A smart building heating method and system based on temperature perception

Abstract

The present invention relates to temperature sensor layout optimization technology, specifically a smart building heating method and system based on temperature perception. The present invention obtains the preset coverage radius of each temperature sensor, sets the location conditions and layout area conditions of the temperature sensor; generates an initialization population of the temperature sensor layout scheme; calculates the fitness value of each individual, selects individuals with higher fitness for reproduction, uses multi-point crossover to combine the sensor positions of two individuals, adjusts the positions of individual sensors, or increases or decreases the number of sensors, and generates a new population of individuals; calculates the fitness of each individual, selects excellent individuals according to the fitness, generates a new generation of individuals, and obtains a new generation of individuals; repeats iterations, and continuously repeats evaluation, selection, crossover and mutation until the fitness change is less than the preset threshold, and obtains the optimal temperature sensor layout.

Description

Technical Field

[0001] The present invention relates to the technical field of temperature sensor layout optimization, and in particular to a smart building heating method and system based on temperature perception. Background Art

[0002] In traditional building heating systems, the design and implementation of heating systems directly affect the comfort, energy consumption and system efficiency of the building. With the development of intelligent building technology, temperature sensors, as a key component of monitoring and control systems, usually have a single layout plan. One or two temperature sensors are usually placed in each indoor area. The layout is not based on indoor functions and traffic flow, and there is no systematic layout plan. This will affect the sensitivity and accuracy of temperature sensors in obtaining temperature and real-time temperature monitoring, which in turn affects the efficiency of the heating system and energy utilization. Summary of the invention

[0003] (1) Technical issues to be resolved

[0004] The purpose of the present invention is to provide a smart building heating method and system based on temperature perception, which improves the sensitivity and accuracy of temperature sensors in traditional heating systems in acquiring temperature and real-time monitoring of temperature, optimizes the layout of temperature sensors, and significantly improves the performance and energy efficiency of the heating system.

[0005] (2) Technical solution

[0006] To achieve the above objectives, on the one hand, the present invention provides a smart building heating method based on temperature perception, which improves the sensitivity and accuracy of the heating system in obtaining the temperature based on the adjustment of the position layout of the temperature sensor, and then controls the heating of the smart building. The method includes:

[0007] S10, obtaining a preset coverage radius of each temperature sensor; setting a location condition and a layout area condition of the temperature sensor, wherein the location condition is a limiting condition that must be met at the location where each temperature sensor is installed, and the layout area condition is an area limiting condition for the overall installation of multiple sensors.

[0008] S20, obtaining the number of temperature sensors that can be installed in the area according to the preset coverage radius of the temperature sensor and the layout area conditions of the temperature sensor ; Generate the initialization population of the temperature sensor layout plan, the initialization population is composed of Individual Each individual includes the location and number of sensors in the area, and each individual is a temperature sensor layout scheme; the individuals that exceed the area limit conditions are eliminated or rearranged to obtain a new initialization population Individual .

[0009] S30, calculate the fitness value of each individual, select individuals with higher fitness for reproduction, use multi-point crossover to combine the sensor positions of two individuals, adjust the position of individual sensors, or increase or decrease the number of sensors to generate a new population Individual ; Calculate the fitness of each individual, select excellent individuals according to the fitness, generate a new generation of individuals, and obtain a new generation of population Individual ; Repeat the iterations, continuously repeat the evaluation, selection, crossover and mutation until the fitness change is less than the preset threshold, and the optimal temperature sensor layout is obtained.

[0010] S40, dividing the internal office area of ​​the building into multiple functional areas, wherein the multiple functional areas are divided into a preset office area, a preset public area, a preset storage area, and a preset technical support area according to their usage functions; and differentiating the sensor layout scheme according to the characteristics of each functional area.

[0011] Furthermore, the method for generating an initialization population of a temperature sensor layout solution includes:

[0012] Initialize the population by Individual Each individual is a sensor layout, including the combination of sensor position and sensor quantity in the area, expressed as: ,in Indicates the location of the sensor. Indicates the number of sensors.

[0013] According to the preset coverage radius of the temperature sensor, the temperature sensors that exceed the area limitation conditions in the individual are removed, and the temperature sensors with overlapping coverage ranges in the individual are removed or rearranged to obtain a new temperature sensor initialization population. Individual .

[0014] Furthermore, the method for initializing population iteration of the temperature sensor includes:

[0015] According to the limited conditions of the temperature sensor layout, the initialization population of temperature sensors is generated, and the fitness function of the temperature sensor population iteration is designed, where the fitness function is expressed as:

[0016] ;

[0017] in, is the coverage of the sensor in the area; is temperature uniformity; is the number of sensors; , , is the weight coefficient.

[0018] The fitness of each individual in the initialized population is calculated separately. The higher the sensor coverage rate in the individual, the smaller the average temperature difference in the region and the fewer the number of sensors in the region, the higher the fitness; individuals with higher fitness are selected for reproduction to form a new temperature sensor population.

[0019] Furthermore, the method of repeatedly evaluating, selecting, crossing and mutating until the fitness change is less than a preset threshold to obtain the optimal temperature sensor layout includes:

[0020] Use single-point crossover or multi-point crossover to combine the positions of two individual temperature sensors to generate a new temperature sensor layout; then randomly adjust the positions of individual sensors, increase or decrease the number of sensors, increase the diversity of the population, and generate a new population Individual .

[0021] Calculate the fitness of each individual in the new population, select excellent individuals according to the fitness, and then perform single-point crossover or multi-point crossover to combine the temperature sensors of two individuals, adjust the positions of individual sensors, increase or decrease the number of sensors, generate a new generation of individuals, and obtain a new generation of population. Individual .

[0022] Repeat the evaluation, selection, crossover and mutation to obtain a new population until the fitness change is less than the preset threshold, then stop the iteration and obtain the optimal population under the preset conditions, that is, the optimal layout plan of the sensors under the preset conditions in the area.

[0023] Furthermore, the method of differentiating sensor layout solutions according to the characteristics of each functional area includes:

[0024] The office area inside the building is divided into multiple functional areas, and the multiple functional areas are divided into preset office areas, preset public areas, preset storage areas, and preset technical support areas according to their usage functions; the flow of people in the preset office areas and preset public areas is greater than a preset flow threshold, and the number of installed temperature sensors is higher than a preset low value of the number of temperature sensors; the flow of people in the preset storage area and preset technical support area is less than a preset flow threshold, and the number of installed temperature sensors is maintained at a preset low value of the number of temperature sensors.

[0025] Considering the air flow indoors, the sensor is installed at a preset standard installation height, which needs to be higher than the preset low value height from the ground; when the area of ​​the area is larger than the preset area, the sensors will be arranged in partitions and a staggered layout will be adopted.

[0026] Based on the same inventive concept, on the other hand, the present invention also provides a smart building heating system based on temperature perception, the system comprising: a first data acquisition module, a second data processing module, a temperature sensor layout iteration module, and a regional differentiation layout module, wherein the modules are connected in sequence;

[0027] The first data acquisition module is used to obtain the preset coverage radius of each temperature sensor; set the location conditions and layout area conditions of the temperature sensor, the location conditions are the limiting conditions that must be met at the location where each temperature sensor is installed, and the layout area conditions are the area limiting conditions for the overall installation of multiple sensors.

[0028] The second data processing module is used to obtain the number of temperature sensors that can be installed in the area according to the preset coverage radius of the temperature sensor and the layout area conditions of the temperature sensor. ; Generate the initialization population of the temperature sensor layout plan, the initialization population is composed of Individual Each individual includes the location and number of sensors in the area, and each individual is a temperature sensor layout scheme; the individuals that exceed the area limit conditions are eliminated or rearranged to obtain a new initialization population Individual .

[0029] The temperature sensor layout iteration module is used to calculate the fitness value of each individual, select individuals with higher fitness for reproduction, combine the sensor positions of two individuals using multi-point crossover, adjust the position of individual sensors, or increase or decrease the number of sensors to generate a new population. Individual ; Calculate the fitness of each individual, select excellent individuals according to the fitness, generate a new generation of individuals, and obtain a new generation of population Individual ; Repeat the iterations, continuously repeat the evaluation, selection, crossover and mutation until the fitness change is less than the preset threshold, and the optimal temperature sensor layout is obtained.

[0030] The regional differentiated layout module is used to divide the internal office area of ​​the building into multiple functional areas, and the multiple functional areas are divided into preset office areas, preset public areas, preset storage areas, and preset technical support areas according to their usage functions; and differentiate the sensor layout plan according to the characteristics of each functional area.

[0031] (3) Beneficial effects

[0032] Compared with the prior art, the beneficial effects of the present invention are: optimizing the layout of temperature sensors in the area, ensuring that the temperature sensors in the area cover the entire room, making the temperature difference obtained by real-time monitoring uniform, and through accurate temperature feedback, the heating system can reasonably adjust the heating according to actual needs to avoid energy waste; a good sensor layout can improve the system's response speed to environmental changes and improve the efficiency of the heating system. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a flowchart of a temperature-sensing-based smart building heating method according to Embodiment 1 of the present invention;

[0034] Figure 2 This is a schematic diagram of the module composition of a temperature-sensing based smart building heating system according to Example 2 of the present invention. DETAILED DESCRIPTION

[0035] 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.

[0036] Example 1: Figure 1 As shown, this embodiment provides a smart building heating method based on temperature perception, which improves the sensitivity and accuracy of the heating system in obtaining the temperature based on the adjustment of the position layout of the temperature sensor, and then controls the heating of the smart building. The method includes:

[0037] S10. Obtain a preset coverage radius for each temperature sensor; set a location condition and a layout area condition for the temperature sensor, wherein the location condition is a limiting condition that must be met at the location where each temperature sensor is installed, and the layout area condition is an area limiting condition for the overall installation of multiple sensors.

[0038] S20: Obtain the number of temperature sensors that can be installed in the area according to the preset coverage radius of the temperature sensor and the layout area conditions of the temperature sensor. ; Generate the initialization population of the temperature sensor layout plan, the initialization population is composed of Individual Each individual includes the location and number of sensors in the area, and each individual is a temperature sensor layout scheme; the individuals that exceed the area limit conditions are eliminated or rearranged to obtain a new initialization population Individual .

[0039] S30, calculate the fitness value of each individual, select individuals with higher fitness for reproduction, use multi-point crossover to combine the sensor positions of two individuals, adjust the position of individual sensors, or increase or decrease the number of sensors to generate a new population Individual ; Calculate the fitness of each individual, select excellent individuals according to the fitness, generate a new generation of individuals, and obtain a new generation of population Individual ; Repeat the iterations, continuously repeat the evaluation, selection, crossover and mutation until the fitness change is less than the preset threshold, and the optimal temperature sensor layout is obtained.

[0040] S40, dividing the internal office area of ​​the building into a plurality of functional areas, wherein the plurality of functional areas are divided into a preset office area, a preset public area, a preset storage area, and a preset technical support area according to their usage functions; and differentiating the sensor layout scheme according to the characteristics of each functional area.

[0041] For example: In the heating system of a smart building, monitoring the internal temperature of the building is the key to regulating the heating supply of the heating system. The layout position of the temperature sensor directly affects the coverage, sensitivity and temperature of the temperature monitoring, thereby improving the regulation ability of the heating system, achieving differentiated heating, saving energy and improving energy efficiency. A genetic algorithm is used to repeatedly evaluate, select, crossover and mutate the initial sensor layout population, and finally obtain the optimal temperature sensor layout. The temperature sensor layout optimized by the genetic algorithm has significant improvements in temperature coverage and uniformity compared to the traditional layout. The location limitation conditions and area limitation conditions of the temperature sensor must be within the boundary of the internal space of the building.

[0042] It should be noted that the method for generating an initialization population for a temperature sensor layout solution includes:

[0043] S21, the population is initialized by Individual Each individual is a sensor layout, including the combination of sensor position and sensor quantity in the area, expressed as: ,in Indicates the location of the sensor. Indicates the number of sensors.

[0044] S22, according to the preset coverage radius of the temperature sensor, remove the temperature sensors in the individuals that exceed the area limitation conditions, remove or rearrange the temperature sensors in the individuals that overlap the coverage range, and obtain a new temperature sensor initialization population Individual .

[0045] For example: set up temperature sensors in a 10m*10m office area, with a sensor coverage radius of 2m and a sensor number range of 3-5; initialize the population size to 5 individuals; individual 1: [(1,1), (2,5), (8,8), (3,3)], check that each sensor is within the area; check the coverage overlap and find that sensors 1 and 4 overlap, and sensors 2 and 4 overlap, reconsider the overlapping sensor positions, set the new position of sensor 4 to (6,6), and check that there is no overlap after the sensor is set to the new position; after verification and overlap processing, the individuals are [(1,1), (2,5), (8,8), (6,6)]; repeat the above steps to generate multiple valid individuals to form the initial population.

[0046] It should be noted that the method for initializing population iteration of the temperature sensor includes:

[0047] S31. Generate an initialization population of temperature sensors according to the limited conditions of the temperature sensor layout, and design a fitness function for the iteration of the temperature sensor population, where the fitness function is expressed as:

[0048] ;

[0049] in, is the coverage of the sensor in the area; is temperature uniformity; is the number of sensors; , , is the weight coefficient.

[0050] S32. Calculate the fitness of each individual in the initialized population separately. The higher the sensor coverage rate in the individual, the smaller the average temperature difference in the region and the fewer the number of sensors in the region, the higher the fitness; select individuals with higher fitness for reproduction to form a new temperature sensor population.

[0051] For example, a temperature sensor is set up in a 10m*10m office area, the sensor coverage radius is 2m, and the number of sensors ranges from 3 to 5. The initial population size is 5 individuals. Individual 1: [(1,1), (2,5), (3,3), (8,8)], individual 2: [(0,0), (5,5), (7,2), (9,1), (3,3)], individual 3: [(1,1), (4,4), (6,6), (3,2)], individual 4: [(2,2), (3,3), (4,4), (5,5)], individual 5: [(5,5), (8,8), (9,9)]; according to the sensor coverage range, the coverage point of sensor (1,1) in individual 1 is obtained as follows: (0,0), (0,1), (0,2), (1,0), (1,1), (1,2), (2,0), (2,1), (2,2), the coverage points of other sensors can be obtained similarly. There are 40 points in the area, so the coverage rate of individual 1 is calculated to be 0.4; the temperature values ​​covered by the sensors in individual 1 are [20.0, 21.5, 22.0, 23.1, 19.8, 22.5], the average temperature is calculated to be about 21.3, the temperature difference is 2.58, the number of sensors is 4, so the fitness value of individual 1 is calculated to be -5.8, the fitness value of individual 2 is 10.5, the fitness value of individual 3 is 8.0, the fitness value of individual 4 is 15.0, and the fitness value of individual 5 is -2.0; according to the calculation results, select individuals 2 and 4 to reproduce new individuals.

[0052] It should be noted that the method of repeatedly evaluating, selecting, crossing and mutating until the fitness change is less than a preset threshold to obtain the optimal temperature sensor layout includes:

[0053] S321, using single-point crossover or multi-point crossover to combine the positions of two individual temperature sensors to generate a new temperature sensor layout; then randomly adjust the positions of individual sensors, increase or decrease the number of sensors, increase the diversity of the population, and generate a new population Individual .

[0054] S322. Calculate the fitness of each individual in the new population, select excellent individuals according to the fitness, and then perform single-point crossover or multi-point crossover to combine the temperature sensors of two individuals, adjust the positions of individual sensors, increase or decrease the number of sensors, generate a new generation of individuals, and obtain a new generation of population. Individual .

[0055] S323, repeating the evaluation, selection, crossover and mutation to obtain a new population, until the fitness change is less than a preset threshold, then stopping the iteration, and obtaining the optimal population under the preset conditions, that is, the optimal layout plan of the sensors under the preset conditions in the area.

[0056] For example, set up temperature sensors in a 10m*10m office area, with a sensor coverage radius of 2m and a sensor number range of 3-5; initialize the population size to 5 individuals; individual 1: [(1,1),(2,5),(3,3),(8,8)], individual 2: [(0,0),(5,5),(7,2),(9,1),(3,3)], individual 3: [(1,1),(4,4),(6,6),(3,2)], individual 4: [(2,2),(3,3),(4,4 ),(5,5)], individual 5: [(5,5),(8,8),(9,9)]; the fitness value of individual 1 is calculated to be -5.8, the fitness value of individual 2 is 10.5, the fitness value of individual 3 is 8.0, the fitness value of individual 4 is 15.0, and the fitness value of individual 5 is -2.0; according to the calculation results, individual 2 and individual 4 are selected to reproduce new individuals, and the new individuals are generated using the crossover method: [(0,0),(5,5),(4,4),(5,5)], and the iterations are repeated until the optimal layout of the temperature sensors is obtained.

[0057] It should be noted that the method of differentiating the sensor layout scheme according to the characteristics of each functional area includes:

[0058] S41. Divide the office area inside the building into multiple functional areas, wherein the multiple functional areas are divided into a preset office area, a preset public area, a preset storage area, and a preset technical support area according to their usage functions; the flow of people in the preset office area and the preset public area is greater than a preset flow threshold, and the number of installed temperature sensors is higher than a preset low value of the number of temperature sensors; the flow of people in the preset storage area and the preset technical support area is less than a preset flow threshold, and the number of installed temperature sensors is maintained at a preset low value of the number of temperature sensors.

[0059] S42. Considering the air flow indoors, the sensor is installed at a preset standard installation height, and the preset standard installation height needs to be higher than a preset low value height from the ground; when the area of ​​the area is larger than the preset area, the sensors will be arranged in partitions and a staggered layout will be adopted.

[0060] For example, an office area with a size of 20m*20m is divided into the following four functional areas: office area 10m*10m, public area 5m*5m, storage area: 3m*4m, technical support area: 2m*1m; the sensors are installed at a standard height of 2m above the ground; 4 temperature sensors are installed in the office area, and the sensor positions are: (2,2), (2,8), (8,2), (8,8); 2 temperature sensors are installed in the public area, and the sensor positions are: (12,12), (12,16); 1 temperature sensor is installed in the storage area, and the sensor position is: (15,10); 1 temperature sensor is installed in the technical support area, and the sensor position is: (18,18).

[0061] Embodiment 2: Based on the same inventive concept, Figure 2 As shown, this embodiment also provides a smart building heating system based on temperature perception, the system comprising: a first data acquisition module, a second data processing module, a temperature sensor layout iteration module, and a regional differentiation layout module, wherein the modules are connected in sequence;

[0062] The first data acquisition module is used to obtain a preset coverage radius of each temperature sensor; set the location conditions and layout area conditions of the temperature sensor, the location conditions are the limiting conditions that must be met at the location where each temperature sensor is installed, and the layout area conditions are the area limiting conditions for the overall installation of multiple sensors.

[0063] The second data processing module is used to obtain the number of temperature sensors that can be installed in the area according to the preset coverage radius of the temperature sensor and the layout area conditions of the temperature sensor. ; Generate the initialization population of the temperature sensor layout plan, the initialization population is composed of Individual Each individual includes the location and number of sensors in the area, and each individual is a temperature sensor layout scheme; the individuals that exceed the area limit conditions are eliminated or rearranged to obtain a new initialization population Individual .

[0064] The temperature sensor layout iteration module is used to calculate the fitness value of each individual, select individuals with higher fitness for reproduction, combine the sensor positions of two individuals using multi-point crossover, adjust the position of individual sensors, or increase or decrease the number of sensors to generate a new population. Individual ; Calculate the fitness of each individual, select excellent individuals according to the fitness, generate a new generation of individuals, and obtain a new generation of population Individual ; Repeat the iterations, continuously repeat the evaluation, selection, crossover and mutation until the fitness change is less than the preset threshold, and the optimal temperature sensor layout is obtained.

[0065] The regional differentiated layout module is used to divide the internal office area of ​​the building into multiple functional areas, and the multiple functional areas are divided into preset office areas, preset public areas, preset storage areas, and preset technical support areas according to their usage functions; and differentiate the sensor layout plan according to the characteristics of each functional area.

[0066] It should be noted that, regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0067] Finally, it should be noted that: Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A temperature-sensing-based smart building heating method, which improves the sensitivity and accuracy of the temperature obtained by the heating system based on the adjustment of the position layout of the temperature sensor, and then controls the heating of the smart building, characterized in that: The method comprises the following steps: S10, obtaining a preset coverage radius of each temperature sensor; setting a location condition and a layout area condition of the temperature sensor, wherein the location condition is a limiting condition that must be met at the location where each temperature sensor is installed, and the layout area condition is an area limiting condition for the overall installation of multiple sensors; S20, obtaining the number of temperature sensors that can be installed in the area according to the preset coverage radius of the temperature sensor and the layout area conditions of the temperature sensor ; Generate the initialization population of the temperature sensor layout plan, the initialization population is composed of Individual Each individual includes the location and number of sensors in the area, and each individual is a temperature sensor layout scheme; the individuals that exceed the area limit conditions are eliminated or rearranged to obtain a new initialization population Individual ; S30, calculate the fitness value of each individual, select individuals with higher fitness for reproduction, use multi-point crossover to combine the sensor positions of two individuals, adjust the position of individual sensors, or increase or decrease the number of sensors to generate a new population Individual ; Calculate the fitness of each individual, select excellent individuals according to the fitness, generate a new generation of individuals, and obtain a new generation of population Individual ; Repeat the iteration, continuously repeat the evaluation, selection, crossover and mutation, until the fitness change is less than the preset threshold, and the optimal temperature sensor layout is obtained; S40, dividing the internal office area of ​​the building into multiple functional areas, wherein the multiple functional areas are divided into a preset office area, a preset public area, a preset storage area, and a preset technical support area according to their usage functions; and differentiating the sensor layout scheme according to the characteristics of each functional area.

2. A temperature sensing-based smart building heating method as claimed in claim 1, characterized in that: The method for generating an initialization population of a temperature sensor layout solution comprises: Initialize the population by Individual Each individual is a sensor layout, including the combination of sensor position and sensor quantity in the area, expressed as: ,in Indicates the location of the sensor. Indicates the number of sensors; According to the preset coverage radius of the temperature sensor, the temperature sensors that exceed the area limitation conditions in the individuals are removed, and the temperature sensors with overlapping coverage ranges in the individuals are removed or rearranged to obtain a new temperature sensor initialization population. Individual .

3. A temperature sensing-based smart building heating method as claimed in claim 2, characterized in that: The method for initializing population iteration of the temperature sensor includes: According to the limited conditions of the temperature sensor layout, the initialization population of temperature sensors is generated, and the fitness function of the temperature sensor population iteration is designed, where the fitness function is expressed as: ； in, is the coverage of the sensor in the area; is temperature uniformity; is the number of sensors; , , is the weight coefficient; The fitness of each individual in the initialized population is calculated separately. The higher the sensor coverage rate in the individual, the smaller the average temperature difference in the region and the fewer the number of sensors in the region, the higher the fitness; individuals with higher fitness are selected for reproduction to form a new temperature sensor population.

4. The temperature sensing-based smart building heating method according to claim 1, characterized in that: The method of repeatedly evaluating, selecting, crossing and mutating until the fitness change is less than a preset threshold to obtain the optimal temperature sensor layout includes: Use single-point crossover or multi-point crossover to combine the positions of two individual temperature sensors to generate a new temperature sensor layout; then randomly adjust the positions of individual sensors, increase or decrease the number of sensors, increase the diversity of the population, and generate a new population Individual ; Calculate the fitness of each individual in the new population, select excellent individuals according to the fitness, and then perform single-point crossover or multi-point crossover to combine the temperature sensors of two individuals, adjust the positions of individual sensors, increase or decrease the number of sensors, generate a new generation of individuals, and obtain a new generation of population. Individual ; Repeat the evaluation, selection, crossover and mutation to obtain a new population until the fitness change is less than the preset threshold, then stop the iteration and obtain the optimal population under the preset conditions, that is, the optimal layout plan of the sensors under the preset conditions in the area.

5. The temperature sensing-based smart building heating method according to claim 1, characterized in that: The method of differentiating sensor layout solutions according to the characteristics of each functional area includes: The office area inside the building is divided into multiple functional areas, and the multiple functional areas are divided into a preset office area, a preset public area, a preset storage area, and a preset technical support area according to their usage functions; the flow of people in the preset office area and the preset public area is greater than a preset flow threshold, and the number of installed temperature sensors is higher than a preset low value of the number of temperature sensors; the flow of people in the preset storage area and the preset technical support area is less than a preset flow threshold, and the number of installed temperature sensors is maintained at a preset low value of the number of temperature sensors; Considering the air flow indoors, the sensor is installed at a preset standard installation height, which needs to be higher than the preset low value height from the ground; when the area of ​​the area is larger than the preset area, the sensors will be arranged in partitions and a staggered layout will be adopted.

6. A temperature-sensing based smart building heating system, used to execute the method according to any one of claims 1 to 5, characterized in that: The system comprises: a first data acquisition module, a second data processing module, a temperature sensor layout iteration module, and a regional differentiation layout module, wherein the modules are connected in sequence; The first data acquisition module is used to obtain a preset coverage radius of each temperature sensor; set the location conditions and layout area conditions of the temperature sensor, the location conditions are the limiting conditions that must be met at the location where each temperature sensor is installed, and the layout area conditions are the area limiting conditions for the overall installation of multiple sensors; The second data processing module is used to obtain the number of temperature sensors that can be installed in the area according to the preset coverage radius of the temperature sensor and the layout area conditions of the temperature sensor. ; Generate the initialization population of the temperature sensor layout plan, the initialization population is composed of Individual Each individual includes the location and number of sensors in the area, and each individual is a temperature sensor layout scheme; the individuals that exceed the area limit conditions are eliminated or rearranged to obtain a new initialization population Individual ; The temperature sensor layout iteration module is used to calculate the fitness value of each individual, select individuals with higher fitness for reproduction, combine the sensor positions of two individuals using multi-point crossover, adjust the position of individual sensors, or increase or decrease the number of sensors to generate a new population. Individual ; Calculate the fitness of each individual, select excellent individuals according to the fitness, generate a new generation of individuals, and obtain a new generation of population Individual ; Repeat the iteration, continuously repeat the evaluation, selection, crossover and mutation, until the fitness change is less than the preset threshold, and the optimal temperature sensor layout is obtained; The regional differentiated layout module is used to divide the internal office area of ​​the building into multiple functional areas, and the multiple functional areas are divided into preset office areas, preset public areas, preset storage areas, and preset technical support areas according to their usage functions; and differentiate the sensor layout plan according to the characteristics of each functional area.

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