Fire safety patrol closed-loop management system

Abstract

The application discloses a fire safety patrol closed-loop management system and belongs to the technical field of fire safety supervision. In order to solve the problem that some existing technologies adopt a code scanning and clock-in mode for patrol management, but most of them only have a simple clock-in recording function, lack a complete closed-loop management mechanism, and cannot realize automatic early warning, multi-level supervision and responsibility tracing of abnormal conditions, the application comprises a front-end identification deployment module, a patrol execution module, a back-end data processing module, a multi-level early warning and supervision module and a responsibility tracing module. The application forms a complete closed loop of "identification deployment-patrol execution-data processing-early warning and supervision-responsibility tracing". From patrol data collection and abnormality determination to multi-level early warning pushing and upgrading supervision, and to whole-process account reservation, each link is seamlessly connected, so that clear process support is ensured from hazard discovery to disposal and from responsibility definition to tracing, and the problems of lost management, missed management and responsibility shirking in traditional management are completely solved.

Description

Technical Field

[0001] This invention relates to the field of fire safety supervision technology, specifically a closed-loop management system for fire safety inspections. Background Technology

[0002] Fire safety is a critical responsibility, but fire management departments generally face prominent problems such as insufficient manpower and difficulty in achieving comprehensive supervision. Existing fire safety management technologies are limited, and various units are prone to loopholes in fire safety management, resulting in significant safety hazards and inadequate implementation of safety risks and fulfillment of responsibilities. Traditional fire safety inspections mainly rely on manual recording and periodic inspections, which not only consume a lot of manpower and time but also suffer from problems such as non-standard inspections, outdated data, difficulty in tracing hazards, and difficulty in defining responsibilities. In addition, the phenomenon of "mismanagement and oversight" is prone to occur, making it impossible to prevent fires and safety production risks in a timely and effective manner.

[0003] Although some existing technologies use QR code scanning and check-in for patrol management, most of them only have simple check-in and record functions and lack a complete closed-loop management mechanism. They cannot achieve automatic early warning of abnormal situations, multi-level supervision, and accountability, making it difficult to fundamentally solve the core problems of fire safety management.

[0004] To address the above issues, a closed-loop management system for fire safety inspections is proposed. Summary of the Invention

[0005] The purpose of this invention is to provide a closed-loop management system for fire safety inspections. By using this invention, the problems of existing technologies that use QR code scanning and card-taking for inspection management are solved. However, most of these technologies only have simple card-taking and recording functions and lack a complete closed-loop management mechanism, which cannot achieve automatic early warning of abnormal situations, multi-level supervision, and accountability.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a fire safety patrol closed-loop management system, comprising a front-end identification deployment module, a patrol execution module, a back-end data processing module, a multi-level early warning and supervision module, and a responsibility tracing module; The front-end identification deployment module can deploy uniquely identified QR codes at key fire-fighting locations and fire-fighting facilities, and the QR codes are associated with the basic information of the corresponding locations or facilities; The patrol execution module is used by patrol personnel to scan a QR code on their user terminal to complete the patrol check-in and upload the patrol data to the backend data processing module in real time. The backend data processing module can receive, store, and analyze patrol data, and determine whether the patrol behavior meets the preset requirements. The multi-level early warning and supervision module, when the backend data processing module determines that the inspection is abnormal, will trigger multi-level notifications according to preset rules, and push early warning information to the directly responsible person, the superior person in charge and the regulatory department in sequence; The responsibility traceability module can record data from the entire inspection process, the handling of early warnings, and information on responsible persons, in order to create a traceable responsibility ledger.

[0007] Furthermore, the QR code deployed by the front-end identification deployment module is a dedicated anti-counterfeiting QR code, and the basic information associated with the QR code includes the name of the fire-fighting location, location coordinates, facility model, maintenance cycle, and corresponding responsible person information; The key fire protection areas include evacuation routes, power distribution rooms, pump rooms, elevated water tank rooms, and control rooms; The fire protection facilities include fire extinguishers, fire hydrants, emergency lighting, and fireproof roller shutters.

[0008] Furthermore, the patrol execution module includes a user registration unit, a QR code check-in unit, and a data upload unit; The user registration unit is used for each unit to register an account. Each unit corresponds to a unique account, and the account is associated with the unit's basic information and the information of all responsible persons. The QR code scanning and check-in unit is used by patrol personnel to scan QR codes within their jurisdiction after logging into their accounts, and to upload on-site photos, patrol time, and patrol personnel identity information during the patrol. The data upload unit uses an encrypted transmission protocol to upload the inspection data to the backend data processing module in real time.

[0009] Furthermore, the backend data processing module includes a data receiving unit, a data storage unit, a data verification unit, and an analysis and early warning unit; The data receiving unit is capable of receiving patrol data uploaded by the patrol execution module in real time; The data storage unit uses a cloud server to store the data; The data verification unit can verify the integrity and validity of the patrol data, and is used to determine whether the patrol time is within the preset patrol period and whether the patrol personnel are the preset responsible persons. The analysis and early warning unit can determine whether the patrol is abnormal based on the verification results. Abnormal situations include failure to patrol within the time limit, failure to patrol by designated personnel, and missing patrol data.

[0010] Furthermore, the multi-level early warning and supervision module includes an early warning triggering unit, a notification push unit, and an upgrade reporting unit; The warning triggering unit triggers a warning according to the anomaly judgment result of the backend data processing module and according to a preset timeout period. The preset timeout period can be customized by the regulatory department or unit. The notification push unit pushes early warning information to the directly responsible person in a multi-level notification manner; The upgrade reporting unit automatically pushes the warning information to the unit's superior if the person directly responsible fails to handle the warning within the preset upgrade time. If the superior still fails to handle it, the unit continues to push the warning information and abnormal details to the higher-level regulatory department.

[0011] Furthermore, the warning information includes the name of the abnormal part, its location coordinates, the type of abnormality, the duration of the timeout, the responsible person, and the handling instructions.

[0012] Furthermore, the responsibility traceability module includes a ledger generation unit, a query and statistics unit, and an export unit; The ledger generation unit can automatically generate inspection ledgers, early warning ledgers, and handling ledgers, and the ledgers include time, location, personnel, situation description, and handling results; The query and statistics unit supports data query and statistical analysis, and generates patrol frequency reports, anomaly rate reports, and performance evaluation reports for responsible persons.

[0013] Furthermore, the backend data processing module also includes a map visualization unit, which marks all locations and facilities with deployed QR codes on an electronic map to display the inspection status of each location in real time, including whether they have been inspected, not inspected, or have unresolved anomalies. Supervisory personnel can view the overall inspection progress and anomaly distribution through the user terminal.

[0014] Furthermore, the map visualization unit supports the function of dividing the area into multiple different areas; it can automatically identify the systemic risk of multiple patrol tasks not being completed on time in each area and push risk warnings to the management personnel responsible for that area.

[0015] Furthermore, the user terminal includes an anomaly reporting unit. When patrol personnel discover safety hazards caused by damage or failure of fire protection facilities during their scanning patrols, they can upload photos of the hazards, descriptions of the hazards, and handling suggestions through the anomaly reporting unit. After receiving the data, the backend data processing module will automatically include it in the early warning ledger and trigger the corresponding early warning process.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention forms a complete closed loop of "identification deployment - inspection execution - data processing - early warning supervision - responsibility tracing". From inspection data collection and anomaly judgment to multi-level early warning push and escalation supervision, and then to full-process ledger retention, each link is seamlessly connected, ensuring that there are clear process support for the discovery and handling of hidden dangers and the definition and tracing of responsibilities, and completely solving the problems of mismanagement, oversight and shirking of responsibility in traditional management.

[0017] 2. The multi-level early warning and supervision module in this invention supports customizable timeout time and notification intervals. It provides progressive notifications through multiple channels, and if not handled in a timely manner, it automatically escalates the issue to the superior person in charge and the regulatory department, forming a supervision procedure of "directly responsible person - superior - regulatory department". At the same time, the early warning information includes precise content such as the coordinates of the abnormal location and handling instructions, which can ensure that the responsible person responds quickly. Compared with the traditional manual notification method, it greatly reduces the risk of the hidden danger escalating.

[0018] 3. This invention automatically generates three types of ledgers—inspection, early warning, and handling—through a responsibility traceability module, ensuring that every inspection task and every hazard handling is traceable and accountable, thus completely solving the industry problem of ambiguous responsibility definition.

[0019] 4. This invention integrates a map visualization unit, which accurately marks key fire-fighting areas and facilities on an electronic map. Supervisors can monitor the overall progress in real time. It also supports dividing the area into multiple different zones and automatically identifies systemic risks of incomplete management in a certain zone and pushes reminders. Compared with the traditional method of checking one by one, the efficiency of supervision is greatly improved, realizing the transformation from passive inspection to proactive prediction.

[0020] 5. The data verification unit in this invention verifies the validity of data from multiple dimensions, including patrol time, personnel permissions, photo clarity, and field integrity. It also supports proactive reporting of anomalies during patrols and reporting of potential hazards in areas without QR codes, ensuring that no potential hazards are overlooked. Furthermore, it ensures the security and integrity of data transmission through technologies such as SSL / TLS encrypted transmission and breakpoint resume. Compared with existing technologies, the accuracy of patrol data is significantly improved, providing reliable data support for subsequent early warning and tracing. Attached Figure Description

[0021] Figure 1 This is a system flowchart of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] To address the technical issues that existing technologies employ QR code scanning and attendance tracking for patrol management, most only offer basic attendance recording functionality and lack a complete closed-loop management mechanism. This prevents them from achieving automatic early warning of abnormal situations, multi-level supervision, and accountability. Figure 1 As shown, the following preferred technical solutions are provided: A fire safety patrol closed-loop management system includes a front-end signage deployment module, a patrol execution module, a back-end data processing module, a multi-level early warning and supervision module, and a responsibility tracing module. The modules work together to form a complete data flow and management closed loop of "signage deployment - patrol execution - data processing - early warning and supervision - responsibility tracing".

[0024] The front-end identification deployment module provides the physical identification foundation for the entire system, enabling unique identification of fire protection elements; the patrol execution module is the terminal for executing patrol actions and collecting data, ensuring the real-time uploading of patrol data; the back-end data processing module is the core data processing center of the system, responsible for receiving, storing, verifying, and analyzing data, providing data support for subsequent early warning and traceability; the multi-level early warning and supervision module initiates automated early warning processes for abnormal situations to ensure timely handling of potential hazards; and the responsibility traceability module records management process data throughout the entire process, enabling traceability and auditability of responsibilities.

[0025] The specific process is as follows: The front-end identification deployment module's core function is to provide unique physical identifiers for key fire protection areas and facilities, enabling patrol personnel to conduct precise scanning inspections and for the system to accurately identify them.

[0026] The QR codes deployed by the front-end identification deployment module are dedicated anti-counterfeiting QR codes, using a unique identification code generation algorithm. Each QR code corresponds to a unique ID, ensuring that there will be no duplicates or forgeries. The QR code generation process is as follows: First, a comprehensive inspection of all key fire protection areas and fire protection facilities within the supervised area is conducted, and the basic information of each area or facility is recorded in detail. The basic information includes the name of the fire protection area, location coordinates, facility model, maintenance cycle, and corresponding responsible person information. Then, the registered basic information is entered into the system database, and the system generates a unique identification code for each area or facility according to the preset coding rules. Finally, the identification code is converted into a QR code pattern and associated with the corresponding basic information to form a dedicated anti-counterfeiting QR code.

[0027] The QR code carrier is made of waterproof and wear-resistant PVC material with a surface coating, which can effectively resist the effects of environmental factors such as humidity, high temperature, and abrasion, ensuring that the QR code remains clear and scannable for a long time. When posting and deploying, follow the principles of "high visibility, easy scanning, and not easily obstructed," and post the code 1.5-2 meters above the ground, avoiding damp, high-temperature, easily bumped, or obstructed locations. For different types of key fire safety areas and facilities, the posting requirements are as follows: Fire protection facilities: Affix QR codes to or near fire extinguishers, fire hydrants, emergency lighting, and fireproof roller shutters in a prominent location to ensure that inspectors can easily scan the codes when checking the facilities. Key fire safety areas: QR codes should be posted at the entrances and key locations inside evacuation routes, electrical distribution rooms, pump rooms, elevated water tank rooms, and control rooms. For larger areas, the number of QR codes can be increased as needed to ensure comprehensive patrols.

[0028] The patrol execution module is the core module for patrol personnel to perform patrol operations and collect data. It integrates functions such as user registration, QR code check-in, data upload, and anomaly reporting, as detailed below: In the user registration unit, each unit registers an account, with one unique account corresponding to each unit. During the registration process, basic information such as the unit name, unified social credit code, address, contact person, and contact number are submitted to the regulatory department for review. After receiving the registration application, the regulatory department verifies the authenticity and completeness of the unit information. Once the review is approved, the system generates a unique unit account for that unit. After logging into the unit account, the unit administrator can add information about the responsible person and inspection personnel of the unit, including their name, mobile phone number, position, and the inspection area they are responsible for. The administrator can also assign corresponding operation permissions to the inspection personnel to ensure that they can only scan QR codes within their own area of ​​responsibility.

[0029] In the QR code check-in unit, after the patrol personnel log in to their account, the system will display the corresponding patrol area and the list of QR codes that need to be patrolled according to their assigned permissions. After the patrol personnel arrive at the designated key fire protection areas or facilities according to the preset patrol route, they scan the corresponding QR code. After the scan is successful, the system automatically recognizes the QR code ID, associates it with the basic information of the corresponding area or facility, and then displays it on the user terminal.

[0030] Patrol personnel need to select the patrol status (normal or abnormal) based on the actual patrol situation. If the patrol status is normal, they can simply click the "Submit" button to complete the check-in. If the patrol status is abnormal, they need to upload on-site photos, a description of the abnormal situation, and handling suggestions, and then click the "Submit" button to complete the check-in.

[0031] The data upload unit uses an SSL / TLS encrypted transmission protocol to ensure the security and integrity of the inspection data during transmission, preventing data leakage or tampering. After the inspection personnel click the "Submit" button, the data upload unit immediately uploads the inspection data, such as QR code ID, inspection time, inspection personnel identity information, inspection status, on-site photos, and anomaly description, to the backend data processing module in real time.

[0032] To ensure the reliability of data uploads, the data upload unit has a resume function. If a network interruption or other abnormal situation occurs during the data upload process, the system will automatically save the collected patrol data and resume uploading the unfinished data after the network is restored, thus avoiding data loss. At the same time, the uploaded data will include a timestamp and an identity verification code. After receiving the data, the backend data processing module can verify the authenticity of the patrol time through the timestamp and verify the legitimacy of the patrol personnel's identity through the identity verification code.

[0033] In addition to reporting anomalies during QR code check-in, the anomaly reporting unit allows patrol personnel to proactively report fire safety hazards in areas without QR codes during routine patrols. The unit provides functions such as manually entering the hazard name, location description, uploading photos, selecting the hazard type, and providing handling suggestions. After submission, the system uploads the anomaly report to the backend data processing module, which automatically includes it in the early warning log and triggers the corresponding early warning process.

[0034] The backend data processing module is the core data processing and control center of the entire system. Deployed on a cloud server using a distributed architecture, it includes a data receiving unit, a data storage unit, a data verification unit, an analysis and early warning unit, and a map visualization unit. It enables real-time data reception, secure storage, accurate verification, intelligent analysis, and visualization, as detailed below: The cloud server for the backend data processing module adopts a distributed architecture, mainly including a web server, an application server, a database server, and a cache server. The web server is used to receive access requests and data upload requests from user terminals; the application server is used to run the core business logic of the system, including data verification, analysis and early warning, and early warning triggering; the database server is used to store all data of the system, including unit information, personnel information, location and facility information, patrol data, early warning data, and processing data; and the cache server is used to cache frequently used data to improve the system's response speed.

[0035] The data receiving unit uses the HTTP / HTTPS protocol to receive patrol data and anomaly reporting data uploaded by the patrol execution module, supporting both batch data upload and real-time single-item upload modes. For batch data uploads, the data receiving unit can quickly parse the batch data and break it down into single data items for subsequent processing. For real-time single-item uploads, the data receiving unit can respond in real time to ensure timely data reception.

[0036] The data receiving unit also has a data format verification function, which verifies the format of the received data. If the data format does not meet the system requirements, it will automatically return an error message to the user terminal and inform the inspection personnel to re-upload the data; if the data format meets the requirements, it will be transmitted to the data storage unit and the data verification unit for further processing.

[0037] The data storage unit adopts a hybrid storage architecture, combining the advantages of MySQL and MongoDB databases to achieve efficient storage of both structured and unstructured data. The MySQL database is used to store structured data, including unit information, personnel information, basic information on facilities and locations, patrol logs, early warning logs, and processing logs. The MongoDB database is used to store unstructured data, mainly including on-site photos and descriptions of abnormal situations uploaded during patrols.

[0038] The data storage unit adopts a regular backup mechanism, with a backup cycle of once a day, and the backup data is stored on an off-site server to ensure data security and recoverability; at the same time, the data retention period is no less than 3 years, which can meet the archiving and auditing requirements of fire safety management.

[0039] The core function of the data verification unit is to verify the integrity and validity of the inspection data, providing a reliable data foundation for subsequent analysis and early warning. The specific verification rules of the data verification unit are as follows: Integrity verification: Check whether the patrol data contains the necessary fields, including QR code ID, patrol time, patrol personnel identity information, and patrol status. If any necessary field is missing, the data is considered incomplete.

[0040] Time validity verification: Determine whether the inspection time is within the preset inspection period. The preset inspection period can be set by the unit administrator or the regulatory department according to the actual situation. If the inspection time exceeds the preset period, it is judged as a time abnormality.

[0041] Personnel validity verification: Verify whether the patrol personnel are the pre-designated responsible persons for the location or facility. If the patrol personnel are not the pre-designated responsible persons and do not have the corresponding authorization, it is determined that the personnel are abnormal.

[0042] Photo validity verification: For patrol data with an abnormal patrol status, check whether on-site photos have been uploaded and whether the photos are clear and identifiable. If no photos have been uploaded or the photos are blurry and unidentifiable, the photos are determined to be abnormal.

[0043] After the data verification unit completes the verification, it will transmit the verification results and anomaly type to the analysis and early warning unit.

[0044] The analysis and early warning unit uses rule engine technology and presets anomaly judgment rules. It can analyze the verification results transmitted by the data verification unit in real time to determine whether the patrol is abnormal. The abnormal situations mainly include overdue patrol, patrol not conducted by designated personnel, missing patrol data, time abnormality, and photo abnormality.

[0045] For determining whether an inspection has exceeded the time limit: The system automatically calculates the estimated inspection time window for each part or facility based on the preset inspection cycle and inspection period. If the system still does not receive the inspection data for that part or facility after the time window ends, it is determined that the inspection has exceeded the time limit.

[0046] After the analysis and early warning unit determines that the patrol is abnormal, it will immediately send an abnormal signal to the multi-level early warning supervision module and synchronize key data such as the basic information of the abnormal location or facility, the type of abnormality, and the time of abnormality, thus triggering the early warning process.

[0047] The map visualization unit can accurately mark all locations and facilities with deployed QR codes on the electronic map, and each marker is associated with the corresponding location or facility name, location coordinates, and responsible person, etc. At the same time, the map visualization unit synchronizes the analysis results of the backend data processing module in real time, and marks the inspection status of each location with different colors: green indicates that it has been inspected and is normal, yellow indicates that it has not been inspected, and red indicates that it is abnormal and has not been dealt with.

[0048] Supervisory personnel can log in to the system via mobile app or computer to view markers and patrol status on the electronic map, enabling them to monitor the overall patrol progress and anomaly distribution in real time. Furthermore, the map visualization unit supports regional division, allowing the supervisory scope to be divided by administrative division, unit type, or geographical region, with each region assigned a corresponding management person. The system will continuously monitor patrol completion rate, anomaly rate, and other data for each region. When multiple patrol tasks in a region are not completed on time, the system will automatically identify a systemic risk of mismanagement in that region and send a risk alert to the corresponding management person. The alert will include the region name, the number of incomplete patrol tasks, and the locations or facilities involved.

[0049] The multi-level early warning and supervision module is a key module to ensure timely handling of abnormal situations. When it receives an abnormal signal from the analysis and early warning unit, it triggers multi-level notifications according to preset rules, pushing early warning information to the directly responsible person, the superior person in charge, and the regulatory department in sequence to ensure that abnormal situations are handled in a timely manner.

[0050] The early warning triggering unit can trigger an early warning according to the abnormal signals and abnormality types transmitted by the analysis and early warning unit, and the preset timeout time can be customized by the unit administrator or regulatory department according to the actual situation.

[0051] The triggering timing of the early warning unit varies depending on the type of abnormal situation, as follows: For abnormalities such as failure to patrol within the expected patrol time window, an early warning is triggered immediately after the expected patrol time window ends; for abnormalities such as failure to patrol by designated personnel or missing patrol data, an early warning is triggered immediately after the data verification unit completes verification and determines the abnormality.

[0052] The notification push unit supports multiple notification methods, sequentially pushing early warning information to the directly responsible person. The interval between each notification method can be set from 30 minutes to 1 hour, and the specific interval can be customized according to the actual situation.

[0053] The content of the early warning information needs to be detailed and standardized, including the name of the abnormal part, location coordinates, abnormal type, timeout duration, corresponding responsible person, and handling instructions, so as to ensure that the responsible person can quickly understand the abnormal situation and take appropriate measures.

[0054] The escalation reporting unit can initiate an escalation process when the directly responsible person fails to handle the warning in a timely manner. If the directly responsible person fails to handle the warning information within the preset escalation time, the escalation reporting unit will automatically extract the information of the unit's superior person in charge and push the warning information and the situation of the directly responsible person's failure to handle it to them. If the superior person in charge still fails to handle it within the preset second escalation time, the escalation reporting unit will continue to push the warning information and abnormal details to the superior regulatory department, and mark it as "pending regulatory handling" in the abnormal list of the regulatory platform to remind the regulatory department to intervene and handle it.

[0055] In addition to basic information such as the name of the abnormal part, location coordinates, and type of abnormality, the upgraded warning information will also include the warning trigger time, notification records, and speculation on the reasons for non-handling, providing comprehensive decision-making basis for superiors and regulatory departments.

[0056] The responsibility traceability module's core function is to record data from the entire inspection process, early warning handling status, and information on responsible personnel. This creates a traceable and auditable responsibility ledger to ensure accountability and verifiability. Specifically: The ledger generation unit can automatically generate three types of ledgers based on the processing results of the backend data processing module and the early warning processing status of the multi-level early warning and supervision module: inspection ledger, early warning ledger, and processing ledger.

[0057] The inspection log records detailed information for each inspection, including inspection ID, unit name, location name, location coordinates, inspection personnel, inspection time, inspection status, photo link, and data upload time. The early warning log records early warning information for all abnormal situations, including early warning ID, abnormal location, abnormal type, trigger time, timeout duration, notification records, and escalation records. The handling log records the handling process and results of abnormal situations, including handling ID, early warning ID, handling personnel, handling time, handling measures, handling results, verification personnel, and verification time.

[0058] The ledger is generated using a real-time update mechanism. When the system receives new inspection data, early warning information, or processing results, the ledger generation unit immediately updates the corresponding ledger to ensure the real-time nature and accuracy of the ledger data.

[0059] The query and statistics unit supports data querying and statistical analysis by multiple dimensions, making it convenient for users to quickly obtain the information they need. Query dimensions include time, unit, location, responsibility, and exception type. Users can select the corresponding query conditions according to their actual needs, and the system will quickly retrieve the corresponding ledger data and display it.

[0060] The statistical analysis function can generate various statistical reports based on the query results, including patrol frequency reports, anomaly rate reports, and responsible person performance evaluation reports. Among them, the patrol frequency report displays the number of patrols and patrol completion rate of each unit and location within a specified time period; the anomaly rate report displays the number of anomalies and the anomaly rate of each unit and location within a specified time period; the responsible person performance evaluation report uses a percentage system to calculate the performance score of each responsible person based on indicators such as patrol completion rate, anomaly handling timeliness rate, and handling qualification rate. The higher the score, the better the performance.

[0061] Statistical reports can be displayed in various chart formats such as bar charts, line charts, and pie charts, presenting data trends and distribution in an intuitive and clear manner, and providing users with visual decision support.

[0062] The export unit can export the generated ledgers and statistical reports. During the export process, the system will format the data to make the data fields clear and standardized, making it convenient for users to edit and analyze them. In addition, the exported data includes information such as the unit name, export time, and exporter to ensure the integrity and traceability of the documents.

[0063] Users can choose to export a single ledger or report, or select multiple ledgers or reports for batch export. The export process is not only fast and efficient, but also does not affect the normal operation of the system.

[0064] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0065] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A closed-loop management system for fire safety patrols, characterized in that, It includes a front-end identification deployment module, an inspection execution module, a back-end data processing module, a multi-level early warning and supervision module, and a responsibility tracing module; The front-end identification deployment module can deploy uniquely identified QR codes at key fire-fighting locations and fire-fighting facilities, and the QR codes are associated with the basic information of the corresponding locations or facilities; The patrol execution module is used by patrol personnel to scan a QR code on their user terminal to complete the patrol check-in and upload the patrol data to the backend data processing module in real time. The backend data processing module can receive, store, and analyze patrol data, and determine whether the patrol behavior meets the preset requirements. The multi-level early warning and supervision module, when the backend data processing module determines that the inspection is abnormal, will trigger multi-level notifications according to preset rules, and push early warning information to the directly responsible person, the superior person in charge and the regulatory department in sequence. The responsibility traceability module can record data from the entire inspection process, the handling of early warnings, and information on responsible persons, in order to create a traceable responsibility ledger.

2. The fire safety patrol closed-loop management system according to claim 1, characterized in that: The QR code deployed by the front-end identification deployment module is a dedicated anti-counterfeiting QR code, and the basic information associated with the QR code includes the name of the fire-fighting location, location coordinates, facility model, maintenance cycle, and corresponding responsible person information; The key fire protection areas include evacuation routes, power distribution rooms, pump rooms, elevated water tank rooms, and control rooms; The fire protection facilities include fire extinguishers, fire hydrants, emergency lighting, and fireproof roller shutters.

3. The fire safety patrol closed-loop management system according to claim 2, characterized in that: The patrol execution module includes a user registration unit, a QR code check-in unit, and a data upload unit; The user registration unit is used for each unit to register an account. Each unit corresponds to a unique account, and the account is associated with the unit's basic information and the information of all responsible persons. The QR code scanning and check-in unit is used by patrol personnel to scan QR codes within their jurisdiction after logging into their accounts, and to upload on-site photos, patrol time, and patrol personnel identity information during the patrol. The data upload unit uses an encrypted transmission protocol to upload the inspection data to the backend data processing module in real time.

4. The fire safety patrol closed-loop management system according to claim 3, characterized in that: The backend data processing module includes a data receiving unit, a data storage unit, a data verification unit, and an analysis and early warning unit; The data receiving unit is capable of receiving patrol data uploaded by the patrol execution module in real time; The data storage unit uses a cloud server to store the data; The data verification unit can verify the integrity and validity of the patrol data, and is used to determine whether the patrol time is within the preset patrol period and whether the patrol personnel are the preset responsible persons. The analysis and early warning unit can determine whether the patrol is abnormal based on the verification results. Abnormal situations include failure to patrol within the time limit, failure to patrol by designated personnel, and missing patrol data.

5. The fire safety patrol closed-loop management system according to claim 4, characterized in that: The multi-level early warning and supervision module includes an early warning triggering unit, a notification push unit, and an upgrade reporting unit. The warning triggering unit triggers a warning according to the anomaly judgment result of the backend data processing module and according to a preset timeout period. The preset timeout period can be customized by the regulatory department or unit. The notification push unit pushes early warning information to the directly responsible person in a multi-level notification manner; The upgrade reporting unit automatically pushes the warning information to the unit's superior if the person directly responsible fails to handle the warning within the preset upgrade time. If the superior still fails to handle it, the unit continues to push the warning information and abnormal details to the higher-level regulatory department.

6. The fire safety patrol closed-loop management system according to claim 5, characterized in that: The warning information includes the name of the abnormal part, its location coordinates, the type of abnormality, the duration of the timeout, the responsible person, and the handling instructions.

7. A fire safety patrol closed-loop management system according to claim 6, characterized in that: The responsibility traceability module includes a ledger generation unit, a query and statistics unit, and an export unit; The ledger generation unit can automatically generate inspection ledgers, early warning ledgers, and handling ledgers, and the ledgers include time, location, personnel, situation description, and handling results; The query and statistics unit supports data query and statistical analysis, and generates patrol frequency reports, anomaly rate reports, and performance evaluation reports for responsible persons.

8. A fire safety patrol closed-loop management system according to claim 7, characterized in that: The backend data processing module also includes a map visualization unit, which marks all locations and facilities with deployed QR codes on an electronic map to display the inspection status of each location in real time, including whether they have been inspected, not inspected, or have unresolved anomalies. Supervisory personnel can view the overall inspection progress and anomaly distribution through the user terminal.

9. A fire safety patrol closed-loop management system according to claim 8, characterized in that: The map visualization unit supports the function of dividing the area into multiple different areas; it can automatically identify the systemic risk of multiple patrol tasks not being completed on time in each area and push risk warnings to the management personnel responsible for that area.

10. A fire safety patrol closed-loop management system according to claim 9, characterized in that: The user terminal includes an anomaly reporting unit. When patrol personnel discover safety hazards caused by damage or failure of fire-fighting facilities during their scanning patrols, they can upload photos of the hazards, descriptions of the hazards, and handling suggestions through the anomaly reporting unit. The backend data processing module receives the data and automatically includes it in the early warning ledger, triggering the corresponding early warning process.

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