted into one-dimensional data. Each row of data is used as a separate data to form one-dimensional data. The data type of each sub-image is [RGB], 0≤R\G\B≤256, that is, each sub-image consists of 3 colors.

[0119] Optionally, each row of data is composed of [[RGB]1[RGB]2…[RGB] n ], each row of data is a single column of data, then the one-dimensional data form of the overall image data is: That is, the entire image is composed of n*m sub-images of 3 colors.

[0120] Alternatively, if Figure 5 The single-stream model structure diagram shown in Figure 1 and Figure 6 The schematic diagram of the process of determining the target feature vector through a single-stream model is shown, which directly takes the environmental information and the thermal imaging image as input, extracts features from the data after the environmental information and the thermal imaging image are fused, and determines the target feature vector.

[0121] It should be noted that MSE, mean squared loss function, represents the mean square error loss function; CEL ， Cross-Entropy Loss function represents the cross entropy loss function; MAE, Mean Absolute Error represents the mean absolute error function.

[0122] Optionally, after fusing the text data with the image data, it can be assumed that there are currently one thousand groups of sample data, and the data is divided into a test set and a training set at a ratio of 7:3. At this time, the text data of the training set is represented by a feature matrix (700*3), and the text data of the test set is represented by a feature matrix (300*3). The image feature data of the training set is represented by a matrix (700*n), and the image data features of the test set are represented by a matrix (300*n). The fusion features of the training set are represented by a matrix (700*(n+3)), and the fusion features of the test set are represented by a matrix (300*(n+3)). Among them, the column vector represents the feature data of each thermal comfort index, and the row vector represents different thermal comfort evaluation data.

[0123] Optionally, after the target feature vector is determined by using the single-stream model and / or the dual-stream model, the target feature vector after fusion processing may be expressed as: The target feature vector will be used as the input value of the thermal comfort prediction model.

[0124] S203: Predicting thermal comfort for the target feature vector to obtain a thermal comfort value;

[0125] In the present application embodiment, Figure 7 The data collection and multimodal learning model establishment process diagram shown in the figure can obtain a thermal comfort prediction model by training the text data and image data pre-stored in the database and the PMV or TSV label data known in the database through multimodal learning.

[0126] Specifically, BP neural network can be used for classification prediction. BP neural network algorithm is an algorithm proposed based on BP neural network. It can select a set of weights at random, use the target output to establish a linear equation for solution, and then use the error between the output value and the actual value to adjust the weights. It is also called the reverse propagation algorithm. It has strong nonlinear mapping ability and flexible network structure, and has relatively mature applications in function approximation, pattern recognition, classification and data compression. Figure 8 As shown in the schematic diagram of the BP neural network structure, the BP neural network algorithm model is divided into an input layer, a single hidden layer, and an output layer.

[0127] Specifically, Figure 8 As shown, the input is x, the output is y, the number of data samples is n, the input variable dimension is p, the output variable dimension is q, the hidden layer is A, the number of nodes is h, the weight matrix connecting each layer is w, and the activation function is the Sigmoid function.

[0128] First, the output of the hidden layer can be calculated by the input layer and then calculated using the activation function. The specific formula is as follows:

[0129]

[0130] In the above formula, f(x) is the activation function, A k is the output value of the kth hidden layer node, w 1 is the weight matrix connecting the input layer and the hidden layer, β k is the threshold of the hidden layer node.

[0131] After obtaining the output value of the hidden layer, it is used as the input data of the output layer to calculate the final output result. The specific formula is as follows.

[0132]

[0133] In the above formula, w 2 is the weight matrix, γ k is the threshold of the output layer node. The predicted output result is finally calculated through the above formula

[0134] The output result The forward propagation of the surface signal ends. Then the weight matrix w is adjusted by error back propagation to find the optimal solution of the prediction model and improve the generalization ability of the model. The formula is as follows:

[0135]

[0136] The above formula can be used to calculate the error E of a single sample during training: i The formula for calculating the total error E of Danz training is as follows:

[0137]

[0138] The single training error E is obtained, which can be used for gradient calculation and then update the weight matrix w. The specific calculation formula is as follows:

[0139]

[0140] w ij =w ij +w ij

[0141] α is the learning rate. If α is too small, it is easy to fall into the local optimum, and if α is too large, it is difficult to find the global optimal solution. When the termination condition is reached, the training ends and the thermal comfort prediction model is obtained.

[0142] Optionally, after inputting the target feature vector into the thermal comfort prediction model for thermal comfort prediction, the label data Y of the thermal comfort value can be obtained. The label data Y is one-dimensional data, as follows: [y], and its value range is -3, -2, -1, 0, 1, 2, 3.

[0143] S204: Determine a target operation strategy according to the thermal comfort value, wherein the target operation strategy is an operation strategy for air conditioning control under the thermal comfort value.

[0144] In the present application embodiment, Fig. 9 As shown in the schematic diagram of the target operation strategy generation process, the air-conditioning control system can upload the indoor temperature, humidity, air outlet speed, and thermal image information taken by the thermal imager to the cloud server through the wifi module, and input them into the cloud artificial intelligence model as input variables. The artificial intelligence model outputs the thermal comfort index (PMV index or TSV index) and transmits the data to the air-conditioning control system via wifi.

[0145] Optionally, the air conditioning control method provided in the embodiment of the present application also includes: determining the change in compressor frequency of the air conditioner and the change in fan speed of the air conditioner corresponding to the thermal comfort value; determining the target operation strategy based on the change in compressor frequency, the change in fan speed and the thermal comfort value.

[0146] In the embodiment of the present application, the frequency change and speed change of the air-conditioning compressor and the fan under the thermal comfort value can be determined according to the thermal comfort value.

[0147] Optionally, the control cycle of the air conditioner can be determined based on the sampling cycle and the communication time with the cloud. For example, one cycle can be set to between 0 and 1 minute.

[0148] Optionally, the air conditioning control method provided in the embodiment of the present application also includes: determining an operating mode of the air conditioner, wherein the operating mode includes at least one of the following: a cooling mode and a heating mode; when the operating mode is the cooling mode, if the thermal comfort value is greater than or equal to a preset value, determining a target operating strategy as an increase in frequency of the compressor according to a change in the compressor frequency, and an increase in gear of the fan according to a change in the fan speed; when the operating mode is the cooling mode, if the thermal comfort value is less than a preset value, determining a target operating strategy as a decrease in frequency of the compressor according to a change in the compressor frequency, and a decrease in gear of the fan according to a change in the fan speed; when the operating mode is the heating mode, if the thermal comfort value is greater than or equal to a preset value, determining a target operating strategy as a decrease in frequency of the compressor according to a change in the compressor frequency, and a decrease in gear of the fan according to a change in the fan speed; when the operating mode is the heating mode, if the thermal comfort value is greater than or equal to a preset value, determining a target operating strategy as a decrease in frequency of the compressor according to a change in the compressor frequency, and a decrease in gear of the fan according to a change in the fan speed; when the operating mode is the heating mode, if the thermal comfort value is less than a preset value, determining a target operating strategy as an increase in frequency of the compressor according to a change in the compressor frequency, and an increase in gear of the fan according to a change in the fan speed.

[0149] Specifically, Fig.10Schematic diagram of controlling the air conditioner operation process according to the target operation strategy. Taking the case where the air conditioner working mode is the cooling mode as an example, when the thermal comfort index (PMV index or TSV index) is 0, the human body is in the best comfort state at this time, and the air conditioner system remains unchanged. When the PMV index or TSV index is -1, it means that the human body's thermal comfort state is slightly cool at this time, the internal fan of the air conditioner reduces the rotation speed by one gear, and the compressor reduces the frequency at a rate of kp1; when the PMV index or TSV index is -2, it means that the human body's thermal comfort state is cool at this time, the internal fan of the air conditioner reduces the rotation speed by one gear, and the compressor reduces the frequency at a speed of kp2; when the PMV index or TSV index is -3, it means that the human body's thermal comfort state is cold at this time, the internal fan of the air conditioner reduces to the lowest rotation speed, and the compressor reduces the frequency at a speed of kp3; when the PMV index or TSV index is 1, it means that the human body's thermal comfort state is slightly warm at this time, the internal fan of the air conditioner increases the rotation speed by one gear, and the compressor increases the frequency at a rate of kp1; when the PMV index or TSV index is 2, it means that the human body's thermal comfort state is warm at this time, the internal fan of the air conditioner increases the rotation speed by one gear, and the compressor increases the frequency at a speed of kp2; when the PMV index or TSV index is 3, it means that the human body's thermal comfort state is hot at this time, the internal fan of the air conditioner increases to the maximum rotation speed, and the compressor increases the frequency at a speed of kp3.

[0150] It should be noted that the heating state of the air conditioner is opposite to the cooling state.

[0151] It should also be noted that the preset value of the thermal comfort value can be set to 0, and the frequency change amount of the compressor can be set as: 0 < kp1 < kp2 < kp3 < the maximum frequency change value of the compressor.

[0152] After determining the target operation strategy according to the thermal comfort value, optionally, the air conditioner control method provided by the embodiments of the present application further includes: if the first compressor frequency after the compressor reduces the frequency according to the compressor frequency change amount is less than the first preset frequency, then control the compressor to stop; if the second compressor frequency after the compressor increases the frequency according to the compressor frequency change amount is greater than the second preset frequency, then control the compressor to operate according to the second preset frequency; if the first fan speed after the fan reduces the gear according to the fan speed change amount is less than the first preset speed, then control the fan to stop; if the second fan speed after the fan increases the gear according to the fan speed change amount is greater than the second preset speed, then control the fan to operate according to the second preset speed.

[0153] In the embodiments of the present application, if the fan speed needs to increase the gear when it is at the highest, it remains at the highest gear, and if the fan speed needs to reduce the gear when it is at the lowest, it remains at the lowest gear.

[0154] Optionally, when the air conditioner is operating in cooling mode, if the thermal comfort index value is -3 to -1 for several consecutive cycles and the compressor frequency has dropped to the minimum (first preset frequency) at the same time, the compressor is turned off. When the thermal comfort index is 1 or above, the compressor starts running again.

[0155] Optionally, when the air conditioner is in cooling mode, if the thermal comfort index value is 1 to 3 for several consecutive cycles and the compressor frequency has risen to the maximum (second preset frequency), the compressor is controlled to operate according to the second preset frequency.

[0156] Optionally, when the air conditioner is in heating mode, if the thermal comfort index value is 1 to 3 for several consecutive cycles and the compressor frequency has dropped to the minimum (first preset frequency), the compressor is turned off. When the thermal comfort index is -1 or above, the compressor starts running again.

[0157] Optionally, when the air conditioner is in heating mode, if the thermal comfort index value is -3 to -1 for several consecutive cycles and the compressor frequency has risen to the maximum (second preset frequency), the compressor is controlled to operate according to the second preset frequency.

[0158] Optionally, when the air conditioner is operating in cooling mode, if the thermal comfort index value is -3 to -1 for several consecutive cycles and the fan speed has dropped to the minimum (first preset speed) at the same time, the fan is turned off. When the thermal comfort index is 1 or above, the fan starts running again.

[0159] Optionally, when the air conditioner is in cooling mode, if the thermal comfort index value is 1 to 3 for several consecutive cycles and the fan speed has risen to the maximum (second preset speed), the fan is controlled to run according to the second preset speed.

[0160] Optionally, when the air conditioner is in heating mode, if the thermal comfort index value is 1 to 3 for several consecutive cycles and the fan speed has dropped to the minimum (first preset speed) at the same time, the fan is turned off. When the thermal comfort index is -1 or above, the fan starts running again.

[0161] Optionally, when the air conditioner is in heating mode, if the thermal comfort index value is -3 to -1 for several consecutive cycles, and at the same time the fan speed has risen to the maximum (second preset speed), the fan is controlled to run according to the second preset speed.

[0162] It should be noted that the air-conditioning system can also be controlled by comprehensively considering the indoor and outdoor temperature conditions.

[0163] Optionally, the air conditioning control method provided in the embodiment of the present application also includes: obtaining a user's thermal comfort evaluation; determining a target operation strategy based on the thermal comfort value and the thermal comfort evaluation, wherein the thermal comfort evaluation is a real-time thermal comfort evaluation of the user.

[0164] In an embodiment of the present application, the data uploaded to the cloud during the operation of the air-conditioning system will continue to train the multimodal learning model. At the same time, people can also conduct real-time thermal comfort evaluation of the current air-conditioning environment through a mobile phone APP. The air-conditioning system will be adjusted according to the real-time evaluation data of the current person to meet the comfort requirements. At the same time, the current data and the person's evaluation of the comfort level will be uploaded to the cloud to continue training the multimodal learning model. When there is enough data from human evaluation, the cloud will generate an AI thermal comfort model that is only suitable for the current person.

[0165] Through the embodiments of the present application, the environmental information of the space where the air conditioner is located and the thermal imaging image of the user in the space are obtained; the target feature vector is determined according to the environmental information and the thermal imaging image; the thermal comfort level of the target feature vector is predicted to obtain a thermal comfort level; the target operation strategy is determined according to the thermal comfort level, wherein the target operation strategy is a technical solution for the operation strategy of air conditioning control under the thermal comfort level. The target operation strategy can be formulated according to the current thermal comfort level of the user, and the air conditioner can be controlled according to the target operation strategy, thereby achieving the technical effect of accurately controlling the operation of the air conditioner according to the thermal comfort level, making the user's perceived temperature closer to the set temperature, and improving the user experience.

[0166] In order to better implement the air conditioning control method of the present application, the present application also provides an air conditioning control device based on the air conditioning control method, wherein the meanings of the terms are the same as those in the air conditioning control method, and the specific implementation details can refer to the description in the method embodiment.

[0167] See also Fig.11 , Fig.11 1 is a schematic diagram of the structure of an air conditioning control device provided in an embodiment of the present application, wherein the air conditioning control device 1100 is applied to an air conditioner, and specifically can be as follows:

[0168] The acquisition module 1101 is used to acquire environmental information of the space where the air conditioner is located, and to acquire thermal imaging images of users in the space;

[0169] A processing module 1102 is used to determine a target feature vector according to environmental information and a thermal imaging image;

[0170] The processing module 1102 is also used to predict the thermal comfort of the target feature vector to obtain a thermal comfort value;

[0171] The processing module 1102 is further configured to determine a target operation strategy according to the thermal comfort value, wherein the target operation strategy is an operation strategy for performing air conditioning control under the thermal comfort value.

[0172] Optionally, in some embodiments of the present application, the processing module 1102 is used to:

[0173] Determine a first eigenvector according to environmental information, wherein the environmental information includes at least one of the following: a temperature value, a humidity value, and a wind speed;

[0174] Encoding the thermal imaging image to determine a second eigenvector, wherein the second eigenvector is used to characterize the color intensity of the thermal imaging image;

[0175] The target feature vector is obtained by fusing the first feature vector and the second feature vector.

[0176] Optionally, in some embodiments of the present application, the processing module 1102 is further configured to:

[0177] Dividing the thermal imaging image into a plurality of sub-images;

[0178] Determine the color intensity of each sub-image in the plurality of sub-images to obtain a plurality of color intensity values, wherein one sub-image corresponds to one color intensity value;

[0179] Based on the plurality of color intensity values, a second eigenvector is determined.

[0180] Optionally, in some embodiments of the present application, the processing module 1102 is further configured to:

[0181] Determine the change in compressor frequency of the air conditioner and the change in fan speed of the air conditioner corresponding to the thermal comfort value;

[0182] The target operation strategy is determined based on the compressor frequency change, fan speed change and thermal comfort value.

[0183] Optionally, in some embodiments of the present application, the processing module 1102 is further configured to:

[0184] Determining an operating mode of the air conditioner, wherein the operating mode includes at least one of the following: a cooling mode and a heating mode;

[0185] When the working mode is cooling mode, if the thermal comfort value is greater than or equal to the preset value, the target operation strategy is determined as the compressor frequency is increased according to the compressor frequency change, and the fan is increased according to the fan speed change;

[0186] When the working mode is cooling mode, if the thermal comfort value is less than a preset value, the target operation strategy is determined as the compressor frequency is reduced according to the compressor frequency change, and the fan is downshifted according to the fan speed change;

[0187] When the working mode is the heating mode, if the thermal comfort value is greater than or equal to the preset value, the target operation strategy is determined as the compressor frequency is reduced according to the compressor frequency change, and the fan is downshifted according to the fan speed change;

[0188] When the working mode is the heating mode, if the thermal comfort value is less than the preset value, the target operation strategy is determined as the compressor frequency is increased according to the compressor frequency change, and the fan is increased according to the fan speed change.

[0189] Optionally, in some embodiments of the present application, the processing module 1102 is further configured to:

[0190] If the first compressor frequency of the compressor after the frequency reduction according to the compressor frequency change is less than the first preset frequency, the compressor is controlled to stop;

[0191] If the second compressor frequency of the compressor after the frequency is increased according to the compressor frequency change amount is greater than the second preset frequency, controlling the compressor to operate according to the second preset frequency;

[0192] If the first fan speed of the fan after the fan is downshifted according to the fan speed change is less than the first preset speed, the fan is controlled to stop;

[0193] If the second fan speed of the fan after the fan is upshifted according to the fan speed change is greater than the second preset speed, the fan is controlled to run according to the second preset speed.

[0194] Optionally, in some embodiments of the present application, the processing module 1102 is further configured to:

[0195] Obtain the user's thermal comfort evaluation;

[0196] The target operation strategy is determined according to the thermal comfort value and the thermal comfort evaluation, wherein the thermal comfort evaluation is the real-time thermal comfort evaluation of the user.

[0197] In the embodiment of the present application, the acquisition module first acquires the environmental information of the space where the air conditioner is located, and acquires the thermal imaging image of the user in the space. Then, the processing module determines the target feature vector based on the environmental information and the thermal imaging image. Subsequently, the processing module predicts the thermal comfort of the target feature vector to obtain the thermal comfort value. Then, the processing module determines the target operation strategy based on the thermal comfort value, wherein the target operation strategy is the operation strategy for controlling the air conditioner under the thermal comfort value.

[0198] Among them, the embodiment of the present application obtains the environmental information of the space where the air conditioner is located, and obtains the thermal imaging image of the user in the space; determines the target feature vector according to the environmental information and the thermal imaging image; predicts the thermal comfort of the target feature vector to obtain the thermal comfort value; determines the target operation strategy according to the thermal comfort value, wherein the target operation strategy is a technical solution for the operation strategy of air conditioning control under the thermal comfort value, and the target operation strategy can be formulated according to the user's current thermal comfort value, and the air conditioner is controlled according to the target operation strategy, thereby realizing the technical effect of accurately controlling the air conditioner operation according to the thermal comfort value, making the user's body temperature closer to the set temperature, and improving the user experience.

[0199] In addition, the present application also provides an electronic device, such as Fig.12 As shown, it shows a schematic diagram of the structure of the electronic device involved in this application, specifically:

[0200] The electronic device may include components such as a processor 1201 with one or more processing cores, a memory 1202 with one or more computer-readable storage media, a power supply 1203, and an input unit 1204. Those skilled in the art will appreciate that Fig.12 The electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0201] The processor 1201 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. By running or executing software programs and / or modules stored in the memory 1202 and calling data stored in the memory 1202, it executes various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. Optionally, the processor 1201 may include one or more processing cores; preferably, the processor 1201 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 1201.

[0202] The memory 1202 can be used to store software programs and modules. The processor 1201 executes various functional applications and data processing by running the software programs and modules stored in the memory 1202. The memory 1202 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 1202 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 1202 may also include a memory controller to provide the processor 1201 with access to the memory 1202.

[0203] The electronic device also includes a power supply 1203 for supplying power to each component. Preferably, the power supply 1203 can be logically connected to the processor 1201 through a power management system, so as to manage charging, discharging, and power consumption through the power management system. The power supply 1203 can also include any components such as one or more DC or AC power supplies, recharging systems, power supply device debugging circuits, power converters or inverters, and power status indicators.

[0204] The electronic device may further include an input unit 1204, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0205] Although not shown, the electronic device may further include a display unit, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 1201 in the electronic device will load the executable files corresponding to the processes of one or more application programs into the memory 1202 according to the following instructions, and the processor 1201 will run the application programs stored in the memory 1202, thereby implementing the steps in any one of the air conditioning control methods provided in the embodiments of the present application.

[0206] The embodiment of the present application obtains environmental information of the space where the air conditioner is located, and obtains a thermal imaging image of the user in the space; determines a target feature vector based on the environmental information and the thermal imaging image; performs thermal comfort prediction on the target feature vector to obtain a thermal comfort value; determines a target operation strategy based on the thermal comfort value, wherein the target operation strategy is a technical solution for an operation strategy for controlling the air conditioner under the thermal comfort value, and can formulate a target operation strategy based on the user's current thermal comfort value, and control the air conditioner based on the target operation strategy, thereby achieving the technical effect of accurately controlling the operation of the air conditioner based on the thermal comfort value, making the user's perceived temperature closer to the set temperature, and improving the user experience.

[0207] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0208] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0209] To this end, the present application provides a computer-readable storage medium, on which a computer program is stored. The computer program can be loaded by a processor to execute the steps in any air conditioning control method provided in the present application.

[0210] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0211] The computer-readable storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0212] Since the instructions stored in the computer-readable storage medium can execute the steps in any air-conditioning control method provided in the present application, the beneficial effects that can be achieved by any air-conditioning control method provided in the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0213] The above is a detailed introduction to an air conditioning control method, device, electronic device and computer-readable storage medium provided by the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. An air conditioning control method, characterized in that: Applied to air conditioning, the method comprises: Acquiring environmental information of a space where the air conditioner is located, and acquiring thermal imaging images of users in the space; Determine a target feature vector according to the environmental information and the thermal imaging image; Performing thermal comfort prediction on the target feature vector to obtain a thermal comfort value; A target operating strategy is determined according to the thermal comfort value, wherein the target operating strategy is an operating strategy for performing air conditioning control under the thermal comfort value.

2. The method according to claim 1, characterized in that The determining of the target feature vector according to the environmental information and the thermal imaging image comprises: Determine a first feature vector according to the environmental information, wherein the environmental information includes at least one of the following: a temperature value, a humidity value, and a wind speed; Encoding the thermal imaging image to determine a second eigenvector, wherein the second eigenvector is used to characterize the color intensity of the thermal imaging image; The target feature vector is obtained by fusing the first feature vector and the second feature vector.

3. The method according to claim 2, characterized in that The step of encoding the thermal imaging image to determine a second feature vector includes: Dividing the thermal imaging image into a plurality of sub-images; Determine the color intensity of each sub-image in the plurality of sub-images to obtain a plurality of color intensity values, wherein one sub-image corresponds to one color intensity value; The second feature vector is determined based on the plurality of color intensity values.

4. The method according to claim 1, characterized in that: Determining a target operation strategy according to the thermal comfort value includes: Determining a change in compressor frequency of the air conditioner and a change in fan speed of the air conditioner corresponding to the thermal comfort value; The target operation strategy is determined according to the compressor frequency change, the fan speed change and the thermal comfort value.

5. The method according to claim 4, characterized in that The determining the target operation strategy according to the compressor frequency change, the fan speed change and the thermal comfort value includes: Determining an operating mode of the air conditioner, wherein the operating mode includes at least one of the following: a cooling mode and a heating mode; In the case where the working mode is the cooling mode, if the thermal comfort value is greater than or equal to a preset value, determining that the target operation strategy is that the compressor frequency is increased according to the compressor frequency change amount, and the fan is increased according to the fan speed change amount; In the case where the working mode is the cooling mode, if the thermal comfort value is less than the preset value, determining the target operation strategy as the compressor frequency reduction according to the compressor frequency change amount, and the fan downshifting according to the fan speed change amount; In the case where the working mode is the heating mode, if the thermal comfort value is greater than or equal to a preset value, determining that the target operation strategy is to reduce the frequency of the compressor according to the compressor frequency change amount, and to reduce the speed of the fan according to the fan speed change amount; When the working mode is the heating mode, if the thermal comfort value is less than the preset value, the target operation strategy is determined as the compressor frequency is increased according to the compressor frequency change, and the fan is increased according to the fan speed change.

6. The method according to claim 5, characterized in that After determining the target operation strategy according to the thermal comfort value, the method further includes: If the first compressor frequency of the compressor after frequency reduction according to the compressor frequency change amount is less than the first preset frequency, controlling the compressor to stop; If the second compressor frequency of the compressor after the frequency is increased according to the compressor frequency change amount is greater than the second preset frequency, controlling the compressor to operate according to the second preset frequency; If the first fan speed of the fan after downshifting according to the fan speed change is less than the first preset speed, controlling the fan to stop; If the second fan speed of the fan after the fan is shifted up according to the fan speed change is greater than a second preset speed, the fan is controlled to operate according to the second preset speed.

7. The method according to claim 1, characterized in that The determining of the target operation strategy according to the thermal comfort value further includes: Obtaining a thermal comfort evaluation of the user; The target operation strategy is determined according to the thermal comfort value and the thermal comfort evaluation, wherein the thermal comfort evaluation is a real-time thermal comfort evaluation of the user.

8. An air conditioning control device, characterized in that: Applied to air conditioning, the device comprises: An acquisition module, used to acquire environmental information of a space where the air conditioner is located, and to acquire thermal imaging images of users in the space; A processing module, used for determining a target feature vector according to the environmental information and the thermal imaging image; The processing module is further used to perform thermal comfort prediction on the target feature vector to obtain a thermal comfort value; The processing module is further used to determine a target operation strategy according to the thermal comfort value, wherein the target operation strategy is an operation strategy for performing air conditioning control under the thermal comfort value.

9. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the air conditioning control method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the air conditioning control method according to any one of claims 1 to 7 are implemented.

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