A temperature and humidity adjusting method and system based on intelligent ventilation control

Abstract

The application 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, which comprises the steps of confirming environment parameters, initializing an adjusting unit, obtaining a control instruction, standardizing a data set, generating a state report, optimizing an abnormal state and dynamically adjusting environment parameters. The system comprises an environment data acquisition module, an environment data analysis module, an abnormal state processing module and a dynamic adjustment module. The application realizes dynamic sensing and accurate regulation of environment data through a multi-modal sensor and a central control system, improves adaptability and abnormal identification efficiency by using a self-learning module and an abnormal detection module, and guarantees data security through an encryption transmission protocol. The application can effectively improve the intelligent level and energy-saving effect of environment regulation and is suitable for temperature and humidity management in complex environments.

Description

Technical Field

[0001] This invention belongs to the field of environmental control technology, specifically a method and system for temperature and humidity regulation based on intelligent ventilation control. Background Technology

[0002] With the rapid development of intelligent control technology, its application in 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 saving, demonstrating significant value in various scenarios such as industrial production, agricultural breeding, and daily life. However, despite the progress made in existing technologies, significant shortcomings remain in terms of intelligence level, regulation accuracy, and ability to adapt to complex application scenarios, affecting the overall system performance and user experience.

[0003] A search revealed that patent CN112361487B discloses a temperature and humidity control system and its control method. By setting up a first heat exchange section and a second heat exchange section, and forming multiple heat exchange paths and flow channels, it effectively solves the problem of excessive resistance in traditional technologies, while improving the control accuracy of indoor cooling. However, this technical solution mainly relies on fixed heat exchange logic and air valve control strategies. When facing dynamically changing environmental conditions (such as rapidly changing temperature and humidity or complex gas composition), its adaptive ability is weak, making it difficult to achieve precise real-time adjustment. In addition, the system's intelligence level is limited, failing to fully utilize modern sensor technology and data analysis algorithms to optimize the control strategy, which may lead to high energy consumption or unsatisfactory adjustment effects.

[0004] Another patent, CN119337150B, proposes an intelligent ventilation control method and system for livestock and poultry farming. It uses sensors to monitor the gas state of the farm around the clock and combines this with simulation calculations based on the depositional heat entropy increase effect to design ventilation logic. This enables the system to dynamically adjust ventilation strategies according to changes in gas temperature, humidity, and ammonia / carbon dioxide concentrations. While this technical solution improves upon the level of intelligence, it still has significant shortcomings. Its temperature and humidity control relies primarily on the ventilation logic, lacking direct intervention methods for air temperature and humidity (such as humidification, dehumidification, or heating functions). This may result in the system failing to meet precise temperature and humidity control requirements under extreme environmental conditions (such as high humidity or extremely low temperatures). Furthermore, the system's real-time processing capability for sensor data and the degree of algorithm optimization still need improvement, potentially leading to response lag or control deviations in complex scenarios.

[0005] The aforementioned issues indicate that existing temperature and humidity control systems still have limitations in terms of intelligent control, dynamic adaptability, and adjustment accuracy under extreme environments, making it difficult to fully meet the demands of modern industrial and residential scenarios for efficient and precise temperature and humidity control. Therefore, there is an urgent need to develop a temperature and humidity control method and system based on intelligent ventilation control. By introducing advanced sensor technology, data processing algorithms, and multi-mode adjustment strategies, the system's intelligence and adaptability can be improved, while simultaneously enhancing its ability to cope with extreme environmental conditions, thereby providing users with a more efficient and precise temperature and humidity control solution. Summary of the Invention

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

[0007] To achieve the above objectives, the present invention provides a temperature and humidity regulation method based on intelligent ventilation control, comprising:

[0008] The environmental parameters are confirmed and the control units are extracted sequentially from the pre-built control units. The extracted control units are initialized to obtain multiple initialized control units. Control commands are obtained based on the environmental parameters and the multiple initialized control units. The environmental parameters include: temperature, humidity, air quality index and light intensity.

[0009] The dataset to be processed is acquired based on control commands, preset operating frequencies, and pre-built multimodal sensors.

[0010] The dataset to be processed is standardized using a pre-built central control system to obtain a standardized dataset. The central control system includes a dynamic balancing 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.

[0011] A standardized dataset is simulated using a self-learning module to obtain a simulated dataset, and a status report is generated based on the simulated dataset.

[0012] The anomaly detection module is used to analyze the status report to obtain the abnormal status.

[0013] An abnormal status report is obtained based on the abnormal status, and the abnormal status report is optimized using the intelligent optimization service system to obtain an optimized status report, wherein the optimized status report includes: environmental equipment status and environmental parameter data;

[0014] The environmental equipment status and environmental parameter data are obtained by parsing the optimization status report. If the environmental equipment status is a preset abnormal environmental equipment status, the environmental health assessment model is used to diagnose the environmental equipment and obtain the diagnosis results. Based on the diagnosis results, a maintenance plan is obtained, and maintenance operations are performed on the environmental equipment using the maintenance plan until the environmental equipment becomes a preset standard environmental equipment.

[0015] If the environmental parameter data is abnormal, 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. The environmental parameter data is then securely transmitted using the encrypted transmission protocol to obtain the transmitted data. The transmitted data is stored in a distributed database to obtain normal environmental parameter data.

[0016] A method for intelligent ventilation control based on standard environmental equipment and normal environmental parameter data to regulate temperature and humidity.

[0017] Optionally, the confirmed environmental parameters include:

[0018] The multimodal sensors include: temperature and humidity sensors, air quality sensors, light intensity sensors, and infrared detectors;

[0019] Multiple historical monitoring periods were acquired, including: morning, noon, evening, and late night;

[0020] Extract historical monitoring periods sequentially from multiple historical monitoring periods, and perform the following operations on the extracted historical monitoring periods:

[0021] Based on the extracted historical monitoring periods and the pre-constructed historical environmental units detected by multimodal sensors, the temperature, humidity, air quality index and light intensity of the historical environmental units are obtained;

[0022] If the temperature is not in the preset temperature range or the humidity is not in the preset humidity range, the central control system is used to reconfigure the operating mode of the historical environmental unit to obtain the configured environmental unit. The operating temperature and operating humidity of the configured environmental unit are detected, and the operating temperature is taken as the temperature and the operating humidity is taken as the humidity. This continues until the temperature is in the temperature range and the humidity is in the humidity range. Then, it is confirmed that the air quality index is in the preset air quality range. The operating modes include: cooling, heating and ventilation.

[0023] If the air quality index is not within the preset air quality range, the central control system will automatically adjust the working intensity of the air purifier until the air quality index is within the preset range.

[0024] If the light intensity is not within the preset light intensity range, the central control system will automatically adjust the opening and closing degree of the shading device until the light intensity is within the light intensity range.

[0025] After confirming that the temperature is within the specified temperature range, the humidity is within the specified humidity range, the air quality index is within the specified air quality range, and the light intensity is within the specified light intensity range, the environmental parameters are obtained.

[0026] Optionally, the step of sequentially extracting adjustment units from a plurality of pre-built adjustment units and performing initialization operations on the extracted adjustment units to obtain a plurality of initialized adjustment units includes:

[0027] Extract control units sequentially from a pre-built set of control units, and perform the following operations on each extracted control unit:

[0028] Based on the extracted regulating unit and central control system, the efficiency loss formula of the regulating unit is obtained. The percentage of performance degradation is then calculated using the efficiency loss formula. The efficiency loss formula of the regulating unit is as follows:

[0029] ;

[0030] Where η represents the percentage decrease in the performance of the regulating unit (unit: %). To adjust the actual output capability of the unit in the current state, To adjust the theoretical maximum output capability of the unit under ideal conditions;

[0031] If the performance degradation percentage is greater than 10%, the extracted adjustment unit needs to be initialized, resulting in the adjustment unit that needs to be initialized; otherwise, the adjustment unit does not need to be initialized, resulting in the first initialized adjustment unit.

[0032] The adjustment unit that needs to be initialized is initialized to obtain the second initialization adjustment unit;

[0033] By combining the second initialization adjustment unit and the first initialization adjustment unit, multiple initialization adjustment units are obtained.

[0034] Optionally, the initialization operation of the adjustment unit to be initialized to obtain the second initialization adjustment unit includes:

[0035] The central control system is used to mark the adjustment units that need to be initialized to obtain the marked adjustment units. The marked adjustment units are then powered off to obtain the target adjustment units. A three-dimensional reference coordinate system is constructed, in which the coordinates of the target adjustment units are preset.

[0036] The current coordinates are obtained in real time using the three-dimensional reference coordinate system and the automated maintenance robot. A movement path is fitted based on the current coordinates and the target adjustment unit coordinates. The central control system controls the automated maintenance robot to move along the movement path until the current coordinates are equal to the target adjustment unit coordinates, and then an initialization command is obtained.

[0037] The surface image of the adjustment unit is obtained by using a pre-built camera in the automated maintenance robot to capture images of the target adjustment unit. The automated maintenance robot also includes a cleaning device, a lubrication system, and calibration tools.

[0038] One or more regions to be initialized are obtained using the surface image of the central control system and the regulating unit. The following operations are performed on each of the one or more regions to be initialized:

[0039] Set initialization parameters according to the area to be initialized, clean the area to be initialized using a cleaning device to obtain a clean area, start the lubrication system according to the initialization parameters to obtain a post-started lubrication system, use the post-started lubrication system to lubricate the clean area to obtain a lubricated area, use a calibration tool to calibrate the lubricated area to obtain an initialized area;

[0040] After confirming that all regions to be initialized in one or more regions to be initialized are already initialized, the second initialization adjustment unit is obtained.

[0041] Optionally, the step of analyzing the status report using the anomaly detection module to obtain the abnormal status includes:

[0042] The status reports are grouped according to a preset unit analysis time period using the anomaly detection module to obtain multiple unit status reports. The following operations are performed on each of the multiple unit status reports:

[0043] Extract the temperature and humidity of the environmental unit from the unit status report;

[0044] The state matching value of the unit state report is determined by using the temperature and humidity of the environmental unit and pre-constructed state matching rules.

[0045] If the state matching value is equal to 0, it means that the temperature and humidity of the environmental unit are in equilibrium, and the initial normal state is obtained. The local deviation factor of the initial normal state is used to determine whether the local deviation factor of the initial normal state is higher than the pre-constructed neighboring local deviation factor. If the local deviation factor of the initial normal state is higher than the pre-constructed neighboring local deviation factor, the initial normal state is confirmed as an abnormal state; otherwise, the initial normal state is skipped.

[0046] If the state matching value is equal to 1, it indicates that the temperature and humidity of the environmental unit are in a non-equilibrium state, resulting in an abnormal state.

[0047] Optionally, the step involves using an intelligent optimization service system to mark and adjust abnormal environmental parameter data until the environmental parameter data falls within a preset environmental parameter range of the intelligent optimization service system, including:

[0048] Use a historical trend database to store environmental parameter data and update the historical trend database in real time. Extract environmental parameter data sequentially from the updated historical trend database and perform the following operations on the extracted environmental parameter data.

[0049] The extracted environmental parameter data is labeled using decision support tools to obtain labeled environmental parameter data;

[0050] If there is no data in the marked environmental parameter data that is not located in the preset environmental parameter range, then the environmental parameter data is confirmed to be located in the preset environmental parameter range of the intelligent optimization service system.

[0051] If there are data in the marked environmental parameter data that are not within the preset environmental parameter range, then remove the data that are not within the preset environmental parameter range from the updated historical trend database to obtain a new updated historical trend database. Use the new updated historical trend database as the updated historical trend database and return to the step of extracting environmental parameter data from the updated historical trend database in sequence.

[0052] After confirming that all extracted environmental parameter data are within the environmental parameter range, the optimal historical trend database is obtained. The periodic optimization model is used to reconstruct all environmental parameter data in the optimal historical trend database to obtain multiple reconstructed environmental parameter data.

[0053] Perform the following operations on the refactoring environment parameter data in multiple refactoring environment parameter data sets:

[0054] 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 exceeds the preset deviation range, 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 preset environmental parameter range of the intelligent optimization service system.

[0055] 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, then the preset environmental parameter range will be adjusted until the environmental parameter data is within the preset environmental parameter range of the intelligent optimization service system.

[0056] Optionally, the step of securely transmitting environmental parameter data using the encrypted transmission protocol to obtain transmitted data, and storing the transmitted data in a distributed database to obtain normal environmental parameter data, includes:

[0057] The environmental parameter data includes: indoor environmental data and outdoor environmental data;

[0058] The following encryption operations are performed on all environmental parameter data using an encrypted transmission protocol:

[0059] The environment parameter data is converted into ciphertext format using the pre-built data encryption mechanism in the encrypted transmission protocol to obtain ciphertext environment parameter data. A key is then randomly generated from the ciphertext environment parameter data to obtain key environment parameter data.

[0060] The key environment parameter data is divided using a pre-built data segmentation strategy to obtain multiple segmented blocks of environment parameter data;

[0061] The transmitted data is obtained based on multiple segmented block environment parameter data and key environment parameter data;

[0062] By utilizing a distributed database to store and transmit data, normal environmental parameter data can be obtained.

[0063] To achieve the above objectives, the present invention also provides a temperature and humidity control system based on intelligent control, comprising:

[0064] The environmental data acquisition module is used to confirm environmental parameters and extract adjustment units sequentially from multiple pre-built adjustment units, and perform initialization operations on the extracted adjustment units to obtain multiple initial adjustment units. Based on the environmental parameters and multiple initial adjustment units, control commands are obtained. The environmental parameters include temperature, humidity, air quality index and light intensity. The data set to be processed is obtained according to the control commands, the preset operating frequency and the pre-built multimodal sensors.

[0065] The environmental data analysis module is used to standardize the dataset to be processed using a pre-built central control system to obtain a standardized dataset. The central control system includes a dynamic balancing 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 self-learning module simulates the standardized dataset to obtain a simulated dataset. A status report is generated based on the simulated dataset. The anomaly detection module analyzes the status report to obtain abnormal states.

[0066] An abnormal state handling module is used to obtain an abnormal state report based on the abnormal state, optimize the abnormal state report using an intelligent optimization service system to obtain an optimized state report, wherein the optimized state report includes: environmental equipment status and environmental parameter data. The module parses the optimized state report to obtain the environmental equipment status and environmental parameter data. If the environmental equipment status is a preset abnormal environmental equipment status, the module uses an environmental health assessment model to diagnose the environmental equipment and obtain a diagnosis result. Based on the diagnosis result, the module obtains a maintenance plan and uses the maintenance plan to perform maintenance operations on the environmental equipment until the environmental equipment becomes a preset standard environmental equipment.

[0067] 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, until the environmental parameter data falls within the preset environmental parameter range of the intelligent optimization service system. The module then uses the encrypted transmission protocol to securely transmit the environmental parameter data, obtains the transmitted data, stores the transmitted data in a distributed database, and obtains the normal environmental parameter data. Based on standard environmental equipment and normal environmental parameter data, the module completes the temperature and humidity regulation method for intelligent ventilation control.

[0068] To address the above problems, the present invention also provides an electronic device, the electronic device comprising:

[0069] Memory, storing at least one instruction; and

[0070] The processor executes the instructions stored in the memory to implement the temperature and humidity regulation method based on intelligent ventilation control described above.

[0071] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the temperature and humidity regulation method based on intelligent ventilation control described above.

[0072] Compared to the problems described in the background art, this invention first identifies environmental parameters and sequentially extracts adjustment units from a pre-built set of adjustment units. Initialization operations are then performed on the extracted adjustment units to obtain multiple initialized adjustment units. Control commands are obtained based on the environmental parameters and the multiple initialized adjustment units. The environmental parameters include temperature, humidity, air quality index, and light intensity. In this embodiment, an automated maintenance robot operates the adjustment units to be initialized, improving initialization efficiency and reducing manual intervention. The dataset to be processed is obtained based on the control commands, a preset operating frequency, and a pre-built multimodal sensor. This invention sets the operating frequency to acquire environmental data in real time. The dataset to be processed is standardized using a pre-built central control system to obtain a standardized dataset. The standardization process described in this embodiment unifies data from different sources onto the same benchmark, facilitating analysis. A self-learning module simulates the standardized dataset to obtain a simulated dataset. A status report is generated based on the simulated dataset. The simulation process facilitates prediction based on different needs, improving adaptability. An anomaly detection module analyzes the status report to obtain abnormal states. This invention employs two methods to analyze abnormal states, improving the efficiency of identifying abnormal states. Anomaly states are then obtained based on these abnormal states. The report utilizes an intelligent optimization service system to optimize abnormal status reports, resulting in an optimized status report. This optimized status report includes environmental equipment status and environmental parameter data. Parsing the optimized status report yields the environmental equipment status and environmental parameter data. If the environmental equipment status is a preset abnormal state, an environmental health assessment model is used to diagnose the environmental equipment, obtaining diagnostic results. Based on these results, a maintenance plan is obtained, and maintenance operations are performed on the environmental equipment until it returns to a preset standard state. The environmental health assessment model described in this embodiment can promptly identify potential equipment problems, thereby improving environmental regulation efficiency. If the environmental parameter data is abnormal, the intelligent optimization service system marks and adjusts the abnormal environmental parameter data until it falls within a preset environmental parameter range. After adjusting the abnormal environmental data, the remaining environmental data is reconstructed to obtain new environmental data. Furthermore, the encrypted transmission protocol is used to securely transmit the environmental parameter data, obtaining transmitted data. This transmitted data is stored in a distributed database to obtain normal environmental parameter data. Based on standard environmental equipment and normal environmental parameter data, a method for intelligent ventilation control of temperature and humidity is completed. Therefore, the present invention can dynamically sense environmental changes and accurately adjust environmental parameters, thereby improving the system's intelligence level and energy-saving effect. Attached Figure Description

[0073] Figure 1 This is a schematic flowchart of a temperature and humidity regulation method based on intelligent ventilation control provided in an embodiment of the present invention.

[0074] Figure 2 A functional block diagram of a temperature and humidity control system based on intelligent control provided in an embodiment of the present invention;

[0075] Figure 3 This is a schematic diagram of the structure of an electronic device that implements the temperature and humidity regulation method based on intelligent ventilation control, according to an embodiment of the present invention. Detailed Implementation

[0076] This invention provides a temperature and humidity regulation method and system based on intelligent ventilation control. It achieves efficient management of temperature and humidity conditions in complex environments by dynamically sensing environmental parameters and combining them with an intelligent optimization service system. The following is in conjunction with the appendix... Figure 1 To be continued Figure 3 The specific embodiments of the present invention will be described in detail below.

[0077] In practical applications, this invention first requires confirming environmental parameters and acquiring relevant data through multimodal sensors. For example... Figure 1 As shown, the multimodal sensor 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 the comprehensiveness of the collected data, the system sequentially extracts historical monitoring time periods (morning, noon, evening, and late night) and uses the multimodal sensor to detect pre-constructed historical environmental units, obtaining the temperature, humidity, air quality index, and light intensity of the historical environmental units. If the detected temperature or humidity is outside the preset temperature or humidity range, the central control system will reconfigure the operating mode of the historical environmental unit, such as cooling, heating, or ventilation, until both temperature and humidity are within the preset range. Subsequently, the system will further confirm whether the air quality index is within the preset air quality range. If it does not meet the requirements, the air purifier's operating intensity will be automatically adjusted. At the same time, the light intensity is also monitored in real time. If it exceeds the preset range, the central control system will automatically adjust the opening and closing degree of the shading device until all environmental parameters meet the requirements.

[0078] After confirming the environmental parameters, the system sequentially extracts control units from a pre-built set of control units and performs initialization operations on the extracted control units. First, based on the extracted control units and the central control system, the efficiency loss formula for the control units is obtained:

[0079] ;

[0080] Where η represents the percentage decrease in the performance of the regulating unit (unit: %). To adjust the actual output capability of the unit in the current state, This is to adjust the theoretical maximum output capability of the unit under ideal conditions.

[0081] When η > 10%, it indicates that the performance loss of the regulating unit exceeds 10% due to aging, dirt accumulation, etc., and initialization is required. When η ≤ 10%, the performance of the regulating unit meets the normal working requirements and does not require initialization; it can be directly used as the first regulating unit to be initialized. For regulating units that need initialization, the system will use an automated maintenance robot to operate them. Specifically, the central control system will mark the regulating unit to be initialized and power it off, then construct a three-dimensional reference coordinate system to determine the coordinate position of the target regulating unit. The automated maintenance robot will acquire the current coordinates in real time, fit a movement path, and move along the path to the target regulating unit position. After reaching the target position, the robot will use a camera to take an image of the regulating unit surface and, in conjunction with the central control system, identify one or more areas that need initialization. For each area that needs initialization, the system will set initialization parameters, use a cleaning device to clean the surface dirt, start the lubrication system to lubricate the cleaned area, and finally use a calibration tool to complete the calibration operation to ensure that the regulating unit is restored to its optimal working state.

[0082] After initialization, the system acquires control commands based on environmental parameters and multiple initialization adjustment units, and obtains the dataset to be processed according to the control commands, preset operating frequency, and multimodal sensors. For example... Figure 2 As shown, the environmental data acquisition module is responsible for the above operations. Its core function is to collect environmental data in real time by setting a reasonable operation frequency, thereby ensuring the timeliness and accuracy of the data. The dataset to be processed 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 balancing 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 the standardization process is to unify data from different sources onto the same benchmark, facilitating subsequent analysis and optimization.

[0083] After standardization, the system uses a self-learning module to simulate the standardized dataset, generating a simulated dataset and a status report based on it. The self-learning module employs deep learning algorithms to continuously optimize the prediction model by learning from historical data, thereby improving the system's adaptability and intelligence. The status reports are then transmitted to the anomaly detection module, which groups the reports according to preset unit analysis periods and performs a status matching rule judgment on each unit's 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 is equal to 0, it indicates that the temperature and humidity are in equilibrium, and the system will further use the local deviation factor to determine whether there is an anomaly in the initial normal state; if the state matching value is equal to 1, it is directly confirmed as an abnormal state. The dual-layer screening mechanism of the anomaly detection module effectively improves the accuracy and efficiency of anomaly state identification.

[0084] When the system detects an abnormal state, it generates an abnormal state report and transmits it to the intelligent optimization service system for optimization processing. For example... Figure 2 As shown, the abnormal status handling module is responsible for parsing the optimization status report and extracting environmental equipment status and environmental parameter data. If the environmental equipment status is a preset abnormal status, the system will use the environmental health assessment model to diagnose the equipment. The environmental health assessment model is based on machine learning algorithms and can quickly identify potential problems and generate maintenance plans. The maintenance plan is executed by the processor of the electronic equipment, performing maintenance operations on the equipment through automated means until the equipment is restored to a 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 remove abnormal data that does not conform to 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.

[0085] After data optimization, the system will use an encrypted transmission protocol to securely transmit environmental parameter data. For example... Figure 3 As shown, the encrypted transmission protocol includes a data encryption mechanism and a data segmentation strategy. First, environmental parameter data is converted into ciphertext format, and a randomly generated key is used to enhance security. Then, the key-based environmental parameter data is divided into multiple blocks, ensuring that even if some data is leaked, the complete information cannot be recovered. 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 an intelligent ventilation control method for temperature and humidity regulation.

[0086] The present invention also provides an electronic device, the structure of which is as follows: Figure 3As shown, the system includes a memory and a processor. The memory stores at least one instruction, while the processor executes the instructions in the memory to implement the aforementioned method. Furthermore, the present invention provides a computer-readable storage medium storing at least one instruction that, when executed by a processor in an electronic device, enables the implementation of the aforementioned method. Through the above technical solutions, the present invention achieves dynamic sensing and precise control of temperature and humidity conditions in complex environments, significantly improving the system's intelligence level and energy-saving effect, and has broad application prospects.

Claims

1. A method for temperature and humidity regulation based on intelligent ventilation control, characterized in that, The method includes: The environmental parameters are confirmed and the control units are extracted sequentially from the pre-built control units. The extracted control units are initialized to obtain multiple initialized control units. Control commands are obtained based on the environmental parameters and the multiple initialized control units. The environmental parameters include: temperature, humidity, air quality index and light intensity. The dataset to be processed is acquired based on control commands, preset operating frequencies, and pre-built multimodal sensors. The dataset to be processed is standardized using a pre-built central control system to obtain a standardized dataset. The central control system includes a dynamic balancing 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. A standardized dataset is simulated using a self-learning module to obtain a simulated dataset, and a status report is generated based on the simulated dataset. The anomaly detection module is used to analyze the status report to obtain the abnormal status. The abnormal status is obtained by analyzing the status report using the anomaly detection module, including: The status reports are grouped according to a preset unit analysis time period using the anomaly detection module to obtain multiple unit status reports. The following operations are performed on each of the multiple unit status reports: Extract the temperature and humidity of the environmental unit from the unit status report; The state matching value of the unit state report is determined by using the temperature and humidity of the environmental unit and pre-constructed state matching rules. If the state matching value is equal to 0, it means that the temperature and humidity of the environmental unit are in equilibrium, and the initial normal state is obtained. The local deviation factor of the initial normal state is used to determine whether the local deviation factor of the initial normal state is higher than the pre-constructed neighboring local deviation factor. If the local deviation factor of the initial normal state is higher than the pre-constructed neighboring 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 indicates that the temperature and humidity of the environmental unit are in a non-equilibrium state, resulting in an abnormal state. An abnormal status report is obtained based on the abnormal status, and the abnormal status report is optimized using the intelligent optimization service system to obtain an optimized status report, wherein the optimized status report includes: environmental equipment status and environmental parameter data; The environmental equipment status and environmental parameter data are obtained by parsing the optimization status report. If the environmental equipment status is a preset abnormal environmental equipment status, the environmental health assessment model is used to diagnose the environmental equipment and obtain the diagnosis results. Based on the diagnosis results, a maintenance plan is obtained, and maintenance operations are performed on the environmental equipment using the maintenance plan until the environmental equipment becomes a preset standard environmental equipment. If the environmental parameter data is abnormal, 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. The environmental parameter data is then securely transmitted using the encrypted transmission protocol to obtain the transmitted data. The transmitted data is stored in a distributed database to obtain normal environmental parameter data. A method for intelligent ventilation control based on standard environmental equipment and normal environmental parameter data to regulate temperature and humidity.

2. The temperature and humidity control method based on intelligent ventilation control as described in claim 1, characterized in that, The confirmed environmental parameters include: The multimodal sensors include: temperature and humidity sensors, air quality sensors, light intensity sensors, and infrared detectors; Multiple historical monitoring periods were acquired, including: morning, noon, evening, and late night; Extract historical monitoring periods sequentially from multiple historical monitoring periods, and perform the following operations on the extracted historical monitoring periods: Based on the extracted historical monitoring periods and the pre-constructed historical environmental units detected by multimodal sensors, the temperature, humidity, air quality index and light intensity of the historical environmental units are obtained; If the temperature is not in the preset temperature range or the humidity is not in the preset humidity range, the central control system is used to reconfigure the operating mode of the historical environmental unit to obtain the configured environmental unit. The operating temperature and operating humidity of the configured environmental unit are detected, and the operating temperature is taken as the temperature and the operating humidity is taken as the humidity. This continues until the temperature is in the temperature range and the humidity is in the humidity range. Then, it is confirmed that the air quality index is in the preset air quality range. 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 will automatically adjust the working intensity of the air purifier until the air quality index is within the preset range. If the light intensity is not within the preset light intensity range, the central control system will automatically adjust the opening and closing degree of the shading device until the light intensity is within the light intensity range. After confirming that the temperature is within the specified temperature range, the humidity is within the specified humidity range, the air quality index is within the specified air quality range, and the light intensity is within the specified light intensity range, the environmental parameters are obtained.

3. The temperature and humidity control method based on intelligent ventilation control as described in claim 1, characterized in that, The step of sequentially extracting adjustment units from a pre-constructed plurality of adjustment units and performing initialization operations on the extracted adjustment units to obtain a plurality of initialized adjustment units includes: Extract control units sequentially from a pre-built set of control units, and perform the following operations on each extracted control unit: Based on the extracted regulating unit and central control system, the efficiency loss formula of the regulating unit is obtained. The percentage of performance degradation is then calculated using the efficiency loss formula, which is shown below: ； Where η represents the percentage decrease in the performance of the regulating unit (unit: %). To adjust the actual output capability of the unit in the current state, To adjust the theoretical maximum output capability of the unit under ideal conditions; If the performance degradation percentage is greater than 10%, the extracted adjustment unit needs to be initialized, resulting in the adjustment unit that needs to be initialized; otherwise, the adjustment unit does not need to be initialized, resulting in the first initialized adjustment unit. The adjustment unit that needs to be initialized is initialized to obtain the second initialization adjustment unit; By combining the second initialization adjustment unit and the first initialization adjustment unit, multiple initialization adjustment units are obtained.

4. The temperature and humidity control method based on intelligent ventilation control as described in claim 3, characterized in that, The initialization operation of the adjustment unit to be initialized, to obtain the second initialization adjustment unit, includes: The central control system is used to mark the adjustment units that need to be initialized to obtain the marked adjustment units. The marked adjustment units are then powered off to obtain the target adjustment units. A three-dimensional reference coordinate system is constructed, in which the coordinates of the target adjustment units are preset. The current coordinates are obtained in real time using the three-dimensional reference coordinate system and the automated maintenance robot. A movement path is fitted based on the current coordinates and the target adjustment unit coordinates. The central control system controls the automated maintenance robot to move along the movement path until the current coordinates are equal to the target adjustment unit coordinates, and then an initialization command is obtained. The surface image of the adjustment unit is obtained by using a pre-built camera in the automated maintenance robot to capture images of the target adjustment unit. The automated maintenance robot also includes a cleaning device, a lubrication system, and calibration tools. One or more regions to be initialized are obtained using the surface image of the central control system and the regulating unit. The following operations are performed on each of the one or more regions to be initialized: Set initialization parameters according to the area to be initialized, clean the area to be initialized using a cleaning device to obtain a clean area, start the lubrication system according to the initialization parameters to obtain a post-started lubrication system, use the post-started lubrication system to lubricate the clean area to obtain a lubricated area, use a calibration tool to calibrate the lubricated area to obtain an initialized area; After confirming that all regions to be initialized in one or more regions to be initialized are already initialized, the second initialization adjustment unit is obtained.

5. The temperature and humidity control method based on intelligent ventilation control as described in claim 1, characterized in that, The process involves using an intelligent optimization service system to mark and adjust abnormal environmental parameter data until the environmental parameter data falls within a preset range of the intelligent optimization service system, including: Use a historical trend database to store environmental parameter data and update the historical trend database in real time. Extract environmental parameter data sequentially from the updated historical trend database and perform the following operations on the extracted environmental parameter data. The extracted environmental parameter data is labeled using decision support tools to obtain labeled environmental parameter data; If there is no data in the marked environmental parameter data that is not located in the preset environmental parameter range, then the environmental parameter data is confirmed to be located in the preset environmental parameter range of the intelligent optimization service system. If there are data in the marked environmental parameter data that are not within the preset environmental parameter range, then remove the data that are not within the preset environmental parameter range from the updated historical trend database to obtain a new updated historical trend database. Use the new updated historical trend database as the updated historical trend database and return to the step of extracting environmental parameter data from the updated historical trend database in sequence. After confirming that all extracted environmental parameter data are within the environmental parameter range, the optimal historical trend database is obtained. The periodic optimization model is used to reconstruct all environmental parameter data in the optimal historical trend database to obtain multiple reconstructed environmental parameter data. Perform the following operations on the refactoring environment parameter data in multiple refactoring environment parameter data sets: 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 exceeds the preset deviation range, 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 preset environmental parameter range of 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, then the preset environmental parameter range will be adjusted until the environmental parameter data is within the preset environmental parameter range of the intelligent optimization service system.

6. The temperature and humidity control method based on intelligent ventilation control as described in claim 1, characterized in that, The environmental parameter data is securely transmitted using the encrypted transmission protocol to obtain the transmitted data. This transmitted data is then 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 all environmental parameter data using an encrypted transmission protocol: The environment parameter data is converted into ciphertext format using the pre-built data encryption mechanism in the encrypted transmission protocol to obtain ciphertext environment parameter data. A key is then randomly generated from the ciphertext environment parameter data to obtain key environment parameter data. The key environment parameter data is divided using a pre-built data segmentation strategy to obtain multiple segmented blocks of environment parameter data; The transmitted data is obtained based on multiple segmented block environment parameter data and key environment parameter data; By utilizing a distributed database to store and transmit data, normal environmental parameter data can be obtained.

7. A temperature and humidity control system based on intelligent control, used to implement the temperature and humidity control method based on intelligent ventilation control as described in claims 1 to 6, characterized in that, The system includes: The environmental data acquisition module is used to confirm environmental parameters and extract adjustment units sequentially from multiple pre-built adjustment units, and perform initialization operations on the extracted adjustment units to obtain multiple initial adjustment units. Based on the environmental parameters and multiple initial adjustment units, control commands are obtained. The environmental parameters include temperature, humidity, air quality index and light intensity. The data set to be processed is obtained according to the control commands, the preset operating frequency and the pre-built multimodal sensors. The environmental data analysis module is used to standardize the dataset to be processed using a pre-built central control system to obtain a standardized dataset. The central control system includes a dynamic balancing 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 self-learning module simulates the standardized dataset to obtain a simulated dataset. A status report is generated based on the simulated dataset. The anomaly detection module analyzes the status report to obtain abnormal states. An abnormal state handling module is used to obtain an abnormal state report based on the abnormal state, optimize the abnormal state report using an intelligent optimization service system to obtain an optimized state report, wherein the optimized state report includes: environmental equipment status and environmental parameter data. The module parses the optimized state report to obtain the environmental equipment status and environmental parameter data. If the environmental equipment status is a preset abnormal environmental equipment status, the module uses an environmental health assessment model to diagnose the environmental equipment and obtain a diagnosis result. Based on the diagnosis result, the module obtains a maintenance plan and uses the maintenance plan to perform maintenance operations on the environmental equipment until the environmental equipment becomes a preset standard environmental equipment. The process of obtaining an abnormal status report based on the abnormal status includes: The status reports are grouped according to a preset unit analysis time period using the anomaly detection module to obtain multiple unit status reports. The following operations are performed on each of the multiple unit status reports: Extract the temperature and humidity of the environmental unit from the unit status report; The state matching value of the unit state report is determined by using the temperature and humidity of the environmental unit and pre-constructed state matching rules. If the state matching value is equal to 0, it means that the temperature and humidity of the environmental unit are in equilibrium, and the initial normal state is obtained. The local deviation factor of the initial normal state is used to determine whether the local deviation factor of the initial normal state is higher than the pre-constructed neighboring local deviation factor. If the local deviation factor of the initial normal state is higher than the pre-constructed neighboring 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 indicates that the temperature and humidity of the environmental unit are in a non-equilibrium state, resulting in an abnormal state. 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, until the environmental parameter data falls within the preset environmental parameter range of the intelligent optimization service system. The module then uses the encrypted transmission protocol to securely transmit the environmental parameter data, obtains the transmitted data, stores the transmitted data in a distributed database, and obtains the normal environmental parameter data. Based on standard environmental equipment and normal environmental parameter data, the module completes the temperature and humidity regulation method for intelligent ventilation control.

8. An electronic device, characterized in that, The electronic device includes: Memory, storing at least one instruction; and The processor executes instructions stored in the memory to implement the temperature and humidity regulation method based on intelligent ventilation control as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction, which is executed by a processor in an electronic device to implement the temperature and humidity regulation method based on intelligent ventilation control as described in any one of claims 1 to 6.

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