Fire-fighting monitoring and early warning system based on project fire analysis

Abstract

The invention belongs to the technical field of fire-fighting monitoring, and particularly relates to a fire-fighting monitoring and early warning system based on project fire analysis. The fire-fighting monitoring and early warning system comprises a data acquisition module, a data transmission module, a fire behavior analysis module, an early warning and alarm module, a user interface module, a data storage and management module, a remote monitoring and control module, a system integration and expansion module and a safety and authority management module. Through the advanced data acquisition, analysis and management functions, the accuracy and efficiency of fire detection and response are improved, the user interaction experience and the system compatibility are enhanced, powerful support is provided for fire safety management, the comprehensiveness, the safety and the flexibility are realized, and meanwhile, the safety of the system is improved. And the total operation cost and the safety risk are reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of fire monitoring, and in particular relates to a fire monitoring and early warning system based on project fire situation analysis. Background Art

[0002] Fire monitoring and early warning refers to an important mechanism that uses advanced monitoring technology and equipment to conduct all-round real-time monitoring of the internal and external environment of a building to identify and evaluate fire risk factors. In daily monitoring, when the initial signs of a fire are detected, such as increased smoke concentration, abnormal temperature or open flames, the system will immediately issue an alarm to promptly notify relevant personnel and the control center, prompting them to take prompt countermeasures. This instant feedback mechanism not only provides valuable time for the emergency response team to help them intervene and extinguish the fire as early as possible, but also effectively reduces the potential risks and property losses caused by the fire. In addition, by strengthening the monitoring and early warning of fire hazards, fire management agencies can continuously improve fire safety management, enhance the public's awareness of fire prevention and control, and ultimately lay a more solid foundation for protecting people's lives and property safety, thereby building a more solid fire prevention and control network. .

[0003] The existing fire monitoring and early warning systems generally only monitor and warn of fires that occur. The accuracy of fire detection and response is poor, the user interaction experience and system compatibility are poor, which is not conducive to fire safety management, and the overall operating costs and safety risks are high. Therefore, we propose a fire monitoring and early warning system based on project fire analysis to solve the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide a fire monitoring and early warning system based on project fire situation analysis, which can not only improve the accuracy and efficiency of fire detection and response through its advanced data collection, analysis and management functions, but also enhance the user interaction experience and system compatibility, provide strong support for fire safety management, achieve comprehensiveness, safety and flexibility, and reduce overall operating costs and safety risks.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A fire monitoring and early warning system based on project fire situation analysis, the fire monitoring and early warning system includes data acquisition module, data transmission module, fire situation analysis module, early warning and alarm module, user interface module, data storage and management module, remote monitoring and control module, system integration and expansion module, security and authority management module.

[0007] In a preferred embodiment, the operation of the fire monitoring and early warning system includes the following steps:

[0008] Step 1. Data collection and transmission: After the system is started, various sensors begin to collect environmental data, video surveillance cameras record real-time video, and the collected data is transmitted to the central processing system via wired or wireless networks;

[0009] Step 2. Data preprocessing: clean the transmitted data, remove noise and invalid data, and convert the data into a unified format;

[0010] Step 3. Fire analysis: Use data analysis algorithms to analyze sensor data in real time, identify abnormal situations, and combine historical data and pattern recognition technology to further improve the accuracy of fire detection;

[0011] Step 4. Early warning and alarm: When a potential fire is detected, the system will immediately trigger the early warning mechanism, generate early warning information, and send an alarm to relevant personnel through sound, light, text message, and email;

[0012] Step 5. User interaction and monitoring: Operators monitor system status, view real-time data and historical records through a graphical user interface, which includes real-time data charts, alarm information, and video monitoring screens;

[0013] Step 6. Data storage and management: Sensor data, video data, and alarm records are stored in the database, and managers can view historical data, conduct trend analysis, and optimize the system.

[0014] Step 7. Remote monitoring and control: Remote monitoring and control through the Internet or a dedicated network, remote system configuration and parameter adjustment;

[0015] Step 8. System integration and expansion: Integrate with other fire protection systems, security systems, and building automation systems to achieve data sharing and linkage control, provide expansion interfaces, add new sensors, or integrate new analysis algorithms.

[0016] In a preferred embodiment, the data collection and transmission also includes deploying temperature sensors, smoke sensors, flame sensors, and gas sensors. The video surveillance camera is started and begins to record real-time images to capture changes in the scene. The surveillance images are preliminarily processed, including motion detection and image compression. The data are grouped and packaged, including timestamps, sensor types, sensor IDs, and data values. The video data is compressed to reduce the amount of data transmitted over the network. The data packets are sent to the central processing system via the selected communication protocol.

[0017] In a preferred embodiment, the data preprocessing also includes the central processing system receiving data packets from the data transmission module, the data including sensor data and video frame data, performing preliminary inspection on the received data, verifying the integrity of the data packets, identifying outliers or abnormal values ​​using statistical analysis, machine learning algorithms or rule-based methods, checking whether there are damaged data packets, malformed data or missing values, interpolating the missing values, filling the missing data with the average of the previous and next data or linear interpolation, selecting to delete or replace with the mean or median method for the identified abnormal values, converting all timestamps into a unified format, converting all data into a consistent data type, and organizing the data into a structured form using a table structure or an object structure.

[0018] In a preferred embodiment, the fire analysis also includes obtaining cleaned and formatted real-time sensor data from a data preprocessing module, including temperature, smoke concentration, and gas concentration, extracting key information from the sensor data, including temperature, humidity, smoke concentration, average value, maximum value, and change rate of adjacent time intervals, setting thresholds for sensor data, and monitoring in real time whether any data exceeds these preset thresholds. Detect abnormal patterns in real-time data using trained decision trees, random forests, and support vector machines, obtain relevant historical data from a storage module for comparison and pattern recognition, and train the model through supervised learning to distinguish between normal conditions and fire conditions.

[0019] In a preferred embodiment, the early warning and alarm also includes receiving detected abnormal conditions from the fire analysis module, cross-validating through multiple sensor data, further confirming the nature and level of the abnormal conditions by using pattern recognition and historical data comparison, applying preset decision logic to determine whether the conditions for triggering the early warning are met, generating early warning information containing detailed fire information, including the type, time, location, and observed values ​​of the abnormal data, determining the early warning level according to the severity of the abnormality, and recording the early warning information in the system log, including the generation time, early warning level, and specific data. The system sends an alarm through a built-in or external speaker to remind on-site personnel and uses flashing lights to attract attention, especially in noisy or imperceptible environments. The early warning information is sent to a preset contact list through a text message alarm system.

[0020] In a preferred embodiment, the user interaction and monitoring also includes displaying real-time sensor data in the GUI, including temperature, smoke concentration, and gas concentration, using dynamic charts for real-time updates, integrating video surveillance images, displaying real-time video streams of the monitored area, and displaying alarm information in real time on the GUI interface, including alarm level, time, location and specific data, displaying the overall operating status of the system, including whether there are faults and device connection status, real-time monitoring of the operating status of each sensor, control device and fire extinguishing equipment, and real-time monitoring of the operating status of each sensor, control device and fire extinguishing equipment in a format.

[0021] In a preferred embodiment, the data storage and management also includes collecting real-time video streams from surveillance cameras and regularly generating video snapshots or video files, recording all alarm information generated in the system, including alarm time, type, source and processing results, selecting a suitable database type according to data characteristics, and writing the real-time collected data into the database in a timely manner through a data writing interface, providing a user interface to allow managers to query data through keywords or conditions and quickly obtain required data.

[0022] In a preferred embodiment, the remote monitoring and control also includes configuring a firewall, VPN, deploying or configuring remote monitoring software, including Web applications, mobile applications or desktop clients. Users log in through the remote monitoring platform, enter their username and password, and use multi-factor authentication to further confirm their identity. The system limits their access and operating scope based on their role and authority. Users interact with the system through a visual interface to perform various operations, including starting, stopping, and restarting equipment, and activating a fire extinguishing system. Parameters and settings modified by users should be saved in real time to the database, and logs of all remote access and operations should be recorded, including user identity, operation time, and operation content. The system monitors remote access behavior in real time and uses SSL / TLS encryption protocols to ensure data transmission security during remote operations.

[0023] In a preferred solution, the system integration and expansion also includes analyzing the architecture, data interface, and communication protocol of the existing system, identifying the integration bottlenecks and expansion opportunities of the current system, listing the functions that need to be integrated or expanded, decomposing technical tasks, defining the expected results of each task, formulating standardized interfaces, and establishing a unified data integration platform to support real-time sharing of data among different systems.

[0024] The technical effects achieved by the present invention are:

[0025] Through comprehensive data collection and real-time analysis, the system can quickly identify fire conditions and reduce the risk of missed or false alarms. It combines data from temperature, smoke concentration, flame and gas sensors to perform cross-validation, improve detection accuracy and ensure timely response. After detecting an abnormal situation, the system quickly triggers an early warning, issues multiple alarms such as sound and light, and notifies relevant personnel in real time via SMS and email to ensure a quick response. It reminds on-site personnel in a variety of ways, especially in noisy environments, to ensure the effective implementation of safety measures;

[0026] The graphical user interface (GUI) provides real-time monitoring, integrated alarm information and video monitoring, allowing operators to quickly and easily obtain important information. Users can quickly query historical data through the interface and perform precise searches based on keywords or conditions to help analyze trends and optimize decision-making. The system can centrally store and manage various types of data, including sensor data, alarm records and video streams, to facilitate subsequent analysis and report generation. Through data preprocessing and cleaning, the accuracy and availability of data are ensured, providing a reliable basis for subsequent analysis;

[0027] Through the Internet or a dedicated network, managers can monitor system status and control equipment anytime and anywhere, improve management efficiency and flexibility, use multi-factor authentication and encryption protocols to ensure remote operation security and reduce potential security risks, and can be seamlessly integrated with other fire protection systems, security systems, building automation systems, etc. to achieve data sharing and linkage control, improve the overall effect of the system, provide expansion interfaces to facilitate the addition of new sensors or the integration of new analysis algorithms in the future to meet changing needs, reduce the need for manual inspections through system automated monitoring and alarms, and reduce the labor intensity and labor costs of operators. Through rapid early warning and efficient management, it reduces property losses and personal injuries caused by fires and improves the overall safety level. It integrates data analysis and historical pattern recognition to provide data-based decision support, enabling management to make more scientific and effective decisions. Through the analysis of historical data, it can identify the patterns of fire occurrence and improve the effectiveness of preventive measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of a fire monitoring and early warning system based on project fire situation analysis of the present invention. DETAILED DESCRIPTION

[0029] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0030] See also Figure 1As shown, the present invention provides a fire monitoring and early warning system based on project fire situation analysis. The fire monitoring and early warning system includes a data acquisition module, a data transmission module, a fire situation analysis module, an early warning and alarm module, a user interface module, a data storage and management module, a remote monitoring and control module, a system integration and expansion module, and a security and authority management module.

[0031] The operation of the fire monitoring and early warning system includes the following steps:

[0032] Step 1. Data collection and transmission: After the system is started, various sensors begin to collect environmental data, video surveillance cameras record real-time video, and the collected data is transmitted to the central processing system via wired or wireless networks;

[0033] Step 2. Data preprocessing: clean the transmitted data, remove noise and invalid data, and convert the data into a unified format;

[0034] Step 3. Fire analysis: Use data analysis algorithms to analyze sensor data in real time, identify abnormal situations, and combine historical data and pattern recognition technology to further improve the accuracy of fire detection;

[0035] Step 4. Early warning and alarm: When a potential fire is detected, the system will immediately trigger the early warning mechanism, generate early warning information, and send an alarm to relevant personnel through sound, light, text message, and email;

[0036] Step 5. User interaction and monitoring: Operators monitor system status, view real-time data and historical records through a graphical user interface, which includes real-time data charts, alarm information, and video monitoring screens;

[0037] Step 6. Data storage and management: Sensor data, video data, and alarm records are stored in the database, and managers can view historical data, conduct trend analysis, and optimize the system.

[0038] Step 7. Remote monitoring and control: Remote monitoring and control through the Internet or a dedicated network, remote system configuration and parameter adjustment;

[0039] Step 8. System integration and expansion: Integrate with other fire protection systems, security systems, and building automation systems to achieve data sharing and linkage control, provide expansion interfaces, add new sensors, or integrate new analysis algorithms.

[0040] Data collection and transmission also include the deployment of temperature sensors, smoke sensors, flame sensors, and gas sensors. The video surveillance camera starts and begins recording real-time images to capture changes in the scene. Preliminary processing of the surveillance images, including motion detection and image compression, packages the data into groups, including timestamps, sensor types, sensor IDs, and data values, compresses the video data, reduces the amount of data transmitted over the network, and sends the data packets to the central processing system via the selected communication protocol.

[0041] Data preprocessing also includes the central processing system receiving data packets from the data transmission module. The data includes sensor data and video frame data, performing preliminary checks on the received data, verifying the integrity of the data packets, using statistical analysis, machine learning algorithms or rule-based methods to identify outliers or abnormal values, checking whether there are damaged data packets, malformed data or missing values, interpolating missing values, filling missing data with the average of the previous and next data or linear interpolation, and selecting deletion, replacement with mean or median methods for identified abnormal values. Convert all timestamps to a unified format, convert all data to a consistent data type, and organize the data into a structured form using a table structure or an object structure.

[0042] Fire analysis also includes obtaining cleaned and formatted real-time sensor data from the data preprocessing module, including temperature, smoke concentration, and gas concentration, extracting key information from the sensor data, including temperature, humidity, smoke concentration, average value, maximum value, and rate of change of adjacent time intervals, setting thresholds for sensor data, and monitoring in real time whether any data exceeds these preset thresholds. The trained decision trees, random forests, and support vector machines are used to detect abnormal patterns in real-time data, and relevant historical data are obtained from the storage module for comparison and pattern recognition. The model is trained through supervised learning to distinguish between normal status and fire status.

[0043] Early warning and alarm also include receiving detected abnormal conditions from the fire analysis module, cross-validating through multiple sensor data, using pattern recognition and historical data comparison to further confirm the nature and level of the abnormal conditions, applying preset decision logic to determine whether the conditions for triggering the early warning are met, generating early warning information containing detailed information about the fire, including the type of abnormal data, time, location, and observed values, determining the early warning level based on the severity of the abnormality, and recording the early warning information in the system log, including the generation time, early warning level, and specific data. The system sounds an alarm through a built-in or external speaker to alert on-site personnel, uses flashing lights to attract attention, especially in noisy or difficult-to-detect environments, and sends early warning information to a preset list of contacts through a text message alarm system.

[0044] User interaction and monitoring also include displaying real-time sensor data in the GUI, including temperature, smoke concentration, and gas concentration, using dynamic charts for real-time updates, integrating video surveillance images, displaying real-time video streams of the monitored area, displaying alarm information in real time on the GUI interface, including alarm level, time, location and specific data, displaying the overall operating status of the system, including whether there are faults and device connection status, real-time monitoring of the operating status of each sensor, control device and fire extinguishing equipment, and real-time monitoring of the operating status of each sensor, control device and fire extinguishing equipment in a real-time format.

[0045] Data storage and management also includes collecting real-time video streams from surveillance cameras and regularly generating video snapshots or video files, recording all alarm information generated in the system, including alarm time, type, source and processing results, selecting the appropriate database type based on data characteristics, and writing the real-time collected data into the database in a timely manner through the data writing interface. A user interface is provided to allow managers to query data using keywords or conditions and quickly obtain the required data.

[0046] Remote monitoring and control also includes configuring firewalls, VPNs, and deploying or configuring remote monitoring software, including Web applications, mobile applications, or desktop clients. Users log in through the remote monitoring platform, enter their username and password, and use multi-factor authentication to further confirm their identity. The system limits their access and operating scope based on their roles and permissions. Users interact with the system through a visual interface and perform various operations, including starting, stopping, and restarting equipment, and activating fire extinguishing systems. Parameters and settings modified by users should be saved in real time to the database, and logs of all remote access and operations should be recorded, including user identity, operation time, and operation content. The system monitors remote access behavior in real time and uses SSL / TLS encryption protocols to ensure data transmission security during remote operations.

[0047] System integration and expansion also includes analyzing the architecture, data interfaces, and communication protocols of existing systems, identifying the integration bottlenecks and expansion opportunities of the current systems, making a list of functions that need to be integrated or expanded, decomposing technical tasks, defining the expected results of each task, developing standardized interfaces, and establishing a unified data integration platform to support real-time sharing of data among different systems.

[0048] In the present invention, the system can quickly identify the fire through comprehensive data collection and real-time analysis, reduce the risk of missed or false alarms, and combine the data of temperature, smoke concentration, flame and gas sensors to perform cross-validation to improve the accuracy of detection and ensure timely response. After detecting an abnormal situation, the system quickly triggers an early warning, issues multiple alarms such as sound and light, and notifies relevant personnel in real time through text messages and emails to ensure a quick response, and reminds on-site personnel in various ways, especially in noisy environments to ensure the effective implementation of safety measures;

[0049] The graphical user interface (GUI) provides real-time monitoring, integrated alarm information and video monitoring, allowing operators to quickly and easily obtain important information. Users can quickly query historical data through the interface and perform precise searches based on keywords or conditions to help analyze trends and optimize decision-making. The system can centrally store and manage various types of data, including sensor data, alarm records and video streams, to facilitate subsequent analysis and report generation. Through data preprocessing and cleaning, the accuracy and availability of data are ensured, providing a reliable basis for subsequent analysis;

[0050] Through the Internet or a dedicated network, managers can monitor system status and control equipment anytime and anywhere, improve management efficiency and flexibility, use multi-factor authentication and encryption protocols to ensure remote operation security and reduce potential security risks, and can be seamlessly integrated with other fire protection systems, security systems, building automation systems, etc. to achieve data sharing and linkage control, improve the overall effect of the system, provide expansion interfaces to facilitate the addition of new sensors or the integration of new analysis algorithms in the future to meet changing needs, reduce the need for manual inspections through system automated monitoring and alarms, and reduce the labor intensity and labor costs of operators. Through rapid early warning and efficient management, it reduces property losses and personal injuries caused by fires, provides data-based decision support, enables management to make more scientific and effective decisions, and through analysis of historical data, can identify the patterns of fire occurrence and improve the effectiveness of preventive measures.

[0051] The above is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the protection scope of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention shall be implemented according to the conventional means in the art unless otherwise specified and limited.

Claims

1. A fire monitoring and early warning system based on project fire situation analysis, characterized in that: The fire monitoring and early warning system includes data acquisition module, data transmission module, fire situation analysis module, early warning and alarm module, user interface module, data storage and management module, remote monitoring and control module, system integration and expansion module, and security and authority management module.

2. According to claim 1, a fire monitoring and early warning system based on project fire analysis is characterized in that: The operation of the fire monitoring and early warning system includes the following steps: Step 1. Data collection and transmission: After the system is started, various sensors begin to collect environmental data, video surveillance cameras record real-time video, and the collected data is transmitted to the central processing system via wired or wireless networks; Step 2. Data preprocessing: clean the transmitted data, remove noise and invalid data, and convert the data into a unified format; Step 3. Fire analysis: Use data analysis algorithms to analyze sensor data in real time, identify abnormal situations, and combine historical data and pattern recognition technology to further improve the accuracy of fire detection; Step 4. Early warning and alarm: When a potential fire is detected, the system will immediately trigger the early warning mechanism, generate early warning information, and send an alarm to relevant personnel through sound, light, text message, and email; Step 5. User interaction and monitoring: Operators monitor system status, view real-time data and historical records through a graphical user interface, which includes real-time data charts, alarm information, and video monitoring screens; Step 6. Data storage and management: Sensor data, video data, and alarm records are stored in the database, and managers can view historical data, conduct trend analysis, and optimize the system. Step 7. Remote monitoring and control: Remote monitoring and control through the Internet or a dedicated network, remote system configuration and parameter adjustment; Step 8. System integration and expansion: Integrate with other fire protection systems, security systems, and building automation systems to achieve data sharing and linkage control, provide expansion interfaces, add new sensors, or integrate new analysis algorithms.

3. A fire monitoring and early warning system based on project fire analysis according to claim 2, characterized in that: The data collection and transmission also includes deploying temperature sensors, smoke sensors, flame sensors, and gas sensors. The video surveillance camera starts and begins recording real-time images to capture changes in the scene. Preliminary processing of the surveillance images, including motion detection and image compression, is performed, and the data is grouped and packaged, including timestamps, sensor types, sensor IDs, and data values. The video data is compressed to reduce the amount of data transmitted over the network. The data packets are sent to the central processing system via the selected communication protocol.

4. A fire monitoring and early warning system based on project fire analysis according to claim 2, characterized in that: The data preprocessing also includes the central processing system receiving data packets from the data transmission module, the data including sensor data and video frame data, performing preliminary inspection on the received data, verifying the integrity of the data packets, identifying outliers or abnormal values ​​using statistical analysis, machine learning algorithms or rule-based methods, checking whether there are damaged data packets, malformed data or missing values, interpolating the missing values, filling the missing data with the average value of the previous and next data or linear interpolation, selecting to delete or replace the identified abnormal values ​​with the mean or median method for processing, converting all timestamps into a unified format, converting all data into a consistent data type, and organizing the data into a structured form using a table structure or an object structure.

5. The fire monitoring and early warning system based on project fire analysis according to claim 2 is characterized by: The fire analysis also includes obtaining cleaned and formatted real-time sensor data from a data preprocessing module, including temperature, smoke concentration, and gas concentration, extracting key information from the sensor data, including temperature, humidity, smoke concentration, average value, maximum value, and change rate of adjacent time intervals, setting thresholds for sensor data, and monitoring in real time whether there is data exceeding these preset thresholds, using trained decision trees, random forests, and support vector machines to detect abnormal patterns in real-time data, obtaining relevant historical data from a storage module for comparison and pattern recognition, and training the model through supervised learning to distinguish between normal conditions and fire conditions.

6. A fire monitoring and early warning system based on project fire analysis according to claim 2, characterized in that: The early warning and alarm also includes receiving detected abnormal conditions from the fire analysis module, cross-validating through multiple sensor data, further confirming the nature and level of the abnormal conditions by using pattern recognition and historical data comparison, applying preset decision logic to determine whether the conditions for triggering the early warning are met, generating early warning information containing detailed information of the fire, including the type of abnormal data, time, location, and observed values, determining the early warning level according to the severity of the abnormality, and recording the early warning information in the system log, including the generation time, early warning level, and specific data. The system sends an alarm through a built-in or external speaker to remind on-site personnel and uses flashing lights to attract attention, especially in noisy or difficult-to-detect environments. The early warning information is sent to a preset contact list through a text message alarm system.

7. A fire monitoring and early warning system based on project fire analysis according to claim 2, characterized in that: The user interaction and monitoring also includes displaying real-time sensor data in the GUI, including temperature, smoke concentration, and gas concentration, using dynamic charts for real-time updates, integrating video surveillance images, displaying real-time video streams of the monitored area, displaying alarm information in real time on the GUI interface, including alarm level, time, location and specific data, displaying the overall operating status of the system, including whether there are faults and device connection status, real-time monitoring of the operating status of each sensor, control device and fire-extinguishing equipment, and real-time monitoring of the operating status of each sensor, control device and fire-extinguishing equipment in a certain format.

8. The fire monitoring and early warning system based on project fire analysis according to claim 2 is characterized by: The data storage and management also includes collecting real-time video streams from surveillance cameras and regularly generating video snapshots or video files, recording all alarm information generated in the system, including alarm time, type, source and processing results, selecting a suitable database type based on data characteristics, and writing real-time collected data into the database in a timely manner through a data writing interface, providing a user interface, allowing managers to query data through keywords or conditions and quickly obtain required data.

9. A fire monitoring and early warning system based on project fire analysis according to claim 2, characterized in that: The remote monitoring and control also includes configuring firewalls, VPNs, deploying or configuring remote monitoring software, including Web applications, mobile applications or desktop clients. Users log in through the remote monitoring platform, enter their usernames and passwords, and use multi-factor authentication to further confirm their identities. The system limits their access and operating scope based on their roles and permissions. Users interact with the system through a visual interface to perform various operations, including starting, stopping, and restarting equipment, and activating fire extinguishing systems. Parameters and settings modified by users should be saved in real time to the database, and logs of all remote access and operations should be recorded, including user identity, operation time, and operation content. The system monitors remote access behavior in real time and uses SSL / TLS encryption protocols to ensure the security of data transmission during remote operations.

10. A fire monitoring and early warning system based on project fire analysis according to claim 2, characterized in that: The system integration and expansion also includes analyzing the architecture, data interface, and communication protocol of the existing system, identifying the integration bottlenecks and expansion opportunities of the current system, listing the functions that need to be integrated or expanded, decomposing technical tasks, defining the expected results of each task, formulating standardized interfaces, and establishing a unified data integration platform to support real-time sharing of data among different systems.

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