Air conditioner control method, device and equipment based on non-contact human body heat feeling prediction

Abstract

The invention provides an air conditioner control method, device and equipment based on non-contact human body heat feeling prediction. The method comprises the steps that according to a first interval duration, latest environment parameters and skin temperature data collected by a sensor module are obtained in a timing mode; inputting the newest environmental parameters and the skin temperature data into a TSV prediction model, and determining the current thermal comfort condition of the target individual based on an output thermal feeling prediction value; and after warm air control parameters corresponding to the thermal comfort condition are obtained according to a preset warm air adjusting strategy, the air conditioning system is controlled according to the warm air control parameters. According to the embodiment of the invention, the TSV prediction model is jointly constructed by using the latest environmental parameters and the skin temperature data, so that the individual thermal feeling can be accurately reflected, the air conditioning system can be regulated and controlled according to individual differences, and the personalized thermal comfort experience of a user is improved.

Description

Technical Field

[0001] The present invention relates to the field of air conditioning, and in particular to an air conditioning control method, device and equipment based on non-contact human thermal sensation prediction. Background Art

[0002] Existing air conditioning systems generally use traditional manual temperature settings or control strategies based on the Predicted Mean Vote (PMV) model. The former relies on active user adjustments and struggles to respond to environmental changes in real time, leading to energy waste and insufficient comfort. The latter, which calculates the PMV based on parameters such as air temperature, relative humidity, air velocity, and human metabolism to control temperature, is relatively more scientific. However, the required parameters are expensive to detect in practice, and PMV targets the average thermal comfort level of a group, making it difficult to account for individual differences. Furthermore, neither approach incorporates the actual thermal comfort state of the human body as feedback into the control loop. This means that even if the set environmental parameters meet the preset standards, an individual may still experience discomfort. Clearly, neither control method can meet people's growing demand for personalized thermal comfort.

[0003] Therefore, the existing air-conditioning system has the problem of being unable to meet the personalized thermal comfort needs of the human body. Summary of the Invention

[0004] The embodiments of the present invention provide an air conditioning control method, device and equipment based on non-contact human thermal sensation prediction, aiming to solve the problem that existing air conditioning systems cannot meet the personalized thermal comfort needs of the human body.

[0005] In a first aspect, an embodiment of the present invention provides an air conditioning control method based on non-contact human thermal sensation prediction, the method comprising:

[0006] Regularly obtain the latest environmental parameters and skin temperature data collected by the sensor module according to the first interval duration;

[0007] After inputting the latest environmental parameters and the skin temperature data into the TSV prediction model, the current thermal comfort status of the target individual is determined based on the output thermal sensation prediction value;

[0008] After obtaining the warm air control parameters corresponding to the thermal comfort condition according to the preset warm air adjustment strategy, the air conditioning system is controlled according to the warm air control parameters.

[0009] In a second aspect, an embodiment of the present invention further provides an air conditioning control device based on non-contact human thermal sensation prediction, the device comprising:

[0010] An acquisition unit, configured to periodically acquire the latest environmental parameters and skin temperature data acquired by the sensor module according to a first interval duration;

[0011] a determination unit, configured to input the latest environmental parameters and the skin temperature data into a TSV prediction model, and determine the current thermal comfort status of the target individual based on the output thermal sensation prediction value;

[0012] The control unit is used to obtain the temperature and air control parameters corresponding to the thermal comfort condition according to a preset temperature and air adjustment strategy, and then control the air conditioning system according to the temperature and air control parameters.

[0013] In a third aspect, an embodiment of the present invention further provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the method described in the first aspect when executing the computer program.

[0014] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the method described in the first aspect can be implemented.

[0015] The present invention provides an air conditioning control method, device, and apparatus based on non-contact human thermal sensation prediction. The method comprises: periodically acquiring the latest environmental parameters and skin temperature data collected by a sensor module according to a first interval; inputting the latest environmental parameters and skin temperature data into a TSV prediction model, and determining the current thermal comfort state of a target individual based on the output thermal sensation prediction value; acquiring thermal sensation control parameters corresponding to the thermal comfort state according to a preset thermal sensation adjustment strategy, and controlling the air conditioning system according to the thermal sensation control parameters. The embodiments of the present invention utilize the latest environmental parameters and skin temperature data to jointly construct a TSV prediction model, which accurately reflects individual thermal sensation, enabling the air conditioning system to be adjusted based on individual differences, thereby enhancing the user's personalized thermal comfort experience; based on the thermal sensation prediction value, acquiring corresponding thermal sensation control parameters, dynamically adjusting the operating parameters of the air conditioning system according to the thermal sensation control parameters, and continuously correcting the thermal sensation control parameters using the regularly fed back thermal sensation prediction value, thereby forming a closed-loop control. The present invention automatically responds to environmental changes and user preferences without manual user intervention, ensuring that the indoor environment is always in an individually thermally comfortable state. Furthermore, the adaptive adjustment mechanism can effectively reduce unnecessary energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 A schematic flow chart of an air conditioning control method based on non-contact human thermal sensation prediction provided by an embodiment of the present invention;

[0018] Figure 2 A schematic block diagram of an air conditioning control device based on non-contact human thermal sensation prediction provided by an embodiment of the present invention;

[0019] Figure 3 A schematic block diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0021] It will be understood that when used in this specification and the appended claims, the terms “comprises” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0022] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the present invention. As used in the specification and appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0023] It should be further understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0024] Figure 1 Schematic diagram of the flow of the air conditioning control method based on non-contact human thermal sensation prediction provided by the embodiment of the present invention. Figure 1 As shown, the method includes steps S110-S130.

[0025] S110 , regularly obtaining the latest environmental parameters and skin temperature data collected by the sensor module according to the first interval duration.

[0026] In this embodiment, the first interval duration can be set to 10 minutes, and the latest environmental parameters and skin temperature data collected by the sensor module are regularly obtained every 10 minutes; specifically, the sensor module includes an environmental parameter sensor and a non-contact sensor; the environmental parameter sensor is used to collect the latest environmental parameters, and the latest environmental parameters include but are not limited to ambient temperature, ambient humidity, and ambient wind speed; the non-contact sensor is used to collect the skin temperature data of the target individual.

[0027] In one embodiment, before step S110, it also includes: when an air-conditioning system start-up signal is detected, determining whether the air-conditioning system is used for the first time; if it is used for the first time, controlling the air-conditioning system based on a preset initialization value; if it is not used for the first time, retrieving the optimal temperature and wind control parameters that match the latest environmental parameters from the historical database, and controlling the air-conditioning system according to the optimal temperature and wind control parameters.

[0028] In this embodiment, when the air-conditioning system start-up signal is detected, it is determined whether the air-conditioning system is used for the first time; if it is used for the first time, the air-conditioning system is controlled based on the preset initialization values; the initialization values ​​include the initial set temperature and the initial wind speed, the initial set temperature can be set to 25°C, and the initial wind speed can be set to medium.

[0029] If it is not the first time use, the optimal temperature and wind control parameters that match the latest environmental parameters are retrieved from the historical database, and the air-conditioning system is controlled according to the optimal temperature and wind control parameters; for example, when the ambient temperature is 25°C, the set temperature in the optimal temperature and wind control parameters is 26°C, and the wind speed is level 2.

[0030] S120 , after inputting the latest environmental parameters and the skin temperature data into the TSV prediction model, determine the current thermal comfort status of the target individual based on the output thermal sensation prediction value.

[0031] In this embodiment, after the latest environmental parameters and the skin temperature data are input into the TSV prediction model, the current thermal comfort condition of the target individual is determined based on the output thermal sensation prediction value; specifically, when -3≤TSV≤-2.5, the thermal comfort condition is "very cold", TSV is the thermal sensation prediction value, when -2.5≤TSV≤-0.5, the thermal comfort condition is "slightly cold", when -0.5≤TSV≤0.5, the thermal comfort condition is "comfortable", when 0.5≤TSV≤2.5, the thermal comfort condition is "slightly hot", and when 2.5≤TSV≤3, the thermal comfort condition is "very hot".

[0032] After the latest environmental parameters and the skin temperature data are input into the TSV prediction model, before determining the current thermal comfort status of the target individual based on the output thermal sensation prediction value, the following preparatory work needs to be completed: in the experimental stage, the subjective thermal perception of a large number of subjects under different indoor air conditions is collected, and subjective evaluation is performed according to the ASHRAE standard 7-level thermal sensation quantification table. At the same time, the corresponding ambient temperature and ambient wind speed are collected to construct data labels; after preprocessing and cleaning the collected raw data (such as subjective thermal perception data, environmental parameter data, etc.) (such as removing outliers, missing values ​​and standardizing data formats), the data is divided into training sets and test sets for subsequent model training and verification; specifically, a variety of machine learning algorithms (such as random forests, gradient boosting trees, neural networks, support vector machines, etc.) are used to train the model, and after cross-validation to evaluate the model prediction performance, the optimal TSV prediction model is selected for deployment for subsequent thermal sensation prediction.

[0033] In one embodiment, determining the current thermal comfort condition of the target individual based on the output thermal sensation prediction value includes: determining the thermal comfort classification interval to which the thermal sensation prediction value belongs according to a preset thermal sensation interval relationship table, and then determining the current thermal comfort condition of the target individual based on the thermal comfort classification interval.

[0034] In this embodiment, after determining the thermal comfort classification interval to which the thermal sensation prediction value belongs according to a preset thermal sensation interval relationship table, the current thermal comfort condition of the target individual is determined based on the thermal comfort classification interval; specifically, when -3≤TSV≤-2.5, the thermal comfort condition is "very cold", TSV is the thermal sensation prediction value, when -2.5≤TSV≤-0.5, the thermal comfort condition is "slightly cold", when -0.5≤TSV≤0.5, the thermal comfort condition is "comfortable", when 0.5≤TSV≤2.5, the thermal comfort condition is "slightly hot", and when 2.5≤TSV≤3, the thermal comfort condition is "very hot".

[0035] S130 : After obtaining a warm air control parameter corresponding to the thermal comfort condition according to a preset warm air adjustment strategy, control the air conditioning system according to the warm air control parameter.

[0036] In this embodiment, after obtaining the warm air control parameters corresponding to the thermal comfort condition according to the preset warm air adjustment strategy, the air conditioning system is controlled according to the warm air control parameters; the warm air adjustment strategy includes a temperature adjustment formula and a wind speed adjustment formula. The temperature adjustment formula is shown in formula (1):

[0037]

[0038] In formula (1), TSV is the predicted value of thermal sensation; T s is the set temperature, Ts0 is the last set temperature; T smax is the maximum set temperature, T smin is the minimum set temperature, K cold is the cooling correction coefficient, which is used to control the heating rate of the air-conditioning system in a relatively cold state, K hot is the thermal correction coefficient, which is used to control the cooling rate of the air conditioning system under hot conditions. e is the thermal perception deviation, e = TSV - TVS best , TVS best Indicates the TSV value under the optimal thermal comfort state, TVS best is 0, K p is the proportionality coefficient, K i is the integral coefficient, K d is the differential coefficient.

[0039] The wind speed adjustment formula is shown in formula (2):

[0040]

[0041] In formula (2), W s To set the wind speed level, W s0 It is the last set wind speed level, W smax is the maximum wind speed, W smin is the minimum wind speed.

[0042] According to the warm wind control strategy (temperature control formula and wind speed control formula), when -3≤TSV≤-2.5 (thermal comfort condition is "very cold"), the warm wind control parameter is "T s =T smax , W s =W smin ”;

[0043] When -2.5≤TSV≤-0.5 (thermal comfort condition is "slightly cold"), the warm air control parameter is "T s =T s0 +K cold ×(TVS+05), W s =W s0 -1", that is, based on the cold correction coefficient K cold Control the heating rate of the air-conditioning system and reduce the current wind speed of the air-conditioning system by one level;

[0044] When -0.5≤TSV≤0.5 (thermal comfort condition is "comfortable"), the PID control algorithm is introduced to regulate the set temperature of the air conditioning system. The PID control algorithm can accurately adjust the temperature according to the thermal sensation deviation so that TVS is stably maintained near 0. At this time, the warm air control parameter is "T s =T s0+PID(e),W s =W s0 ”;

[0045] When 0.5≤TSV≤2.5 (thermal comfort condition is “slightly hot”), the warm air control parameter is “T s =T s0 +K hot ×(TVS-05),W s =W s0 +1", which is based on the thermal correction coefficient K hot Control the cooling rate of the air-conditioning system and increase the current wind speed of the air-conditioning system by one level;

[0046] When 2.5≤TSV≤3 (thermal comfort condition is “very hot”), the warm air control parameter is “T s =T smin , W s =W smax ”.

[0047] In an embodiment of the present invention, when the thermal sensation prediction value is in the non-comfort zone, a linear adjustment strategy is adopted to quickly pull the thermal sensation prediction value back to the comfort zone, thereby quickly improving the ambient temperature and ensuring that people no longer feel extremely cold or hot; when the thermal sensation prediction value is in the comfort zone, a PID control strategy is adopted for fine adjustment to maintain the optimal thermal comfort state; at the same time, the wind speed adjustment algorithm is used as an auxiliary means to further improve the overall control effect; by dynamically adjusting the wind speed, air circulation can be more effectively promoted and the thermal comfort of the human body can be enhanced. This comprehensive control strategy can improve the response speed of the system and ensure stability and comfort over a long period of time.

[0048] In one embodiment, step S130 includes: if the thermal comfort condition is very cold, controlling the air-conditioning system according to the maximum set temperature and minimum wind speed in the warm wind adjustment strategy; if the thermal comfort condition is very hot, controlling the air-conditioning system according to the minimum set temperature and maximum wind speed in the warm wind adjustment strategy.

[0049] In this embodiment, when -3≤TSV≤-2.5, the thermal comfort state is "very cold". At this time, according to the maximum set temperature T in the warm air adjustment strategy, smax and minimum wind speed W smin Control the air conditioning system; preferably, a non-contact sensor is used to obtain the position of the personnel, and the air conditioning system is controlled to guide the air according to the position of the personnel.

[0050] When 2.5≤TSV≤3, the thermal comfort condition is "very hot". At this time, according to the minimum set temperature T in the temperature and wind control strategy, smin and maximum wind speed W smaxControl the air conditioning system; preferably, combine with a non-contact sensor to obtain the position of the personnel, and control the air conditioning system to avoid people and guide the air according to the position of the personnel.

[0051] In one embodiment, step S130 includes: if the thermal comfort condition is slightly cold, then after controlling the set temperature of the air-conditioning system according to the cold correction coefficient in the warm wind adjustment strategy, the current wind speed level of the air-conditioning system is lowered by one level; if the thermal comfort condition is slightly hot, then after controlling the set temperature of the air-conditioning system according to the hot correction coefficient in the warm wind adjustment strategy, the current wind speed level of the air-conditioning system is raised by one level.

[0052] In this embodiment, when -2.5≤TSV≤-0.5, the thermal comfort state is "slightly cold". At this time, according to the cooling correction coefficient K in the warm air adjustment strategy, cold The set temperature T of the air conditioning system s After the control is performed, the current wind speed level of the air conditioning system is lowered by one level; wherein, T s =T s0 +K cold ×(TVS+05), T s0 is the last set temperature, K cold It is the cooling correction coefficient, which is used to control the heating rate of the air-conditioning system.

[0053] When 0.5≤TSV≤2.5, the thermal comfort condition is "slightly hot". At this time, according to the thermal correction coefficient K in the temperature and wind control strategy, hot The set temperature T of the air conditioning system s After the control is performed, the current wind speed level of the air conditioning system is adjusted up by one level; wherein, T s =T s0 +K hot ×(TVS-05), K hot It is the thermal correction coefficient, which is used to control the cooling rate of the air-conditioning system.

[0054] In one embodiment, step S130 includes: if the thermal comfort condition is comfortable, regulating the set temperature of the air-conditioning system according to the PID control algorithm in the temperature and wind adjustment strategy, and keeping the current wind speed level unchanged.

[0055] In this embodiment, when -0.5≤TSV≤0.5, the thermal comfort condition is comfortable. At this time, according to the PID control algorithm T in the temperature and wind adjustment strategy, s =T s0 +PID(e) sets the temperature of the air conditioning system to T s Control and keep the current wind speed level unchanged; where e is the thermal sensation deviation, e = TSV - TVSbest , TVS best Indicates the TSV value under the optimal thermal comfort state.

[0056] The present invention introduces a PID control algorithm to regulate the set temperature of the air-conditioning system. The PID control algorithm can accurately adjust the temperature according to the thermal sensation deviation, so that the TVS is stably maintained near 0, ensuring that the indoor environment is always in an individual thermal comfort state.

[0057] In one embodiment, after regulating the set temperature of the air-conditioning system according to the PID control algorithm in the temperature wind adjustment strategy and keeping the current wind speed level unchanged, it also includes: adjusting the first interval duration to the second interval duration, and using the second interval duration as a period to execute the step of periodically obtaining the latest environmental parameters and skin temperature data collected by the sensor module.

[0058] In this embodiment, when -0.5≤TSV≤0.5, after the first interval duration is adjusted to the second interval duration, the step of periodically obtaining the latest environmental parameters and skin temperature data collected by the sensor module is performed with the second interval duration as a period to achieve adaptive adjustment of the indoor environment; wherein, the second interval duration can be set to 5 minutes.

[0059] In summary, the embodiment of the present invention utilizes the latest environmental parameters and skin temperature data to jointly construct a TSV prediction model, which can accurately reflect individual thermal perception, so that the air-conditioning system can be adjusted according to individual differences, thereby improving the user's personalized thermal comfort experience; based on the thermal sensation prediction value, the corresponding warm wind control parameters are obtained, and the operating parameters of the air-conditioning system are dynamically adjusted according to the warm wind control parameters. The warm wind control parameters are continuously corrected through the thermal sensation prediction value fed back at regular intervals, thereby forming a closed-loop control. The present invention does not require manual user intervention, automatically responds to environmental changes and user preferences, and ensures that the indoor environment is always in an individual thermal comfort state. At the same time, the adaptive adjustment mechanism can also effectively reduce unnecessary energy consumption.

[0060] Figure 2 This is a schematic block diagram of an air conditioning control device based on non-contact human thermal sensation prediction provided by an embodiment of the present invention. Figure 2 As shown, corresponding to the above air conditioning control method based on non-contact human thermal sensation prediction, the present invention also provides an air conditioning control device based on non-contact human thermal sensation prediction. Figure 2 The air conditioning control device 700 based on non-contact human thermal sensation prediction includes:

[0061] The acquisition unit 701 is configured to periodically acquire the latest environmental parameters and skin temperature data collected by the sensor module according to a first interval duration;

[0062] A determination unit 702 is configured to input the latest environmental parameters and the skin temperature data into a TSV prediction model, and determine the current thermal comfort status of the target individual based on the output thermal sensation prediction value;

[0063] The control unit 703 is configured to obtain a temperature control parameter corresponding to the thermal comfort condition according to a preset temperature adjustment strategy, and then control the air conditioning system according to the temperature control parameter.

[0064] In some embodiments, when executing the step of determining the current thermal comfort status of the target individual based on the output thermal sensation prediction value, the determining unit 702 is specifically configured to:

[0065] After determining the thermal comfort classification interval to which the thermal sensation prediction value belongs according to a preset thermal sensation interval relationship table, the current thermal comfort status of the target individual is determined based on the thermal comfort classification interval.

[0066] In some embodiments, after the control unit 703 obtains the temperature control parameters corresponding to the thermal comfort condition according to the preset temperature adjustment strategy, when controlling the air conditioning system according to the temperature control parameters, it is specifically used to:

[0067] If the thermal comfort condition is very cold, the air conditioning system is controlled according to the maximum set temperature and minimum wind speed in the warm air adjustment strategy;

[0068] If the thermal comfort condition is very hot, the air conditioning system is controlled according to the minimum set temperature and maximum wind speed in the warm wind adjustment strategy.

[0069] In some embodiments, after the control unit 703 obtains the temperature control parameters corresponding to the thermal comfort condition according to the preset temperature adjustment strategy, when controlling the air conditioning system according to the temperature control parameters, it is specifically used to:

[0070] If the thermal comfort condition is slightly cold, the set temperature of the air-conditioning system is controlled according to the cold correction coefficient in the warm air adjustment strategy, and the current wind speed level of the air-conditioning system is lowered by one level;

[0071] If the thermal comfort condition is slightly hot, the set temperature of the air-conditioning system is controlled according to the thermal sensitivity correction coefficient in the warm air adjustment strategy, and then the current wind speed level of the air-conditioning system is increased by one level.

[0072] In some embodiments, after the control unit 703 obtains the temperature control parameters corresponding to the thermal comfort condition according to the preset temperature adjustment strategy, when controlling the air conditioning system according to the temperature control parameters, it is specifically used to:

[0073] If the thermal comfort condition is comfortable, the set temperature of the air-conditioning system is regulated according to the PID control algorithm in the temperature and wind adjustment strategy, and the current wind speed level is kept unchanged.

[0074] In some embodiments, after executing the step of regulating the set temperature of the air-conditioning system according to the PID control algorithm in the temperature and wind adjustment strategy and maintaining the current wind speed level unchanged, the control unit 703 is further configured to:

[0075] After the first interval duration is adjusted to the second interval duration, the step of periodically acquiring the latest environmental parameters and skin temperature data collected by the sensor module is performed with the second interval duration as a period.

[0076] In some embodiments, before executing the step of periodically acquiring the latest environmental parameter and skin temperature data collected by the sensor module according to the first interval duration, the collection unit 701 is further configured to:

[0077] When an air conditioning system start-up signal is detected, determining whether the air conditioning system is used for the first time;

[0078] If it is the first time to use, the air conditioning system is controlled based on the preset initialization value;

[0079] If it is not the first time to use, the optimal temperature and air control parameters matching the latest environmental parameters are retrieved from the historical database, and the air conditioning system is controlled according to the optimal temperature and air control parameters.

[0080] It should be noted that technical personnel in the relevant field can clearly understand that the specific implementation process of the above-mentioned air-conditioning control device and each unit based on non-contact human thermal sensation prediction can refer to the corresponding description in the aforementioned method embodiment. For the convenience and conciseness of the description, it will not be repeated here.

[0081] The air conditioning control device based on non-contact human thermal sensation prediction can be implemented in the form of a computer program. The computer program can be used in Figure 3 Runs on the electronic devices shown.

[0082] See also Figure 3 , Figure 3 FIG. 8 is a schematic block diagram of an electronic device provided by an embodiment of the present invention. The electronic device 800 may be a controller of an air conditioning system.

[0083] See Figure 3 The electronic device 800 includes a processor 802 , a memory, and a network interface 805 connected via a system bus 801 , wherein the memory may include a non-volatile storage medium 803 and an internal memory 804 .

[0084] The non-volatile storage medium 803 can store an operating system 8031 ​​and a computer program 8032. The computer program 8032 includes program instructions, which, when executed, can enable the processor 802 to execute an air conditioning control method based on non-contact human thermal sensation prediction.

[0085] The processor 802 is used to provide computing and control capabilities to support the operation of the entire electronic device 800.

[0086] The internal memory 804 provides an environment for the operation of the computer program 8032 in the non-volatile storage medium 803. When the computer program 8032 is executed by the processor 802, the processor 802 can execute an air conditioning control method based on non-contact human thermal sensation prediction.

[0087] The network interface 805 is used to communicate with other devices over the network. Figure 3 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present invention, and does not constitute a limitation on the electronic device 800 to which the solution of the present invention is applied. The specific electronic device 800 may include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0088] The processor 802 is configured to execute a computer program 8032 stored in the memory to implement the following steps:

[0089] Regularly obtain the latest environmental parameters and skin temperature data collected by the sensor module according to the first interval duration;

[0090] After inputting the latest environmental parameters and the skin temperature data into the TSV prediction model, the current thermal comfort status of the target individual is determined based on the output thermal sensation prediction value;

[0091] After obtaining the warm air control parameters corresponding to the thermal comfort condition according to the preset warm air adjustment strategy, the air conditioning system is controlled according to the warm air control parameters.

[0092] In some embodiments, when implementing the step of determining the current thermal comfort status of the target individual based on the output thermal sensation prediction value, the processor 802 specifically implements the following steps:

[0093] After determining the thermal comfort classification interval to which the thermal sensation prediction value belongs according to a preset thermal sensation interval relationship table, the current thermal comfort status of the target individual is determined based on the thermal comfort classification interval.

[0094] In some embodiments, after the processor 802 obtains the temperature control parameters corresponding to the thermal comfort condition according to the preset temperature adjustment strategy, when controlling the air conditioning system according to the temperature control parameters, the processor 802 specifically implements the following steps:

[0095] If the thermal comfort condition is very cold, the air conditioning system is controlled according to the maximum set temperature and minimum wind speed in the warm air adjustment strategy;

[0096] If the thermal comfort condition is very hot, the air conditioning system is controlled according to the minimum set temperature and maximum wind speed in the warm wind adjustment strategy.

[0097] In some embodiments, after the processor 802 obtains the temperature control parameters corresponding to the thermal comfort condition according to the preset temperature adjustment strategy, when controlling the air conditioning system according to the temperature control parameters, the processor 802 specifically implements the following steps:

[0098] If the thermal comfort condition is slightly cold, the set temperature of the air-conditioning system is controlled according to the cold correction coefficient in the warm air adjustment strategy, and the current wind speed level of the air-conditioning system is lowered by one level;

[0099] If the thermal comfort condition is slightly hot, the set temperature of the air-conditioning system is controlled according to the thermal sensitivity correction coefficient in the warm air adjustment strategy, and then the current wind speed level of the air-conditioning system is increased by one level.

[0100] In some embodiments, after the processor 802 obtains the temperature control parameters corresponding to the thermal comfort condition according to the preset temperature adjustment strategy, when controlling the air conditioning system according to the temperature control parameters, the processor 802 specifically implements the following steps:

[0101] If the thermal comfort condition is comfortable, the set temperature of the air-conditioning system is regulated according to the PID control algorithm in the temperature and wind adjustment strategy, and the current wind speed level is kept unchanged.

[0102] In some embodiments, after implementing the step of regulating the set temperature of the air conditioning system according to the PID control algorithm in the temperature and air conditioning adjustment strategy and maintaining the current wind speed level unchanged, the processor 802 further implements the following steps:

[0103] After the first interval duration is adjusted to the second interval duration, the step of periodically acquiring the latest environmental parameters and skin temperature data collected by the sensor module is performed with the second interval duration as a period.

[0104] In some embodiments, before implementing the step of periodically acquiring the latest environmental parameter and skin temperature data collected by the sensor module according to the first interval duration, the processor 802 further implements the following steps:

[0105] When an air conditioning system start-up signal is detected, determining whether the air conditioning system is used for the first time;

[0106] If it is the first time to use, the air conditioning system is controlled based on the preset initialization value;

[0107] If it is not the first time to use, the optimal temperature and air control parameters matching the latest environmental parameters are retrieved from the historical database, and the air conditioning system is controlled according to the optimal temperature and air control parameters.

[0108] It should be understood that in the embodiment of the present invention, the processor 802 may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0109] Those skilled in the art will appreciate that all or part of the steps in the method of the above-described embodiment can be implemented by instructing the relevant hardware through a computer program. The computer program includes program instructions, which can be stored in a storage medium that is computer-readable. The program instructions are executed by at least one processor in the computer system to implement the steps in the method of the above-described embodiment.

[0110] Therefore, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. When the program instructions are executed by a processor, the processor performs the following steps:

[0111] Regularly obtain the latest environmental parameters and skin temperature data collected by the sensor module according to the first interval duration;

[0112] After inputting the latest environmental parameters and the skin temperature data into the TSV prediction model, the current thermal comfort status of the target individual is determined based on the output thermal sensation prediction value;

[0113] After obtaining the warm air control parameters corresponding to the thermal comfort condition according to the preset warm air adjustment strategy, the air conditioning system is controlled according to the warm air control parameters.

[0114] In one embodiment, when the processor executes the program instructions to implement the step of determining the current thermal comfort status of the target individual based on the output thermal sensation prediction value, the processor specifically implements the following steps:

[0115] After determining the thermal comfort classification interval to which the thermal sensation prediction value belongs according to a preset thermal sensation interval relationship table, the current thermal comfort status of the target individual is determined based on the thermal comfort classification interval.

[0116] In one embodiment, after the processor executes the program instructions to obtain the temperature control parameters corresponding to the thermal comfort condition according to the preset temperature adjustment strategy, the processor specifically implements the following steps when controlling the air conditioning system according to the temperature control parameters:

[0117] If the thermal comfort condition is very cold, the air conditioning system is controlled according to the maximum set temperature and minimum wind speed in the warm air adjustment strategy;

[0118] If the thermal comfort condition is very hot, the air conditioning system is controlled according to the minimum set temperature and maximum wind speed in the warm wind adjustment strategy.

[0119] In one embodiment, after the processor executes the program instructions to obtain the temperature control parameters corresponding to the thermal comfort condition according to the preset temperature adjustment strategy, the processor specifically implements the following steps when controlling the air conditioning system according to the temperature control parameters:

[0120] If the thermal comfort condition is slightly cold, the set temperature of the air-conditioning system is controlled according to the cold correction coefficient in the warm air adjustment strategy, and the current wind speed level of the air-conditioning system is lowered by one level;

[0121] If the thermal comfort condition is slightly hot, the set temperature of the air-conditioning system is controlled according to the thermal sensitivity correction coefficient in the warm air adjustment strategy, and then the current wind speed level of the air-conditioning system is increased by one level.

[0122] In one embodiment, after the processor executes the program instructions to obtain the temperature control parameters corresponding to the thermal comfort condition according to the preset temperature adjustment strategy, the processor specifically implements the following steps when controlling the air conditioning system according to the temperature control parameters:

[0123] If the thermal comfort condition is comfortable, the set temperature of the air-conditioning system is regulated according to the PID control algorithm in the temperature and wind adjustment strategy, and the current wind speed level is kept unchanged.

[0124] In one embodiment, after the processor executes the program instructions to control the set temperature of the air-conditioning system according to the PID control algorithm in the temperature and air conditioning adjustment strategy and maintains the current wind speed level unchanged, it further implements the following steps:

[0125] After the first interval duration is adjusted to the second interval duration, the step of periodically acquiring the latest environmental parameters and skin temperature data collected by the sensor module is performed with the second interval duration as a period.

[0126] In one embodiment, before executing the program instructions to implement the step of periodically acquiring the latest environmental parameter and skin temperature data collected by the sensor module according to the first interval duration, the processor further implements the following steps:

[0127] When an air conditioning system start-up signal is detected, determining whether the air conditioning system is used for the first time;

[0128] If it is the first time to use, the air conditioning system is controlled based on the preset initialization value;

[0129] If it is not the first time to use, the optimal temperature and air control parameters matching the latest environmental parameters are retrieved from the historical database, and the air conditioning system is controlled according to the optimal temperature and air control parameters.

[0130] The storage medium may be any computer-readable storage medium that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disk.

[0131] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the composition and steps of each example according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0132] In the several embodiments provided herein, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the various units is merely a logical functional division, and actual implementation may employ other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not implemented.

[0133] The steps in the methods of the embodiments of the present invention may be adjusted in order, combined, or deleted as needed. The units in the devices of the embodiments of the present invention may be combined, divided, or deleted as needed. Furthermore, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit.

[0134] If this integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the existing technology, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes a number of instructions for causing an electronic device (such as a personal computer, terminal, or network device) to execute all or part of the steps of the method described in various embodiments of the present invention.

[0135] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and such modifications or substitutions are intended to be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. An air conditioning control method based on non-contact human thermal sensation prediction, characterized in that: The method comprises: Regularly obtain the latest environmental parameters and skin temperature data collected by the sensor module according to the first interval duration; After inputting the latest environmental parameters and the skin temperature data into the TSV prediction model, the current thermal comfort status of the target individual is determined based on the output thermal sensation prediction value; After obtaining the warm air control parameters corresponding to the thermal comfort condition according to the preset warm air adjustment strategy, the air conditioning system is controlled according to the warm air control parameters.

2. The air conditioning control method based on non-contact human thermal sensation prediction according to claim 1, characterized in that: The determining of the current thermal comfort condition of the target individual based on the output thermal sensation prediction value includes: After determining the thermal comfort classification interval to which the thermal sensation prediction value belongs according to a preset thermal sensation interval relationship table, the current thermal comfort status of the target individual is determined based on the thermal comfort classification interval.

3. The air conditioning control method based on non-contact human thermal sensation prediction according to claim 1, characterized in that: After obtaining the temperature control parameters corresponding to the thermal comfort condition according to the preset temperature adjustment strategy, controlling the air conditioning system according to the temperature control parameters includes: If the thermal comfort condition is very cold, the air conditioning system is controlled according to the maximum set temperature and minimum wind speed in the warm air adjustment strategy; If the thermal comfort condition is very hot, the air conditioning system is controlled according to the minimum set temperature and maximum wind speed in the warm wind adjustment strategy.

4. The air conditioning control method based on non-contact human thermal sensation prediction according to claim 1, characterized in that: After obtaining the temperature control parameters corresponding to the thermal comfort condition according to the preset temperature adjustment strategy, controlling the air conditioning system according to the temperature control parameters includes: If the thermal comfort condition is slightly cold, the set temperature of the air-conditioning system is controlled according to the cold correction coefficient in the warm air adjustment strategy, and the current wind speed level of the air-conditioning system is lowered by one level; If the thermal comfort condition is slightly hot, the set temperature of the air-conditioning system is controlled according to the thermal sensitivity correction coefficient in the warm air adjustment strategy, and then the current wind speed level of the air-conditioning system is increased by one level.

5. The air conditioning control method based on non-contact human thermal sensation prediction according to claim 1, characterized in that: After obtaining the temperature control parameters corresponding to the thermal comfort condition according to the preset temperature adjustment strategy, controlling the air conditioning system according to the temperature control parameters includes: If the thermal comfort condition is comfortable, the set temperature of the air-conditioning system is regulated according to the PID control algorithm in the temperature and wind adjustment strategy, and the current wind speed level is kept unchanged.

6. The air conditioning control method based on non-contact human thermal sensation prediction according to claim 5, characterized in that: After the set temperature of the air conditioning system is regulated according to the PID control algorithm in the temperature and wind adjustment strategy and the current wind speed level is kept unchanged, the method further includes: After the first interval duration is adjusted to the second interval duration, the step of periodically acquiring the latest environmental parameters and skin temperature data collected by the sensor module is performed with the second interval duration as a period.

7. The air conditioning control method based on non-contact human thermal sensation prediction according to claim 1, characterized in that: Before regularly acquiring the latest environmental parameters and skin temperature data collected by the sensor module according to the first interval duration, the method further includes: When an air conditioning system start-up signal is detected, determining whether the air conditioning system is used for the first time; If it is the first time to use, the air conditioning system is controlled based on the preset initialization value; If it is not the first time to use, the optimal temperature and air control parameters matching the latest environmental parameters are retrieved from the historical database, and the air conditioning system is controlled according to the optimal temperature and air control parameters.

8. An air conditioning control device based on non-contact human thermal sensation prediction, characterized in that: The device comprises: An acquisition unit, configured to periodically acquire the latest environmental parameters and skin temperature data acquired by the sensor module according to a first interval duration; a determination unit, configured to input the latest environmental parameters and the skin temperature data into a TSV prediction model, and determine the current thermal comfort status of the target individual based on the output thermal sensation prediction value; The control unit is used to obtain the temperature and air control parameters corresponding to the thermal comfort condition according to a preset temperature and air adjustment strategy, and then control the air conditioning system according to the temperature and air control parameters.

9. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the 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 storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the method according to any one of claims 1 to 7 can be implemented.

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