Temperature and humidity adjusting method and system based on intelligent ventilation control

Abstract

The invention relates to the technical field of intelligent environment control, in particular to a temperature and humidity adjusting method and system based on intelligent ventilation control, and the method comprises the steps: confirming environment parameters, initializing an adjusting unit, obtaining a control instruction, standardizing a data set, generating a state report, optimizing an abnormal state, dynamically adjusting the environment parameters, and the like. The system comprises an environment data acquisition module, an environment data analysis module, an abnormal state processing module and a dynamic adjustment module. According to the application, dynamic perception and accurate regulation and control of environmental data are realized through the multi-mode sensor and the central control system, adaptability and anomaly recognition efficiency are improved by using the self-learning module and the anomaly detection module, and data security is guaranteed through an encrypted transmission protocol. The intelligent level and the energy-saving effect of environment adjustment can be effectively improved, and the system is suitable for temperature and humidity management in a complex environment.

Description

Technical Field

[0001] The present invention belongs to the technical field of environmental control, and specifically relates to a temperature and humidity adjustment method and system based on intelligent ventilation control. Background Art

[0002] With the rapid development of intelligent control technology, its application in the field of temperature and humidity regulation is becoming increasingly widespread. Temperature and humidity regulation methods and systems based on intelligent ventilation control have gradually become a research hotspot due to their high efficiency, precision, and energy efficiency. They have demonstrated significant value in various scenarios, including industrial production, agricultural breeding, and daily life. However, despite certain progress in existing technologies, significant deficiencies remain in terms of intelligence, regulation accuracy, and adaptability to complex application scenarios, affecting the overall performance of the system and the user experience.

[0003] A search revealed that patent publication number CN112361487B discloses a temperature and humidity control system and control method. By providing a first and second heat exchange section, and forming multiple heat exchange paths and circulation channels, this system effectively addresses the problem of excessive resistance in traditional technologies while improving the control accuracy of indoor cooling. However, this technical solution primarily relies on fixed heat exchange logic and damper control strategies. When faced with dynamically changing environmental conditions (such as rapidly changing temperature and humidity or complex gas composition), its adaptive capabilities are weak, making it difficult to achieve precise real-time adjustment. Furthermore, the system's intelligence level is limited, failing to fully utilize modern sensor technology and data analysis algorithms to optimize control strategies, potentially resulting in high energy consumption or suboptimal regulation results.

[0004] Another patent, published under the patent number CN119337150B, proposes an intelligent ventilation control method and system for livestock and poultry farming. This system uses sensors to monitor the gas status of the farm around the clock. The system then simulates and calculates the entropy increase effect of heat deposition to design ventilation logic. This system dynamically adjusts ventilation strategies based on changes in gas temperature and humidity, as well as ammonia and carbon dioxide concentrations. While this technical solution offers some improvements in intelligence, it still has significant shortcomings. Its temperature and humidity control relies primarily on ventilation logic, lacking direct intervention in air temperature and humidity (such as humidification, dehumidification, or heating). This can result in the system failing to meet precise temperature and humidity control requirements in extreme environments (such as high humidity or very low temperatures). Furthermore, the system's real-time processing capabilities for sensor data and algorithm optimization still need to be improved, potentially leading to response lags or control deviations in complex scenarios.

[0005] The above issues indicate that existing temperature and humidity control systems still have certain limitations in terms of intelligent control, dynamic adaptability, and regulation accuracy in extreme environments. These limitations make it difficult to fully meet the demands of modern industrial and lifestyle scenarios for efficient and precise temperature and humidity regulation. Therefore, there is an urgent need to develop a temperature and humidity regulation method and system based on intelligent ventilation control. By introducing advanced sensor technology, data processing algorithms, and multi-mode regulation strategies, this approach can enhance the system's intelligence and adaptability, while also strengthening its ability to cope with extreme environmental conditions. This approach can provide users with a more efficient and precise temperature and humidity regulation solution. Summary of the Invention

[0006] The present invention provides a temperature and humidity adjustment method and system based on intelligent ventilation control, the main purpose of which is to achieve efficient management of temperature and humidity conditions in complex environments through dynamic perception and precise regulation, thereby improving the system's adaptability and energy-saving effect.

[0007] To achieve the above objectives, the present invention provides a temperature and humidity adjustment method based on intelligent ventilation control, comprising: confirming environmental parameters and sequentially extracting adjustment units from a plurality of pre-built adjustment units, performing initialization operations on the extracted adjustment units to obtain a plurality of initialized adjustment units, and obtaining control instructions based on the environmental parameters and the plurality of initialized adjustment units, wherein the environmental parameters include: temperature, humidity, air quality index, and light intensity; Acquire a data set to be processed according to control instructions, preset operating frequencies, and pre-built multimodal sensors; A pre-built central control system is used to standardize a dataset to be processed to obtain a standardized dataset, wherein the central control system includes: a dynamic balancing module, an adaptive adjustment module, a cloud storage platform, and an intelligent optimization service system, wherein the cloud storage platform includes: a distributed database, an encrypted transmission protocol, a self-learning module, and an anomaly detection module, wherein the intelligent optimization service system includes: an environmental health assessment model, a historical trend database, and a decision support tool; Using a self-learning module to simulate a standardized data set to obtain a simulated data set, and generating a status report based on the simulated data set; Use the anomaly detection module to analyze the status report and obtain the abnormal status; Obtaining an abnormal status report based on the abnormal status, optimizing the abnormal status report using an intelligent optimization service system to obtain an optimized status report, wherein the optimized status report includes: environmental equipment status and environmental parameter data; Analyze the optimization status report to obtain environmental equipment status and environmental parameter data. If the environmental equipment status is a preset abnormal environmental equipment status, diagnose the environmental equipment using the environmental health assessment model to obtain a diagnosis result. Based on the diagnosis result, obtain a maintenance plan. Use the maintenance plan to perform maintenance operations on the environmental equipment until the environmental equipment returns to a preset standard environmental equipment. If the environmental parameter data is abnormal environmental parameter data, the abnormal environmental parameter data is marked and adjusted by the intelligent optimization service system until the environmental parameter data is within the environmental parameter range preset by the intelligent optimization service system, and the environmental parameter data is securely transmitted using the encryption transmission protocol to obtain transmission data, and the transmission data is stored in a distributed database to obtain normal environmental parameter data; A temperature and humidity adjustment method for intelligent ventilation control is completed based on standard environmental equipment and normal environmental parameter data.

[0008] Optionally, the confirming environmental parameters includes: Among them, the multimodal sensors include: temperature and humidity sensors, air quality sensors, light intensity sensors and infrared detectors; Obtain multiple historical monitoring periods, where the multiple historical monitoring periods include: morning, noon, evening and late night; Extract historical monitoring periods from multiple historical monitoring periods in sequence, and perform the following operations on the extracted historical monitoring periods: Based on the extracted historical monitoring period and the pre-constructed historical environmental unit detected by multimodal sensors, the temperature, humidity, air quality index and light intensity of the historical environmental unit are obtained; If the temperature is not within the preset temperature range or the humidity is not within the preset humidity range, the central control system is used to reconfigure the operating mode of the historical environment unit to obtain a configured environment unit, and the operating temperature and operating humidity of the configured environment unit are detected, with the operating temperature being the temperature and the operating humidity being the humidity, until the temperature is within the temperature range and the humidity is within the humidity range, then it is confirmed that the air quality index is within the preset air quality range, wherein the operating modes include: cooling, heating and ventilation; If the air quality index is not within the preset air quality range, the central control system automatically adjusts the working intensity of the air purifier until the air quality index is within the said air quality range; If the light intensity is not within the preset light intensity range, the central control system automatically adjusts the opening and closing degree of the shading device until the light intensity is within the said light intensity range; After confirming that the temperature is within the temperature range, the humidity is within the humidity range, the air quality index is within the air quality range, and the light intensity is within the light intensity range, the environmental parameters are obtained.

[0009] Optionally, extracting adjustment units in sequence from a plurality of pre-constructed adjustment units and performing initialization operations on the extracted adjustment units to obtain a plurality of initialized adjustment units includes: Extract adjustment units from the pre-built multiple adjustment units in sequence, and perform the following operations on the extracted adjustment units: The efficiency loss formula of the regulating unit is obtained based on the extracted regulating unit and central control system, and the performance degradation percentage is calculated based on the efficiency loss formula of the regulating unit. The efficiency loss formula of the regulating unit is as follows: ; in Indicates the percentage of performance degradation, which is the percentage of performance degradation of the regulating unit caused by aging or pollution. To adjust the actual output capacity of the unit, It is the theoretical maximum output capacity of the regulating unit under ideal conditions; If the performance degradation percentage is greater than 10, the extracted adjustment unit needs to be initialized, and an adjustment unit that needs to be initialized is obtained; otherwise, the adjustment unit does not need to be initialized, and a first initialized adjustment unit is obtained; Performing an initialization operation on the adjustment unit to be initialized to obtain a second initialized adjustment unit; The second initialization adjustment unit and the first initialization adjustment unit are aggregated to obtain a plurality of initialization adjustment units.

[0010] Optionally, performing an initialization operation on the adjustment unit to be initialized to obtain a second initialized adjustment unit includes: Using a central control system to mark the adjustment unit to be initialized to obtain a marked adjustment unit, and powering off the marked adjustment unit to obtain a target adjustment unit, and constructing a three-dimensional reference coordinate system, wherein the coordinates of the target adjustment unit are preset in the three-dimensional reference coordinate system; Using the three-dimensional reference coordinate system and the automated maintenance robot to obtain the current coordinates in real time, fitting a movement path based on the current coordinates and the coordinates of the target adjustment unit, and controlling the automated maintenance robot to move along the movement path using a central control system until the current coordinates are equal to the coordinates of the target adjustment unit, and then obtaining an initialization instruction; Using a pre-built camera in the automated maintenance robot to photograph the target adjustment unit to obtain an image of the adjustment unit surface, wherein the automated maintenance robot also includes: a cleaning device, a lubrication system, and a calibration tool; One or more areas to be initialized are acquired using the central control system and the surface image of the regulating unit, and the following operations are performed on each of the one or more areas to be initialized: Initialization parameters are set according to the area to be initialized, the area to be initialized is cleaned using a cleaning device to obtain a clean area, the lubrication system is started according to the initialization parameters to obtain a post-startup lubrication system, the clean area is lubricated using the post-startup lubrication system to obtain a post-lubrication area, and the post-lubrication area is calibrated using a calibration tool to obtain an initialized area; After confirming that the regions to be initialized in the one or more regions to be initialized are all initialized regions, a second initialization adjustment unit is obtained.

[0011] Optionally, analyzing the status report using an anomaly detection module to obtain an abnormal status includes: The status reports are grouped according to a preset unit analysis period using an anomaly detection module to obtain a plurality of unit status reports, and the following operations are performed on each of the plurality of unit status reports: extracting the temperature of the environmental unit and the humidity of the environmental unit from the unit status report; Determining a state matching value of the unit state report using the temperature of the environment unit, the humidity of the environment unit, and a pre-established state matching rule; If the state matching value is equal to 0, it indicates that the temperature of the environmental unit and the humidity of the environmental unit are in a balanced state, and an initial normal state is obtained. A pre-constructed local deviation factor is used to determine whether the local deviation factor of the initial normal state is higher than the pre-constructed adjacent local deviation factor. If the local deviation factor of the initial normal state is higher than the pre-constructed adjacent local deviation factor, the initial normal state is confirmed as an abnormal state. Otherwise, the initial normal state is skipped. If the state matching value is equal to 1, it means that the ambient unit temperature and the ambient unit humidity are in a non-equilibrium state, resulting in an abnormal state.

[0012] Optionally, the method of using the intelligent optimization service system to mark and adjust abnormal environmental parameter data until the environmental parameter data is within an environmental parameter range preset by the intelligent optimization service system includes: Utilize the historical trend database to save the environmental parameter data and update the historical trend database in real time, extract the environmental parameter data from the updated historical trend database in sequence, and perform the following operations on the extracted environmental parameter data; Using a decision support tool to mark the extracted environmental parameter data to obtain marked environmental parameter data; If there is no data that is not within the preset environmental parameter range in the marked environmental parameter data, it is confirmed that the environmental parameter data is within the environmental parameter range preset by the intelligent optimization service system; If there is data in the marked environmental parameter data that is not within the preset environmental parameter range, then the data that is not within the preset environmental parameter range is removed from the updated historical trend database to obtain a newly updated historical trend database, and the newly updated historical trend database is used as the updated historical trend database, and the process returns to the step of sequentially extracting environmental parameter data from the updated historical trend database; After confirming that all the extracted environmental parameter data are within the environmental parameter range, an optimal historical trend database is obtained, and all the environmental parameter data in the optimal historical trend database are reconstructed using a periodic optimization model to obtain a plurality of reconstructed environmental parameter data; The following operations are performed on each of the plurality of reconstruction environment parameter data: If the reconstructed environmental parameter data exceeds the preset environmental parameter interval, and the environmental parameter data corresponding to the reconstructed environmental parameter data in the optimal historical trend database exceeds the preset deviation interval, then return to the step of sequentially extracting environmental parameter data from the updated historical trend database until the environmental parameter data is within the environmental parameter interval preset by the intelligent optimization service system; If the reconstructed environmental parameter data exceeds the preset environmental parameter range, and the environmental parameter data corresponding to the reconstructed environmental parameter data in the optimal historical trend database is within the preset deviation range, the preset environmental parameter range is adjusted until the environmental parameter data is within the preset environmental parameter range of the intelligent optimization service system.

[0013] Optionally, the securely transmitting the environmental parameter data using the encrypted transmission protocol to obtain the transmission data, storing the transmission data in a distributed database, and obtaining the normal environmental parameter data includes: The environmental parameter data includes: indoor environmental data and outdoor environmental data; The following encryption operations are performed on the environmental parameter data using the encrypted transmission protocol: The environment parameter data is converted into a ciphertext format using a pre-built data encryption mechanism in the encryption transmission protocol to obtain ciphertext environment parameter data, and a key is randomly generated for the ciphertext environment parameter data to obtain key environment parameter data; Divide the key environment parameter data using a pre-built data segmentation strategy to obtain multiple segmented block environment parameter data; Acquire transmission data based on the plurality of segmentation block environment parameter data and the key environment parameter data; Use distributed database to store and transmit data to obtain normal environmental parameter data.

[0014] To achieve the above object, the present invention further provides a temperature and humidity control system based on intelligent control, comprising: An environmental data acquisition module is used to confirm environmental parameters and sequentially extract adjustment units from a plurality of pre-built adjustment units, perform initialization operations on the extracted adjustment units to obtain a plurality of initialized adjustment units, obtain control instructions based on the environmental parameters and the plurality of initialized adjustment units, wherein the environmental parameters include: temperature, humidity, air quality index and light intensity, and obtain a data set to be processed based on the control instructions, a preset operating frequency and a pre-built multimodal sensor; An environmental data analysis module is used to standardize a dataset to be processed using a pre-built central control system to obtain a standardized dataset, wherein the central control system includes: a dynamic balancing module, an adaptive adjustment module, a cloud storage platform, and an intelligent optimization service system, wherein the cloud storage platform includes: a distributed database, an encrypted transmission protocol, a self-learning module, and an anomaly detection module, wherein the intelligent optimization service system includes: an environmental health assessment model, a historical trend database, and a decision support tool, wherein the self-learning module is used to simulate the standardized dataset to obtain a simulated dataset, a status report is generated based on the simulated dataset, and the status report is analyzed using the anomaly detection module to obtain an abnormal status; an abnormal state processing module, configured to obtain an abnormal state report based on the abnormal state, optimize the abnormal state report using the intelligent optimization service system to obtain an optimized state report, wherein the optimized state report includes: environmental equipment status and environmental parameter data, parse the optimized state report to obtain the environmental equipment status and environmental parameter data, and if the environmental equipment status is a preset environmental equipment abnormal state, diagnose the environmental equipment using an environmental health assessment model to obtain a diagnosis result, obtain a maintenance plan based on the diagnosis result, and perform maintenance operations on the environmental equipment using the maintenance plan until the environmental equipment returns to a preset standard environmental equipment; The dynamic adjustment module is used to mark and adjust the abnormal environmental parameter data using the intelligent optimization service system if the environmental parameter data is abnormal environmental parameter data, until the environmental parameter data is within the environmental parameter range preset by the intelligent optimization service system, and use the encrypted transmission protocol to securely transmit the environmental parameter data to obtain the transmitted data, store the transmitted data in a distributed database, obtain normal environmental parameter data, and complete the temperature and humidity adjustment method of intelligent ventilation control based on standard environmental equipment and normal environmental parameter data.

[0015] In order to solve the above problem, the present invention further provides an electronic device, comprising: a memory storing at least one instruction; and The processor executes the instructions stored in the memory to implement the temperature and humidity adjustment method based on intelligent ventilation control.

[0016] In order to solve the above problems, the present invention also provides a computer-readable storage medium, which stores at least one instruction, and the at least one instruction is executed by a processor in an electronic device to implement the above-mentioned temperature and humidity adjustment method based on intelligent ventilation control.

[0017] Compared to the problems described in the background art, the present invention first confirms environmental parameters and sequentially extracts adjustment units from a plurality of pre-constructed adjustment units, and performs initialization operations on the extracted adjustment units to obtain a plurality of initialized adjustment units. Control instructions are obtained based on the environmental parameters and the plurality of initialized adjustment units, wherein the environmental parameters include: temperature, humidity, air quality index, and light intensity. In the embodiment of the present invention, an automated maintenance robot is used to operate the adjustment units to be initialized, thereby improving initialization efficiency and reducing manual intervention. A data set to be processed is obtained according to control instructions, a preset operating frequency, and a pre-constructed multimodal sensor. The present invention sets the operating frequency to obtain environmental data in real time. The data set to be processed is standardized using a pre-constructed central control system to obtain a standardized data set. The standardized processing described in the embodiment of the present invention can unify data from different sources to the same benchmark for easy analysis. The standardized data set is simulated using a self-learning module to obtain a simulated data set. A status report is generated based on the simulated data set. The simulation described in the embodiment of the present invention facilitates prediction based on different needs and improves adaptability. The status report is analyzed using an anomaly detection module to obtain an abnormal state. The present invention uses two methods to analyze the abnormal state to improve the efficiency of identifying the abnormal state, and obtains the abnormal state based on the abnormal state. Report, use the intelligent optimization service system to optimize the abnormal status report to obtain an optimized status report, wherein the optimized status report includes: environmental equipment status and environmental parameter data, parse the optimized status report to obtain the environmental equipment status and environmental parameter data, if the environmental equipment status is a preset environmental equipment abnormal state, use the environmental health assessment model to diagnose the environmental equipment to obtain a diagnosis result, obtain a maintenance plan based on the diagnosis result, and perform maintenance operations on the environmental equipment using the maintenance plan until the environmental equipment is a preset standard environmental equipment. The environmental health assessment model described in the embodiment of the present invention can timely discover potential equipment problems, thereby improving environmental adjustment efficiency. If the environmental parameter data is abnormal environmental parameter data, the intelligent optimization service system is used to mark and adjust the abnormal environmental parameter data until the environmental parameter data is within the environmental parameter range preset by the intelligent optimization service system. After adjusting the abnormal environmental data, the present invention reconstructs the remaining environmental data to obtain new environmental data. Secondly, the environmental parameter data is securely transmitted using the encrypted transmission protocol to obtain transmission data, and the transmission data is stored in a distributed database to obtain normal environmental parameter data. The temperature and humidity adjustment method of intelligent ventilation control is completed based on the standard environmental equipment and normal environmental parameter data. Therefore, the present invention can dynamically sense environmental changes and accurately adjust environmental parameters, thereby improving the intelligence level and energy-saving effect of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic flow chart of a temperature and humidity adjustment method based on intelligent ventilation control provided in one embodiment of the present invention; Figure 2 A functional module diagram of a temperature and humidity control system based on intelligent control provided by one embodiment of the present invention; Figure 3 A schematic structural diagram of an electronic device for implementing the temperature and humidity adjustment method based on intelligent ventilation control provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0019] The present invention provides a temperature and humidity adjustment method and system based on intelligent ventilation control, which realizes efficient management of temperature and humidity conditions in complex environments by dynamically sensing environmental parameters and combining with an intelligent optimization service system. Figure 1 To the attached Figure 3 Specific embodiments of the present invention are described in detail.

[0020] In practical applications, the present invention first needs to confirm environmental parameters and obtain relevant data through multimodal sensors. Figure 1 As shown, the multimodal sensor system includes a temperature and humidity sensor, an air quality sensor, a light intensity sensor, and an infrared detector, used to detect temperature, humidity, air quality index, and light intensity in the environment. To ensure comprehensive data collection, the system sequentially extracts historical monitoring periods (morning, noon, evening, and late night) and uses the multimodal sensor to detect pre-built historical environmental units, obtaining the temperature, humidity, air quality index, and light intensity of each unit. If the temperature or humidity is detected to be outside the preset temperature range or humidity range, the central control system reconfigures the operating mode of the historical environmental unit, such as cooling, heating, or ventilation, until both temperature and humidity are within the preset range. The system then further verifies whether the air quality index is within the preset air quality range. If not, it automatically adjusts the operating intensity of the air purifier. Light intensity is also monitored in real time. If it exceeds the preset range, the central control system automatically adjusts the opening and closing of the light shielding device until all environmental parameters meet the requirements.

[0021] After confirming the environmental parameters, the system will extract the adjustment units from the pre-built multiple adjustment units in sequence and perform initialization operations on the extracted adjustment units. First, the adjustment unit efficiency loss formula is obtained based on the extracted adjustment units and the central control system: ; in Indicates the percentage of performance degradation, To adjust the actual output capacity of the unit, It is the theoretical maximum output capacity of the adjustment unit under ideal conditions. If the calculated performance degradation percentage is greater than 10%, the adjustment unit needs to be initialized, otherwise no initialization is required. For the adjustment units that need to be initialized, the system will use an automated maintenance robot to operate them. Specifically, the central control system will mark the adjustment unit that needs to be initialized and cut off the power, and then construct a three-dimensional reference coordinate system to determine the coordinate position of the target adjustment unit. The automated maintenance robot will obtain the current coordinates in real time, fit the movement path, and move along the path to the target adjustment unit position. After reaching the target position, the robot will use the camera to capture the surface image of the adjustment unit, and in conjunction with the central control system, identify one or more areas that need to be initialized. For each area that needs to be initialized, the system will set the initialization parameters, use the cleaning device to clean the surface dirt, start the lubrication system to lubricate the cleaned area, and finally use the calibration tool to complete the calibration operation to ensure that the adjustment unit is restored to the best working condition.

[0022] After completing the initialization operation, the system will obtain control instructions based on environmental parameters and multiple initialization adjustment units, and obtain the data set to be processed according to the control instructions, preset operating frequency and multimodal sensors. Figure 2 As shown in the figure, the environmental data acquisition module is responsible for the above operations. Its core is to collect environmental data in real time by setting a reasonable operating frequency, thereby ensuring the timeliness and accuracy of the data. The processed data set is then transmitted to the environmental data analysis module, which uses a pre-built central control system to standardize the data. The central control system includes a dynamic balance module, an adaptive adjustment module, a cloud storage platform, and an intelligent optimization service system. The cloud storage platform includes a distributed database, an encrypted transmission protocol, a self-learning module, and an anomaly detection module. The intelligent optimization service system includes an environmental health assessment model, a historical trend database, and decision support tools. The core of standardization is to unify data from different sources to the same benchmark to facilitate subsequent analysis and optimization.

[0023] After standardization, the system uses a self-learning module to simulate the standardized data set, generating a simulated data set and generating status reports based on it. The self-learning module uses a deep learning algorithm to continuously optimize the prediction model by learning from historical data, thereby improving the system's adaptability and intelligence. The status report is then transmitted to the anomaly detection module, which groups the status reports according to preset unit analysis periods and applies the status matching rule to each unit status report. The core formula of the status matching rule is: , where M represents the state matching value, T is the temperature of the environmental unit, and H is the humidity of the environmental unit. If the state matching value equals 0, indicating that the temperature and humidity are in equilibrium, the system further uses the local deviation factor to determine whether there is an anomaly in the initial normal state. If the state matching value equals 1, the abnormal state is directly confirmed. The double-layer screening mechanism of the anomaly detection module effectively improves the accuracy and efficiency of abnormal state identification.

[0024] When the system detects an abnormal state, it will generate an abnormal state report and transmit it to the intelligent optimization service system for optimization processing. Figure 2 As shown, the abnormal status processing module is responsible for parsing the optimization status report and extracting the environmental equipment status and environmental parameter data. If the environmental equipment status is the preset abnormal environmental equipment status, the system will use the environmental health assessment model to diagnose the equipment. The environmental health assessment model is based on a machine learning algorithm and can quickly identify potential problems and generate a maintenance plan. The maintenance plan is executed by the processor of the electronic device, and maintenance operations are performed on the equipment through automated means until the equipment is restored to the standard state. If the environmental parameter data is abnormal, the system will use the intelligent optimization service system to mark and adjust it. Specifically, the historical trend database will save the environmental parameter data and update it in real time, and the decision support tool will mark the data and eliminate abnormal data that does not meet the preset environmental parameter range. Subsequently, the system will use the periodic optimization model to reconstruct the remaining data. If the reconstructed data still exceeds the environmental parameter range, the preset range will be further adjusted until all data meets the requirements.

[0025] After completing the data optimization, the system will use the encrypted transmission protocol to transmit the environmental parameter data securely. Figure 3 As shown in Figure 1, the encrypted transmission protocol includes a data encryption mechanism and a data segmentation strategy. First, the environmental parameter data is converted into ciphertext format, and a randomly generated key is used to enhance security. Subsequently, the keyed environmental parameter data is divided into multiple blocks, ensuring that even if partial data is leaked, the complete information cannot be restored. The transmitted data is ultimately stored in a distributed database, forming normal environmental parameter data. Based on standard environmental equipment and normal environmental parameter data, the system can implement temperature and humidity adjustment methods for intelligent ventilation control.

[0026] The present invention also provides an electronic device, the structure of which is as follows Figure 3As shown, it includes a memory and a processor. The memory is used to store at least one instruction, and the processor is responsible for executing the instructions in the memory to implement the above method. In addition, the present invention also provides a computer-readable storage medium, which stores at least one instruction, and when the instruction is executed by the processor in the electronic device, it can implement the above method. Through the above technical solution, the present invention realizes dynamic perception and precise control of temperature and humidity conditions in complex environments, significantly improves the intelligence level and energy-saving effect of the system, and has broad application prospects.

Claims

1. A temperature and humidity adjustment method based on intelligent ventilation control, characterized in that: The method comprises: confirming environmental parameters and sequentially extracting adjustment units from a plurality of pre-built adjustment units, performing initialization operations on the extracted adjustment units to obtain a plurality of initialized adjustment units, and obtaining control instructions based on the environmental parameters and the plurality of initialized adjustment units, wherein the environmental parameters include: temperature, humidity, air quality index, and light intensity; Acquire a data set to be processed according to control instructions, preset operating frequencies, and pre-built multimodal sensors; A pre-built central control system is used to standardize a dataset to be processed to obtain a standardized dataset, wherein the central control system includes: a dynamic balancing module, an adaptive adjustment module, a cloud storage platform, and an intelligent optimization service system, wherein the cloud storage platform includes: a distributed database, an encrypted transmission protocol, a self-learning module, and an anomaly detection module, wherein the intelligent optimization service system includes: an environmental health assessment model, a historical trend database, and a decision support tool; Using a self-learning module to simulate a standardized data set to obtain a simulated data set, and generating a status report based on the simulated data set; Use the anomaly detection module to analyze the status report and obtain the abnormal status; Obtaining an abnormal status report based on the abnormal status, optimizing the abnormal status report using an intelligent optimization service system to obtain an optimized status report, wherein the optimized status report includes: environmental equipment status and environmental parameter data; Analyze the optimization status report to obtain environmental equipment status and environmental parameter data. If the environmental equipment status is a preset abnormal environmental equipment status, diagnose the environmental equipment using the environmental health assessment model to obtain a diagnosis result. Based on the diagnosis result, obtain a maintenance plan. Use the maintenance plan to perform maintenance operations on the environmental equipment until the environmental equipment returns to a preset standard environmental equipment. If the environmental parameter data is abnormal environmental parameter data, the abnormal environmental parameter data is marked and adjusted by the intelligent optimization service system until the environmental parameter data is within the environmental parameter range preset by the intelligent optimization service system, and the environmental parameter data is securely transmitted using the encryption transmission protocol to obtain transmission data, and the transmission data is stored in a distributed database to obtain normal environmental parameter data; A temperature and humidity adjustment method for intelligent ventilation control is completed based on standard environmental equipment and normal environmental parameter data.

2. The temperature and humidity adjustment method based on intelligent ventilation control according to claim 1, characterized in that: The confirmed environmental parameters, include: Among them, the multimodal sensors include: temperature and humidity sensors, air quality sensors, light intensity sensors and infrared detectors; Obtain multiple historical monitoring periods, where the multiple historical monitoring periods include: morning, noon, evening and late night; Extract historical monitoring periods from multiple historical monitoring periods in sequence, and perform the following operations on the extracted historical monitoring periods: Based on the extracted historical monitoring period and the pre-constructed historical environmental unit detected by multimodal sensors, the temperature, humidity, air quality index and light intensity of the historical environmental unit are obtained; If the temperature is not within the preset temperature range or the humidity is not within the preset humidity range, the central control system is used to reconfigure the operating mode of the historical environment unit to obtain a configured environment unit, and the operating temperature and operating humidity of the configured environment unit are detected, with the operating temperature being the temperature and the operating humidity being the humidity, until the temperature is within the temperature range and the humidity is within the humidity range, then it is confirmed that the air quality index is within the preset air quality range, wherein the operating modes include: cooling, heating and ventilation; If the air quality index is not within the preset air quality range, the central control system automatically adjusts the working intensity of the air purifier until the air quality index is within the said air quality range; If the light intensity is not within the preset light intensity range, the central control system automatically adjusts the opening and closing degree of the shading device until the light intensity is within the said light intensity range; After confirming that the temperature is within the temperature range, the humidity is within the humidity range, the air quality index is within the air quality range, and the light intensity is within the light intensity range, the environmental parameters are obtained.

3. The temperature and humidity adjustment method based on intelligent ventilation control according to claim 1, characterized in that: The step of extracting adjustment units from the pre-built multiple adjustment units in sequence and performing initialization operations on the extracted adjustment units to obtain multiple initialized adjustment units includes: Extract adjustment units from the pre-built multiple adjustment units in sequence, and perform the following operations on the extracted adjustment units: The efficiency loss formula of the regulating unit is obtained based on the extracted regulating unit and central control system, and the performance degradation percentage is calculated based on the efficiency loss formula of the regulating unit. The efficiency loss formula of the regulating unit is as follows: ； in Indicates the percentage of performance degradation, To adjust the actual output capacity of the unit, It is the theoretical maximum output capacity of the regulating unit under ideal conditions; If the performance degradation percentage is greater than 10, the extracted adjustment unit needs to be initialized, and an adjustment unit that needs to be initialized is obtained; otherwise, the adjustment unit does not need to be initialized, and a first initialized adjustment unit is obtained; Performing an initialization operation on the adjustment unit to be initialized to obtain a second initialized adjustment unit; The second initialization adjustment unit and the first initialization adjustment unit are aggregated to obtain a plurality of initialization adjustment units.

4. The temperature and humidity adjustment method based on intelligent ventilation control according to claim 3, characterized in that: The initialization operation is performed on the adjustment unit to be initialized to obtain a second initialization adjustment unit, including: Using a central control system to mark the adjustment unit to be initialized to obtain a marked adjustment unit, and powering off the marked adjustment unit to obtain a target adjustment unit, and constructing a three-dimensional reference coordinate system, wherein the coordinates of the target adjustment unit are preset in the three-dimensional reference coordinate system; Using the three-dimensional reference coordinate system and the automated maintenance robot to obtain the current coordinates in real time, fitting a movement path based on the current coordinates and the coordinates of the target adjustment unit, and controlling the automated maintenance robot to move along the movement path using a central control system until the current coordinates are equal to the coordinates of the target adjustment unit, and then obtaining an initialization instruction; Using a pre-built camera in the automated maintenance robot to photograph the target adjustment unit to obtain an image of the adjustment unit surface, wherein the automated maintenance robot also includes: a cleaning device, a lubrication system, and a calibration tool; One or more areas to be initialized are acquired using the central control system and the surface image of the regulating unit, and the following operations are performed on each of the one or more areas to be initialized: Initialization parameters are set according to the area to be initialized, the area to be initialized is cleaned using a cleaning device to obtain a clean area, a lubrication system is started according to the initialization parameters to obtain a post-startup lubrication system, the clean area is lubricated using the post-startup lubrication system to obtain a post-lubrication area, and the post-lubrication area is calibrated using a calibration tool to obtain an initialized area; After confirming that the regions to be initialized in the one or more regions to be initialized are all initialized regions, a second initialization adjustment unit is obtained.

5. The temperature and humidity adjustment method based on intelligent ventilation control according to claim 1, characterized in that: The abnormality detection module is used to analyze the status report to obtain the abnormal status, including: The status reports are grouped according to a preset unit analysis period using an anomaly detection module to obtain a plurality of unit status reports, and the following operations are performed on each of the plurality of unit status reports: extracting the temperature of the environmental unit and the humidity of the environmental unit from the unit status report; Determining a state matching value of the unit state report using the temperature of the environment unit, the humidity of the environment unit, and a pre-established state matching rule; If the state matching value is equal to 0, it indicates that the temperature of the environmental unit and the humidity of the environmental unit are in a balanced state, and an initial normal state is obtained. A pre-constructed local deviation factor is used to determine whether the local deviation factor of the initial normal state is higher than the pre-constructed adjacent local deviation factor. If the local deviation factor of the initial normal state is higher than the pre-constructed adjacent local deviation factor, the initial normal state is confirmed as an abnormal state. Otherwise, the initial normal state is skipped. If the state matching value is equal to 1, it means that the ambient unit temperature and the ambient unit humidity are in a non-equilibrium state, resulting in an abnormal state.

6. The temperature and humidity adjustment method based on intelligent ventilation control according to claim 1, characterized in that: The intelligent optimization service system is used to mark and adjust abnormal environmental parameter data until the environmental parameter data is within the environmental parameter range preset by the intelligent optimization service system, including: Utilize the historical trend database to save the environmental parameter data and update the historical trend database in real time, extract the environmental parameter data from the updated historical trend database in sequence, and perform the following operations on the extracted environmental parameter data; Using a decision support tool to mark the extracted environmental parameter data to obtain marked environmental parameter data; If there is no data that is not within the preset environmental parameter range in the marked environmental parameter data, it is confirmed that the environmental parameter data is within the environmental parameter range preset by the intelligent optimization service system; If there is data in the marked environmental parameter data that is not within the preset environmental parameter range, then the data that is not within the preset environmental parameter range is removed from the updated historical trend database to obtain a newly updated historical trend database, and the newly updated historical trend database is used as the updated historical trend database, and the process returns to the step of sequentially extracting environmental parameter data from the updated historical trend database; After confirming that all the extracted environmental parameter data are within the environmental parameter range, an optimal historical trend database is obtained, and all the environmental parameter data in the optimal historical trend database are reconstructed using a periodic optimization model to obtain a plurality of reconstructed environmental parameter data; The following operations are performed on each of the plurality of reconstruction environment parameter data: If the reconstructed environmental parameter data exceeds the preset environmental parameter interval, and the environmental parameter data corresponding to the reconstructed environmental parameter data in the optimal historical trend database exceeds the preset deviation interval, then return to the step of sequentially extracting environmental parameter data from the updated historical trend database until the environmental parameter data is within the environmental parameter interval preset by the intelligent optimization service system; If the reconstructed environmental parameter data exceeds the preset environmental parameter range, and the environmental parameter data corresponding to the reconstructed environmental parameter data in the optimal historical trend database is within the preset deviation range, the preset environmental parameter range is adjusted until the environmental parameter data is within the preset environmental parameter range of the intelligent optimization service system.

7. The temperature and humidity adjustment method based on intelligent ventilation control according to claim 1, characterized in that: The environmental parameter data is securely transmitted using the encryption transmission protocol to obtain transmission data, and the transmission data is stored in a distributed database to obtain normal environmental parameter data. include: The environmental parameter data includes: indoor environmental data and outdoor environmental data; The following encryption operations are performed on the environmental parameter data using the encrypted transmission protocol: The environment parameter data is converted into a ciphertext format using a pre-built data encryption mechanism in the encryption transmission protocol to obtain ciphertext environment parameter data, and a key is randomly generated for the ciphertext environment parameter data to obtain key environment parameter data; Divide the key environment parameter data using a pre-built data segmentation strategy to obtain multiple segmented block environment parameter data; Acquire transmission data based on the plurality of segmentation block environment parameter data and the key environment parameter data; Use distributed database to store and transmit data to obtain normal environmental parameter data.

8. A temperature and humidity control system based on intelligent control, characterized in that: The system comprises: An environmental data acquisition module is used to confirm environmental parameters and sequentially extract adjustment units from a plurality of pre-built adjustment units, perform initialization operations on the extracted adjustment units to obtain a plurality of initialized adjustment units, obtain control instructions based on the environmental parameters and the plurality of initialized adjustment units, wherein the environmental parameters include: temperature, humidity, air quality index and light intensity, and obtain a data set to be processed based on the control instructions, a preset operating frequency and a pre-built multimodal sensor; An environmental data analysis module is used to standardize a dataset to be processed using a pre-built central control system to obtain a standardized dataset, wherein the central control system includes: a dynamic balancing module, an adaptive adjustment module, a cloud storage platform, and an intelligent optimization service system, wherein the cloud storage platform includes: a distributed database, an encrypted transmission protocol, a self-learning module, and an anomaly detection module, wherein the intelligent optimization service system includes: an environmental health assessment model, a historical trend database, and a decision support tool, wherein the self-learning module is used to simulate the standardized dataset to obtain a simulated dataset, a status report is generated based on the simulated dataset, and the status report is analyzed using the anomaly detection module to obtain an abnormal status; an abnormal state processing module, configured to obtain an abnormal state report based on the abnormal state, optimize the abnormal state report using the intelligent optimization service system to obtain an optimized state report, wherein the optimized state report includes: environmental equipment status and environmental parameter data, parse the optimized state report to obtain the environmental equipment status and environmental parameter data, and if the environmental equipment status is a preset environmental equipment abnormal state, diagnose the environmental equipment using an environmental health assessment model to obtain a diagnosis result, obtain a maintenance plan based on the diagnosis result, and perform maintenance operations on the environmental equipment using the maintenance plan until the environmental equipment returns to a preset standard environmental equipment; The dynamic adjustment module is used to mark and adjust the abnormal environmental parameter data using the intelligent optimization service system if the environmental parameter data is abnormal environmental parameter data, until the environmental parameter data is within the environmental parameter range preset by the intelligent optimization service system, and use the encrypted transmission protocol to securely transmit the environmental parameter data to obtain the transmitted data, store the transmitted data in a distributed database, obtain normal environmental parameter data, and complete the temperature and humidity adjustment method of intelligent ventilation control based on standard environmental equipment and normal environmental parameter data.

9. An electronic device, characterized in that: The electronic device comprises: a memory storing at least one instruction; and A processor executes instructions stored in the memory to implement the temperature and humidity adjustment method based on intelligent ventilation control according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores at least one instruction, and the at least one instruction is executed by a processor in an electronic device to implement the temperature and humidity adjustment method based on intelligent ventilation control according to any one of claims 1 to 7.

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