A smart bracelet, thermal environment adjustment system and method

Abstract

The present invention provides a smart bracelet, a thermal environment adjustment system and a method, which relate to the technical field of indoor environment control. The smart bracelet is worn on the wrist of a user, and comprises an infrared temperature sensing module, a room temperature measurement module and a wireless communication module; the infrared temperature sensing module and the room temperature measurement module are both connected to the wireless communication module; the infrared temperature sensing module detects the body temperature of the user; the room temperature measurement module is used to measure the ambient temperature; the smart bracelet is applied to the thermal environment adjustment system, and can improve the accuracy and automation level of indoor temperature adjustment.

Description

Technical Field

[0001] The present invention relates to the technical field of indoor environment control, and in particular to a smart bracelet, a thermal environment adjustment system and a method. Background Art

[0002] More than 80% of a person's life is spent indoors. Building a comfortable indoor environment is beneficial to human health and improves work efficiency. In addition to architectural design, the creation of an indoor environment also involves the control of the indoor environment. Traditional indoor environment control methods include control methods based on user-defined temperature settings, control methods based on PMV (Predicted Mean Vote), and control methods based on thermal sensation voting.

[0003] (1) Control method based on user-defined temperature setting value

[0004] The traditional control method for indoor buildings is to adjust the indoor ambient temperature based on the user's self-set air conditioning set value to reflect the indoor temperature and temperature of the people. However, the temperature set value set by the user is often set too low or too high, which leads to a significant increase in building energy consumption. In addition, it also makes the indoor people uncomfortable in an overly cold or overheated environment. Studies have shown that a reasonable indoor temperature setting can reduce air conditioning energy consumption by 2.3% compared with a constant indoor temperature setting of 26°C. Due to changes in people's clothing, changes in climate and seasons, it is difficult for people to accurately determine their comfortable temperature range, so unreasonable temperature settings often occur.

[0005] (2) Thermal environment control based on PMV

[0006] An improved indoor thermal environment control method is to replace the traditional temperature setting control method based on the PMV index. The PMV theory was proposed by the research team of Professor Fanger of Denmark. It uses six indicators, namely, clothing, metabolic rate, air velocity, relative humidity, air temperature and radiation temperature, to comprehensively and quantitatively characterize the thermal comfort level of people in the indoor environment of a building. However, the PMV model is an average thermal comfort model obtained based on statistics. The control method based on PMV cannot take into account the personalized differences of users and the dynamic changes in thermal comfort.

[0007] (3) Thermal environment control based on thermal sensation reporting

[0008] Traditional set value control cannot achieve reasonable temperature setting, and PMV-based control cannot achieve personalized thermal comfort control. Therefore, some researchers have proposed a control method based on thermal sensation reporting, which can feedback the user's thermal sensation through active or passive thermal sensation reporting to achieve personalized thermal environment control. Studies have shown that control based on user thermal sensation reporting can save 11% of air conditioning energy consumption compared to the traditional method of users setting temperature set values ​​independently. However, the control method based on thermal sensation reporting requires users to submit thermal sensations, which interferes with the user's work. If thermal sensations are not submitted, personalized thermal comfort control cannot be achieved.

[0009] Therefore, the control strategy of the existing environmental regulation system cannot accurately adjust the indoor temperature according to the user's thermal comfort level. Summary of the invention

[0010] The purpose of the present invention is to provide a smart bracelet, a thermal environment adjustment system and a method, which can improve the automation level of indoor temperature adjustment.

[0011] To achieve the above object, the present invention provides the following solutions:

[0012] A smart bracelet, provided with:

[0013] Infrared temperature sensing module, room temperature measurement module and the wireless communication module;

[0014] The infrared temperature sensing module and the room temperature measurement module are both connected to the wireless communication module;

[0015] The infrared temperature sensing module detects the user's body temperature;

[0016] The room temperature measurement module is used to measure the ambient temperature;

[0017] The wireless communication module is used to send the body temperature and the ambient temperature.

[0018] Optionally, the smart bracelet further includes: a thermal comfort level selection module;

[0019] The thermal comfort level selection module is provided with a plurality of thermal comfort level selection buttons; the thermal comfort level selection module is connected to the wireless communication module; the thermal comfort level selection module is used for sending a corresponding thermal comfort level selection signal when any thermal comfort level selection button is pressed.

[0020] A thermal environment adjustment system, comprising:

[0021] A cloud computing platform, a temperature regulating device and the above-mentioned smart bracelet;

[0022] The cloud computing platform is connected to the wireless communication modules of the temperature regulating device and the smart bracelet respectively;

[0023] The smart bracelet is worn on the wrist of the user; the smart bracelet is used to detect the ambient temperature and the user's body temperature;

[0024] The cloud computing platform is used to determine the target thermal comfort level of the user according to the thermal comfort level selection signal when receiving the thermal comfort level selection signal; the cloud computing platform is also used to determine the predicted thermal comfort level of the user as the target thermal comfort level according to the ambient temperature and the user's body temperature when not receiving the thermal comfort level selection signal; the cloud computing platform is also used to determine the target temperature range according to the user's target thermal comfort level;

[0025] The temperature regulating device is used to regulate the room temperature according to the target temperature range.

[0026] Optional,

[0027] The number of the temperature adjustment devices connected to the cloud computing platform is one or more;

[0028] The number of users within the temperature adjustment range covered by any of the temperature adjustment devices is one or more; and the users correspond one to one with the smart bracelets.

[0029] Optionally, the temperature regulating device is an air conditioner.

[0030] Optionally, the system further includes:

[0031] Data processing module;

[0032] The data processing module is connected to the cloud computing platform and the plurality of smart bracelets respectively; the data processing module is used to clean the body temperature detected by the smart bracelets and send the cleaned body temperature to the cloud computing platform.

[0033] A thermal environment adjustment method, the method is applied to the thermal environment adjustment system as claimed in claim 1, the method comprising:

[0034] The smart bracelet detects the ambient temperature and the user’s body temperature;

[0035] The cloud computing platform inputs the ambient temperature and the user's body temperature detected by the same smart bracelet into the thermal comfort level prediction model of the corresponding user, and obtains the prediction result as the user's target thermal comfort level; different smart bracelets correspond to different thermal comfort level prediction models; one of the thermal comfort level prediction models is obtained by training a classifier model using the ambient temperature history data and the body temperature history data measured by the same smart bracelet; the classifier model is a support vector machine or a neural network;

[0036] Determine the target temperature range according to the user's target thermal comfort level;

[0037] The temperature adjustment device adjusts the room temperature according to the target temperature range.

[0038] Optionally, before the cloud computing platform inputs the ambient temperature and the user's body temperature detected by the same smart bracelet into a thermal comfort level prediction model of the corresponding user to obtain a prediction result as the user's target thermal comfort level, the method further includes:

[0039] The cloud computing platform determines whether a thermal comfort level selection signal is received, and obtains a first determination result;

[0040] If the first judgment result is yes, determining the user's target thermal comfort level according to the thermal comfort level selection signal, and executing the step of "determining the target temperature range according to the user's target thermal comfort level";

[0041] If the first judgment result is no, execute the step "the cloud computing platform inputs the ambient temperature detected by the same smart bracelet and the user's body temperature into the thermal comfort level prediction model of the corresponding user, and obtains the prediction result as the user's target thermal comfort level".

[0042] Optionally, determining the target temperature range according to the user's target thermal comfort level specifically includes:

[0043] Determine any temperature adjustment device as the current temperature adjustment device;

[0044] Determine whether the number of users within the temperature adjustment range covered by the current temperature adjustment device is 1, and obtain a second judgment result;

[0045] If the second judgment result is yes, the user within the temperature adjustment range covered by the current temperature adjustment device is determined to be the current user, and the temperature interval corresponding to the target thermal comfort level of the current user is determined to be the target temperature interval; different users have different target temperature intervals corresponding to the same thermal comfort level; the target temperature intervals corresponding to different thermal comfort levels of the same user are determined by using a fuzzy algorithm based on the historical thermal comfort level data of the same user;

[0046] If the second judgment result is no, determining that a plurality of users within the temperature adjustment range covered by the current temperature adjustment device are the current user group;

[0047] Determine whether the priorities of multiple users in the current user group are consistent, and obtain a third determination result;

[0048] If the third judgment result is yes, then respectively determining the temperature intervals corresponding to the target thermal comfort levels of multiple users in the current user group to obtain multiple target temperature initial intervals;

[0049] The target temperature interval is obtained by taking the average value of the first endpoints of the multiple target temperature initial intervals as the first endpoint of the target temperature interval; taking the average value of the second endpoints of the multiple target temperature initial intervals as the second endpoint of the target temperature interval; the temperature value corresponding to the first endpoint is less than the temperature value corresponding to the second endpoint;

[0050] If the third judgment result is no, then the temperature interval corresponding to the target thermal comfort level of the user with the highest priority in the current user group is determined as the target temperature interval.

[0051] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0052] The present invention provides a smart bracelet, a thermal environment regulation system and a method. The smart bracelet is worn on the wrist of a user and is applied to the thermal environment regulation system. The smart bracelet measures the ambient temperature and the user's body temperature by setting an infrared temperature sensing module and a room temperature measurement module. The ambient temperature and the user's body temperature measured by the smart bracelet are applied to the thermal environment regulation system, which can improve the accuracy and automation level of indoor temperature regulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0054] Figure 1 This is a schematic diagram of the structure of a smart bracelet provided in Embodiment 1 of the present invention;

[0055] Figure 2 A schematic diagram of the structure of a thermal environment adjustment system provided in Embodiment 2 of the present invention;

[0056] Figure 3 This is a flow chart of the thermal environment adjustment method provided in Embodiment 3 of the present invention;

[0057] Description of the drawings: 1-infrared temperature sensing module; 2-room temperature measurement module; 3-wireless communication module; 4-thermal comfort level selection module; 5-cloud computing platform; 6-temperature adjustment device; 7-smart bracelet. DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] The purpose of the present invention is to provide a smart bracelet, a thermal environment adjustment system and a method, which can improve the automation level of indoor temperature adjustment.

[0060] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0061] Embodiment 1

[0062] like Figure 1 This embodiment provides a smart bracelet, which is provided with:

[0063] Infrared temperature sensing module 1, room temperature measurement module 2 and wireless communication module 3;

[0064] The infrared temperature sensing module and the room temperature measuring module are both connected to the wireless communication module;

[0065] The user's body temperature is detected by the infrared temperature sensing module;

[0066] The room temperature measurement module is used to measure the ambient temperature;

[0067] The wireless communication module is used to send body temperature and ambient temperature.

[0068] In addition, the smart bracelet also includes: thermal comfort level selection module;

[0069] The thermal comfort level selection module 4 is provided with a plurality of thermal comfort level selection buttons; the thermal comfort level selection module is connected to the wireless communication module; the thermal comfort level selection module is used to send a corresponding thermal comfort level selection signal when any thermal comfort level selection button is pressed.

[0070] Embodiment 2

[0071] like Figure 2 , this embodiment provides a thermal environment adjustment system, including:

[0072] A cloud computing platform 5, a temperature regulating device 6 and a smart bracelet 7 as described in the first embodiment;

[0073] The cloud computing platform is connected to the wireless communication modules of the temperature regulating device and the smart bracelet respectively;

[0074] The smart bracelet is worn on the user's wrist; the smart bracelet is used to detect the ambient temperature and the user's body temperature;

[0075] The cloud computing platform is used to determine the user's target thermal comfort level according to the thermal comfort level selection signal when receiving the thermal comfort level selection signal; the cloud computing platform is also used to determine the user's predicted thermal comfort level as the target thermal comfort level according to the ambient temperature and the user's body temperature when not receiving the thermal comfort level selection signal; the cloud computing platform is also used to determine the target temperature range according to the user's target thermal comfort level; the cloud computing platform includes multiple thermal comfort level prediction models; the cloud computing platform inputs the ambient temperature and the user's body temperature detected by the same smart bracelet into the thermal comfort level prediction model of the corresponding user, and obtains the prediction result as the user's target thermal comfort level; different smart bracelets have different corresponding thermal comfort level prediction models; a thermal comfort level prediction model is obtained by training a classifier model using the ambient temperature history data and the body temperature history data measured by the same smart bracelet; the classifier model is a support vector machine or a neural network;

[0076] The temperature regulating device is used to adjust the room temperature according to the target temperature range.

[0077] Specifically,

[0078] The number of temperature regulating devices connected to the cloud computing platform is one or more;

[0079] The number of users within the temperature adjustment range covered by any temperature adjustment device is one or more; and the users correspond one to one with the smart bracelets.

[0080] Preferably, the temperature regulating device is an air conditioner.

[0081] In addition, the thermal environment adjustment system provided in this embodiment also includes:

[0082] Data processing module;

[0083] The data processing module is connected to the cloud computing platform and multiple smart bracelets respectively; the data processing module is used to clean the body temperature detected by the smart bracelets and send the cleaned body temperature to the cloud computing platform.

[0084] The present invention uses an intelligent wearable device, such as a smart bracelet, to measure the user's skin temperature and predict the user's thermal sensation, without the user having to frequently report the thermal sensation (thermal comfort level), and intelligently implements personalized thermal comfort control. In order to achieve the above purpose, the present invention includes the following contents:

[0085] The system based on intelligent wearable device prediction of personalized thermal sensation includes: wearable device, signal processor, cloud computing platform. Based on the online learning method of personalized thermal comfort model and thermal sensation prediction model, the indoor temperature setting value reset logic and the operation control logic of the air conditioning device are determined to control the temperature control device. The specific composition and functions of each module are as follows:

[0086] (1) Wearable devices

[0087] The wearable device includes an infrared temperature sensing module, a thermal comfort level selection button, and a Bluetooth wireless communication module. The skin temperature signal and the thermal comfort level selection signal measured by the wearable device are broadcasted.

[0088] (2) Signal Processor

[0089] The signal receiver includes: Bluetooth and WiFi communication modules, and information processing modules. The Bluetooth communication module scans the surrounding wearable devices at a certain frequency and transmits the received information to the information processing module. After receiving the data, the information processing module cleans the data and uploads the processed data to the cloud computing platform.

[0090] (3) Cloud computing platform

[0091] The cloud computing platform is used to manage huge amounts of data, learn and store users' personalized thermal comfort models. The cloud computing platform sets up a user thermal sensation visualization webpage to facilitate viewing of each user's thermal sensation at any time. The user's personalized thermal comfort model is sent to the controller in each user's area to control the air conditioning device in the user's area.

[0092] (4) Online learning method of personalized thermal comfort model

[0093] Based on the measured historical data, the skin temperature, PMV calculated value, and the thermal sensation data reported by the user in the environment are used to train the classifier model, such as SVM (Support Vector Machine), neural network, etc., to learn online a thermal comfort model that reflects the user's personalization for the next step of thermal sensation prediction.

[0094] (5) Thermal sensation prediction model

[0095] The trained classifier model is used to input the skin temperature measured by the smart wearable device and the PMV value calculated by the environmental parameters to predict the user's thermal sensation state and reset the indoor temperature setting value.

[0096] (6) Indoor temperature setpoint reset logic based on predicted thermal sensation

[0097] According to the predicted user thermal sensation, the outdoor temperature setting value is reset through the fuzzy algorithm so that the indoor temperature meets the personalized comfort requirements.

[0098] (7) Controllers, air conditioning devices

[0099] The controller adjusts the cooling or heating delivered to the room by the air conditioning device according to the deviation between the set temperature obtained by (6) and the actual measured ambient temperature through the PID control algorithm, so that the room temperature reaches the set value.

[0100] Embodiment 3

[0101] like Figure 3 This embodiment provides a thermal environment adjustment method, which is applied to the thermal environment adjustment system as described in the second embodiment, and includes:

[0102] Step 301: The smart bracelet detects the ambient temperature and the user's body temperature;

[0103] Step 302: the cloud computing platform inputs the ambient temperature and the user's body temperature detected by the same smart bracelet into the thermal comfort level prediction model of the corresponding user, and obtains the prediction result as the user's target thermal comfort level; different smart bracelets correspond to different thermal comfort level prediction models; a thermal comfort level prediction model is obtained by training a classifier model using the ambient temperature history data and the body temperature history data measured by the same smart bracelet; the classifier model is a support vector machine or a neural network;

[0104] Step 303: determining a target temperature range according to the user's target thermal comfort level;

[0105] Step 304: The temperature adjustment device adjusts the room temperature according to the target temperature range.

[0106] Before step 302, the method further includes:

[0107] The cloud computing platform determines whether a thermal comfort level selection signal is received, and obtains a first determination result;

[0108] If the first judgment result is yes, the user's target thermal comfort level is determined according to the thermal comfort level selection signal, and step 303 is executed;

[0109] If the first judgment result is no, step 302 is executed.

[0110] Step 303 specifically includes:

[0111] Determine any temperature adjustment device as the current temperature adjustment device;

[0112] Determine whether the number of users within the temperature adjustment range covered by the current temperature adjustment device is 1, and obtain a second judgment result;

[0113] If the second judgment result is yes, the user within the temperature adjustment range covered by the current temperature adjustment device is determined to be the current user, and the temperature interval corresponding to the target thermal comfort level of the current user is determined to be the target temperature interval; different users have different target temperature intervals corresponding to the same thermal comfort level; the target temperature intervals corresponding to different thermal comfort levels of the same user are determined by using a fuzzy algorithm based on the historical thermal comfort level data of the same user;

[0114] If the second judgment result is no, then determining that a plurality of users within the temperature adjustment range covered by the current temperature adjustment device are the current user group;

[0115] Determine whether the priorities of multiple users in the current user group are consistent, and obtain a third determination result;

[0116] If the third judgment result is yes, then determining the temperature intervals corresponding to the target thermal comfort levels of multiple users in the current user group respectively, and obtaining multiple target temperature initial intervals;

[0117] The target temperature interval is obtained by taking the average value of the first endpoints of the multiple target temperature initial intervals as the first endpoint of the target temperature interval; taking the average value of the second endpoints of the multiple target temperature initial intervals as the second endpoint of the target temperature interval; the temperature value corresponding to the first endpoint is less than the temperature value corresponding to the second endpoint;

[0118] If the third judgment result is no, then the temperature interval corresponding to the target thermal comfort level of the user with the highest priority in the current user group is determined as the target temperature interval.

[0119] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0120] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. 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 limiting the present invention.

Claims

1. A thermal environment adjustment system, characterized in that: The thermal environment adjustment system comprises: Cloud computing platforms, temperature control devices and smart bracelets; The smart bracelet is provided with: an infrared temperature sensing module, a comfort level selection module, a room temperature measurement module and a wireless communication module; the infrared temperature sensing module and the room temperature measurement module are both connected to the wireless communication module; the infrared temperature sensing module detects the user's body temperature; the room temperature measurement module is used to measure the ambient temperature; the wireless communication module is used to send the body temperature and the ambient temperature; the thermal comfort level selection module is provided with a plurality of thermal comfort level selection buttons; the thermal comfort level selection module is connected to the wireless communication module; the thermal comfort level selection module is used to send a corresponding thermal comfort level selection signal when any thermal comfort level selection button is pressed; The cloud computing platform is connected to the wireless communication modules of the temperature regulating device and the smart bracelet respectively; The smart bracelet is worn on the wrist of the user; the smart bracelet is used to detect the ambient temperature and the user's body temperature; The cloud computing platform is used to determine the user's target thermal comfort level according to the thermal comfort level selection signal when receiving the thermal comfort level selection signal; the cloud computing platform is also used to determine the user's predicted thermal comfort level as the target thermal comfort level according to the ambient temperature and the user's body temperature when no thermal comfort level selection signal is received; the cloud computing platform is also used to determine the target temperature range according to the user's target thermal comfort level; the cloud computing platform is used to determine any temperature adjustment device as the current temperature adjustment device; determine whether the number of users within the temperature adjustment range covered by the current temperature adjustment device is 1, and obtain a second judgment result; if the second judgment result is yes, determine that the user within the temperature adjustment range covered by the current temperature adjustment device is the current user, and determine the temperature range corresponding to the current user's target thermal comfort level as the target temperature range; different users have the same thermal comfort level and correspond to different target temperature ranges; different thermal comfort levels of the same user have different target temperature ranges The corresponding target temperature interval is determined by a fuzzy algorithm based on the historical thermal comfort level data of the same user; if the second judgment result is no, multiple users within the temperature adjustment range covered by the current temperature adjustment device are determined as the current user group; whether the priorities of multiple users in the current user group are consistent is determined to obtain a third judgment result; if the third judgment result is yes, the temperature intervals corresponding to the target thermal comfort levels of multiple users in the current user group are determined respectively to obtain multiple target temperature initial intervals; the average value of the first endpoints of the multiple target temperature initial intervals is used as the first endpoint of the target temperature interval; the average value of the second endpoints of the multiple target temperature initial intervals is used as the second endpoint of the target temperature interval to obtain the target temperature interval; the temperature value corresponding to the first endpoint is less than the temperature value corresponding to the second endpoint; if the third judgment result is no, the temperature interval corresponding to the target thermal comfort level of the user with the highest priority in the current user group is determined as the target temperature interval; There are one or more temperature control devices connected to the cloud computing platform; there are one or more users within the temperature control range covered by any one of the temperature control devices; the users correspond one-to-one to the smart bracelets; and the temperature control device is used to adjust the room temperature according to the target temperature range.

2. The thermal environment adjustment system according to claim 1, characterized in that: The temperature regulating device is an air conditioner.

3. The thermal environment adjustment system according to claim 1, characterized in that: The system further comprises: Data processing module; The data processing module is connected to the cloud computing platform and the plurality of smart bracelets respectively; the data processing module is used to clean the body temperature detected by the smart bracelets and send the cleaned body temperature to the cloud computing platform.

4. A thermal environment adjustment method, characterized in that: The method is applied to the thermal environment adjustment system according to any one of claims 1 to 3, and the method comprises: The smart bracelet detects the ambient temperature and the user’s body temperature; The cloud computing platform inputs the ambient temperature and the user's body temperature detected by the same smart bracelet into the thermal comfort level prediction model of the corresponding user, and obtains the prediction result as the user's target thermal comfort level; different smart bracelets correspond to different thermal comfort level prediction models; one of the thermal comfort level prediction models is obtained by training a classifier model using the ambient temperature history data and the body temperature history data measured by the same smart bracelet; the classifier model is a support vector machine or a neural network; Determine the target temperature range according to the user's target thermal comfort level; The temperature regulating device regulates the room temperature according to the target temperature range; Determining the target temperature range according to the user's target thermal comfort level specifically includes: Determine any temperature adjustment device as the current temperature adjustment device; Determine whether the number of users within the temperature adjustment range covered by the current temperature adjustment device is 1, and obtain a second judgment result; If the second judgment result is yes, the user within the temperature adjustment range covered by the current temperature adjustment device is determined to be the current user, and the temperature interval corresponding to the target thermal comfort level of the current user is determined to be the target temperature interval; different users have different target temperature intervals corresponding to the same thermal comfort level; the target temperature intervals corresponding to different thermal comfort levels of the same user are determined by using a fuzzy algorithm based on the historical thermal comfort level data of the same user; If the second judgment result is no, determining that a plurality of users within the temperature adjustment range covered by the current temperature adjustment device are the current user group; Determine whether the priorities of multiple users in the current user group are consistent, and obtain a third determination result; If the third judgment result is yes, then respectively determining the temperature intervals corresponding to the target thermal comfort levels of multiple users in the current user group to obtain multiple target temperature initial intervals; The target temperature interval is obtained by taking the average value of the first endpoints of the multiple target temperature initial intervals as the first endpoint of the target temperature interval; taking the average value of the second endpoints of the multiple target temperature initial intervals as the second endpoint of the target temperature interval; the temperature value corresponding to the first endpoint is less than the temperature value corresponding to the second endpoint; If the third judgment result is no, then the temperature interval corresponding to the target thermal comfort level of the user with the highest priority in the current user group is determined as the target temperature interval.

5. The thermal environment adjustment method according to claim 4, characterized in that: Before the cloud computing platform inputs the ambient temperature and the user's body temperature detected by the same smart bracelet into the thermal comfort level prediction model of the corresponding user to obtain the prediction result as the user's target thermal comfort level, it also includes: The cloud computing platform determines whether a thermal comfort level selection signal is received, and obtains a first determination result; If the first judgment result is yes, the user's target thermal comfort level is determined according to the thermal comfort level selection signal, and the step of "determining the target temperature range according to the user's target thermal comfort level" is executed; If the first judgment result is no, execute the step "the cloud computing platform inputs the ambient temperature detected by the same smart bracelet and the user's body temperature into the thermal comfort level prediction model of the corresponding user, and obtains the prediction result as the user's target thermal comfort level".

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