Air conditioner operation safety monitoring and alarming system based on Internet of Things

Abstract

The invention discloses an air conditioner operation safety monitoring and alarming system based on the Internet of Things. According to the system, the operation data, such as temperature, humidity, current and voltage, of the air conditioner are collected in real time through the sensor module and analyzed through the data processing module. And the real-time monitoring sub-module can find problems in time, such as abnormal temperature rise or abnormal current increase, so that equipment faults or safety accidents can be prevented. The data processing and analysis sub-module uses analysis methods such as a moving average algorithm and the like to provide insight of the temperature change trend and help users and operation and maintenance personnel to make more proper decisions. The predictive maintenance sub-module can predict the future state of the equipment through analyzing historical data, and discover potential faults in advance, thereby reducing sudden faults and maintenance cost. The security and management sub-module ensures the security of data, prevents unauthorized access and data leakage, monitors the operation state of the system, and ensures the stability and reliability of the system.

Description

Technical Field

[0001] The present invention belongs to the technical field of air conditioner safety monitoring, and specifically relates to an air conditioner operation safety monitoring and alarm system based on the Internet of Things. Background Art

[0002] Air conditioning operation safety monitoring is a monitoring system designed to ensure the safe, stable, and efficient operation of air conditioning systems. Through real-time monitoring and data analysis of air conditioning equipment, the system can help users promptly identify and resolve potential safety hazards, ensuring the normal operation of the air conditioning system. The main functions of air conditioning operation safety monitoring include: Real-time data monitoring: The system uses sensors to collect real-time operating data from air conditioning equipment, such as temperature, humidity, current, voltage, and other data, as well as the equipment's operating status. Abnormal alarm: When the monitored air conditioning system operating data exceeds the normal range or the equipment malfunctions, the system immediately issues an alarm signal, notifying relevant personnel for prompt action. Data analysis: The system conducts in-depth analysis of the collected data to identify potential fault causes and operating trends, providing decision-making support for users. Remote control: Users can remotely control the air conditioning equipment's start / stop, adjust the temperature, and other operations, facilitating remote management of the air conditioning system. Maintenance reminders: The system automatically reminds users to perform maintenance and servicing based on the equipment's operating hours and maintenance cycles, ensuring normal operation. In short, air conditioning operation safety monitoring is a valuable tool that helps users monitor the operating status of their air conditioning systems in real time, promptly identify and resolve potential safety hazards, and improve the safety and efficiency of the air conditioning system. With the widespread application of air-conditioning systems and the continuous advancement of technology, air-conditioning operation safety monitoring will play an increasingly important role in the operation and maintenance of air-conditioning systems.

[0003] However, common monitoring systems cannot monitor the system operation status, cannot detect and handle system anomalies in a timely manner, and thus affect the stable operation of the system. Summary of the Invention

[0004] The purpose of the present invention is to provide an air conditioning operation safety monitoring and alarm system based on the Internet of Things in order to solve the above-mentioned problems.

[0005] The technical solution adopted by the present invention is as follows: an air-conditioning operation safety monitoring and alarm system based on the Internet of Things, the system comprising: a sensor module, a data processing module, a communication module, a cloud platform module, an alarm module, a user interface module and a control module;

[0006] The data processing module is internally provided with: a data storage submodule, a data processing and analysis submodule, a real-time monitoring submodule, a predictive maintenance submodule and a security and management submodule;

[0007] The sensor module is connected to the data processing module: the raw data collected by the sensor module needs to be processed by the data processing module to extract useful information and convert it into a standard format.

[0008] The data processing module is connected to the sensor module to receive and process the data collected by the sensor. The data processing module is connected to the communication module to send the processed data to the communication module for uploading to the cloud platform.

[0009] The communication module is connected to the cloud platform module: data is uploaded to the cloud platform via a wireless network.

[0010] The cloud platform module is connected to the communication module, which receives uploaded data and stores, analyzes, and processes it. It is also connected to the alarm module, which triggers the alarm when an anomaly is detected. It is also connected to the user interface module, which provides real-time monitoring and historical data for user query. It is also connected to the control module, which receives control commands from the user interface to enable remote control of the air conditioner.

[0011] The alarm module is connected to the cloud platform module to receive alarm signals from the cloud platform and execute alarm operations. The alarm module is connected to the user interface module to display alarm information to the user. The user interface module is connected to the cloud platform module to obtain real-time monitoring data and historical data from the cloud platform and display them to the user.

[0012] In a preferred embodiment, the sensor module serves as the front end of the system, responsible for real-time monitoring of the air conditioner's operating status. It includes temperature sensors, humidity sensors, current sensors, and voltage sensors. The temperature sensor monitors the air conditioner's internal and external temperatures to ensure it operates within the appropriate temperature range; the humidity sensor monitors humidity to ensure proper dehumidification; the current sensor monitors the air conditioner's current to determine load conditions; and the voltage sensor monitors the air conditioner's voltage to ensure it operates at a stable voltage. These sensors transmit the collected data in real time to the data processing module, providing raw data for subsequent analysis and processing.

[0013] In a preferred embodiment, the data processing module processes the received raw data, extracts useful information, and converts it into a standard format. This module includes functions such as data cleaning, data aggregation, and data compression to ensure data accuracy and validity. The data processing module also performs data preprocessing, such as removing outliers and filling in missing values, to provide high-quality data for subsequent data analysis and processing.

[0014] In a preferred embodiment, the communication module is responsible for transmitting the processed data to the cloud platform via a wireless network. Multiple communication methods are supported, such as WiFi, Bluetooth, and ZigBee. The communication module packages the data output by the data processing module and transmits it to the cloud platform via wireless signals.

[0015] In a preferred embodiment, the data storage submodule is responsible for receiving raw data from sensors, formatting this data, and storing it in a database. This submodule first timestamps the data to ensure its timeliness and traceability. It then stores the data in real-time and historical data tables to facilitate subsequent data processing and analysis. The data storage submodule also regularly clears old data to free up storage space and improve database performance. Furthermore, the data storage submodule ensures data security and integrity to prevent unauthorized access or tampering.

[0016] In a preferred embodiment, the data processing and analysis submodule uses a moving average algorithm to process and analyze temperature data. The calculation process of the moving average algorithm is as follows:

[0017] a. Data preparation: Retrieve real-time or historical data from the temperature sensor from the data storage submodule. Ensure that the data is arranged in chronological order.

[0018] b. Parameter definition: Define the moving average window size N, that is, the number of data points included in the average calculation.

[0019] c. Calculate the moving average: For each data point T in the time series i , calculate the average value M of the first N data points Ai The calculation formula is as follows:

[0020] d. Among them, T j is the jth data point in the time series, and MAi is the moving average of the ith data point.

[0021] e. Apply moving average: Apply the calculated moving average to the data series, replacing the original data points, or displaying it as a new data series.

[0022] f. Result Analysis: Analyze the moving average data series and observe the temperature trend. If the moving average shows an upward trend, it means the temperature is increasing; if it shows a downward trend, it means the temperature is decreasing.

[0023] g. Anomaly detection: If the difference between the original data point and the moving average exceeds the set threshold, it can be considered an anomaly.

[0024] In a preferred embodiment, the real-time monitoring submodule is responsible for acquiring the latest data from the data storage submodule and displaying it in real time on the user interface. This submodule uses visualization elements such as charts and dashboards to present data to users in an intuitive manner, allowing them to understand the operating status of the air conditioner at any time. The real-time monitoring submodule also includes a threshold detection function. When monitored data exceeds a set threshold, such as excessive temperature or excessive current, the system automatically triggers an alarm and notifies the user via text message, phone call, etc.

[0025] In a preferred embodiment, the predictive maintenance submodule is responsible for analyzing historical data, identifying signs of equipment performance degradation, and predicting future equipment status. This submodule uses predictive models, such as time series analysis, regression analysis, and machine learning algorithms, to analyze historical data and predict equipment failures or performance degradation. Through predictive maintenance, users can identify and resolve problems in advance, avoiding losses caused by equipment failures.

[0026] The security and management submodule is responsible for ensuring system security and stability. It utilizes technologies such as data encryption, user authentication, and authorization to prevent unauthorized access or data tampering. It also monitors the system's operating status, promptly identifying and addressing system anomalies to ensure stable operation. Furthermore, the security and management submodule provides system configuration and user settings, allowing users to customize the system to their needs.

[0027] In a preferred embodiment, the alarm module automatically triggers an alarm when an abnormality occurs in the air conditioner's operating state, such as excessive temperature or excessive current. The alarm module promptly notifies the user via text message, phone call, or other means, allowing them to take timely measures to prevent accidents. The alarm module can be integrated into the cloud platform or a standalone module. When an alarm is triggered, the alarm module sends the user detailed information, including the cause of the alarm, the time of the alarm, and recommended corrective measures.

[0028] In a preferred embodiment, the user interface module is a window for users to interact with the system. Users can view the operating status of the air conditioner, including parameters such as temperature, humidity, current, and voltage, and receive alarm information through a mobile phone app or a website. The user interface typically includes functions such as real-time monitoring, historical data query, and alarm logging. Through the user interface, users can monitor the operating status of the air conditioner anytime and anywhere, keeping abreast of its operation and ensuring its safe operation.

[0029] The control module allows users to remotely control the air conditioner, such as turning it on and off, and adjusting the temperature, via a mobile app or website. The control module receives control commands from the user interface and transmits them to the cloud platform via the communication module. The cloud platform then forwards these commands to the air conditioner. The control module also includes functions such as timing control and scene control to meet user needs in different scenarios. Through the control module, users can conveniently adjust the air conditioner's operating status, achieving the dual goals of energy conservation and consumption reduction while maintaining a comfortable lifestyle.

[0030] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0031] 1. In the present invention, the system uses a sensor module to collect real-time air conditioner operating data, such as temperature, humidity, current, and voltage, and analyzes it through the data processing module. The real-time monitoring submodule can promptly detect problems, such as abnormally high temperatures or current increases, thereby preventing equipment failures or safety incidents. The data processing and analysis submodule uses analytical methods such as moving average algorithms to provide insights into temperature trends, helping users and operation and maintenance personnel make more informed decisions. The predictive maintenance submodule analyzes historical data to predict the future state of the equipment and detect potential failures in advance, thereby reducing sudden failures and repair costs. The security and management submodule ensures data security, prevents unauthorized access and data leakage, and monitors system operating status to ensure system stability and reliability. The user interface module allows users to view the air conditioner's operating status anytime, anywhere and remotely control the air conditioner through the control module, improving user convenience and comfort. Through real-time monitoring and remote control functions, users can more effectively manage air conditioner usage, achieve energy savings, and reduce operating costs.

[0032] 2. In this invention, the data storage submodule ensures data timeliness and traceability. Timestamps and data formatting facilitate data storage and analysis. Long-term storage of historical data allows for trend analysis and auditing. Regularly clearing old data helps optimize database performance while ensuring data security and integrity. The data processing and analysis submodule improves data accuracy and validity through data processing techniques such as cleaning, aggregation, and compression. Preprocessing steps such as removing outliers and filling missing values ​​provide high-quality data for subsequent analysis. Algorithms such as moving averages are used to extract data features and patterns, helping users better understand data trends and detect anomalies. The real-time monitoring submodule provides a visual display of real-time data, allowing users to quickly understand the operating status of the air conditioner. The threshold detection function triggers an immediate alarm when data exceeds a preset range, promptly notifying the user and preventing potential safety risks. The predictive maintenance submodule analyzes historical data to predict future equipment performance and potential failures, enabling preventive maintenance. This helps reduce unplanned downtime, extend equipment life, and reduce maintenance costs. The security and management submodule ensures system data security and access control, preventing data leakage and unauthorized access. Monitor system operation status, detect and handle system anomalies in a timely manner, and ensure stable system operation. Provide system configuration and user setting functions, allowing users to adjust system behavior according to their needs, enhancing system flexibility and adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 is a block diagram of the overall system of the present invention;

[0034] Figure 2 This is a system block diagram of the data processing module in the present invention. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0036] Reference Figure 1-2 ,

[0037] An air conditioning operation safety monitoring and alarm system based on the Internet of Things, the system includes: a sensor module, a data processing module, a communication module, a cloud platform module, an alarm module, a user interface module and a control module;

[0038] The internal configuration of the data processing module includes: data storage submodule, data processing and analysis submodule, real-time monitoring submodule, predictive maintenance submodule and security and management submodule;

[0039] The sensor module is connected to the data processing module: the raw data collected by the sensor module needs to be processed by the data processing module to extract useful information and convert it into a standard format.

[0040] The data processing module is connected to the sensor module: it receives and processes the data collected by the sensor. The data processing module is connected to the communication module: it sends the processed data to the communication module for uploading to the cloud platform.

[0041] The communication module is connected to the cloud platform module: data is uploaded to the cloud platform via a wireless network.

[0042] The cloud platform module connects to the communication module: it receives uploaded data and stores, analyzes, and processes it. It also connects to the alarm module: when an anomaly is detected, the cloud platform triggers the alarm module. It connects to the user interface module: it provides real-time monitoring and historical data for user query. It also connects to the control module: it receives control commands from the user interface, enabling remote control of the air conditioner.

[0043] The alarm module connects to the cloud platform module: it receives alarm signals from the cloud platform and executes alarm operations. The alarm module connects to the user interface module: it needs to display alarm information to the user. The user interface module connects to the cloud platform module: it obtains real-time monitoring data and historical data from the cloud platform and displays it to the user.

[0044] The sensor module is the front end of the system, responsible for real-time monitoring of the air conditioner's operating status. It includes temperature sensors, humidity sensors, current sensors, and voltage sensors. The temperature sensor monitors the air conditioner's internal and external temperatures to ensure operation within the appropriate temperature range; the humidity sensor monitors humidity to ensure proper dehumidification; the current sensor monitors the air conditioner's current to determine load conditions; and the voltage sensor monitors the air conditioner's voltage to ensure stable operation. These sensors transmit the collected data in real time to the data processing module, providing raw data for subsequent analysis and processing.

[0045] The data processing module processes the received raw data, extracts useful information, and converts it into a standard format. This module includes functions such as data cleaning, data aggregation, and data compression to ensure data accuracy and validity. The data processing module also performs data preprocessing, such as removing outliers and filling in missing values, to provide high-quality data for subsequent data analysis and processing.

[0046] The communication module is responsible for transmitting processed data to the cloud platform via a wireless network. It supports multiple communication methods, such as WiFi, Bluetooth, and ZigBee. The communication module packages the data output by the data processing module and sends it to the cloud platform via wireless signals.

[0047] The data storage submodule is responsible for receiving raw data from sensors, formatting it, and storing it in a database. This submodule first timestamps the data to ensure its timeliness and traceability. It then stores the data in real-time and historical data tables for subsequent data processing and analysis. The data storage submodule also needs to regularly clean up old data to free up storage space and improve database performance. Furthermore, the data storage submodule must ensure data security and integrity to prevent unauthorized access or tampering.

[0048] The data processing and analysis submodule uses the moving average algorithm to process and analyze temperature data. The calculation process of the moving average algorithm is as follows:

[0049] a. Data preparation: Retrieve real-time or historical data from the temperature sensor from the data storage submodule. Ensure that the data is arranged in chronological order.

[0050] b. Parameter definition: Define the moving average window size N, that is, the number of data points included in the average calculation.

[0051] c. Calculate the moving average: For each data point T in the time series i , calculate the average value M of the first N data points Ai The calculation formula is as follows:

[0052] d. Among them, T j is the jth data point in the time series, and MAi is the moving average of the ith data point.

[0053] e. Apply moving average: Apply the calculated moving average to the data series, replacing the original data points, or displaying it as a new data series.

[0054] f. Result Analysis: Analyze the moving average data series and observe the temperature trend. If the moving average shows an upward trend, it means the temperature is increasing; if it shows a downward trend, it means the temperature is decreasing.

[0055] g. Anomaly detection: If the difference between the original data point and the moving average exceeds the set threshold, it can be considered an anomaly.

[0056] The real-time monitoring submodule is responsible for acquiring the latest data from the data storage submodule and displaying it in real time on the user interface. This submodule uses visualization elements such as charts and dashboards to present this data to users in an intuitive manner, allowing them to keep abreast of the air conditioner's operating status. The real-time monitoring submodule also includes a threshold detection function. When monitored data exceeds a set threshold, such as excessive temperature or current, the system automatically triggers an alarm and notifies the user via text message or phone call.

[0057] The predictive maintenance submodule analyzes historical data, identifies signs of equipment performance degradation, and predicts future equipment status. This submodule uses predictive models, such as time series analysis, regression analysis, and machine learning algorithms, to analyze historical data and predict equipment failures or performance degradation. Through predictive maintenance, users can identify and resolve problems in advance, avoiding losses caused by equipment failures.

[0058] The security and management submodule is responsible for ensuring the security and stability of the system. This submodule uses technologies such as data encryption, user authentication, and authorization to prevent data from being illegally accessed or tampered with. At the same time, it monitors the system's operating status, promptly detects and handles system anomalies, and ensures stable system operation. In addition, the security and management submodule provides system configuration and user settings functions, allowing users to personalize the system according to their needs.

[0059] The alarm module automatically triggers an alarm when an abnormality occurs in the air conditioner's operating state, such as excessive temperature or excessive current. The alarm module notifies the user in a timely manner through text messages, phone calls, etc., so that the user can take timely measures to prevent accidents. The alarm module can be integrated into the cloud platform or be a standalone module. When an alarm is triggered, the alarm module will send detailed alarm information to the user, including the alarm cause, alarm time, and recommended treatment measures.

[0060] The user interface module is the window through which users interact with the system. Users can view the operating status of the air conditioner, including parameters such as temperature, humidity, current, and voltage, and receive alarm information through a mobile app or website. The user interface typically includes functions such as real-time monitoring, historical data query, and alarm logging. Through the user interface, users can monitor the operating status of the air conditioner anytime and anywhere, keeping abreast of its operating conditions and ensuring its safe operation.

[0061] The control module allows users to remotely control the air conditioner via a mobile app or website, enabling controls such as turning it on and off, and adjusting the temperature. The control module receives control commands from the user interface and transmits them to the cloud platform via the communication module. The cloud platform then forwards these commands to the air conditioner. The control module also includes functions such as timing control and scene control to meet user needs in various scenarios. Through the control module, users can conveniently adjust the air conditioner's operating status, achieving the dual goals of energy conservation and consumption reduction while maintaining a comfortable lifestyle.

[0062] In the present invention, the system uses a sensor module to collect real-time air conditioner operating data, such as temperature, humidity, current, and voltage, and analyzes it through a data processing module. The real-time monitoring submodule can promptly detect problems, such as abnormally high temperatures or abnormally high current, thereby preventing equipment failures or safety accidents. The data processing and analysis submodule uses analytical methods such as moving average algorithms to provide insights into temperature trends, helping users and operation and maintenance personnel make more informed decisions. The predictive maintenance submodule analyzes historical data to predict the future state of the equipment and detect potential failures in advance, thereby reducing sudden failures and repair costs. The security and management submodule ensures data security, prevents unauthorized access and data leakage, and monitors the system's operating status to ensure system stability and reliability. The user interface module allows users to view the air conditioner's operating status anytime, anywhere and remotely control the air conditioner through the control module, improving user convenience and comfort. Through real-time monitoring and remote control functions, users can more effectively manage air conditioner usage, achieve energy savings, and reduce operating costs.

[0063] In this invention, the data storage submodule ensures data timeliness and traceability, using timestamps and data formatting to facilitate data storage and analysis. Long-term storage of historical data allows for trend analysis and auditing. Regularly clearing old data helps optimize database performance while ensuring data security and integrity. The data processing and analysis submodule improves data accuracy and validity through data processing techniques such as cleaning, aggregation, and compression. Preprocessing steps such as removing outliers and filling missing values ​​provide high-quality data for subsequent analysis. Algorithms such as moving averages are used to extract data features and patterns, helping users better understand data trends and detect anomalies. The real-time monitoring submodule provides a visual display of real-time data, allowing users to quickly understand the operating status of the air conditioner. The threshold detection function triggers an immediate alarm when data exceeds a preset range, promptly notifying the user and preventing potential safety risks. The predictive maintenance submodule analyzes historical data to predict future equipment performance and potential failures, enabling preventive maintenance. This helps reduce unplanned downtime, extend equipment life, and reduce maintenance costs. The security and management submodule ensures system data security and access control, preventing data leakage and unauthorized access. Monitor system operation status, detect and handle system anomalies in a timely manner, and ensure stable system operation. Provide system configuration and user setting functions, allowing users to adjust system behavior according to their needs, enhancing system flexibility and adaptability.

[0064] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements that are inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device that includes the element.

[0065] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. An air conditioning operation safety monitoring and alarm system based on the Internet of Things, characterized by: The system includes: a sensor module, a data processing module, a communication module, a cloud platform module, an alarm module, a user interface module and a control module; The data processing module is internally provided with: a data storage submodule, a data processing and analysis submodule, a real-time monitoring submodule, a predictive maintenance submodule and a security and management submodule; The sensor module is connected to the data processing module: the raw data collected by the sensor module needs to be processed by the data processing module to extract useful information and convert it into a standard format; The data processing module is connected to the sensor module to receive and process the data collected by the sensor; the data processing module is connected to the communication module to send the processed data to the communication module for uploading to the cloud platform; The communication module is connected to the cloud platform module: the data is uploaded to the cloud platform via a wireless network; The cloud platform module is connected to the communication module: it receives the uploaded data and performs storage, analysis and processing; the cloud platform module is connected to the alarm module: when an abnormality is detected, the cloud platform will trigger the alarm module; the cloud platform module is connected to the user interface module: it provides real-time monitoring data and historical data for users to query; the cloud platform module is connected to the control module: it receives control instructions from the user interface to achieve remote control of the air conditioner; The alarm module is connected to the cloud platform module: it receives the alarm signal from the cloud platform and executes the alarm operation; the alarm module is connected to the user interface module: it needs to display the alarm information to the user; the user interface module is connected to the cloud platform module: it obtains real-time monitoring data and historical data from the cloud platform and displays them to the user.

2. The air conditioning operation safety monitoring and alarm system based on the Internet of Things as claimed in claim 1, characterized in that: The sensor module is the front end of the system and is responsible for real-time monitoring of the operating status of the air conditioner. It includes a temperature sensor, a humidity sensor, a current sensor and a voltage sensor. The temperature sensor is used to monitor the internal and external temperatures of the air conditioner to ensure that the air conditioner operates within a suitable temperature range. The humidity sensor is used to monitor the humidity of the air conditioner to ensure that the dehumidification function of the air conditioner is normal. The current sensor is used to monitor the current of the air conditioner to determine the load condition of the air conditioner. The voltage sensor is used to monitor the voltage of the air conditioner to ensure that the air conditioner operates under a stable voltage. These sensors transmit the real-time collected data to the data processing module to provide raw data for subsequent data analysis and processing.

3. The air conditioning operation safety monitoring and alarm system based on the Internet of Things as claimed in claim 1, characterized in that: The data processing module processes the received raw data, extracts useful information, and converts it into a standard format; this module includes data cleaning, data aggregation, and data compression functions to ensure the accuracy and effectiveness of the data; The data processing module also pre-processes the data.

4. The air conditioning operation safety monitoring and alarm system based on the Internet of Things as claimed in claim 1, characterized in that: The communication module is responsible for transmitting the processed data to the cloud platform via a wireless network; it supports multiple communication methods.

5. The air conditioning operation safety monitoring and alarm system based on the Internet of Things as claimed in claim 1, characterized in that: The data storage submodule is responsible for receiving the raw data from the sensor and storing the data in the database after formatting it. This submodule will first timestamp the data to ensure the timeliness and traceability of the data. Then, the data will be stored in the real-time data table and the historical data table for subsequent data processing and analysis. The data storage submodule also needs to regularly clean up old data to free up storage space and improve database performance.

6. The air conditioning operation safety monitoring and alarm system based on the Internet of Things as claimed in claim 1, characterized in that: The data processing and analysis submodule uses a moving average algorithm to process and analyze temperature data. The calculation process of the moving average algorithm is as follows: a. Data preparation: retrieve the real-time or historical data of the temperature sensor from the data storage submodule; ensure that the data is arranged in chronological order; b. Parameter definition: Define the window size N of the moving average, that is, the number of data points included when calculating the average value; c. Calculate the moving average: For each data point T in the time series i , calculate the average value M of the first N data points Ai ; The calculation formula is as follows: d. Among them, T j is the jth data point in the time series, and MAi is the moving average of the ith data point; e. Apply moving average: Apply the calculated moving average to the data series, replacing the original data points, or displaying it as a new data series; f. Result analysis: Analyze the data sequence of the moving average and observe the trend of temperature change; if the moving average shows an upward trend, it means that the temperature is increasing; if it shows a downward trend, it means that the temperature is decreasing; g. Anomaly detection: If the difference between the original data point and the moving average exceeds the set threshold, it is considered an anomaly.

7. The air conditioning operation safety monitoring and alarm system based on the Internet of Things as claimed in claim 1, characterized in that: The real-time monitoring submodule is responsible for obtaining the latest data from the data storage submodule and displaying it in real time on the user interface; this submodule uses charts and dashboard visualization elements to display the data to the user in an intuitive manner, so that the user can understand the operating status of the air conditioner at any time.

8. The air conditioning operation safety monitoring and alarm system based on the Internet of Things as claimed in claim 1, characterized in that: The predictive maintenance submodule is responsible for analyzing historical data, looking for signs of equipment performance degradation, and predicting future equipment status. This submodule uses predictive models, including time series analysis, regression analysis, and machine learning algorithms, to analyze historical data and predict equipment failures or performance degradation. Through predictive maintenance, users can discover and solve problems in advance and avoid losses caused by equipment failures. The security and management submodule is responsible for ensuring the security and stability of the system; This sub-module uses data encryption, user authentication and authorization technologies to prevent data from being illegally accessed or tampered with; at the same time, it monitors the system's working status, promptly detects and handles system anomalies, and ensures the stable operation of the system; in addition, the security and management sub-module also provides system configuration and user setting functions, allowing users to personalize the system according to their needs.

9. The air conditioning operation safety monitoring and alarm system based on the Internet of Things as claimed in claim 1, characterized in that: When the alarm module is abnormal in the operation state of the air conditioner, such as excessive temperature or excessive current, the system will automatically trigger an alarm; the alarm module will promptly notify the user through text messages and phone calls so that the user can take timely measures to prevent accidents; the alarm module is integrated in the cloud platform and is also an independent module; when the alarm is triggered, the alarm module will send detailed alarm information to the user, including the cause of the alarm, the alarm time and the recommended handling measures.

10. The air-conditioning operation safety monitoring and alarm system based on the Internet of Things as claimed in claim 1, characterized in that: The user interface module is a window for users to interact with the system. Users can view the operating status of the air conditioner, including temperature, humidity, current, voltage parameters, and receive alarm information through the mobile phone APP or web page. The user interface usually includes real-time monitoring, historical data query, and alarm recording functions. Through the user interface, users can monitor the operating status of the air conditioner anytime and anywhere, understand the operating status of the air conditioner in a timely manner, and ensure the safe operation of the air conditioner. The control module allows the user to remotely control the air conditioner through a mobile phone APP or a web page, such as turning it on and off, and adjusting the temperature; the control module receives control instructions from the user interface, sends the instructions to the cloud platform through the communication module, and then the cloud platform forwards the instructions to the air conditioning equipment; the control module also includes timing control and scene control functions to meet the needs of users in different scenarios; through the control module, the user can conveniently adjust the operating status of the air conditioner to achieve the dual goals of energy saving and consumption reduction and comfortable life.

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