Air conditioner control method, device and equipment based on millimeter wave radar and medium

Abstract

The invention discloses an air conditioner control method, device and equipment based on millimeter wave radar and a medium. The method comprises the following steps: acquiring position data and motion data of personnel in a space area in real time through a millimeter wave radar, and dynamically dividing the space area into a plurality of temperature control areas through a clustering algorithm according to the position data; according to the area of the temperature control area, the personnel density and the motion data, the thermal load capacity corresponding to the temperature control area is calculated through a preset thermal load prediction model; and air conditioner operation parameters of the temperature control area corresponding to the thermal load capacity are adjusted according to the thermal load capacity. The thermal load capacity of different temperature control areas is calculated through the thermal load model, the different temperature control areas can adjust the operation parameters of the air conditioner according to the corresponding thermal load capacity, in this way, each temperature control area can accurately meet the temperature requirement of the corresponding temperature control area, regional accurate dynamic regulation and control of the air conditioner are achieved, energy waste is reduced, and the energy efficiency is improved. And the comfort is improved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the technical field of air conditioners, and particularly to an air conditioner control method, device, equipment and medium based on millimeter-wave radar. Background Art

[0002] In crowded places such as shopping malls and exhibition halls, air conditioning systems usually adopt a fixed zoning control strategy. For example, the space is pre-divided into several geometric regions, and unified temperature parameters are set based on historical experience, or basic temperature control operations are triggered after detecting whether there are people in the region through infrared sensors. Such traditional solutions face significant bottlenecks in actual operation. Taking a shopping mall promotion activity as an example, when a large number of customers suddenly gather at a certain commodity booth, there may be only a few people staying in the adjacent rest area. Since the traditional system cannot perceive the actual population density of each sub-region in real time, the air conditioner still continuously supplies air to the entire partition within the preset range. At this time, the high heat load generated by the retention of people in the booth area is difficult to relieve in time, while the low-density rest area causes energy waste due to excessive cooling. At the same time, when customers move to other regions, the system response delay causes the temperature regulation to always lag behind the actual demand. In such scenarios, due to the lack of dynamic perception and adaptive capabilities of traditional air conditioning technologies, it is difficult to balance the local thermal environment requirements and the overall energy efficiency, resulting in an increasingly prominent contradiction between user experience and energy consumption. Summary of the Invention

[0003] The present invention provides an air conditioner control method, device, equipment and medium based on millimeter-wave radar, aiming to solve the problem that the existing strategy of regulating the temperature of air conditioners according to fixed partitions is difficult to perceive the changes in heat demand in real time, resulting in energy waste and temperature control lag.

[0004] In a first aspect, an embodiment of the present invention provides an air conditioner control method based on millimeter-wave radar, the method comprising:

[0005] Obtaining the position data and movement data of people in a spatial region in real time through a millimeter-wave radar, and dynamically dividing the spatial region into a plurality of temperature control regions according to the position data by means of a clustering algorithm;

[0006] Calculating the heat load amount corresponding to the temperature control region according to the area of the temperature control region, the population density and the movement data through a preset heat load prediction model;

[0007] Adjusting the air conditioner operating parameters corresponding to the temperature control region according to the heat load amount.

[0008] In a second aspect, the present invention also provides an air conditioner control device based on millimeter-wave radar, comprising units for executing the above method.

[0009] In a third aspect, an embodiment of the present invention further provides a computer device, which includes a memory and a processor. A computer program is stored on the memory, and when the processor executes the computer program, the above method is implemented.

[0010] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium storing a computer program, which can implement the above method when executed by a processor.

[0011] The present invention provides an air conditioner control method, device, equipment and medium based on a millimeter-wave radar. The method includes: obtaining the position data and movement data of a person in a spatial area in real time through a millimeter-wave radar, and dynamically dividing the spatial area into multiple temperature control areas according to the position data by using a clustering algorithm; calculating the heat load amount corresponding to the temperature control area according to the area of the temperature control area, the population density and the movement data through a preset heat load prediction model; and adjusting the air conditioner operation parameters of the corresponding temperature control area according to the heat load amount. The present invention calculates the heat load amount of different temperature control areas through a heat load model, so that different temperature control areas can adjust the operation parameters of the air conditioner according to their respective corresponding heat load amounts. In this way, each temperature control area can accurately match its own temperature requirements, realizing accurate and dynamic control of the air conditioner in different areas, reducing energy waste and improving comfort. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0013] Figure 1 It is a schematic flowchart of the steps of the air conditioner control method based on a millimeter-wave radar according to an embodiment of the present invention;

[0014] Figure 2 It is a schematic flowchart of the sub-steps of the air conditioner control method based on a millimeter-wave radar according to an embodiment of the present invention;

[0015] Figure 3 It is another schematic flowchart of the sub-steps of the air conditioner control method based on a millimeter-wave radar according to an embodiment of the present invention;

[0016] Figure 4 It is yet another schematic flowchart of the sub-steps of the air conditioner control method based on a millimeter-wave radar according to an embodiment of the present invention;

[0017] Figure 5 It is still another schematic flowchart of the sub-steps of the air conditioner control method based on a millimeter-wave radar according to an embodiment of the present invention;

[0018] Figure 6 This is another sub-step process schematic diagram of the air conditioner control method based on millimeter-wave radar according to an embodiment of the present invention;

[0019] Figure 7 This is another sub-step process schematic diagram of the air conditioner control method based on millimeter-wave radar according to an embodiment of the present invention;

[0020] Figure 8 This is a schematic block diagram of an air conditioner control device based on millimeter-wave radar provided by an embodiment of the present invention;

[0021] Figure 9 This is a schematic block diagram of a computer device provided by an embodiment of the present invention. Detailed implementation manners

[0022] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0023] It should be understood that when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0024] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in this specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms.

[0025] It should be further understood that the term " / and / or" used in this specification of the present invention and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0026] As used in this specification and the appended claims, the term "if" may be construed contextually as "when" or "once" or "in response to determining" or "in response to detecting". Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be construed contextually to mean "once determined" or "in response to determining" or "once [the described condition or event] is detected" or "in response to detecting [the described condition or event]".

[0027] In public places with a large number of people and high mobility, such as shopping malls and gyms, traditional air conditioning systems mostly rely on fixed zoning control or basic presence detection to achieve temperature control adjustment. Such solutions often lead to problems such as lag in local area temperature regulation and excessive energy consumption because they cannot perceive the dynamic distribution and activity intensity of people in real time. Especially in scenarios where the hotspots of people gathering frequently shift, the existing technologies are difficult to accurately match the actual heat load requirements, easily resulting in coexistence of insufficient cooling in high-activity areas and energy redundancy in low-density areas. In addition, solutions based on vision or infrared sensing have privacy concerns and environmental adaptability defects. Therefore, there is an urgent need for a new air conditioning control method that can balance real-time response, energy efficiency optimization, and privacy protection to address the challenges of dynamic environment regulation in complex public places. For this purpose, the embodiments of the present invention propose an air conditioning control method, device, equipment, and medium based on millimeter-wave radar, which can achieve accurate and dynamic zoning control of the air conditioner, reduce energy waste, and improve comfort. Specifically as follows:

[0028] Please refer to Figure 1 , Figure 1 which is a flowchart of the air conditioning control method based on millimeter-wave radar provided by the embodiments of the present invention. The air conditioning control method based on millimeter-wave radar will be described in detail below. As Figure 1 shown, the method includes the following steps: S110 - S130.

[0029] S110. Obtain the position data and motion data of people in the spatial area in real time through a millimeter-wave radar, and dynamically divide the spatial area into multiple temperature control areas according to the position data through a clustering algorithm;

[0030] In this embodiment, the spatial region refers to the indoor monitoring range covered by the millimeter-wave radar signal, the position data refers to the three-dimensional coordinate information of a person within the indoor monitoring range, and the motion data refers to the quantified data related to human motion, such as motion amplitude, motion type, and motion displacement. The clustering algorithm refers to a method for aggregating and calculating spatial discrete points based on data density characteristics. For example, the DBSCAN clustering algorithm, DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is a density-based clustering algorithm that is suitable for discovering clusters of any shape and can effectively identify noise points (outliers). Different from distance-based algorithms such as K-means, DBSCAN performs clustering by analyzing the local density distribution of data points, without the need to pre-specify the number of clusters, and is robust to noise and outliers. The temperature control region refers to an independently controllable region dynamically generated based on the personnel distribution. Specifically, first, a millimeter-wave radar array is deployed on the ceiling of the indoor space. The millimeter-wave radar uses a 77GHz frequency band, with a resolution ≤0.5m, a scanning period of 100ms, and supports horizontal 120° and vertical 60° scanning, so that the millimeter-wave radar array emits electromagnetic waves in the 77GHz frequency band with a scanning period of 100ms. Of course, it can be understood that the millimeter-wave radar can also adopt other parameters, which are not limited here. By deploying the millimeter-wave radar array on the ceiling to emit electromagnetic waves in the 77GHz frequency band with a scanning period of 100ms, the position data and motion data of the personnel are parsed after receiving the human body reflection signals. Different numbers of people generate different heat loads. The larger the number of people, the higher the personnel density in the region, the greater the heat load generated, and the greater the cooling demand, and vice versa. Therefore, the entire spatial region can be divided into multiple sub-regions by clustering according to the personnel distribution. Specifically, after obtaining the position data of the personnel, the distribution of each person's position in the spatial region can be known. In this way, the region with a certain number of personnel distributions can be divided into temperature control regions, and the regions without personnel distributions are excluded, thereby obtaining multiple temperature control regions for temperature regulation. The other excluded regions do not require temperature regulation, thus avoiding energy waste. In a specific example, the millimeter-wave radar in the gym detects that there are 7 people in the treadmill area, 3 people in the rest area, and no people in the strength training area. After analysis by the clustering algorithm, the treadmill area and the rest area are divided into two temperature control regions, and the area without people in the strength training area is excluded and does not require regulation.Through the coupling of high-precision perception of millimeter-wave radar and clustering algorithms, the millisecond-level dynamic recognition of personnel gathering areas is achieved, solving the problem of lag in regulation of traditional fixed zoning that cannot adapt to changes in the flow of people. The dynamic division of temperature control areas is realized. Only in the temperature control areas will corresponding temperature regulation be carried out, while in non-temperature control areas, no temperature regulation is required. Accurate local area temperature regulation is achieved, avoiding energy waste and greatly improving the comfort of people in the temperature control areas.

[0031] In one embodiment, as Figure 2 shown, the step S110 further includes: S111 - S112.

[0032] S111. Real-time collect the motion trajectory data of the human body limbs through a millimeter-wave radar to generate a continuous spatio-temporal coordinate sequence;

[0033] S112. Periodically analyze the spatio-temporal coordinate sequence to determine whether it is a repetitive action. If so, count the number of times of the repetitive action within a unit time period to obtain the movement frequency of the person.

[0034] In this embodiment, the motion trajectory data refers to the continuous tracking data of the displacement paths of the key points of the human body limbs (such as elbows, knees, hips, etc.) by the millimeter-wave radar. The spatio-temporal coordinate sequence refers to the three-dimensional position data set of the limb points sorted by time stamps (including X / Y / Z axis coordinates and time information). The periodic analysis refers to identifying the regularity of actions through waveform features or spectral analysis methods. The repetitive action refers to the periodic behavior in which the limbs show similar motion trajectories within a time period. The unit time period refers to a time period (such as 5 seconds, 10 seconds, 1 minute, etc.). Specifically, the millimeter-wave radar emits a 77GHz frequency-modulated continuous wave signal and receives the human body reflection signal, extracts the Doppler frequency shift and phase difference information of the key points of the limbs, and generates a spatio-temporal coordinate sequence with centimeter-level accuracy; the spatio-temporal coordinate sequence is unfolded into a displacement-time waveform in the time dimension, and the main frequency component is extracted by using the fast Fourier transform (FFT). If the main frequency amplitude exceeds the preset threshold and the waveforms are similar in consecutive periods, it is determined as a repetitive action; the number of complete action cycles within the unit time period is counted, and the movement frequency (Hz) is calculated. Of course, it can be understood that the movement frequency can also be obtained through Doppler frequency shift analysis. In a specific example, the swing trajectory of the left arm of a user on a treadmill in a gym is captured by the millimeter-wave radar and generates a spatio-temporal coordinate sequence with a length of 5 seconds. The FFT analysis shows that the main frequency of the waveform is 2Hz and the similarity of consecutive periods > 85%, which is determined as a repetitive action. It is counted that 10 complete swings are completed within 5 seconds, and the movement frequency is calculated to be 2Hz. Through the high-precision motion tracking of the millimeter-wave radar and the recognition of periodic repetitive actions, the real-time quantitative analysis of the dynamic behavior characteristics of the human body is realized, solving the technical defect that traditional sensors can only identify the presence of personnel and cannot capture the motion state of personnel, and providing accurate metabolic activity parameters for heat load prediction.

[0035] In one embodiment, as Figure 3 shown, the step S110 further includes: S113 - S115.

[0036] S113. Divide the point cloud data corresponding to the spatial region according to a preset neighborhood radius to obtain a plurality of initial spatial regions;

[0037] S114. Determine the number of people in each of the initial spatial regions according to the distribution of the position data in the initial spatial regions;

[0038] S115. Mark the initial spatial regions with the number of people greater than the preset minimum number in the plurality of initial spatial regions as temperature control regions.

[0039] In this embodiment, the preset neighborhood radius refers to the spatial coverage threshold (e.g., 2 m) during the division of millimeter-wave radar point cloud data. The initial spatial region refers to the candidate sub-regions formed by evenly dividing the monitoring space based on the neighborhood radius. The position data distribution refers to the statistical result of the number of personnel coordinate points in each initial region. The preset minimum number of people refers to the minimum number threshold (e.g., 3 people) for determining the effectiveness of the temperature control region. Specifically, after mapping the real-time point cloud data of the millimeter-wave radar array to a two-dimensional plane coordinate system, the entire spatial region is divided into multiple equally spaced grid cells (e.g., square grids with a side length of 2 m) with the preset neighborhood radius as the unit. Each grid corresponds to an initial spatial region. Traverse all grid cells and count the number of personnel coordinate points falling into each cell. If the number of people in a certain cell exceeds the preset minimum number of people, mark this cell as a temperature control region; otherwise, it is regarded as an invalid region and excluded. In a specific example, a gym is divided into 10 initial spatial regions of 2 m × 2 m. Among them, 5 personnel coordinate points are detected in the grid of the treadmill area, 2 personnel coordinate points are detected in the grid of the strength training area, and there are no coordinate points in the grid of the rest area. Based on the threshold of the minimum number of 3 people, only the grid of the treadmill area is marked as a temperature control region, and the other regions are all excluded. Through the collaborative mechanism of neighborhood radius division and minimum number of people screening, the rapid conversion from spatial discrete points to effective temperature control regions is realized, which not only avoids the subjective defects of traditional manual zoning but also filters out the ineffective regulation of low-density regions through hard thresholds, significantly improving the execution efficiency and energy efficiency ratio of the temperature control system.

[0040] In one embodiment, as Figure 4 shown, step S110 further includes: S116 - S117.

[0041] S116. Determine whether the distance between adjacent temperature control regions is less than the preset distance threshold and whether the difference in personnel density is less than the preset personnel density difference threshold;

[0042] S117. If so, merge the adjacent temperature control regions.

[0043] In this embodiment, the adjacent temperature control regions refer to the marked and valid temperature control regions with adjacent spatial positions. The preset distance threshold refers to the upper limit of the boundary spacing for determining region merging (e.g., 1 m). The personnel density difference refers to the percentage difference in the ratio of the number of people per unit area between adjacent regions. The preset personnel density difference threshold refers to the maximum density fluctuation range allowed for merging (e.g., 15%). Specifically, after completing the initial marking of the temperature control regions, traverse the adjacent relationships of all valid regions in the space and calculate the minimum distance between the boundaries of each pair of regions. If the distance between two temperature control regions is less than the preset distance threshold, further compare their personnel densities (density = number of people / region area). If the absolute value of the density difference is less than the preset threshold, merge the two regions into a single temperature control unit, and recalculate the boundary and comprehensive density parameters of the merged region, that is, update the position and personnel density corresponding to the merged temperature control region. In a specific example, temperature control region A (area 12 ㎡, 8 people, density 0.67 people / ㎡) in a shopping mall is adjacent to region B (area 10 ㎡, 7 people, density 0.7 people / ㎡). After detection, the distance is 0.8 m (<1 m), and the density difference is |0.7 - 0.67| / 0.67×100% = 4.5% (<15%), meeting the merging conditions, and finally merged into a new temperature control region AB (area 22 ㎡, 15 people, density 0.68 people / ㎡). By dynamically merging adjacent regions with low density differences, it avoids the redundant air supply caused by independent regulation of scattered small regions, reduces the number of air-conditioning control commands while ensuring temperature uniformity, and improves the system response efficiency and energy utilization rate.

[0044] S120. Calculate the heat load amount corresponding to the temperature control region according to the region area, personnel density of the temperature control region, and the motion data through a preset heat load prediction model;

[0045] In this embodiment, the area of the region refers to the numerical value of the spatial coverage range of the temperature control region (unit: square meters). The population density is calculated by the ratio of the total number of people in the temperature control region to the area of the region (unit: people per square meter). The motion data includes the motion frequency of the human body limbs collected in real time by a millimeter-wave radar (unit: Hz). The heat load prediction model refers to a standard mathematical model for calculating the temperature control demand. The heat load amount refers to the cooling capacity required to maintain the target temperature. Specifically, after dividing the temperature control region, the area of each temperature control region is obtained, and the population density is calculated based on the number of people distributed in the temperature control region and the area of the region. For example, if the area of temperature control region A is 10 square meters and the number of people is 5, then the population density of temperature control region A is 0.5 people / ㎡. The area of the region, the population density, and the motion data are all input into the heat load prediction model, and the heat load amount of the temperature control region is calculated through the heat load prediction model. Using this heat load amount, it can be known how much cooling capacity the air conditioner needs to provide to keep the people in the temperature control region comfortable. The heat load prediction model uses the area of the region, the population density, and the motion data as input parameters, comprehensively considering the influence of the building environment, the heat generated by the number of people, and the heat generated by human activities on the heat load amount, and outputs a calculated value representing the heat load demand of the temperature control region. For example, for the same area region, when the population density increases or the exercise intensity increases, the heat load amount output by the model increases accordingly, and vice versa. By integrating static environmental parameters and dynamic motion characteristics, multi-dimensional accurate modeling of the heat load prediction model is realized, overcoming the defect that the traditional solution ignores the difference in human activity intensity, providing a quantitative basis for differential temperature control, being able to accurately match the heat load demand of the temperature control region, and significantly improving the energy efficiency utilization rate and user comfort.

[0046] In one embodiment, as Figure 5 shown, step S120 includes: S121 - S122.

[0047] S121. Calculate the human heat load according to the population density in the temperature control region, calculate the building environment heat load according to the area of the temperature control region, and determine the basic heat load according to the human heat load and the building environment heat load, where the heat load amount includes the basic heat load and the motion compensation heat load;

[0048] In this embodiment, the human heat load refers to the heat load generated by people within the temperature control area, the building environment heat load refers to the heat load of the building structure and environment within the temperature control area, which is related to building materials, structural layout, etc., and the basic heat load refers to the sum of the human heat load and the building environment heat load. Specifically, for each dynamically divided temperature control area, the human heat load can be calculated based on the preset unit density heat load coefficient (e.g., 100 W / person) and the real-time statistical human density (number of people / area of the area), and at the same time, the building environment heat load can be calculated based on the preset building environment heat load coefficient (e.g., 200 W / ㎡) and the actual area of the temperature control area. Finally, the two are added together to generate the basic heat load value. In a specific example, for a temperature control area with a human density of 0.5 person / ㎡, an area of 20 ㎡, a unit density heat load coefficient of 100 W / person, and a building environment heat load coefficient of 200 W / ㎡, the human heat load is 0.5×20×100 = 1000 W, the building environment heat load is 20×200 = 4000 W, and the basic heat load is 1000 + 4000 = 5000 W. By separating the heat contributions of human activities and the building structure environment and establishing a standardized calculation model, the rapid estimation of the basic heat load is achieved, providing a quantifiable benchmark for dynamic temperature control, providing an extensible standardized input for differential temperature control strategies, avoiding the accuracy loss problem in mixed calculations in traditional solutions, improving the calculation accuracy of the heat load, enabling the temperature control of the air conditioner to better match the heat load, and improving comfort.

[0049] In one embodiment, as Figure 6 shown, step S121 includes: S1211 - S1213.

[0050] S1211. Calculate the human heat load according to the human density, area of the area, sensible heat load of the human body, and latent heat load of the human body;

[0051] S1212. Calculate the building environment heat load according to the area of the area and the building environment load coefficient;

[0052] S1213. Determine the basic heat load based on the sum of the human heat load and the building environment heat load.

[0053] In this embodiment, the sensible heat load refers to the heat transferred from the human body to the environment through temperature difference, and the latent heat load refers to the heat dissipated by the human body through phase change processes such as breathing and sweating. Specifically, for each dynamically divided temperature control area, the following calculation process is performed: Based on the product of the personnel density and the area of the area, multiply it by a preset sensible heat load coefficient per unit density (e.g., 60 W / person) and a latent heat load coefficient per unit density (e.g., 30 W / person) respectively to calculate the sensible heat load and latent heat load of the personnel. The sum of the two is the personnel heat load; at the same time, calculate the building environment heat load according to the product of the area of the area and a preset building environment load coefficient (e.g., 200 W / ㎡); finally, add the personnel heat load and the building environment heat load to obtain the basic heat load. Specifically, the formula for the basic heat load in this embodiment is as follows: Q base = A·ρ·(Q sensible + Q latent) + k 建筑 ·A; where ρ is the personnel density (persons / ㎡), A is the area of the area (m), Q sensible = 60 W / person is the sensible heat load coefficient, Q latent = 30 W / person is the latent heat load coefficient, k 建筑 = 200 W / m 2 is the building environment heat load coefficient. k 建筑 ·A is also the building environment heat load Q 建筑 , and A·ρ·(Q sensible + Q latent) is also the personnel heat load Q 人员 . In a specific example, for a temperature control area with a personnel density of 0.5 persons / ㎡, an area of 20㎡, a sensible heat load coefficient per unit density of 60 W / person, a latent heat load coefficient of 30 W / person, and a building environment load coefficient of 200 W / ㎡, the sensible heat load of the personnel is 0.5×20×60 = 600 W, the latent heat load is 0.5×20×30 = 300 W, and the personnel heat load is 600 + 300 = 900 W; the building environment heat load is 20×200 = 4000 W, and the basic heat load is 900 + 4000 = 4900 W. Through the sub-item calculation of sensible heat and latent heat and the independent modeling of the building environment heat load, the refined splitting of the basic heat load is realized, the error caused by mixed calculation in the traditional scheme is overcome, the interpretability of heat load prediction and the flexibility of the control strategy are improved, and a high-precision data basis is provided for the differential temperature control of the air conditioner.

[0054] S122. Determine the heat load compensation coefficient according to the movement frequency and a preset compensation coefficient per unit movement frequency, compensate the personnel heat load according to the heat load compensation coefficient, and determine the movement compensation heat load based on the compensated personnel heat load and the building environment heat load, where the movement data includes the movement frequency.

[0055] In this embodiment, the heat load compensation coefficient refers to a proportionality factor for dynamically correcting the human heat load based on the movement frequency. The unit movement frequency compensation coefficient α represents the enhancement ratio of the human heat load per unit movement frequency (1 Hz) (for example, α = 0.05 means that each 1 Hz movement frequency increases the heat load by 5%). The movement frequency is calculated from the number of periodic limb movements of the person (unit: Hz) collected in real time by the millimeter-wave radar. The movement-compensated heat load refers to the comprehensive heat load demand after being corrected by the movement frequency. For each temperature control zone, based on the formula: Q 补偿 = Q 人员 (1 + α*f) + Q 建筑 ; calculate the movement-compensated heat load, where the heat load compensation coefficient is α*f, representing the overall enhancement effect of the movement state on the human heat load. Q 人员 is the uncompensated human heat load value, and Q 建筑 is the building environment heat load value. In a specific example, the human heat load in a certain temperature control zone is 900 W, the building environment heat load is 4000 W, the detected average movement frequency is 2 Hz, and the preset α = 0.05. Then the heat load compensation coefficient is 0.05 × 2 = 0.1, the compensated human heat load is 900×(1 + 0.1) = 990 W, and the movement-compensated heat load is 990 + 4000 = 4990 W. By calculating the heat load compensation coefficient based on the movement frequency, the differential effects of different activity intensities on the heat load are quantified, solving the defect that the static model in the traditional solution cannot respond to dynamic metabolic changes, enabling the air-conditioning system to adjust the air supply strategy in real time according to the movement intensity, and improving the temperature control response speed in high-intensity movement scenarios such as gyms.

[0056] In other embodiments, the motion data may further include motion amplitude, motion type, motion displacement, etc. in addition to the motion frequency. The heat load compensation coefficient can also be compensated by the above-mentioned motion data. For example, the motion amplitude can be identified through the motion trajectory data, and the heat load compensation coefficient can be adjusted based on the magnitude of the motion amplitude. Suppose a gym user is performing dumbbell lateral raises, and the millimeter-wave radar captures the periodic displacement of their arm in the vertical direction, with the maximum amplitude of a single action being 0.6 m (from the hip to the shoulder). According to the preset rule, when the amplitude > 0.5 m, the compensation coefficient increases by 0.03, and finally the heat load in this area increases by 3%. Another example is that the motion type can be identified through the motion trajectory data, such as jumping jacks, running, and walking slowly, and the heat load compensation coefficient can be adjusted based on the difficulty of different motion types. Suppose the millimeter-wave radar detects that the user's trajectory shows high-frequency and small-amplitude periodic fluctuations (the characteristics match "running in place"), and the classification model outputs the motion type as "running", and the retrieved compensation coefficient α = 0.05, with the heat load correction amount being 5%. Another example is that the displacement of a person can be identified through the motion trajectory data, and the heat load compensation coefficient can be adjusted based on the magnitude of the displacement distance. Suppose a badminton player quickly runs from the baseline of the court (coordinate X1 = 2 m) to the net front (X2 = 8 m) during training, with a cumulative round-trip displacement of 30 meters within a single round. The millimeter-wave radar tracks the trajectory of the center point of their torso in real time, calculates the total displacement as 30 m. According to the preset rule, for every 10-meter displacement, the heat load compensation coefficient increases by 0.015. Finally, the compensation coefficient increases by 0.045 (30 / 10 × 0.015), and the total heat load in the temperature control area where the player is located increases by 4.5%.

[0057] S130. Adjust the air-conditioning operation parameters of the corresponding temperature control area according to the heat load amount.

[0058] In this embodiment, the air conditioner operation parameters include the target set temperature and the fan speed. Of course, it can be understood that other parameters can also be used, such as the compressor frequency, refrigerant flow rate, etc., which are not limited here. After obtaining the heat load, the amount of cooling capacity required by the air conditioner to ensure the comfort of the people in the temperature control area can be calculated based on this heat load, and then the air conditioner operation parameters can be adjusted accordingly to make the air conditioner increase the corresponding cooling capacity to maintain a comfortable temperature and ensure the comfort of the people. In principle, the greater the heat load, the lower the air conditioner operation parameters such as the set temperature need to be adjusted. And the heat load in this embodiment is an accurate value, so the adjustment of the air conditioner operation parameters can be accurately matched with the heat load. Moreover, the heat loads corresponding to different temperature control areas are different, further realizing high-precision temperature control adjustment with differences in different temperature control areas. In a specific example, the gym is dynamically divided into two temperature control areas, namely the running area and the rest area. The heat load in the running area is 8000W, and the heat load in the rest area is 3000W. The original set temperature is 26°C. Then, the air conditioner operation parameters corresponding to the running area, such as the set temperature, are adjusted to 22.8°C, and the air conditioner operation parameters corresponding to the rest area, such as the set temperature, are adjusted to 24.8°C. Through the real-time matching of the heat load and the air conditioner performance, the precise linkage control of the temperature and the wind speed is realized, and the rapid cooling in the high-intensity exercise area and the energy-saving operation in the low-load area are achieved.

[0059] In one embodiment, as Figure 7 shown, the step S130 includes: S131 - S132.

[0060] S131. Compensate the preset adjustment temperature difference according to the ratio of the motion compensation heat load to the maximum heat load of the air conditioner to obtain the target adjustment temperature difference, and determine the target set temperature based on the current temperature and the target adjustment temperature difference, and control the air conditioner to operate according to the target set temperature; and / or,

[0061] In this embodiment, the maximum heat load of the air conditioner refers to the maximum heat load capacity (unit: W) that the air conditioner equipment can handle when operating at full load. The preset adjustment temperature difference refers to the maximum temperature adjustment range allowed by the system (for example, ΔT = 4°C). The target adjustment temperature difference refers to the temperature compensation amount dynamically scaled based on the heat load ratio. The target set temperature refers to the final regulated air conditioner operation temperature. Specifically, according to the following formula:

[0062]

[0063] Calculate the target set temperature, where Q 补偿 is the motion compensation heat load, Q max is the maximum heat load of the air conditioner, ΔT is the preset adjustment temperature difference, T 当前 is the current temperature, q 目标 is the target set temperature. For target temperature difference adjustment. In a specific example, the moving compensation heat load of one temperature control area is 8000W, the maximum heat load capacity of the air conditioner is 10000W, the reference temperature is 26°C, and the preset adjustment temperature difference is 4°C. Then the target adjustment temperature difference is 4×(8000 / 10000) = 3.2°C, and the target set temperature is 26 - 3.2 = 22.8°C. The air conditioner adjusts to operate at 22.8°C accordingly. Through the dynamic scaling mechanism of the heat load ratio, the strict matching between the temperature adjustment range and the actual load demand is achieved, solving the problems of overcooling or insufficiency caused by traditional fixed temperature difference adjustment, improving the accuracy of temperature control in crowded places, reducing ineffective refrigeration, and enhancing energy efficiency.

[0064] S132. Judge whether the ratio of the moving compensation heat load to the maximum heat load of the air conditioner is greater than the preset proportion threshold. If so, increase the fan speed gear of the air conditioner.

[0065] In this embodiment, the preset proportion threshold refers to the minimum heat load proportion standard for determining the increase of the fan speed gear (for example, 80%), and the fan speed gear refers to the hierarchical control mode of the air conditioner's air supply intensity (such as low speed / medium speed / high speed). Specifically, calculate the moving compensation heat load Q 补偿 in real time and the ratio η of the maximum heat load capacity Q max of the air conditioner, and then judge η > γ 阈值 , where γ 阈值 is the preset proportion threshold, for example, 80%. If so, increase the fan speed to a higher gear to enhance the heat dissipation efficiency. In a specific example, for a certain temperature control area, Q 补偿 = 8500W, Q max = 10000W, then η = 85%, exceeding the preset threshold of 80%, triggering the fan speed to increase from "medium speed" to "high speed" gear, and the wind speed increasing from 2.5m / s to 4.0m / s. By dynamically adjusting the fan speed, the rapid heat exchange ability in high-load areas is ensured, avoiding the problem of temperature rise caused by insufficient air supply in the traditional fixed-speed air supply mode, shortening the time for the user's perceived temperature to stabilize, and at the same time avoiding excessive air supply in low-load areas through hierarchical control, reducing the overall energy consumption.

[0066] In summary, in the first aspect of the embodiments of the present invention, millimeter-wave radar is used to achieve millisecond-level dynamic detection of personnel, greatly reducing the air-conditioning instruction delay and improving the response speed. In the second aspect, dynamic zoning is used to reduce the ineffective cooling / heating areas and lower the overall energy consumption. In the third aspect, the thermal load model based on the movement frequency matches the perceived temperature with the human metabolic rate, greatly reducing the error of the user's perceived temperature. In the fourth aspect, only the movement parameters are analyzed by the millimeter-wave radar, avoiding the privacy risk of image acquisition. Therefore, the present invention combines millimeter-wave radar with dynamic algorithms to achieve "adjusting immediately when people move and precise zoning" intelligent air-conditioning control, with both high energy efficiency and high comfort, and is applicable to public places with complex personnel flow.

[0067] Figure 8 FIG. is a schematic block diagram of an air-conditioning control device 200 based on millimeter-wave radar provided by an embodiment of the present invention. As Figure 8 shown, corresponding to the above air-conditioning control method based on millimeter-wave radar, the present invention also provides an air-conditioning control device 200 based on millimeter-wave radar. The air-conditioning control device 200 based on millimeter-wave radar includes units for executing the above air-conditioning control method based on millimeter-wave radar, and the device can be configured in a computer device. Specifically, please refer to Figure 8 , the air-conditioning control device 200 based on millimeter-wave radar includes: a dynamic partitioning unit 201, a calculation unit 202, and an adjustment unit 203.

[0068] Among them, the dynamic partitioning unit 201 is used to obtain the position data and movement data of personnel in the spatial area in real time through millimeter-wave radar, and dynamically partition the spatial area into multiple temperature control areas according to the position data through a clustering algorithm; the calculation unit 202 is used to calculate the heat load amount corresponding to the temperature control area according to the area of the temperature control area, the personnel density, and the movement data through a preset heat load prediction model; the adjustment unit 203 is used to adjust the air-conditioning operation parameters of the corresponding temperature control area according to the heat load amount.

[0069] In one embodiment, the dynamic partitioning unit 201 includes: a trajectory acquisition unit, a frequency statistics unit, an initial partitioning unit, a distribution unit, a marking unit, a judgment unit, and a merging unit.

[0070] Among them, a trajectory acquisition unit is configured to collect in real time the motion trajectory data of a person's limbs through a millimeter-wave radar, and generate a continuous spatio-temporal coordinate sequence; a frequency statistics unit is configured to perform periodic analysis on the spatio-temporal coordinate sequence to determine whether it is a repetitive action, and if so, count the number of times of the repetitive action within a unit time period to obtain the motion frequency of the person; an initial division unit is configured to divide the point cloud data corresponding to the spatial region according to a preset neighborhood radius to obtain a plurality of initial spatial regions; a distribution unit is configured to determine the number of people in each of the initial spatial regions according to the distribution of the position data in the initial spatial regions; a marking unit is configured to mark the initial spatial regions with the number of people greater than a preset minimum number in the plurality of initial spatial regions as temperature control regions; a judgment unit is configured to judge whether the distance between adjacent temperature control regions is less than a preset distance threshold and whether the difference in personnel density is less than a preset personnel density difference threshold; a merging unit is configured to, if so, merge adjacent temperature control regions.

[0071] In one embodiment, the calculation unit 202 includes: a basic heat load unit and a motion compensation heat load unit.

[0072] Among them, the basic heat load unit is configured to calculate the personnel heat load according to the personnel density in the temperature control region, calculate the building environment heat load according to the area of the temperature control region, and determine the basic heat load according to the personnel heat load and the building environment heat load, where the heat load amount includes the basic heat load and the motion compensation heat load; the motion compensation heat load unit is configured to determine a heat load compensation coefficient according to the motion frequency and a preset unit motion frequency compensation coefficient, compensate the personnel heat load according to the heat load compensation coefficient, and determine the motion compensation heat load based on the compensated personnel heat load and the building environment heat load, where the motion data includes the motion frequency.

[0073] In one embodiment, the basic heat load unit includes: a first calculation unit, a second calculation unit, and a third calculation unit.

[0074] Among them, the first calculation unit is configured to calculate the personnel heat load according to the personnel density, the area, the sensible heat load of the human body, and the latent heat load of the human body; the second calculation unit is configured to calculate the building environment heat load according to the area and the building environment load coefficient; the third calculation unit is configured to determine the basic heat load based on the sum of the personnel heat load and the building environment heat load.

[0075] In one embodiment, the adjustment unit 203 includes: a temperature adjustment unit and a wind speed adjustment unit.

[0076] Among them, a temperature adjustment unit is configured to compensate a preset adjustment temperature difference according to a ratio of the motion compensation heat load to the maximum heat load of the air conditioner to obtain a target adjustment temperature difference, and determine a target set temperature according to the current temperature and the target adjustment temperature difference, and control the air conditioner to operate according to the target set temperature; and / or, a wind speed adjustment unit is configured to determine whether the ratio of the motion compensation heat load to the maximum heat load of the air conditioner is greater than a preset proportion threshold, and if so, increase the gear of the fan speed of the air conditioner.

[0077] The above-mentioned air conditioner control device 200 based on millimeter wave radar can be implemented in the form of a computer program, and this computer program can run on a computer device as shown in Figure 9 the following.

[0078] Please refer to Figure 9 , Figure 9 which is a schematic block diagram of a computer device provided by an embodiment of the present application. The computer device 500 may be a terminal.

[0079] Refer to Figure 9 , the computer device 500 includes a processor 502, a memory, and a network interface 505 connected through a system bus 501. Among them, the memory may include a non-volatile storage medium 503 and an internal memory 504.

[0080] The non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions, and when the program instructions are executed, the processor 502 can be caused to execute an air conditioner control method based on millimeter wave radar.

[0081] The processor 502 is configured to provide computing and control capabilities to support the operation of the entire computer device 500.

[0082] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can be caused to execute an air conditioner control method based on millimeter wave radar.

[0083] The network interface 505 is configured to communicate with other devices through a network. Those skilled in the art can understand that Figure 9 the structure shown in is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device 500 to which the solution of the present application is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0084] Among them, the processor 502 is used to run the computer program 5032 stored in the memory to implement the steps of the above method.

[0085] It should be understood that in the embodiments of the present application, the processor 502 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0086] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, and the storage medium is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above method.

[0087] 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, where the computer program includes program instructions. When the program instructions are executed by the processor, the processor is caused to execute the steps of the above method.

[0088] The storage medium may be a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, an optical disk, or other computer-readable storage media that can store program codes.

[0089] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the components and steps of the examples have been generally described according to their functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0090] In several embodiments provided by the present invention, 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 each unit is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0091] The steps in the method embodiments of the present invention can be adjusted, combined, and deleted according to actual needs. The units in the device embodiments of the present invention can be combined, divided, and deleted according to actual needs. In addition, the functional units in each embodiment of the present invention can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0092] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0093] In the above embodiments, the descriptions of the various embodiments have their own focuses. For the parts not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0094] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, provided that these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

[0095] As described above, the above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. An air conditioner control method based on a millimeter-wave radar, characterized in that The method includes: Obtaining, in real time by a millimeter-wave radar, position data and motion data of people in a spatial area, and dynamically dividing the spatial area into a plurality of temperature control areas according to the position data by means of a clustering algorithm; Calculating a heat load amount corresponding to the temperature control area according to the area of the temperature control area, the personnel density, and the motion data by means of a preset heat load prediction model; Adjusting the air-conditioning operation parameters of the temperature control area corresponding thereto according to the heat load amount.

2. The method according to claim 1, wherein The step of calculating a heat load amount corresponding to the temperature control area according to the area of the temperature control area, the personnel density, and the motion data by means of a preset heat load prediction model includes: Calculating a personnel heat load according to the personnel density in the temperature control area, calculating a building environment heat load according to the area of the temperature control area, and determining a basic heat load according to the personnel heat load and the building environment heat load, wherein the heat load amount includes the basic heat load and a motion compensation heat load; Determining a heat load compensation coefficient according to a motion frequency and a preset unit motion frequency compensation coefficient, compensating the personnel heat load according to the heat load compensation coefficient, and determining a motion compensation heat load based on the compensated personnel heat load and the building environment heat load, wherein the motion data includes the motion frequency.

3. The method according to claim 2, wherein The step of calculating a personnel heat load according to the personnel density in the temperature control area, calculating a building environment heat load according to the area of the temperature control area, and determining a basic heat load according to the personnel heat load and the building environment heat load includes: Calculating a personnel heat load according to the personnel density, the area, the sensible heat load of the human body, and the latent heat load of the human body; Calculating a building environment heat load according to the area and a building environment load coefficient; Determining a basic heat load based on the sum of the personnel heat load and the building environment heat load.

4. The method according to claim 2, wherein The step of adjusting the air-conditioning operation parameters of the temperature control area corresponding thereto according to the heat load amount includes: Compensating a preset adjustment temperature difference according to a ratio of the motion compensation heat load to the maximum heat load of the air conditioner to obtain a target adjustment temperature difference, determining a target set temperature according to the current temperature and the target adjustment temperature difference, and controlling the air conditioner to operate according to the target set temperature; and / or Judging whether the ratio of the motion compensation heat load to the maximum heat load of the air conditioner is greater than a preset proportion threshold, and if so, increasing the gear of the fan speed of the air conditioner.

5. The method according to any one of claims 1-4, characterized in that, The step of dynamically dividing the spatial area into a plurality of temperature control areas according to the position data by means of a clustering algorithm includes: Dividing point cloud data corresponding to the spatial area according to a preset neighborhood radius to obtain a plurality of initial spatial areas; Determining the number of people in each of the initial spatial areas according to the distribution of the position data in the initial spatial areas; Marking the initial spatial areas with the number of people greater than a preset minimum number among the plurality of initial spatial areas as temperature control areas.

6. The method according to claim 5, wherein The step of dynamically dividing the spatial area into a plurality of temperature control areas according to the position data by means of a clustering algorithm further includes: Determine whether the distance between adjacent temperature control regions is less than a preset distance threshold and whether the difference in personnel density is less than a preset personnel density difference threshold; If so, merge the adjacent temperature control regions.

7. The method according to claim 1, characterized in that, The step of obtaining the movement data of personnel in the spatial region in real time through the millimeter wave radar includes: Collect the movement trajectory data of the personnel's limbs in real time through the millimeter wave radar to generate a continuous sequence of spatio-temporal coordinates; Perform periodic analysis on the spatio-temporal coordinate sequence to determine whether it is a repetitive action. If so, count the number of times of the repetitive action within a unit time period to obtain the movement frequency of the personnel.

8. An air conditioner control device based on a millimeter-wave radar, characterized in that, The device includes a unit for executing the method according to any one of claims 1-7 above.

9. A computer device, characterized in that, The computer device includes a memory and a processor. A computer program is stored on the memory. When the processor executes the computer program, the method according to any one of claims 1-7 is implemented.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program. When the computer program is executed by the processor, the method according to any one of claims 1-7 can be implemented.

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