Air conditioner control method and system and electronic equipment

Abstract

The embodiment of the invention discloses an air conditioner control method and system and electronic equipment, and belongs to the technical field of air conditioner system control. The air conditioner control method comprises the steps that according to human body biological feedback signals detected in real time, biological characteristic information and spatial distribution information of at least one target person in a first space are determined, the biological characteristic information is used for representing the identity of the target person, and the spatial distribution information represents the movement trend of the target person; according to the biological characteristic information and the spatial distribution information, when it is determined that the target person moves from a first space to a second space, migration response information is generated; and in response to the migration response information, a second air conditioner in the second space is controlled to operate according to a first operation parameter, and the first operation parameter is the operation parameter of the first air conditioner when the target person is located in the first space.

Description

Technical Field

[0001] This application relates to the field of air conditioning system control technology, and more specifically, to an air conditioning control method, system, and electronic device. Background Technology

[0002] With the significant growth in demand for smart homes and personalized environmental control, users expect their indoor environment to seamlessly adjust to their personal activities and locations. Existing methods primarily rely on mobile phone positioning, Bluetooth / wearable devices, or cameras for personnel identification and location awareness: the former requires users to carry the device, and its effectiveness may be affected by obstructions or disconnections; the latter raises privacy concerns and obstruction issues. Traditional temperature control is fixed on a room-by-room basis, rarely enabling continuous and automatic migration across rooms based on individual preferences. High-resolution millimeter-wave radar can passively and imperceptibly capture micro-doppler movements of the human body, such as breathing, heartbeat, and muscle tremors. It is robust to slight obstructions and can operate stably in low-light or nighttime environments, providing a new approach for non-wearable, low-invasive individual identification and continuous tracking. Based on this, it is possible to migrate an individual's personalized air conditioning parameters from the source room to the target room in real time, thereby improving comfort and energy efficiency and overcoming the shortcomings of existing technologies in terms of imperceptible identification, cross-room migration, and privacy protection. Summary of the Invention

[0003] This application provides an air conditioning control method, system, and electronic device to at least solve the technical problems in the related art of being unable to achieve seamless, cross-room individual identification and environmental parameter migration.

[0004] According to a first aspect of the embodiments of this application, an air conditioning control method is provided, comprising: Based on real-time detected human biofeedback signals, the biometric information and spatial distribution information of at least one target person in the first space are determined. The biometric information is used to characterize the identity of the target person, and the spatial distribution information characterizes the movement trend of the target person. Based on the biometric information and spatial distribution information, when the target person moves from the first space to the second space, migration response information is generated. In response to the migration response information, the second air conditioner in the second space is controlled to operate with the first operating parameters. The first operating parameters are the operating parameters of the first air conditioner when the target person is in the first space.

[0005] This solution utilizes human biofeedback signals to achieve seamless identification of target individuals and combines this with their movement trends to determine cross-room movement behavior, thereby generating migration response information. After the target individual enters the second space, personalized air conditioning parameters from the first space are transferred to the second space, ensuring consistent comfort and energy efficiency across different spaces. This process requires no additional equipment from the user, avoids the impact of obstructions or disconnections, and solves the problem of traditional temperature control systems being unable to migrate personalized parameters across rooms, thus improving the intelligence level of smart home environment regulation.

[0006] Optionally, if the human biofeedback signal is determined by real-time acquired radar echo signals, then based on the real-time detected human biofeedback signal, the biometric information and spatial distribution information of at least one target person in the first space are determined, including: analyzing the real-time radar echo signal to extract the target person's respiratory rate, heart rate, and limb micro-movement characteristics; determining the target person's identity based on the respiratory rate, heart rate, and limb micro-movement characteristics; incorporating the identity into the biometric information; determining the target person's spatial position and spatial angle based on the real-time radar echo signal; determining the target person's movement direction and movement speed based on the spatial position and spatial angle; and incorporating the movement direction and movement speed into the spatial distribution information.

[0007] This solution analyzes radar echo signals to extract respiratory rate, heart rate, and limb micro-movement characteristics of target individuals. These highly individualized features effectively distinguish the identities of different individuals. Simultaneously, based on the phase difference and signal intensity distribution in the radar echo signals, the spatial position and angle of the target individuals are calculated. By recording the target position coordinates at multiple time points and performing differential calculations, the direction and speed of movement of the target individuals are determined. These data collectively constitute the biometric and spatial distribution information of the target individuals, providing precise data support for subsequent cross-room migration.

[0008] Optionally, the biometric information includes the heart rate cycle, and the first operating parameters include temperature setpoint, wind speed setpoint, and wind direction setpoint. Based on the biometric information and spatial distribution information, when the target person moves from the first space to the second space, migration response information is generated, including: determining whether the target person has entered the threshold area based on the heart rate cycle, movement direction, and movement speed; the threshold area is the junction area between the first space and the second space; if the target person has entered the threshold area, determining the movement trajectory and movement confidence level of the target person based on the real-time radar echo signal; determining whether the target person has completed inter-room movement based on the movement trajectory and movement confidence level; if the inter-room movement has been completed, generating migration response information based on the temperature setpoint, wind speed setpoint, and wind direction setpoint.

[0009] This scheme utilizes the target person's heart rate cycle, direction of movement, and speed to determine whether they have entered the threshold area. Once the target person enters the threshold area, their real-time radar echo signal is further analyzed to determine their movement trajectory and movement confidence level. Through comprehensive analysis of the movement trajectory and confidence level, it is determined whether the target person has completed inter-room movement. Once inter-room movement is confirmed, migration response information is generated based on the temperature, wind speed, and wind direction setpoints within the first space, providing a basis for subsequent air conditioning parameter adjustments.

[0010] Optionally, in response to the migration response information, controlling the second air conditioner in the second space to operate with the first operating parameters includes: generating a migration trigger command based on the migration response information and the first operating parameters of the first air conditioner in the first space, wherein the first operating parameters are the operating parameters of the first air conditioner when the target person is in the first space; and controlling the second air conditioner in the second space to operate with the first operating parameters based on the migration trigger command.

[0011] This solution generates a migration trigger command after generating migration response information, based on the first operating parameters of the first air conditioner in the first space. This command includes the target person's personalized air conditioning parameters in the first space, such as temperature setpoint, fan speed setpoint, and airflow direction setpoint. Subsequently, this command is sent to the second air conditioner in the second space, causing it to operate according to the first operating parameters, thereby achieving the migration of personalized air conditioning parameters across rooms.

[0012] Optionally, after generating migration response information based on biometric information and spatial distribution information to determine when a target person moves from the first space to the second space, the method further includes: determining the distribution of obstacles in the target room based on real-time radar echo signals; adjusting the operating mode of the environmental control equipment in the target room based on the obstacle distribution; and optimizing the distribution of environmental parameters in the target room based on the operating mode and real-time control commands.

[0013] This solution analyzes real-time radar echo signals after personnel have moved between rooms, extracting static echo characteristics to determine the location and size of obstacles. Based on obstacle distribution, the operating mode of environmental control equipment in the target room is adjusted, such as adjusting the angle of air deflectors or the direction of airflow, to avoid the impact of obstacles on airflow. Subsequently, combining the operating mode and real-time control commands, the distribution of environmental parameters in the target room is optimized to ensure uniform airflow throughout the room, improving the efficiency and comfort of environmental regulation.

[0014] Optionally, the distribution of obstacles in the target room is determined based on real-time radar echo signals, including: extracting static echo features in the target room based on real-time radar echo signals; determining the location and volume of obstacles in the target room based on static echo features; and incorporating the location and volume of obstacles into the obstacle distribution.

[0015] This solution analyzes real-time radar echo signals to extract static echo characteristics within the target room. These characteristics reflect the presence and properties of fixed objects within the room. Based on these static echo characteristics, the specific location and volume of obstacles are determined and incorporated into obstacle distribution data, providing precise data support for subsequent adjustments to the operating modes of environmental control equipment.

[0016] Optionally, based on the operating mode and real-time control commands, the distribution of environmental parameters in the target room is optimized, including: determining the initial distribution of environmental parameters in the target room based on the real-time control commands; adjusting the boundary of the distribution of environmental parameters in the target room based on the distribution of obstacles; and generating the optimized distribution of environmental parameters based on the boundary of the distribution of environmental parameters and the initial distribution of environmental parameters.

[0017] This solution first determines the initial environmental parameter distribution within the target room upon receiving real-time control commands. Then, by incorporating obstacle distribution data, the environmental parameter distribution boundaries are adjusted to avoid the impact of obstacles on airflow. Finally, based on the adjusted environmental parameter distribution boundaries and the initial distribution, an optimized environmental parameter distribution is generated, ensuring that airflow evenly covers the entire room and improving the effectiveness of environmental regulation.

[0018] Optionally, based on the real-time detected human biofeedback signals, the determination of the biometric information and spatial distribution information of at least one target person in the first space further includes: extracting the respiratory frequency and heart rate from the real-time radar echo signal using short-time Fourier transform or wavelet transform algorithms; and extracting the micro-movement features of the target person's limbs by analyzing the Doppler frequency shift changes in the real-time radar echo signal.

[0019] This scheme employs short-time Fourier transform or wavelet transform algorithms to process real-time radar echo signals, extracting the respiratory and heart rates of the target individual. Simultaneously, by analyzing Doppler frequency shift changes, it extracts the micro-movement features of the target individual's limbs. These features collectively constitute the target individual's biometric information, providing accurate data support for subsequent identity recognition and movement trend analysis.

[0020] Optionally, based on the real-time detected human biofeedback signals, determine the spatial distribution information of at least one target person in the first space, including: calculating the spatial position and spatial angle of the target person based on the phase difference and signal intensity distribution in the real-time radar echo signal; and determining the movement direction and movement speed of the target person by recording the target position coordinates at multiple time points and performing differential operations on them.

[0021] This scheme utilizes the phase difference and signal strength distribution in radar echo signals to calculate the spatial location and angle of target personnel. Simultaneously, by recording the target's position coordinates at multiple time points and performing differential calculations, the direction and speed of movement of the target personnel are determined. These data collectively constitute the spatial distribution information of the target personnel, providing accurate data support for subsequent cross-room migration assessments.

[0022] Optionally, the operating mode of the environmental control equipment in the target room can be adjusted according to the distribution of obstacles, including: when the obstacle is in front of the air outlet, adjusting the angle of the air guide plate to avoid the impact of the obstacle on the airflow; and adjusting the air supply direction according to the distribution of obstacles to ensure that the airflow can evenly cover the target room.

[0023] This solution adjusts the angle of the air deflector when an obstacle is detected in front of the air outlet, allowing airflow to avoid the obstacle's influence. Simultaneously, it adjusts the airflow direction based on the obstacle's distribution, ensuring even airflow coverage of the entire target room and improving the efficiency and comfort of environmental regulation.

[0024] Optionally, calculating the migration confidence based on the biometric stability and the spatial distribution stability includes: Based on the real-time radar echo signal, determine the range of fluctuations in the target personnel's biometric characteristics and the range of fluctuations in their spatial distribution; Based on the range of fluctuations in the biometric characteristics and the range of fluctuations in the spatial distribution, the migration confidence score is calculated using the following formula:

[0025] in, This represents the migration confidence level. This indicates the range of fluctuation of the aforementioned biological characteristics. This indicates the range of spatial distribution fluctuations. and These are the weighting coefficients.

[0026] This scheme uses real-time radar echo signal analysis to determine the range of fluctuations in the biometrics of target personnel (such as the amplitude of changes in heart rate) and the range of fluctuations in spatial distribution (such as the standard deviation of location changes). Based on this data, a migration confidence score is calculated using a formula, where the ranges of biometric fluctuations and spatial distribution fluctuations are weighted by weighting coefficients. The sigmoid function in the formula ensures that the output range of the migration confidence score is between 0 and 1, facilitating subsequent decision-making. This calculation method improves the quantitative accuracy of migration confidence scores and provides a scientific basis for the migration of environmental parameters.

[0027] Optionally, after generating real-time control instructions based on the migration confidence and the migration response information, the method further includes: The distribution of obstacles in the target room is determined based on the real-time radar echo signal; Adjust the operating mode of the environmental control equipment in the target room according to the distribution of the obstacles; Based on the operating mode and the real-time control commands, optimize the distribution of environmental parameters in the target room.

[0028] This solution utilizes further analysis of real-time radar echo signals to determine the distribution of obstacles within the target room. Based on this obstacle distribution information, the operating mode of the environmental control equipment in the target room is adjusted (e.g., adjusting the angle of the air deflectors or changing the airflow direction) to avoid the impact of obstacles on the distribution of environmental parameters. Furthermore, by combining real-time control commands, the distribution of environmental parameters within the target room is optimized, ensuring that personnel can quickly perceive environmental changes that align with their preferences. This process enhances the adaptability and comfort of the environmental control system.

[0029] Optionally, determining the obstacle distribution within the target room based on the real-time radar echo signal includes: Based on the real-time radar echo signal, extract the static echo characteristics within the target room; Based on the static echo characteristics, determine the location and volume of obstacles in the target room; The location and volume of the obstacle are included in the obstacle distribution.

[0030] This solution processes real-time radar echo signals to extract static echo characteristics within the target room. These characteristics reflect the presence and properties of stationary objects within the room. Based on these static echo characteristics, the location and volume of obstacles are further determined and incorporated into the obstacle distribution information. This process provides precise data support for subsequent adjustments to the operating modes of environmental control equipment, ensuring the system can effectively cope with complex spatial environments.

[0031] Optionally, optimizing the distribution of environmental parameters in the target room based on the operating mode and the real-time control commands includes: The initial environmental parameter distribution within the target room is determined based on the real-time control command. Adjust the environmental parameter distribution boundary within the target room based on the obstacle distribution; Based on the environmental parameter distribution boundary and the initial environmental parameter distribution, an optimized environmental parameter distribution is generated.

[0032] This solution determines the initial environmental parameter distribution within the target room based on real-time control commands. Then, by incorporating obstacle distribution information, it adjusts the boundaries of the environmental parameter distribution to avoid the influence of obstacles on the propagation of environmental parameters. Based on this, an optimized environmental parameter distribution is generated, ensuring that the target personnel can quickly perceive environmental changes that align with their preferences, while simultaneously preventing interference from obstacles. This process significantly improves the efficiency and comfort of the environmental control system.

[0033] According to a second aspect of the embodiments of this application, the present invention provides an air conditioning control system, comprising: The signal processing module is used to determine the biometric information and spatial distribution information of at least one target person in the first space based on the real-time detected human biofeedback signals. The biometric information is used to characterize the identity of the target person, and the spatial distribution information characterizes the movement trend of the target person. The migration triggering module is used to generate migration response information when the target person moves from the first space to the second space based on the biometric information and the spatial distribution information. The processing module is configured to respond to the migration response information and control the second air conditioner in the second space to operate with a first operating parameter, wherein the first operating parameter is the operating parameter of the first air conditioner when the target person is located in the first space.

[0034] According to a third aspect of the embodiments of this application, the present invention provides an electronic device, including: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the air conditioning control method of the first aspect or any corresponding embodiment described above.

[0035] According to a fourth aspect of the embodiments of this application, the present specification provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the air conditioning control method as described in any of the preceding claims.

[0036] According to a fifth aspect of the embodiments of this application, this specification provides a computer program product or computer program, the computer program product including a computer program stored in a computer-readable storage medium; a processor of a computer device reads the computer program from the computer-readable storage medium, and when the processor executes the computer program, it implements the air conditioning control method as described in any of the preceding claims.

[0037] The technical effects achieved by the second to fifth aspects mentioned above are similar to those achieved by the corresponding technical means in the first aspect, and will not be repeated here. Attached Figure Description

[0038] Figure 1 This is a schematic flowchart of the air conditioning control method provided in the embodiments of this application; Figure 2 This is a schematic diagram of the structure of the air conditioning control system provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0039] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0040] It should be understood that "multiple" as mentioned herein refers to two or more. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B; "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. In addition, to facilitate a clear description of the technical solutions of the embodiments of this application, the terms "first," "second," etc., are used in the embodiments of this application to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first," "second," etc., do not limit the quantity or execution order, and the terms "first," "second," etc., do not necessarily imply that they are different.

[0041] Furthermore, the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, such that a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or apparatus.

[0042] As the background technology states, with the significant increase in demand for smart homes and personalized environmental control, users expect indoor environments to seamlessly adjust to their personal activities and locations. Existing methods mainly rely on mobile phone positioning, Bluetooth / wearable devices, or cameras for personnel identification and location awareness: the former requires users to carry the device, which may affect its effectiveness in scenarios with obstruction or disconnection; the latter raises privacy concerns and obstruction issues. Traditional temperature control is fixed on a room-by-room basis, rarely enabling continuous and automatic migration across rooms based on individual preferences. High-resolution millimeter-wave radar can passively and imperceptibly capture micro-doppler movements of the human body, such as breathing, heartbeat, and muscle tremors. It is robust to slight obstruction and can operate stably in low-light or nighttime environments, providing a new approach for non-wearable, low-invasive individual identification and continuous tracking. Based on this, it is possible to migrate an individual's personalized air conditioning parameters from the source room to the target room in real time, thereby improving comfort and energy efficiency and overcoming the shortcomings of existing technologies in terms of imperceptible identification, cross-room migration, and privacy protection.

[0043] Based on this, embodiments of this application provide an air conditioning control method. This method acquires millimeter-wave radar echo signals in real time, combines this with the biometric information and spatial distribution information of target personnel to generate migration response information, and adjusts first operating parameters according to this condition to complete the environmental parameter migration. The implementation steps and related details of this method will be described in detail below. Figure 1 The method shown includes the following processing steps.

[0044] S101: Based on the real-time detected human biofeedback signals, determine the biometric information and spatial distribution information of at least one target person in the first space. Acquire real-time radar echo signals, and determine the biometric information and spatial distribution information of the target personnel based on the real-time radar echo signals.

[0045] In practical implementation, high-resolution millimeter-wave radar equipment needs to be deployed first. Millimeter-wave radar equipment is typically installed on the ceiling or walls of a room, with its detection range covering the entire room area. The radar equipment captures dynamic information about target personnel by emitting millimeter-wave signals and receiving the reflected echo signals. The radar echo signal acquisition frequency should be set to a standard value that meets real-time requirements, such as more than 100 times per second, to ensure data continuity and accuracy. Data transmission between the radar equipment and the central processing unit is conducted via wired or wireless communication. The central processing unit is responsible for analyzing and processing the received radar echo signals.

[0046] In terms of system composition, the millimeter-wave sensing unit can employ a 77 GHz (or 60–79 GHz) FMCW millimeter-wave radar or a phased array radar, supporting large bandwidth (e.g., B = 4 GHz) and sufficient sampling and frame rates to provide three-dimensional echo information of range, velocity, and angle, and supporting multi-channel (MIMO) to form angle resolution. The signal preprocessing module filters, denoises, and performs time-frequency transformation on the raw echo signals acquired by the millimeter-wave radar, outputting the target's motion characteristics and micro-Doppler characteristics. The target detection and clustering module uses the CFAR method to identify real targets, and then uses a clustering algorithm (such as DBSCAN) to separate the echoes of different targets according to angle, range, and velocity characteristics, obtaining an independent echo set (ROI) corresponding to each target.

[0047] After acquiring real-time radar echo signals, the first step is to extract the biometric information of the target personnel. This process includes time-frequency analysis of the echo signals to separate the target personnel's respiratory rate, heart rate, and limb micro-movement features. These features constitute the core of the biometric information. The extraction of respiratory rate and heart rate can be achieved using algorithms such as Short-Time Fourier Transform (STFT) or Wavelet Transform (WFT). Specifically, the micro-Doppler extraction module performs STFT or CWT on the target's complex envelope to obtain a spectrogram or scalogram, and extracts the amplitude envelope and phase changes for subsequent feature calculations. Limb micro-movement features are obtained by analyzing the Doppler frequency shift changes in the echo signals. After extracting the above features, the target personnel's identity identifier is further constructed. The identity identifier can be stored in the form of a feature vector, where each dimension corresponds to a specific biometric value. To improve recognition accuracy, a machine learning model can be introduced to classify and train the feature vectors, thereby improving the accuracy of the identity identifier.

[0048] Next, it is necessary to determine the spatial distribution information of the target personnel. This spatial distribution information includes the target personnel's spatial position, spatial angle, direction of movement, and speed. The spatial position and spatial angle are calculated based on the phase difference and signal strength distribution in the radar echo signal. The radar equipment contains multiple antenna arrays; by comparing the phase difference of the signals received by different antennas, the position coordinates of the target personnel relative to the radar equipment can be calculated. The signal strength distribution is used to assist in determining the specific angle of the target personnel. The direction of movement and speed are calculated based on the changes in the target personnel's position over a continuous time period. By recording the target's position coordinates at multiple time points and performing differential operations on them, the direction of movement and speed of the target personnel can be obtained.

[0049] During the deployment and system calibration phase, coverage simulation is performed based on the room layout. It is recommended to place at least one pair of opposing or lateral radars at each doorway, with nodes synchronized via Ethernet and clock synchronization (PTP / NTP + PPS). Initial calibration is performed: ranging calibration (aligning with the ranging target), angle and array calibration (calibrating array phase), and clock deviation correction. During the data acquisition and synchronization phase, I / Q data from each receiving channel is continuously acquired, ensuring the frame rate and sampling rate cover the biological micro-motion bandwidth. The frame rate is recommended to be no less than 10–50 Hz; the number of distance sampling points Nr should meet the required distance resolution (ΔR is determined by the bandwidth B). In the preprocessing phase, the raw I / Q data is converted to the range-Doppler-angle domain, static clutter is removed, and candidate detection maps are generated. In the target segmentation and ROI extraction phase, CFAR detection points are clustered (DBSCAN / k-means or connected components), and a clustering space is constructed using range-Doppler-angle features. For each cluster, neighborhood samples are extracted from the original complex envelope to form the target-level complex envelope temporal sequence. In the micro-Doppler time-frequency extraction stage, the complex envelope is bandpass filtered (0.05–10 Hz), and then STFT (window length 256–1024, window shift 50%) is performed to obtain a spectrogram; or CWT (Morlet) is used to obtain a scalogram. The phase sequence is unwrapped and phase differencing is performed to enhance the micro-motion components. Peak tracking and autocorrelation can be used to estimate the dominant frequencies of respiration and heartbeat. The output includes time-frequency plots, amplitude envelope curves, phase change curves, and estimated fundamental frequencies (respiration, heartbeat) and their confidence indices. In the feature construction and quality scoring stage, the frequency band energy proportion, peak frequency, spectral entropy, MFCC class spectral envelope, time-domain autocorrelation peak value, phase stability index, and AoA distribution statistics are calculated; the features are standardized and reduced to 64–256 dimensions using PCA or UMAP; SNR and stability score are calculated for each sample, and samples below the threshold are marked as low quality and discarded or downweighted. The feature vector sequence and quality score for each frame or window are output for input to the recognition model. During the model training and deployment phase, the model architecture adopts 2D-CNN (time-frequency graph) combined with LSTM or Transformer (time series). Based on the feature sequence, a model that can distinguish individuals is trained and deployed to edge devices for real-time inference.

[0050] S102: Based on biometric information and spatial distribution information, when a target person moves from the first space to the second space, generate migration response information.

[0051] In practice, after acquiring biometric and spatial distribution information, the next step is to determine whether the triggering conditions for environmental parameter migration are met. This process requires analysis of the target person's heart rate cycle, movement direction, and speed. The heart rate cycle reflects the target person's physiological state; significant fluctuations in the heart rate cycle may indicate that the target person is engaged in strenuous exercise or is under stress. In this case, the system will focus on the target person's movement behavior. If the system detects that the target person's movement direction is towards the room's threshold area and their movement speed exceeds a preset threshold, it determines that the target person has entered the threshold area. The threshold area refers to a specific area near the room's exit, and its range can be set according to the actual scenario.

[0052] Once the target person is confirmed to have entered the threshold area, the system further analyzes its real-time radar echo signal to determine its movement trajectory and movement confidence. The movement trajectory is calculated based on a sequence of position coordinates over a continuous time period, while the movement confidence is derived by statistically analyzing the stability of the target person's movement trajectory. During the multi-radar data association and migration determination phase, each node maintains a short-term trajectory and periodically reports candidates (position, embedding, confidence). The edge fusion center performs data association based on the time window: constructing a cost matrix (position difference + embedding distance + ID confidence penalty), matching using the Hungarian algorithm; smoothing the trajectory using Kalman filtering or particle filtering and predicting the door crossing time. A specific determination logic is set in the threshold area: if the same embedding or high similarity appears in two adjacent nodes in chronological order and the position crosses the threshold, the migration is marked as started or ended. If the movement confidence is higher than a preset threshold, the target person is determined to have completed cross-room movement.

[0053] S103: In response to migration response information, control the second air conditioner in the second space to operate with the first operating parameters, where the first operating parameters are the operating parameters of the first air conditioner when the target person is in the first space.

[0054] In practice, after confirming that the target personnel have completed inter-room movement, the system generates migration response information. This information includes the source room's temperature, wind speed, and wind direction settings. These parameters are preset by the user and stored in the system database. The system retrieves the corresponding primary operating parameters from the database based on the target personnel's identification and incorporates them as part of the migration response information. Simultaneously, the system also records the target personnel's environmental preferences within the source room for subsequent adjustments.

[0055] After generating migration response information, the system needs to assess the biometric stability and spatial distribution stability of the target personnel to calculate migration confidence. Biometric stability is measured by analyzing the range of heart rate fluctuations, while spatial distribution stability is measured by analyzing the magnitude of location changes. Specifically, the system calculates the standard deviation of heart rate over a continuous time period as the heart rate fluctuation range and the variance of location coordinates as the location fluctuation range. During the control decision and smooth execution phase, migration confidence (including ID confidence, trajectory coherence, and node consistency) is calculated using a threshold triggering strategy (e.g., 0.9). Based on these two indicators, the system uses the following formula for calculation: ; in, This represents the migration confidence level. This indicates the range of fluctuation of the aforementioned biological characteristics. This indicates the range of spatial distribution fluctuations. and These are the weighting coefficients.

[0056] The weighting coefficients can be adjusted according to the actual application scenario to balance the impact of biometrics and spatial distribution on migration confidence. The final calculated migration confidence is used to verify the effectiveness of the migration response information.

[0057] When the migration confidence level reaches a preset threshold, the system generates real-time control commands and sends them to the environmental control equipment in the target room. These real-time control commands include temperature, wind speed, and wind direction adjustments. These commands are generated by the system based on migration response information and the environmental preferences of the target personnel. Upon receiving the commands, the environmental control equipment immediately executes the corresponding operations to adjust the environmental parameters in the target room. To ensure the accuracy and comfort of the environmental parameter adjustments, the system also needs to analyze the obstacle distribution within the target room. This obstacle distribution analysis is based on the static echo characteristics in radar echo signals. Static echo characteristics reflect the presence and characteristics of stationary objects within the room. The system calculates the location and volume of obstacles by extracting static echo characteristics and incorporates them into the obstacle distribution information.

[0058] Based on obstacle distribution information, the system adjusts the operating mode of environmental control equipment in the target room. For example, when an obstacle is located in front of an air vent, the system adjusts the angle of the air deflector to avoid the obstacle's impact on airflow. Furthermore, the system adjusts the airflow direction according to obstacle distribution to ensure even airflow coverage of the target room. After adjusting the operating mode, the system optimizes the distribution of environmental parameters in the target room using real-time control commands. The optimization process includes determining the initial environmental parameter distribution, adjusting the environmental parameter distribution boundaries, and generating the optimized environmental parameter distribution. The initial environmental parameter distribution is directly determined by real-time control commands, while the adjustment of the environmental parameter distribution boundaries is based on obstacle distribution information. By avoiding the impact of obstacles on the propagation of environmental parameters, the system generates an optimized environmental parameter distribution, ensuring that target personnel can quickly perceive environmental changes that match their preferences.

[0059] In an example of an application scenario, user A sets the air conditioner in the living room to 24°C, low fan speed, and downward airflow. A gets up and goes to the bedroom. The system continuously observes and correlates data via the doorway radar. The system recognizes the ID and the migration confidence score reaching 0.95, triggering a migration. The bedroom air conditioner receives a smooth control command and smoothly adjusts the temperature from 26°C to 24°C within 10 minutes, adjusting the fan speed and direction to match A's preference. If A further fine-tunes the temperature in the bedroom, this adjustment will be used as feedback to update A's preference template.

[0060] Throughout the process, the system dynamically adjusts its primary operating parameters to meet the needs of the target individuals by continuously monitoring their biometric and spatial distribution information. For example, after a target individual has stayed in the target room for a period of time, the system reassesses the stability of their biometrics and spatial distribution and adjusts the environmental parameters accordingly. This dynamic adjustment mechanism ensures the intelligence level of the environmental control system and the user experience.

[0061] To further enhance the system's adaptability, a multi-radar collaborative working mode can be introduced. In this mode, multiple millimeter-wave radar devices are distributed across different rooms and share data and perform collaborative analysis through a central processing unit. This mode effectively addresses the limited coverage of a single radar device and improves the accuracy of detecting personnel movement across rooms. Furthermore, the multi-radar collaborative mode can enhance the reliability of biometric and spatial distribution information through cross-validation, thereby further improving the overall system performance.

[0062] In practical deployment, the system also needs to consider integration with other smart home devices. For example, the environmental control system can be linked with the smart lighting system to automatically adjust the brightness and color temperature of the lights to match the preferences of the target person entering the room. Furthermore, the system can be integrated with a voice assistant, allowing users to adjust environmental parameters or query the current environmental status via voice commands. This integration not only enhances the system's functionality but also strengthens the user's interactive experience.

[0063] To ensure the long-term stable operation of the system, a robust fault detection and recovery mechanism is also required. For example, when a radar device malfunctions, the system will automatically switch to backup equipment or adjust the operating mode of other equipment to compensate for the functional deficiencies of the faulty device. Furthermore, the system will periodically perform self-checks on the radar equipment and generate maintenance reports to promptly identify potential problems. This mechanism can effectively reduce the risk of system failure and improve its reliability.

[0064] Throughout the implementation process, all data collection, processing, and transmission must adhere to strict security protocols to protect user privacy. For example, the storage and transmission of radar echo signals should employ encryption technology to prevent data leakage. Furthermore, the system must provide user access control functionality to ensure that only authorized users can access and modify primary operating parameters. These security measures not only comply with relevant laws and regulations but also enhance user trust in the system.

[0065] In one example, the air conditioning control method of the present invention can be widely applied to various scenarios such as homes, offices, and hotels. For instance, in a home setting, the present invention can enable personalized air conditioning parameter migration for family members in different rooms, improving their comfort. In an office setting, the present invention can enable personalized air conditioning parameter migration for employees in different office areas, improving their work efficiency. In a hotel setting, the present invention can enable personalized air conditioning parameter migration for guests in different rooms, enhancing their stay experience.

[0066] The air conditioning control method of this invention achieves seamless identification of target personnel by utilizing radar echo signals and determines their cross-room movement behavior based on their movement trends, thereby generating migration response information. After the target personnel enter the second space, personalized air conditioning parameters from the first space are migrated to the second space, ensuring consistent comfort and energy efficiency for the target personnel in different spaces. This process requires no additional equipment from the user, avoids the impact of obstructions or disconnections, and solves the problem of traditional temperature control systems being unable to migrate personalized parameters across rooms, thus improving the intelligence level of smart home environment regulation. To better enable those skilled in the art to fully understand and implement this invention, the specific implementation principle of this invention is further explained below with reference to a specific application scenario.

[0067] In a home setting, assuming the first space is the living room and the second space is the bedroom, when target person A is active in the living room, radar equipment continuously detects their respiratory rate, heart rate, and limb micro-movement characteristics, and calculates their spatial position and angle. The radar equipment is installed in the center of the ceiling in both the living room and bedroom, and its detection range covers the entire room area. The radar equipment acquires target person A's biofeedback signals by emitting millimeter-wave signals and receiving reflected signals. These signals are processed using short-time Fourier transform or wavelet transform algorithms to extract target person A's respiratory rate and heart rate. Simultaneously, by analyzing Doppler frequency shift changes, target person A's limb micro-movement characteristics are extracted. These characteristics collectively constitute target person A's biometric information.

[0068] Subsequently, the radar equipment calculates the spatial position and angle of target person A based on the phase difference and signal strength distribution in the echo signal. By recording the target's position coordinates at multiple time points and performing differential calculations, the direction and speed of movement of target person A are determined. These data collectively constitute the spatial distribution information of target person A. The radar equipment transmits this information to the central control system, which then generates migration response information based on the biometric information and spatial distribution information.

[0069] When person A moves from the living room to the bedroom, the central control system determines whether person A has entered the threshold area based on their heart rate cycle, direction of movement, and speed. The threshold area is defined as the transition zone between the living room and the bedroom. If person A enters the threshold area, the central control system further analyzes their real-time radar echo signal to determine their movement trajectory and movement confidence level. Through comprehensive analysis of the movement trajectory and confidence level, it determines whether person A has completed the inter-room movement. Once the inter-room movement is confirmed, the central control system generates migration response information based on the temperature setpoint, wind speed setpoint, and wind direction setpoint in the living room.

[0070] After generating the migration response information, the central control system combines the first operating parameters of the first air conditioner in the living room to generate a migration trigger command. This command includes the personalized air conditioning parameters for target person A in the living room, such as temperature setpoint, fan speed setpoint, and airflow direction setpoint. Subsequently, the central control system sends this command to the second air conditioner in the bedroom, causing it to operate according to the first operating parameters, thereby realizing the migration of personalized air conditioning parameters across rooms.

[0071] After target person A completes the inter-room movement, the central control system further analyzes the real-time radar echo signal, extracts the static echo characteristics within the bedroom, and determines the location and size of obstacles. Based on the obstacle distribution, the operating mode of the environmental control equipment in the bedroom is adjusted. For example, when an obstacle is located in front of the air vent, the angle of the air guide plate is adjusted to avoid the obstacle's impact on airflow. Simultaneously, the airflow direction is adjusted according to the obstacle distribution to ensure that airflow can evenly cover the entire bedroom.

[0072] Specifically, the central control system analyzes real-time radar echo signals to extract static echo characteristics within the bedroom. These characteristics reflect the presence and properties of fixed objects in the room. Based on these static echo characteristics, the system determines the specific location and volume of obstacles and incorporates them into the obstacle distribution data. Upon receiving real-time control commands, the central control system first determines the initial environmental parameter distribution within the bedroom. Subsequently, combining the obstacle distribution data, it adjusts the environmental parameter distribution boundaries to avoid the impact of obstacles on airflow. Finally, based on the adjusted environmental parameter distribution boundaries and the initial environmental parameter distribution, it generates an optimized environmental parameter distribution to ensure that airflow can uniformly cover the entire bedroom.

[0073] Furthermore, in practical applications, the installation location and detection range of radar equipment need to be adjusted according to the specific layout of the room. For example, in a larger room, multiple radar devices can be installed to ensure that the detection range covers the entire room area. Simultaneously, the signal processing algorithms of the radar equipment need to be optimized according to different application scenarios to improve the accuracy of target personnel identification and the reliability of movement trend judgment. The data processing capabilities of the central control system also need to be expanded according to actual needs to support the simultaneous detection of multiple targets and their movement across rooms.

[0074] During implementation, communication between the radar equipment and the central control system utilizes a wireless or wired network connection to ensure real-time and stable data transmission. Similarly, communication between the central control system and the air conditioner also employs a wireless or wired network connection to ensure the timely transmission and execution of migration trigger commands. Furthermore, the central control system can be integrated with other smart home devices, such as lighting and curtain control systems, to achieve more intelligent home environment adjustment.

[0075] In practical deployment, the system also needs to consider integration with other smart home devices. For example, the environmental control system can be linked with the smart lighting system to automatically adjust the brightness and color temperature of the lights to match the preferences of the target person when they enter the bedroom. Furthermore, the system can be integrated with a voice assistant, allowing users to adjust environmental parameters or query the current environmental status via voice commands. This integration not only enhances the system's functionality but also strengthens the user's interactive experience.

[0076] This application also provides an air conditioning control system, such as... Figure 2 As shown, it includes: The signal processing module 201 is used to determine the biometric information and spatial distribution information of at least one target person in the first space based on the real-time detected human biofeedback signals. The biometric information is used to characterize the identity of the target person, and the spatial distribution information characterizes the movement trend of the target person. The migration triggering module 202 is used to generate migration response information when it determines that a target person has moved from the first space to the second space based on biometric information and spatial distribution information. Processing module 203 is used to respond to migration response information and control the second air conditioner in the second space to operate with first operating parameters. The first operating parameters are the operating parameters of the first air conditioner when the target person is in the first space.

[0077] This application also provides a computer program product, which includes computer program instructions that, when executed by a processor, cause the processor to perform the steps of the air conditioning control method according to various embodiments of this specification as described in the "Exemplary Methods" section above.

[0078] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this specification. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages.

[0079] This application also provides a computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor of the steps in the air conditioning control method according to various embodiments of this specification as described in the "Exemplary Methods" section above.

[0080] This application also provides an electronic device, including a memory and a processor. The memory stores an air conditioning control method, and the processor is used to employ the air conditioning control method described above when executing the air conditioning control method.

[0081] Specifically, such as Figure 3As shown, the electronic device includes a processor 100, at least one communication bus 200, a user interface 300, at least one external communication interface 400, and a memory 500. The communication bus 200 is configured to enable communication between these components. The user interface 300 may include a display screen, and the external communication interface 400 may include standard wired and wireless interfaces. The memory 500 stores an air conditioning control method. The processor 100 is used to employ the air conditioning control method stored in the memory 500 when executing the aforementioned method.

[0082] The descriptions of the above computer program products, computer-readable storage media, and electronic devices are similar to those of the above method embodiments, and have similar beneficial effects. For any technical details not disclosed in the computer program products, computer-readable storage media, and electronic devices of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0083] The sequence numbers or order of description of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0084] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0085] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0086] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0087] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer, or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., digital versatile disc (DVD)), or a semiconductor medium (e.g., solid state disk (SSD)). It is worth noting that the computer-readable storage medium mentioned in the embodiments of this application can be a non-volatile storage medium; in other words, it can be a non-transient storage medium. It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals involved in the embodiments of this application are all authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the scene data of the current frame in the 3D virtual scene involved in the embodiments of this application, the client's device information, and the scene interaction information are all obtained with full authorization.

[0088] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. An air conditioning control method, characterized in that, The method includes: Based on real-time detected human biofeedback signals, the biometric information and spatial distribution information of at least one target person in the first space are determined. The biometric information is used to characterize the identity of the target person, and the spatial distribution information characterizes the movement trend of the target person. Based on the biometric information and the spatial distribution information, when the target person moves from the first space to the second space, migration response information is generated; In response to the migration response information, the second air conditioner in the second space is controlled to operate with a first operating parameter, which is the operating parameter of the first air conditioner when the target person is in the first space.

2. The method according to claim 1, characterized in that, The human biofeedback signal is determined by acquiring real-time radar echo signals. Therefore, determining the biometric information and spatial distribution information of at least one target person in the first space based on the real-time detected human biofeedback signal includes: Analyze the real-time radar echo signal to extract the target person's respiratory rate, heart rate, and limb micro-movement characteristics; The identity of the target person is determined based on the respiratory rate, the heart rate, and the micro-movement characteristics of the limbs; The identity identifier is incorporated into the biometric information; Based on the real-time radar echo signal, determine the spatial position and spatial angle of the target personnel; Based on the spatial location and the spatial angle, determine the target person's movement direction and speed; The direction of movement and the speed of movement are incorporated into the spatial distribution information.

3. The method according to claim 2, characterized in that, The biometric information includes heart rate cycle, and the first operating parameters include temperature setpoint, wind speed setpoint, and wind direction setpoint. When the target person moves from the first space to the second space based on the biometric information and the spatial distribution information, migration response information is generated, including: Based on the heart rate cycle, the direction of movement, and the speed of movement, it is determined whether the target person has entered the threshold area, which is the passageway between the first space and the second space. If the target person enters the threshold area, the movement trajectory and movement confidence level are determined based on the real-time radar echo signal. Based on the movement trajectory and the movement confidence level, determine whether the target person has completed the inter-room movement; If the inter-room movement is completed, migration response information is generated based on the temperature setting, the wind speed setting, and the wind direction setting.

4. The method according to claim 1, characterized in that, The step of controlling the second air conditioner in the second space to operate with the first operating parameters in response to the migration response information includes: Based on the migration response information and the first operating parameters of the first air conditioner in the first space, a migration trigger command is generated, wherein the first operating parameters are the operating parameters of the first air conditioner when the target person is in the first space; According to the migration trigger command, the second air conditioner in the second space is controlled to operate, so that the second air conditioner operates with the first operating parameters.

5. The method according to claim 4, characterized in that, After determining, based on the biometric information and the spatial distribution information, when the target person moves from the first space to the second space, and generating migration response information, the method further includes: The distribution of obstacles in the target room is determined based on the real-time radar echo signal; Adjust the operating mode of the environmental control equipment in the target room according to the distribution of the obstacles; Based on the operating mode and the real-time control commands, optimize the distribution of environmental parameters in the target room.

6. The method according to claim 5, characterized in that, Determining the distribution of obstacles in the target room based on the real-time radar echo signal includes: Based on the real-time radar echo signal, extract the static echo characteristics within the target room; Based on the static echo characteristics, determine the location and volume of obstacles in the target room; The location and volume of the obstacle are included in the obstacle distribution.

7. The method according to claim 5, characterized in that, The step of optimizing the distribution of environmental parameters in the target room according to the operating mode and the real-time control commands includes: The initial environmental parameter distribution within the target room is determined based on the real-time control command. Adjust the environmental parameter distribution boundary within the target room based on the obstacle distribution; Based on the environmental parameter distribution boundary and the initial environmental parameter distribution, an optimized environmental parameter distribution is generated.

8. The method according to claim 2, characterized in that, The step of determining the biometric information and spatial distribution information of at least one target person in the first space based on real-time detected human biofeedback signals further includes: The respiratory rate and heart rate in the real-time radar echo signal are extracted using short-time Fourier transform or wavelet transform algorithms. By analyzing the Doppler frequency shift changes in the real-time radar echo signal, the micro-movement features of the target person's limbs are extracted.

9. The method according to claim 2, characterized in that, Based on real-time detected human biofeedback signals, determine the spatial distribution information of at least one target person in the first space, including: Based on the phase difference and signal strength distribution in the real-time radar echo signal, the spatial position and spatial angle of the target personnel are calculated. By recording the target location coordinates at multiple time points and performing differential calculations on them, the movement direction and speed of the target personnel can be determined.

10. The method according to claim 5, characterized in that, The step of adjusting the operating mode of the environmental control equipment in the target room according to the distribution of obstacles includes: When an obstacle is located in front of the air outlet, adjust the angle of the air guide plate to avoid the impact of the obstacle on the airflow. Adjust the air supply direction according to the distribution of obstacles to ensure that the airflow can evenly cover the target room.

11. An air conditioning control system, characterized in that, include: The signal processing module is used to determine the biometric information and spatial distribution information of at least one target person in the first space based on the real-time detected human biofeedback signals. The biometric information is used to characterize the identity of the target person, and the spatial distribution information characterizes the movement trend of the target person. The migration triggering module is used to generate migration response information when the target person moves from the first space to the second space based on the biometric information and the spatial distribution information. The processing module is configured to respond to the migration response information and control the second air conditioner in the second space to operate with a first operating parameter, wherein the first operating parameter is the operating parameter of the first air conditioner when the target person is located in the first space.

12. An electronic device, characterized in that, include: The system includes a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the air conditioning control method according to any one of claims 1 to 10.

Images