A multi-zone monitoring and dehumidification frequency conversion control system based on indoor swimming pools

Abstract

The present invention relates to a multi-zone monitoring and dehumidification variable frequency control system based on an indoor swimming pool. The system uses an interpolation method to process the temperature and humidity of each sub-zone to obtain the spatial distribution of temperature and humidity within the swimming pool. Temperature and humidity targets are set for each sub-zone and then adjusted based on the targets. A high-definition camera is used to capture the dynamic distribution of people in the swimming pool after the temperature and humidity adjustments are made. The suitability of each sub-zone is determined based on the dynamic distribution of people, and the overall suitable temperature and humidity within the swimming pool is accumulated to obtain the desired temperature and humidity within the swimming pool. Temperature and humidity control is then performed based on the relationship between the variable frequency parameters and the overall suitable temperature and humidity. This invention addresses the existing difficulties in obtaining the spatial distribution of temperature and humidity within the swimming pool for temperature and humidity adjustment in each zone, as well as the difficulty in determining the overall suitable temperature and humidity within the swimming pool based on user preferences, resulting in inaccurate temperature and humidity control.

Description

Technical Field

[0001] The invention belongs to the technical field of indoor dehumidification, and relates to a multi-zone monitoring and dehumidification frequency conversion control system based on an indoor swimming pool. Background Art

[0002] Indoor swimming pools are increasingly popular as a popular place for leisure and exercise in modern life. However, their unique environmental characteristics present numerous challenges, particularly the precise control of humidity and temperature. Due to the constant evaporation of the pool water surface, indoor air humidity can easily remain high. Furthermore, different areas, such as the pool perimeter, spectator areas, and locker rooms, have varying comfort requirements for temperature and humidity. Traditional control methods often struggle to precisely regulate each area simultaneously, leading to a series of drawbacks, including wasted energy, poor environmental comfort, and susceptible equipment damage due to humidity.

[0003] Existing technologies make it difficult to determine the spatial distribution of temperature and humidity within a swimming pool and adjust the temperature and humidity in each area. Furthermore, existing technologies make it difficult to determine the overall comfort index of the swimming pool's temperature and humidity based on user preferences, resulting in inaccurate temperature and humidity control. Summary of the Invention

[0004] The present invention provides a multi-zone monitoring and dehumidification frequency conversion control system based on an indoor swimming pool. The system aims to use the interpolation method to process the temperature and humidity of each sub-zone to obtain the spatial distribution of temperature and humidity in the swimming pool; set the temperature and humidity targets for each sub-zone for adjustment; and simultaneously use a high-definition camera to obtain the dynamic distribution of people in the swimming pool after the temperature and humidity are adjusted to characterize people's preferences for temperature and humidity, so as to accurately control the temperature and humidity in the swimming pool.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] The present application provides a multi-zone monitoring and dehumidification variable frequency control system based on an indoor swimming pool, comprising a variable frequency wind module, a refrigerant module, and an electronic control module, wherein the variable frequency wind module, the refrigerant module, and the electronic control module are communicatively connected, wherein:

[0007] The variable frequency wind module consists of an anti-cold bridge box, a variable frequency centrifugal supply fan, a variable frequency centrifugal return fan and an air valve, which is used to draw indoor air into the dehumidification heat pump box through the air duct and send the treated air back to the room through the supply fan;

[0008] The refrigerant module consists of a variable frequency compressor, an evaporator, a reheat condenser, an outdoor condenser, a titanium bulb, a liquid reservoir, an electronic expansion valve, a drying filter and a copper tube, and is used to dehumidify and cool the indoor air or dehumidify and heat it;

[0009] The electronic control module consists of a control panel, a main control board, a variable frequency drive module, several contactors, and several temperature and humidity sensors. It is used to automatically control the variable frequency centrifugal return air fan and variable frequency compressor according to the temperature and humidity in different areas of the swimming pool, including:

[0010] Divide the indoor area of ​​the swimming pool into several sub-areas, and use temperature and humidity sensors to monitor the temperature and humidity of each sub-area;

[0011] The temperature and humidity of each sub-area are processed using the interpolation method to obtain the spatial distribution of temperature and humidity in the swimming pool;

[0012] Setting temperature and humidity targets for each sub-area, and adjusting the temperature and humidity for each sub-area according to the temperature and humidity targets;

[0013] Using a high-definition camera to obtain the dynamic distribution of people in the swimming pool after adjusting the temperature and humidity, and determining the suitability of each sub-area based on the dynamic distribution of people;

[0014] Calculate the overall suitable temperature and humidity in the swimming pool based on the suitability of each sub-area;

[0015] quantifying the response relationship between the variable frequency parameters of the variable frequency centrifugal return fan and the variable frequency compressor and the overall suitable temperature and humidity through a generalized additive model;

[0016] According to the response relationship, the frequency conversion parameters are controlled so that the overall suitable temperature and humidity in the swimming pool room are maintained above a preset threshold.

[0017] Furthermore, the interpolation method is calculated as follows:

[0018]

[0019]

[0020] Where, T p represents the temperature and humidity at a certain point p in the indoor space of the swimming pool; T i represents the temperature and humidity of the i-th sub-area, n is the number of sub-areas; w i represents the distance weight of the i-th sub-region; D p Represents the Euclidean distance from point p to the monitoring point in the i-th sub-region.

[0021] Furthermore, the method of using a high-definition camera to obtain the dynamic distribution of people in the swimming pool after adjusting the temperature and humidity, and determining the suitability of each sub-area according to the dynamic distribution of people, includes the following steps:

[0022] Real-time image acquisition: HD cameras collect image information of each sub-area of ​​the indoor swimming pool according to pre-configured parameters, convert the actual scene into digital image signals, and transmit the collected image data to the back-end image processing server via wired or wireless communication;

[0023] Preprocessing the image data, including image format unification and normalization, as well as noise removal and enhancement processing;

[0024] Person detection and recognition: Using computer vision technology, we extract person features from pre-processed images and output the location information of people in each sub-region of the image.

[0025] Person tracking and trajectory construction: Based on the results of person detection, the person tracking algorithm is used to associate the same person in multiple consecutive frames of images and construct a continuous person movement trajectory;

[0026] Extracting dynamic distribution features of people: Extracting key indicators that reflect the dynamic distribution of people in each sub-area from the constructed movement trajectories and related location and time information. These key indicators are then counted and organized to form a dataset of dynamic distribution of people that changes over time. These key indicators include the real-time number of people in each sub-area, the average length of stay, the frequency of entry and exit, and the degree of concentration of people.

[0027] Determination of suitability of sub-regions: cluster analysis method is used to divide the key indicator data set into several clusters; the suitability levels are numbered according to the numerical range of the key indicators of the clusters; and the suitability level of each sub-region is determined.

[0028] Furthermore, the personnel feature extraction includes extracting edge features, texture features and high-level semantic features of the personnel based on a deep learning model.

[0029] Furthermore, the personnel tracking algorithm is configured as a multi-target tracking method based on Kalman filtering combined with the Hungarian algorithm or a DeepSORT algorithm based on deep learning.

[0030] Furthermore, the cluster analysis method is configured as a K-means clustering method, including: data preparation, collecting and organizing dynamic key indicator data of personnel in each sub-area, and performing standardization processing; determining the number of clusters; randomly selecting initial cluster centers, iteratively updating cluster centers and allocating samples until convergence, and finally completing cluster analysis.

[0031] Furthermore, the overall suitable temperature and humidity are calculated as follows:

[0032] S z =S1+S2+...+S n ,

[0033] Where S z Indicates the overall suitable temperature and humidity; S1, S2, ..., S n is the suitability of each sub-region, and n is the number of sub-regions.

[0034] Furthermore, the generalized additive model includes the following construction steps:

[0035] Determine model parameters: Determine model parameters based on data characteristics. The model parameters include a distribution family form, a smoothing function, and a number of nodes. The distribution family form is configured as a Poisson distribution, the smoothing function is configured as a cubic spline function, and the number of nodes is configured as half of the number of samples.

[0036] Model optimization: Use the test set to evaluate the model's prediction results for fitness, and optimize the model parameters based on the prediction results until they are within the preset error range.

[0037] Furthermore, controlling the frequency conversion parameters according to the response relationship so that the overall suitable temperature and humidity in the swimming pool room are maintained above a preset threshold value includes the following steps:

[0038] Visualize the response relationship between the variable frequency parameters and the overall suitable temperature and humidity by fitting the response relationship curve of the generalized additive model

[0039] When the overall suitable temperature and humidity in the swimming pool room is lower than a preset threshold, determining abnormal frequency conversion parameters that are not within the overall suitable temperature and humidity threshold range in the response relationship curve;

[0040] Adjust the abnormal frequency conversion parameters until the overall suitable temperature and humidity remain above the preset threshold.

[0041] Beneficial effects of the present invention:

[0042] The temperature and humidity of each sub-area are processed using an interpolation method to obtain the spatial distribution of temperature and humidity within the swimming pool. A temperature and humidity target is set for each sub-area and then adjusted based on the target. A high-definition camera is used to capture the dynamic distribution of people within the swimming pool after the adjustment. The suitability of each sub-area is determined based on this dynamic distribution, and the overall suitable temperature and humidity within the swimming pool is accumulated to obtain the desired temperature and humidity. Temperature and humidity control is then performed based on the relationship between the frequency conversion parameters and the overall suitable temperature and humidity. This invention addresses the existing difficulties in obtaining the spatial distribution of temperature and humidity within the swimming pool for temperature and humidity adjustment in each area, as well as the difficulty in determining the overall suitable temperature and humidity within the swimming pool based on user preferences, resulting in inaccurate temperature and humidity control. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] To facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0044] Figure 1 This is a structural diagram of a multi-zone monitoring and dehumidification frequency conversion control system based on an indoor swimming pool in the present invention.

[0045] Figure 2 This is a flow chart of automatically controlling a variable frequency centrifugal return air fan and a variable frequency compressor according to the temperature and humidity in different areas of a swimming pool in one embodiment of the present invention.

[0046] Figure 3 This is a flow chart of using a high-definition camera to obtain the dynamic distribution of people in a swimming pool after adjusting the temperature and humidity in one embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to further illustrate the technical means and effects adopted by the present invention to achieve the predetermined purpose of the invention, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0048] See also Figure 1-Figure 3 The present application provides a multi-zone monitoring and dehumidification variable frequency control system based on an indoor swimming pool, including a variable frequency wind module, a refrigerant module and an electronic control module, wherein the variable frequency wind module, the refrigerant module and the electronic control module are communicatively connected, wherein:

[0049] The variable frequency wind module consists of an anti-cold bridge box, a variable frequency centrifugal supply fan, a variable frequency centrifugal return fan and an air valve, which is used to draw indoor air into the dehumidification heat pump box through the air duct and send the treated air back to the room through the supply fan;

[0050] In this embodiment, the core components of the variable-frequency air module include an anti-cold bridge housing, a variable-frequency centrifugal supply blower, a variable-frequency centrifugal return blower, and an air damper. The anti-cold bridge housing effectively prevents condensation and cold bridges caused by large temperature differences between inside and outside, ensuring the proper operation of the entire module, minimizing energy loss, and creating a stable operating environment for the internal equipment.

[0051] The variable-frequency centrifugal supply and return fans are the "power engines" of air flow. The return fan draws air from various indoor locations into the dehumidification heat pump housing via ductwork. This allows the air to flow continuously into the core area of ​​the system, paving the way for subsequent dehumidification, temperature control, and other processes. After a series of meticulous treatments, such as dehumidification and cooling or heating, performed by the refrigerant module, the variable-frequency centrifugal supply fan begins to function, returning air that meets preset environmental requirements to the indoor environment. This ensures that each area of ​​the room maintains an appropriate temperature and humidity range, creating a comfortable environment for the indoor swimming pool.

[0052] The presence of the air valve further enhances the controllability of the entire air circulation system. By adjusting the opening of the air valve, the air volume and air flow direction in different areas can be flexibly controlled. Combined with the variable frequency function of the supply fan and return fan, according to the actual indoor temperature and humidity conditions and the usage requirements of different areas, the efficient circulation and reasonable distribution of air can be accurately achieved, so that the air environment of the entire indoor swimming pool is always kept in an ideal state.

[0053] The refrigerant module consists of a variable frequency compressor, an evaporator, a reheat condenser, an outdoor condenser, a titanium bulb, a liquid reservoir, an electronic expansion valve, a drying filter and a copper tube, and is used to dehumidify and cool the indoor air or dehumidify and heat it;

[0054] In this embodiment, the refrigerant module serves as the core functional unit and undertakes the key task of dehumidifying and cooling or dehumidifying and heating the indoor air. Its components include a variable frequency compressor, an evaporator, a reheat condenser, an outdoor condenser, a titanium bulb, a liquid reservoir, an electronic expansion valve, a drying filter and a copper tube. Through the complex and orderly synergy between the components, precise control of the entire thermal process is achieved.

[0055] As the power core of the refrigerant circulation system, the variable-frequency compressor dynamically adjusts its operating frequency based on the system's control instructions, thereby precisely regulating the refrigerant's pressure and flow, providing a continuous and variable driving force for the entire refrigerant cycle. From a thermodynamic perspective, changes in its operating frequency directly affect the refrigerant's state parameters, determining the intensity and efficiency of the subsequent heat exchange process. This enables the system to flexibly adapt its operating state based on real-time temperature and humidity data monitored in various areas of the indoor pool to meet diverse environmental regulation needs.

[0056] The evaporator plays a key role in the heat exchange process and is a crucial step in achieving dehumidification and cooling. Based on the principle of heat and mass transfer, the hot, humid air in the room exchanges heat with the low-temperature refrigerant within the evaporator. The air's heat is absorbed by the refrigerant, causing the air temperature to drop. Simultaneously, water vapor in the air condenses and precipitates after reaching the dew point on the low-temperature surface, completing the physical process of dehumidification, thereby reducing the air's moisture content and achieving the desired dehumidification and cooling effect.

[0057] The reheat condenser plays an indispensable role in specific operating conditions, where dehumidification and heating are required. Leveraging the heat carried by the high-temperature, high-pressure refrigerant discharged from the compressor, the reheat condenser transfers this heat to the dehumidified air through heat conduction, raising the air temperature to the desired range. This process cleverly achieves the coordinated regulation of dehumidification and heating, ensuring that indoor air maintains a comfortable temperature while reducing humidity.

[0058] The outdoor condenser is mainly responsible for maintaining the thermal balance of the entire refrigerant circulation system. By exchanging heat with the outdoor environment, it releases excess heat inside the system to the external environment, ensuring that the refrigerant can continue to maintain a stable thermodynamic state during the circulation process, ensuring the stable operation of the system and the orderly progress of each heat exchange process.

[0059] As a key component adapted to the special environment of indoor swimming pools, titanium bubbles, with their excellent corrosion resistance and good thermal conductivity, ensure a stable and efficient heat exchange process between the refrigerant and other media in specific links of the refrigerant circulation, providing a strong guarantee for the reliable operation of the entire system in high humidity environments.

[0060] The setting of the liquid receiver is intended to ensure sufficient supply of refrigerant under different working conditions. By storing a certain amount of refrigerant, it effectively avoids the problem of insufficient or excessive refrigerant caused by factors such as changes in system load, and maintains the stability and continuity of the refrigerant circulation system.

[0061] As a key component for precisely controlling the refrigerant flow, the electronic expansion valve is based on thermal control theory and, according to the real-time needs of the system, achieves subtle and precise control of the refrigerant flow by precisely adjusting its opening, thereby accurately regulating the degree of cooling or heating, laying the foundation for precise regulation of air temperature and humidity.

[0062] The filter drier plays an important role in maintaining the healthy operation of the entire refrigerant module. It effectively removes moisture, impurities, and possible tiny particles contained in the refrigerant through physical or chemical adsorption, preventing these substances from causing adverse phenomena such as ice blockage, pipeline corrosion, and blockage of throttling elements during the refrigerant circulation process, ensuring the normal operation of the refrigerant circulation system and the stable performance of each component.

[0063] Copper tubes, as the refrigerant delivery carrier, rely on their excellent thermal conductivity, good plasticity and high sealing properties to build a refrigerant circulation network that is tightly connected between the components, ensuring the smooth circulation of the refrigerant in the entire module, and enabling the heat exchange process between the components to be connected in an orderly manner, collaboratively completing the dehumidification and cooling or dehumidification and heating of the indoor air.

[0064] The electronic control module consists of a control panel, a main control board, a variable frequency drive module, several contactors and several temperature and humidity sensors, and is used to automatically control the variable frequency centrifugal return air fan and variable frequency compressor according to the temperature and humidity in different areas of the swimming pool;

[0065] In this embodiment, the electronic control module occupies the core control hub position. It integrates key components such as the control panel, main control board, variable frequency drive module, several contactors and several temperature and humidity sensors, and together constructs a highly intelligent and refined automatic control system. It is designed to accurately respond to temperature and humidity changes in different areas of the swimming pool, and then implement scientific and efficient automatic control of the variable frequency centrifugal return fan and variable frequency compressor to ensure that the indoor temperature and humidity always meet the preset ideal state and meet the heat and humidity regulation needs in complex environments.

[0066] As the key interface between the system and operators, the control panel is designed according to the principles of human-computer interaction engineering, featuring intuitiveness, ease of use, and versatility. It not only provides operators with a convenient operation window for accurately setting target parameter values ​​for temperature and humidity in each area of ​​the indoor swimming pool, but also displays real-time monitoring data for temperature and humidity in each area, as well as information on the operating status of the entire system. From the academic perspective of information visualization and interactive design, its interface layout, operational logic, and data presentation have all been carefully considered to ensure that users can efficiently and accurately complete operational tasks such as system parameter configuration, operation monitoring, and troubleshooting, thereby achieving seamless integration between humans and the control system and meeting diverse practical management needs.

[0067] The main control board, the core control unit of the electronic control module, deeply integrates theories and technologies from multiple disciplines, including control theory, signal processing, and computer science. It receives real-time environmental data from temperature and humidity sensors distributed throughout key areas of the indoor pool. These sensors, leveraging thermal and hygrometric principles and advanced sensing technology, accurately and reliably convert the physical quantities of temperature and humidity into corresponding electrical signals, which are then fed back to the main control board. The main control board then applies sophisticated algorithms to deeply process and analyze this massive, multi-source data. These algorithms are typically based on classical control theory (such as PID control and optimal control), modern intelligent control methods (such as fuzzy control and neural network control), and advanced data fusion techniques. By constructing rigorous mathematical models or sophisticated rule bases, they comprehensively consider numerous factors, including the instantaneous values, rates of change, spatiotemporal correlations, and overall environmental dynamics of each zone's temperature and humidity, to accurately determine both the overall indoor environmental state and subtle variations in local areas. Based on this comprehensive and in-depth analysis, the main control board generates precise control instructions in strict accordance with the preset optimization control strategy, providing clear action guidelines for subsequent actuators and driving the entire system to dynamically adjust towards the goal of maintaining a stable and comfortable indoor environment.

[0068] The variable frequency drive module plays a crucial role in the entire electronic control system, serving as the link between the main control board and the two core power components: the variable frequency centrifugal return air blower and the variable frequency compressor. Its operating mechanism is deeply rooted in power electronics and motor control theory. Based on precise control commands from the main control board, the variable frequency drive module utilizes advanced power electronics conversion technology to precisely convert the input power signal into different frequencies, transform the voltage, and modulate the waveform. This generates a drive signal tailored to the motor characteristics of the variable frequency centrifugal return air blower and the variable frequency compressor, and outputs it to the corresponding motor terminals, achieving highly precise linear control of motor speed and output power. From the perspective of electrical engineering and power transmission, this drive approach, based on variable frequency technology, enables flexible and precise adjustment of the equipment's operating state based on the actual heat and humidity load requirements of the environment. This effectively avoids the energy waste and limited adjustment accuracy associated with traditional fixed frequency devices under certain operating conditions, achieving energy-saving, efficient, and precise control of air circulation volume and refrigerant circulation intensity, laying a solid foundation for refined environmental regulation in indoor swimming pools.

[0069] As an indispensable electrical actuator in the electronic control module, the contactor plays a vital role in the circuit control of the entire system based on electromagnetic principles and electrical control theory. Based on instructions issued by the main control board, multiple contactors systematically implement on-off control of different circuit branches, strictly controlling the timing of the connection and disconnection of various electrical devices during system operation, ensuring the safety and stability of the entire electrical system and the orderly coordination between various components. In complex circuit topologies, the reliable operation of the contactor can effectively prevent circuit failures such as short circuits and overloads, while ensuring that different devices operate in a predetermined logical and temporal order, avoiding system anomalies caused by unreasonable electrical connections or equipment start-up and shutdown sequences, thereby providing solid electrical protection for the stable operation of the entire system.

[0070] The automatic control of the variable frequency centrifugal return fan and the variable frequency compressor according to the temperature and humidity in different areas of the swimming pool includes:

[0071] S1. Divide the indoor area of ​​the swimming pool into several sub-areas and use temperature and humidity sensors to monitor the temperature and humidity of each sub-area;

[0072] In this embodiment, the indoor swimming pool space is characterized by its diverse functions and complex environment. To achieve accurate temperature and humidity monitoring and subsequent effective control and adjustment, it must be divided into several sub-areas based on scientific and rational principles. From a spatial function perspective, the following functional areas can generally be divided according to different functional areas, such as the pool surface, spectator area, locker room, shower room, rest area, and equipment room. These areas have significant differences in temperature and humidity generation mechanisms, human comfort requirements, and overall environmental impact. For example, above the surface of the swimming pool, due to the continuous evaporation of water, a large amount of water vapor is released, the humidity is very easy to rise and fluctuate frequently, and the dehumidification requirements are relatively strict; the audience area is mainly concerned with the comfort of the human body during the viewing of activities, and the temperature and humidity need to be maintained in a range suitable for viewing and staying; the locker rooms and showers are frequently entered and exited, and clothing is changed. Humidity control is crucial to prevent bacterial growth and keep the air fresh; the rest area is more focused on creating a quiet and comfortable resting atmosphere, and the temperature and humidity must be in line with the physical needs of the human body in a relaxed state; although the equipment room does not directly serve personnel activities, the equipment in the room has specific requirements for the temperature and humidity environment to ensure its stable operation and extend its service life.

[0073] S2. Use the interpolation method to process the temperature and humidity of each sub-area to obtain the spatial distribution of temperature and humidity in the swimming pool;

[0074] Furthermore, the interpolation method is calculated as follows:

[0075]

[0076] Where, T p represents the temperature and humidity at a certain point p in the indoor space of the swimming pool; T i represents the temperature and humidity of the i-th sub-area, n is the number of sub-areas; w i represents the distance weight of the i-th sub-region; D p Represents the Euclidean distance from point p to the monitoring point in the i-th sub-region.

[0077] S3. Setting temperature and humidity targets for each sub-area, and adjusting the temperature and humidity for each sub-area according to the temperature and humidity targets;

[0078] In this embodiment, setting the temperature and humidity targets for each sub-area is an important step in achieving personalized environmental control. The setting of this target needs to comprehensively consider multiple factors such as human comfort, swimming pool operation requirements, and relevant environmental standards. According to the functional characteristics of different sub-areas, appropriate temperature and humidity ranges are determined respectively. For example, above the surface of the swimming pool, more emphasis may be placed on humidity control to avoid excessive accumulation of water vapor, while the locker room needs to take into account the temperature and humidity balance to prevent the breeding of bacteria. Subsequently, based on the set temperature and humidity targets, the system adjusts the temperature and humidity of each sub-area in a targeted manner, and generates corresponding control instructions through the main control board based on the built-in control algorithm to drive the variable frequency centrifugal return fan and variable frequency compressor and other equipment to work together to change the air circulation and refrigerant circulation status, so as to gradually achieve the temperature and humidity of each sub-area close to the target value, and meet the local environmental comfort and functional requirements.

[0079] S4. Using a high-definition camera to obtain the dynamic distribution of people in the swimming pool after adjusting the temperature and humidity, and determining the suitability of each sub-area based on the dynamic distribution of people;

[0080] In this embodiment, high-definition cameras are used to capture the dynamic distribution of people within the pool after temperature and humidity adjustments are adjusted. This information, used as a basis for determining the suitability of each sub-area, is a key component in achieving refined and user-friendly environmental control. With their high-precision imaging capabilities and wide viewing angle coverage, these cameras are carefully positioned at key locations throughout the indoor pool, ensuring comprehensive real-time image capture of every sub-area. These cameras continuously capture image information at a preset frame rate, and the resulting massive amounts of image data are then transmitted to a dedicated image processing system via wired or wireless transmission.

[0081] The image processing system leverages advanced computer vision technology for in-depth analysis. First, an object detection algorithm accurately identifies individuals within the image and distinguishes their locations within each sub-area. Next, a target tracking algorithm continuously tracks the movement of individuals, providing a clear understanding of their duration of stay, range of activity, and frequency of entry and exit within each sub-area over different time periods. Through this detailed analysis, a complete and real-time map of the dynamic distribution of indoor occupants is constructed.

[0082] The suitability of each sub-area is determined based on this dynamic distribution of people. In principle, people tend to gravitate toward areas with more favorable environmental conditions, such as temperature and humidity. Therefore, indicators like crowd density and length of stay can intuitively reflect the suitability of each sub-area. For example, in the audience area, if high-definition cameras detect a large gathering of people during a specific period, with most remaining for extended periods and few frequently moving around or changing seats due to discomfort, this indicates that the current temperature and humidity conditions in that sub-area meet human comfort requirements and are considered suitably high. Similarly, in the rest area, if people enter and exit in an orderly manner and generally enjoy a long rest period after entering, this also indicates that the temperature and humidity in that area create a comfortable and relaxing environment, indicating a good suitability. Conversely, if a sub-area is sparsely populated, or if people briefly stay and then quickly leave, frequently changing locations, this likely indicates that the temperature and humidity in that area are suboptimal, resulting in a relatively low suitability and requiring further optimization.

[0083] Furthermore, the method of using a high-definition camera to obtain the dynamic distribution of people in the swimming pool after adjusting the temperature and humidity, and determining the suitability of each sub-area according to the dynamic distribution of people, includes the following steps:

[0084] S41, real-time image acquisition:

[0085] During system operation, each high-definition camera continuously and stably captures image information from each sub-area of ​​the indoor pool according to pre-configured parameters, converting the actual scene into digital image signals, recording the images of people at different times and locations. Image continuity must be ensured during the acquisition process to avoid frame dropouts caused by equipment failures, network fluctuations, and other factors. Any missing frame could affect accurate assessment of occupant movement.

[0086] The collected image data is transmitted promptly and accurately to a back-end image processing server or control unit with appropriate processing capabilities via wired communication (e.g., using Ethernet cables to establish a stable local area network transmission, suitable for scenarios with long distances and high requirements for data transmission stability) or wireless communication (e.g., utilizing high-performance Wi-Fi networks, which facilitate flexible camera placement and avoid complex wiring issues, but require sufficient bandwidth and signal strength). During this process, network communication technologies such as data verification and retransmission mechanisms are used to ensure the integrity of the image data and prevent transmission errors, data loss, and other problems.

[0087] S42, image data preprocessing, including:

[0088] Image format unification and normalization: Because images captured by different cameras may vary in format (such as common JPEG and PNG), size (different pixel sizes), and color mode (RGB, grayscale, etc.), the received image data must first be uniformly processed. All images must be converted to a uniform format, size, and color mode to facilitate subsequent processing using a unified algorithm. For example, uniformly converting images to JPEG format at a specific resolution (such as 1920×1080 pixels) in RGB color mode ensures the standardization of the entire image dataset.

[0089] Noise Removal and Enhancement: Indoor lighting fluctuations, interference from electrical equipment, and other factors can cause image noise, affecting the accuracy of person detection. Appropriate filtering algorithms, such as Gaussian filtering for effective noise removal and median filtering for effective suppression of salt-and-pepper noise, are employed to reduce image noise interference and achieve clearer and smoother images. Image enhancement techniques, such as histogram equalization, are also employed to enhance image contrast and highlight the difference between the subject and the background, facilitating accurate identification of person outlines and features, improving image quality and facilitating subsequent analysis and processing.

[0090] S43. Personnel detection and identification, including:

[0091] Feature extraction and model selection: Computer vision techniques are used to extract features from preprocessed images, such as edge and texture features of people, as well as high-level semantic features extracted using deep learning models. Based on the actual application scenario and the combined requirements for detection accuracy and speed, an appropriate person detection model is selected. Classic convolutional neural network (CNN)-based object detection models (such as SSD and YOLOv5) are examples. These models are trained on large datasets of annotated person images to learn the characteristic representations of people in different postures, angles, and lighting conditions, enabling them to accurately locate people in images.

[0092] Person Target Localization and Annotation: The selected person detection model is applied to each image frame. The model outputs the person's location within the image, typically as a rectangular box (bounding box) that outlines the approximate area where the person is located. A corresponding confidence score is also assigned, reflecting the reliability of the detection result. Reliable person detection results are screened based on a set confidence threshold (e.g., 0.5, which can be adjusted based on actual detection results). Detected person targets are annotated on the image, clearly showing the specific location of each person within each sub-area, paving the way for subsequent person tracking.

[0093] S44. Personnel tracking and trajectory construction, including:

[0094] Tracking algorithm selection and initialization: Based on the results of person detection, an appropriate person tracking algorithm is selected to associate the same person in different frames and construct a continuous person motion trajectory. Common tracking algorithms include multi-target tracking methods based on Kalman filtering combined with the Hungarian algorithm. This method uses Kalman filtering to predict the motion state (position, speed, etc.) of a person, and then uses the Hungarian algorithm to solve the multi-target matching problem to achieve accurate tracking of multiple people. There are also algorithms such as DeepSORT based on deep learning, which learn the appearance and motion characteristics of people for more accurate tracking. Based on factors such as the complexity of the activities of people in the indoor pool and the system's computing resources, an appropriate tracking algorithm is selected and initialized, such as setting relevant parameters such as the state transition model and observation model.

[0095] Personnel trajectory generation: As image sequences are continuously input, the tracking algorithm continuously tracks each person based on the detected position information and pre-set rules, correlating the positions of the same person in multiple consecutive frames of images to gradually generate a complete person's movement trajectory. For example, if a person in the audience area is observed to rise from their seat, move to the aisle, and then walk to the exit, the tracking algorithm can accurately record the corresponding movement trajectory coordinate sequence and time nodes, clearly showing the person's movement routes and stops in each sub-area.

[0096] S45. Extraction of dynamic personnel distribution features, including:

[0097] Determination of key indicators: Extract key indicators that can reflect the dynamic distribution of people in each sub-area from the constructed personnel movement trajectory and related location and time information. These indicators include but are not limited to: the real-time number of people in each sub-area (counting the number of people detected in the area in each time period), the average length of stay of people (calculating the average length of time people stay in the area, reflecting the area's attractiveness and comfort for people), the frequency of entry and exit of people (counting the number of times people enter and exit the area and the relationship between the time interval, reflecting the activity and ease of use of the area), the degree of personnel aggregation (by analyzing the distance distribution between people, etc., to determine whether it is a dispersed or concentrated state, reflecting the regional space utilization and environmental suitability), etc.

[0098] Data statistics and collation: For each sub-area, the above key indicators are counted and collated at certain time intervals (such as every minute, every five minutes, etc., determined according to the actual environmental change speed and control accuracy requirements) to form a data set of dynamic personnel distribution that changes over time. This clearly shows the specific values ​​of indicators such as the number of people in each sub-area, length of stay, and frequency of entry and exit at different times, providing a detailed data basis for subsequent suitability determination.

[0099] S46. Determination of suitability of sub-regions: Use cluster analysis to divide the key indicator data set into several clusters; number the suitability levels according to the numerical range of the key indicators of the clusters; and determine the suitability level of each sub-region.

[0100] Cluster analysis is used to determine the suitability of sub-areas. First, a dataset of key indicators of the dynamic distribution of people in each sub-area is collected, covering factors such as the number of people and average length of stay. Cluster analysis algorithms, such as K-Means, are then used to partition the data into clusters based on their inherent characteristics, grouping data with similar characteristics. This process involves: data preparation, collecting and standardizing data on key indicators of people's dynamics in each sub-area; determining the number of clusters; randomly selecting initial cluster centers, iteratively updating cluster centers and assigning samples until convergence, and finally completing the cluster analysis. Next, the numerical ranges of key indicators within each cluster are carefully analyzed, and suitability levels are assigned according to a set of rules, such as assigning higher numbers to clusters with the best values ​​and lower numbers to clusters with less favorable values. Finally, by comparing the clusters of key indicators within each sub-area, the corresponding suitability level is determined. This allows for a precise understanding of the environmental suitability of each sub-area, providing a robust basis for subsequent temperature and humidity control in the indoor swimming pool.

[0101] S5. Calculate the overall suitable temperature and humidity of the swimming pool based on the suitability of each sub-area;

[0102] In this embodiment, after determining the suitability of each sub-area, calculating the overall optimal temperature and humidity for the swimming pool is relatively straightforward. Since the suitability of each sub-area already reflects the comfort level of its environment, the suitability values ​​for all sub-areas can simply be accumulated. The resulting sum provides a comprehensive overview of the suitability of the swimming pool's indoor environment. Based on past experience or the system's established relationship between the summed suitability and temperature and humidity, the corresponding overall optimal temperature and humidity can be determined, providing a precise target basis for further scientific and precise control of the swimming pool's indoor temperature and humidity.

[0103] Furthermore, the overall suitable temperature and humidity are calculated as follows:

[0104] S z =S1+S2+...+S n ,

[0105] Where S z Indicates the overall suitable temperature and humidity; S1, S2, ..., S n is the suitability of each sub-region, and n is the number of sub-regions.

[0106] S6. quantifying the response relationship between the frequency conversion parameters of the variable frequency centrifugal return fan and the variable frequency compressor and the overall suitable temperature and humidity through a generalized additive model;

[0107] In this embodiment, the generalized additive model (GAM) is an advanced statistical analysis model that significantly extends the traditional linear regression model. While traditional linear regression assumes a linear relationship between the dependent variable and the independent variable, the GAM overcomes this limitation by allowing the independent variable to influence the dependent variable in the form of a nonlinear function. The GAM is used to quantify the response relationship between the frequency conversion parameters of variable-frequency centrifugal return fans and variable-frequency compressors and the overall optimal temperature and humidity in indoor swimming pool environmental control for several reasons. First, the relationship between frequency conversion parameters (such as fan speed and compressor frequency) and the overall optimal temperature and humidity is often not simply linear; complex nonlinear correlations may exist. For example, the rate of change of the impact of speed on temperature and humidity changes after a certain speed is increased. The GAM can accurately capture these situations. Second, the model is highly flexible and can adaptively explore the true relationship between variables based on actual collected data, without assuming a specific nonlinear function form. This allows for accurate visualization of how temperature and humidity respond to changes in operating parameters. Third, it can provide intuitive visual results to help staff clearly understand the strength and trend of the impact of different parameters on temperature and humidity, thereby providing a strong basis for scientifically and rationally adjusting the operating status of equipment and achieving precise environmental control.

[0108] In the control of indoor swimming pool environment, the frequency conversion parameters involving variable frequency centrifugal return fans and variable frequency compressors cover many key aspects. For variable frequency centrifugal return fans, speed is a key parameter, measured in revolutions per minute (rpm). The speed directly affects the air circulation speed and flow rate, and has a significant impact on temperature and humidity control. Air volume is also critical, measured in cubic meters per hour (m 3 Air flow (m / h) is measured and affects indoor air renewal and the efficiency of heat and moisture diffusion. Wind pressure, measured in Pascals (Pa), ensures smooth air flow through complex air ducts and maintains stable temperature and humidity in all areas. Motor current and power, measured in amperes (A), watts (W), or kilowatts (kW), reflect motor load and energy consumption, indirectly affecting temperature and humidity regulation and equipment operation.

[0109] As for variable-frequency compressors, their operating frequency is measured in Hertz (Hz). By varying this frequency, cooling or heating capacity is adjusted. The higher the frequency, the greater the cooling or heating power, making their role significant. Cooling capacity and heating capacity are also crucial. Cooling capacity reflects the amount of heat removed from the room per unit time, while heating capacity is the opposite. Both are typically measured in kilowatts (kW), and they directly determine the actual effectiveness of regulating indoor temperature and humidity. These operating parameters interact synergistically to influence the temperature and humidity conditions of indoor swimming pools, and are crucial considerations in constructing a generalized additive model to quantify their relationship to the overall optimal temperature and humidity response.

[0110] Furthermore, the generalized additive model includes the following construction steps:

[0111] S61. Determine model parameters: Determine model parameters based on data characteristics. The model parameters include a distribution family form, a smoothing function, and a number of nodes. The distribution family form is configured as a Poisson distribution, the smoothing function is configured as a cubic spline function, and the number of nodes is configured as half of the number of samples.

[0112] When constructing a generalized additive model, properly determining model parameters is a crucial and fundamental step. First, consider the various parameter settings based on the characteristics of the collected data. For the distribution family, a Poisson distribution is used. This is chosen because overall temperature and humidity suitability is a discrete variable, making it a more realistic probability distribution assumption. It effectively describes the frequency of rare events within a certain time or spatial range, helping to accurately characterize the probability distribution characteristics of variables such as overall temperature and humidity suitability under different conditions, laying the foundation for subsequent precise model analysis.

[0113] The smoothing function is configured as a cubic spline function. This function offers excellent smoothness and flexibility, allowing it to approximate complex nonlinear relationships between variables using a piecewise polynomial form. When dealing with non-linear relationships between variable-frequency parameters (such as the speed and air volume of a variable-frequency centrifugal return fan, and the operating frequency of a variable-frequency compressor) and the overall optimal temperature and humidity, the system adaptively adjusts based on data trends, smoothly and accurately fitting the true response relationship. This allows the model to capture local details while ensuring overall continuity.

[0114] The number of nodes is configured to be half the number of samples. This determines the accuracy of the spline function's fit to the data. This choice is based on a comprehensive balance between model complexity and the risk of overfitting. Too few nodes can lead to underfitting and fail to fully capture the complexity of variable relationships. While too many nodes can provide a more detailed fit to the data, they can also easily lead to overfitting, impairing the model's generalization to new data. Using half the number of nodes as the number of samples helps strike a balance between these two factors, allowing the model to better fit the response relationship between the variable frequency parameters and the overall optimum temperature and humidity for the current dataset.

[0115] S62. Model optimization: Use the test set to evaluate the model's prediction results on suitability, and optimize the model parameters according to the prediction results until they are within the preset error range.

[0116] After completing the initial model parameter setting, model performance needs to be further improved through model optimization. The model's predictions of suitability (here, suitability based on overall suitable temperature and humidity indicators) are evaluated using a test set. This process is performed by partitioning the existing dataset into a separate test set. The test set contains data that the model has not encountered during training, simulating how the model will perform when faced with new data in real-world applications.

[0117] Based on the prediction results, analyze the error between the model's predicted values ​​and the actual suitability values ​​in the test set. If the error exceeds the preset range, it means that the model's current parameter settings may not be ideal and cannot accurately capture the impact of frequency conversion parameter changes on the overall suitable temperature and humidity. In this case, it is necessary to adjust and optimize the model parameters, such as appropriately increasing or decreasing the number of nodes, and then re-evaluate using the test set. Repeat this process until the model's suitability prediction results fall within the preset error range, ensuring the model's good accuracy and generalization ability, allowing it to be reliably used for subsequent quantitative analysis of the relationship between frequency conversion parameters and the overall suitable temperature and humidity response, as well as for practical environmental control decision-making.

[0118] S7. According to the response relationship, control the frequency conversion parameters so that the overall suitable temperature and humidity in the swimming pool room are maintained above a preset threshold.

[0119] In this embodiment, in an indoor swimming pool's environmental control system, a generalized additive model was used to successfully quantify the relationship between the frequency conversion parameters of the variable-frequency centrifugal return air fan and the variable-frequency compressor and the overall optimal temperature and humidity. This relationship was then used as a basis for precise equipment parameter control. First, a threshold for the overall optimal temperature and humidity within the swimming pool was clearly defined. This threshold was determined based on a combination of factors, including human comfort, swimming pool operational requirements, and relevant standards. Next, the current optimal temperature and humidity values ​​were monitored in real time and compared with the preset thresholds.

[0120] When the overall suitable temperature and humidity are found to be approaching or trending below the preset threshold, the control system quickly analyzes the necessary adjustments to the frequency conversion parameters using the established response relationship. For example, if the response relationship indicates that increasing the speed and air volume of the variable-frequency centrifugal return fan, while also appropriately increasing the operating frequency of the variable-frequency compressor, can effectively improve the temperature and humidity, the control system will precisely issue instructions to drive the corresponding equipment to change the operating parameters as required, causing the temperature and humidity to return to above the preset threshold. Throughout the entire process, continuous monitoring, comparison, and adjustment are carried out in a cycle to ensure that the overall suitable temperature and humidity in the swimming pool are always stable and above the preset threshold, creating a comfortable and standard indoor environment for users and realizing intelligent and refined control of the temperature and humidity of the indoor swimming pool.

[0121] Furthermore, controlling the frequency conversion parameters according to the response relationship so that the overall suitable temperature and humidity in the swimming pool room are maintained above a preset threshold value includes the following steps:

[0122] S71. Visualize the response relationship between the frequency conversion parameters and the overall suitable temperature and humidity by fitting the response relationship curve of the generalized additive model;

[0123] After constructing the generalized additive model, professional data analysis software or drawing tools are used to perform curve fitting and visualization of the response relationship between the variable frequency parameters of the variable frequency centrifugal return fan and the variable frequency compressor and the overall suitable temperature and humidity revealed by the model. For example, with the speed of the variable frequency centrifugal return fan as the horizontal axis and the overall suitable temperature and humidity in the swimming pool room as the vertical axis, curve fitting is performed based on the data points output by the model to draw a curve that can intuitively show how the overall suitable temperature and humidity change accordingly with changes in the fan speed. Similarly, corresponding response relationship curves are also drawn for other key operating parameters such as the operating frequency of the variable frequency compressor. Through these visualized curves, staff can clearly and intuitively observe how changes in different frequency conversion parameters dynamically affect the overall suitable temperature and humidity, understand the general trend of the influence of each parameter, the sensitivity level, and the possible interaction between parameters, and provide an intuitive basis for subsequent judgment and regulation.

[0124] S72. When the overall suitable temperature and humidity in the swimming pool room is lower than a preset threshold, determining abnormal frequency conversion parameters that are not within the overall suitable temperature and humidity threshold range in the response relationship curve;

[0125] The overall suitable temperature and humidity in the swimming pool room are continuously monitored in real time and compared with pre-set thresholds. If the overall suitable temperature and humidity are found to be lower than the threshold, it means that the current equipment operating status fails to maintain the desired environmental conditions and needs to be adjusted. At this time, refer to the previously fitted response relationship curves and carefully check the difference between the overall suitable temperature and humidity values ​​corresponding to the current frequency conversion parameters and the values ​​that should correspond to the normal threshold range. Frequency conversion parameters that fall outside the overall suitable temperature and humidity threshold range corresponding to the normal response relationship curve are abnormal frequency conversion parameters. For example, according to the response relationship curve, under a specific combination of compressor operating frequency and fan speed, the overall suitable temperature and humidity should be above the set threshold, but it is actually lower than the threshold. At this time, the corresponding parameters such as compressor operating frequency and fan speed are judged to be abnormal parameters. Their actual operating conditions do not meet the expected requirements for maintaining a suitable environment and require further investigation and adjustment.

[0126] S73. Adjust the abnormal frequency conversion parameters until the overall suitable temperature and humidity remain above the preset threshold.

[0127] After determining the abnormal frequency conversion parameters, make targeted adjustments to these abnormal parameters based on the rules revealed by the response relationship curve and past equipment control experience. If the speed of the variable frequency centrifugal return fan is too low, resulting in substandard temperature and humidity, then gradually increase the fan speed and observe the changes in the overall suitable temperature and humidity values ​​in real time; if the operating frequency of the variable frequency compressor does not meet the requirements, then increase or decrease its frequency accordingly, and adjust it in conjunction with other related parameters to avoid the adverse effects of single parameter adjustments. During the adjustment process, continue to pay attention to the overall suitable temperature and humidity values, repeatedly compare them with the preset thresholds, and continuously fine-tune the frequency conversion parameters until the overall suitable temperature and humidity recover and remain stable above the preset thresholds, ensuring that the indoor environment of the swimming pool is always comfortable and meets the requirements, and realizing indoor environment optimization management based on precise analysis and effective control.

[0128] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as above in terms of a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can, without departing from the scope of the technical solution of the present invention, make some changes or modifications to equivalent embodiments using the technical contents disclosed above. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A multi-zone monitoring and dehumidification frequency conversion control system based on an indoor swimming pool, characterized by: It includes a variable frequency wind module, a refrigerant module and an electric control module, which are communicatively connected to each other, wherein: The electronic control module is used to automatically control the variable frequency centrifugal return air fan and variable frequency compressor according to the temperature and humidity in different areas of the swimming pool, including: Divide the indoor area of ​​the swimming pool into several sub-areas, and use temperature and humidity sensors to monitor the temperature and humidity of each sub-area; The temperature and humidity of each sub-area are processed using the interpolation method to obtain the spatial distribution of temperature and humidity in the swimming pool; Setting temperature and humidity targets for each sub-area, and adjusting the temperature and humidity for each sub-area according to the temperature and humidity targets; Using a high-definition camera to obtain the dynamic distribution of people in the swimming pool after adjusting the temperature and humidity, and determining the suitability of each sub-area based on the dynamic distribution of people; Calculate the overall suitable temperature and humidity in the swimming pool based on the suitability of each sub-area; quantifying the response relationship between the variable frequency parameters of the variable frequency centrifugal return fan and the variable frequency compressor and the overall suitable temperature and humidity through a generalized additive model; According to the response relationship, the frequency conversion parameters are controlled so that the overall suitable temperature and humidity in the swimming pool room are maintained above a preset threshold value; The interpolation method is calculated as follows: ， ， Where, T p Indicates a point in the indoor space of the swimming pool p Temperature and humidity; T i Indicates the i The temperature and humidity of each sub-area, n is the number of sub-regions; w i Indicates the i The distance weight of each sub-region; D p Indicates a point p To i The Euclidean distance between monitoring points in each sub-region; The method of obtaining the dynamic distribution of people in the swimming pool after adjusting the temperature and humidity by using a high-definition camera and determining the suitability of each sub-area according to the dynamic distribution of people includes the following steps: Real-time image acquisition: HD cameras collect image information of each sub-area of ​​the indoor swimming pool according to pre-configured parameters, convert the actual scene into digital image signals, and transmit the collected image data to the back-end image processing server via wired or wireless communication; Preprocessing the image data, including image format unification and normalization, as well as noise removal and enhancement processing; Person detection and recognition: Using computer vision technology, we extract person features from pre-processed images and output the location information of people in each sub-region of the image. Person tracking and trajectory construction: Based on the results of person detection, the person tracking algorithm is used to associate the same person in multiple consecutive frames of images and construct a continuous person movement trajectory; Extracting dynamic distribution features of people: Extracting key indicators that reflect the dynamic distribution of people in each sub-area from the constructed movement trajectories and related location and time information. These key indicators are then counted and organized to form a dataset of dynamic distribution of people that changes over time. These key indicators include the real-time number of people in each sub-area, the average length of stay, the frequency of entry and exit, and the degree of concentration of people. Determination of suitability of sub-regions: cluster analysis method is used to divide the key indicator data set into several clusters; the suitability levels are numbered according to the numerical range of the key indicators of the clusters; and the suitability level of each sub-region is determined; The overall suitable temperature and humidity are calculated as follows: ， Where, S z Indicates the overall suitable temperature and humidity; S 1 , S 2 ,…, S n is the suitability of each sub-region, n is the number of sub-regions; The multi-zone monitoring and dehumidification frequency conversion control system based on an indoor swimming pool is characterized in that: according to the response relationship, the frequency conversion parameters are controlled so that the overall suitable temperature and humidity in the swimming pool are maintained above a preset threshold, including the following steps: The response relationship between the variable frequency parameters and the overall suitable temperature and humidity is visualized by fitting the response relationship curve of the generalized additive model; When the overall suitable temperature and humidity in the swimming pool room is lower than a preset threshold, determining abnormal frequency conversion parameters that are not within the overall suitable temperature and humidity threshold range in the response relationship curve; Adjust the abnormal frequency conversion parameters until the overall suitable temperature and humidity remain above the preset threshold.

2. The multi-zone monitoring and dehumidification frequency conversion control system based on an indoor swimming pool according to claim 1 is characterized in that: The personnel feature extraction includes extracting edge features, texture features and high-level semantic features of personnel based on a deep learning model.

3. The multi-zone monitoring and dehumidification frequency conversion control system based on an indoor swimming pool according to claim 1 is characterized in that: The personnel tracking algorithm is configured as a multi-target tracking method based on Kalman filtering combined with the Hungarian algorithm or a DeepSORT algorithm based on deep learning.

4. The multi-zone monitoring and dehumidification frequency conversion control system based on an indoor swimming pool according to claim 1 is characterized in that: The cluster analysis method is configured as a K-means clustering method, which includes: data preparation, collecting and organizing dynamic key indicator data of personnel in each sub-area, and performing standardization processing; determining the number of clusters; randomly selecting initial cluster centers, iteratively updating cluster centers and allocating samples until convergence, and finally completing cluster analysis.

5. The multi-zone monitoring and dehumidification frequency conversion control system based on an indoor swimming pool according to claim 1 is characterized in that: The generalized additive model includes the following construction steps: Determine model parameters: Determine model parameters based on data characteristics. The model parameters include a distribution family form, a smoothing function, and a number of nodes. The distribution family form is configured as a Poisson distribution, the smoothing function is configured as a cubic spline function, and the number of nodes is configured as half of the number of samples. Model optimization: Use the test set to evaluate the model's prediction results for fitness, and optimize the model parameters based on the prediction results until they are within the preset error range.

6. The multi-zone monitoring and dehumidification frequency conversion control system based on an indoor swimming pool according to claim 1, characterized in that: It includes a variable frequency wind module, a refrigerant module and an electric control module, which are communicatively connected to each other, wherein: The variable frequency wind module consists of an anti-cold bridge box, a variable frequency centrifugal supply fan, a variable frequency centrifugal return fan and an air valve, which is used to draw indoor air into the dehumidification heat pump box through the air duct and send the treated air back to the room through the supply fan; The refrigerant module consists of a variable frequency compressor, an evaporator, a reheat condenser, an outdoor condenser, a titanium bulb, a liquid reservoir, an electronic expansion valve, a drying filter and a copper tube, and is used to dehumidify and cool the indoor air or dehumidify and heat it; The electric control module is composed of a control panel, a main control board, a variable frequency drive module, several contactors and several temperature and humidity sensors.

Images