A modular intelligent fire-fighting management system capable of remote operation and maintenance

Abstract

The application discloses a modular intelligent fire-fighting management system capable of remote operation and maintenance, and belongs to the technical field of intelligent fire-fighting. The application realizes flexible plug-in deployment of various fire-fighting sensing devices and executing devices through a standardized module interface, supports on-demand increase and decrease of function modules and device points, realizes local data real-time processing, device state autonomous diagnosis and offline emergency management and control by relying on an edge computing unit, realizes remote fault troubleshooting, parameter configuration, program upgrading, device operation and maintenance, risk early warning and intelligent linkage scheduling in combination with a cloud platform, simultaneously carries multiple protocol adaptation encryption transmission mechanisms and digital twin visual operation and maintenance models, and solves problems such as poor compatibility, complicated operation and maintenance, lagging response and data security risks of traditional systems. The application can realize intelligent remote operation and maintenance of fire-fighting devices in the whole life cycle and closed-loop management and control of fire risks, and greatly reduces on-site operation and maintenance labor costs.

Description

Technical Field

[0001] This invention relates to the field of intelligent fire protection technology, and in particular to a modular intelligent fire protection management system that can be remotely operated and maintained. Background Technology

[0002] With the rapid development of smart cities and smart buildings, intelligent fire protection systems have become a core component of building safety and security systems. Traditional fire protection systems are gradually iterating towards intelligence, digitalization, and networking. Currently, most mainstream fire protection management systems on the market have a fixed, integrated architecture with high equipment integration and fixed functional modules. This results in numerous technical defects and application shortcomings, severely restricting the improvement of intelligent fire protection management.

[0003] First, the existing fire protection system architecture is rigid and has extremely poor modular scalability. Traditional fire protection systems have highly integrated functions such as detection, alarm, linkage, storage, and control, with strong coupling between functional units, inconsistent interfaces, and incompatible protocols. When building fire protection points are expanded, functions are upgraded, or old equipment is replaced, it is impossible to replace parts of the module and expand functions. Often, the entire system needs to be renovated, which is costly, time-consuming, and can easily cause the original fire protection system to shut down and fail, resulting in extremely poor adaptability and flexibility. At the same time, fire sensors, alarm devices, sprinkler systems, and emergency equipment from different manufacturers use different communication protocols, making it impossible to achieve unified access and collaborative operation. This creates a large number of data silos and equipment silos, resulting in low overall system utilization.

[0004] Secondly, traditional fire protection system operation and maintenance models are outdated, relying excessively on on-site manual operation, resulting in high costs and low efficiency. The parameter configuration, program upgrades, fault detection, fault repair, daily inspections, calibration, and debugging of existing fire protection equipment all require on-site work by maintenance personnel. For scenarios with dispersed locations and wide coverage, such as high-rise buildings, industrial parks, and large commercial districts, the workload is enormous. Furthermore, manual inspections suffer from problems such as missed inspections, false inspections, and delayed inspections, making it impossible to monitor the real-time operating status of fire protection equipment. Hidden equipment faults cannot be detected in a timely manner, often only becoming apparent during a fire, posing significant safety hazards. Simultaneously, on-site maintenance requires the permanent presence of specialized technical personnel, resulting in high labor and time costs and making large-scale maintenance extremely difficult.

[0005] Furthermore, existing intelligent fire protection systems suffer from weak data processing capabilities and insufficient precision in coordinated control. Traditional systems mostly employ a centralized cloud-based data processing model, uploading all front-end sensing data to the cloud for analysis and processing. This results in high data transmission latency and frequent lag, making it impossible to achieve millisecond-level coordinated response in emergency fire scenarios. Moreover, most systems only possess simple over-limit alarm functions and cannot perform integrated analysis and trend prediction of multi-dimensional data such as fire equipment operating status, environmental risk data, pipeline pressure, and power supply conditions, lacking proactive risk warning capabilities. Additionally, equipment malfunctions cannot be autonomously located or diagnosed; fault diagnosis requires manual verification, leading to extremely low maintenance efficiency. In extreme network outage conditions, the system directly collapses, losing its emergency control capabilities.

[0006] Finally, existing fire protection systems suffer from weak data security and a lack of closed-loop operation and maintenance management. Traditional fire protection data transmission often uses plaintext transmission or simple encryption, posing a high risk of data tampering and leakage. Remote control commands are easily hijacked and forged, creating security vulnerabilities for malicious manipulation of fire protection equipment. Furthermore, existing systems lack full lifecycle operation and maintenance records, fault tracing, and incident archiving mechanisms, failing to form a closed-loop management system of "monitoring-early warning-response-operation and maintenance-archiving." This results in insufficient standardization and digitalization of fire protection management, making it difficult to meet the compliance requirements of modern fire safety supervision.

[0007] To address the shortcomings of the existing technologies, this invention proposes a modular intelligent fire management system with a flexible and scalable architecture, supporting remote operation and maintenance throughout the entire process, possessing autonomous edge processing capabilities, precise linkage response, and secure and reliable data. This system solves the technical problems of traditional systems, such as rigidity, cumbersome operation and maintenance, delayed response, poor stability, and weak scalability. Summary of the Invention

[0008] The purpose of this invention is to overcome the shortcomings of existing fire protection systems, such as rigid architecture, poor scalability, reliance on manual operation and maintenance, delayed fault response, low linkage accuracy, network outage failure, data insecurity, and lack of closed-loop management. This invention provides a modular intelligent fire protection management system capable of remote operation and maintenance. Through standardized modular design, edge-cloud collaborative architecture, end-to-end remote operation and maintenance mechanism, and multi-dimensional intelligent data analysis and encrypted transmission technology, this invention achieves flexible expansion of fire protection equipment, unmanned remote operation and maintenance, autonomous fault diagnosis and repair, precise intelligent linkage, offline emergency control, and closed-loop management throughout the entire lifecycle, comprehensively improving the stability, flexibility, and intelligent management level of the fire protection system.

[0009] A modular intelligent fire management system capable of remote operation and maintenance includes a front-end sensing module group, an edge computing operation and maintenance module, an encrypted network transmission module, a cloud-based remote operation and maintenance management platform, and a terminal execution linkage module; the front-end sensing module group, the edge computing operation and maintenance module, the encrypted network transmission module, the cloud-based remote operation and maintenance management platform, and the terminal execution linkage module are sequentially connected in communication. The front-end sensing module group is a distributed data acquisition terminal, including a fire detection submodule, an equipment status monitoring submodule, an environmental security monitoring submodule, a pipeline network condition monitoring submodule, and a power supply status monitoring submodule, which are used to collect multi-dimensional data such as fire characteristics, fire-fighting equipment conditions, on-site environment, pipeline network parameters, and power supply status. The edge computing operation and maintenance module is deployed in the local fire protection zone and includes a data preprocessing submodule, a device self-diagnosis submodule, a local operation and maintenance submodule, an offline linkage control submodule, and a data caching submodule, which are used to realize local data processing. The encrypted network transmission module adopts a dual-link redundant transmission architecture and has a built-in protocol adaptation unit, data encryption unit, and instruction verification unit to realize multi-protocol device adaptation, bidirectional encrypted data transmission, and secure instruction verification. The cloud-based remote operation and maintenance management platform includes a digital twin visualization operation and maintenance sub-module, a full-process remote operation and maintenance sub-module, an intelligent analysis and early warning sub-module, a multi-level linkage scheduling sub-module, a data storage and archiving sub-module, and an access security management sub-module, which are used to realize visualized remote inspection, remote operation and maintenance, intelligent risk early warning and hierarchical access control. The terminal execution linkage module includes an alarm prompting submodule, a fire extinguishing execution submodule, and a ventilation and smoke exhaust submodule, which are used to receive control commands and complete the linkage execution of fire alarm, fire extinguishing, and smoke exhaust operations.

[0010] Furthermore, the data preprocessing submodule incorporates a Kalman filter algorithm and a data standardization algorithm to perform noise reduction, filtering, format unification, and abnormal data removal on multi-source heterogeneous data from the front end, thereby improving the accuracy of data collection. The data caching submodule adopts a power-loss protected storage design, caching local data when the network is interrupted and automatically synchronizing it to the cloud after the network is restored.

[0011] Furthermore, the device self-diagnosis submodule has a built-in device fault feature database and status judgment model, which can autonomously diagnose device offline, abnormal parameters, component damage, and operational lag faults, accurately locate the fault location and fault type, and classify the faults into three levels: minor parameter abnormality, general operation fault, and serious failure fault, and generate corresponding differentiated operation and maintenance solutions such as automatic reset, operation and maintenance reminders, and emergency alarms.

[0012] Furthermore, the offline linkage control submodule is pre-set with multi-level emergency linkage logic. Under network interruption or cloud connection failure conditions, it can independently complete fire level determination, alarm triggering, equipment linkage, and emergency start-up and shutdown operations, realizing local autonomous emergency control without cloud intervention.

[0013] Furthermore, the encrypted network transmission module uses the AES-256 encryption algorithm to achieve bidirectional encrypted transmission of data and instructions. Through a triple verification mechanism of identity verification, permission verification, and instruction integrity verification, it intercepts illegally tampered or hijacked control instructions, ensuring the security of system transmission and management.

[0014] Furthermore, the full-process remote operation and maintenance submodule supports remote device parameter configuration, remote program upgrade, remote fault reset, remote device calibration, remote start-up and shutdown debugging, and remote log reading. It also has a built-in operation and maintenance work order system that automatically generates, assigns, records, and archives operation and maintenance tasks, realizing closed-loop management of the operation and maintenance process, and supports batch remote operation and maintenance of multiple devices.

[0015] Furthermore, the intelligent analysis and early warning submodule incorporates an equipment aging model and a fire risk prediction model. Through long-term operational data trend analysis, it can predict the remaining service life of equipment, send early reminders for equipment replacement, and identify hidden fire hazards, thereby achieving preventative risk warning and equipment maintenance.

[0016] Furthermore, the digital twin visualization operation and maintenance submodule builds a three-dimensional digital twin model of the building fire protection scene, which maps the location, operating status, data parameters, fault points and risk areas of fire protection equipment in real time, so as to realize the visualization of the fire situation and remote inspection and operation and maintenance management of the whole area.

[0017] Furthermore, each module is an independent and decoupled structure, uniformly configured with RS485, Ethernet, and wireless universal interfaces, supporting independent plug-and-play installation, replacement, and functional expansion of a single module.

[0018] Furthermore, the permission security management submodule sets up a multi-level permission hierarchy system to distinguish the operation permissions of administrators, operation and maintenance personnel, supervisors, and ordinary users.

[0019] The beneficial effects of this invention are as follows: 1. This invention adopts a fully modular decoupled architecture design, with each functional module being independently controllable and having standardized interfaces. It supports plug-and-play installation, partial replacement, and flexible expansion, solving the problems of rigid architecture, difficult modification, and poor compatibility of traditional fire protection systems. It can adapt to the fire control needs of buildings of different sizes and types, and significantly reduce the cost of system upgrades, modifications, and expansions.

[0020] 2. This invention enables remote operation and maintenance of the entire fire protection system. Relying on the cloud-based operation and maintenance platform and the edge local operation and maintenance collaboration mechanism, it can remotely complete all operation and maintenance operations such as equipment parameter configuration, program upgrade, fault diagnosis, reset and repair, calibration and debugging, and log reading. No manual on-site duty is required, which greatly reduces the workload of on-site operation and maintenance and reduces manpower and time costs. It is especially suitable for large-scale operation and maintenance management of large-scale, multi-point, and decentralized fire protection scenarios.

[0021] 3. This invention has intelligent risk prediction and preventive operation and maintenance capabilities. By analyzing equipment operation trends and environmental risk changes through big data modeling, it can identify potential fire hazards and equipment failures in advance, realizing the upgrade of management and control from "post-event handling" to "pre-event prevention". At the same time, the equipment self-diagnosis function can accurately locate the fault location and fault type, greatly improving the efficiency of fault diagnosis and repair. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a diagram of the modular system layered architecture of the present invention; Figure 2 This is a flowchart of the intelligent emergency response closed-loop process of the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0025] A modular intelligent fire management system capable of remote operation and maintenance is applied to fire control scenarios in multi-story buildings of large commercial complexes. The system adopts a modular and layered architecture, consisting of a front-end perception module group, an edge computing operation and maintenance module, an encrypted network transmission module, a cloud-based remote operation and maintenance management platform, and a terminal execution linkage module. Each module is connected through a standardized and universal interface, with functions decoupled and operating collaboratively.

[0026] During the specific deployment and installation phase, front-end sensing module groups are deployed in a distributed manner according to the fire compartment division of each floor of the commercial complex. Each fire compartment is independently configured with a sensing unit, including four types of fire detection sensors: smoke, temperature, flame, and combustible gas. Simultaneously, equipment status acquisition terminals, pipeline pressure / level / flow sensors, video surveillance cameras, and power monitoring terminals are deployed to comprehensively collect data on on-site fire characteristics, equipment operating conditions, pipeline status, environmental security, and power supply status. All front-end sensing devices use standardized pluggable interfaces, allowing for flexible addition or removal of devices based on the fire point requirements of each floor without modifying the system backbone architecture.

[0027] The edge computing operation and maintenance module is deployed in floor-by-floor zones, with one edge computing host configured for every two floors, responsible for the real-time processing of all front-end sensing data within its area. During operation, the data preprocessing submodule receives multi-source data collected from the front end in real time, uses a Kalman filter algorithm to remove abnormal data caused by environmental interference, and performs data noise reduction and standardized format conversion to ensure data accuracy and effectiveness. The equipment self-diagnosis submodule compares equipment operating parameters with a built-in standard threshold library in real time, autonomously diagnosing faults such as sensor malfunction, equipment offline, abnormal pipeline pressure, unstable power supply, and equipment jamming. It accurately locates the faulty equipment number, installation location, and fault type, and automatically generates a fault operation and maintenance report. For minor faults with slight deviations in equipment parameters, the system automatically performs remote parameter calibration and reset. For general faults such as intermittent equipment failure and pipeline pressure fluctuations, real-time operation and maintenance reminders are pushed to the mobile devices of management personnel. For serious faults such as complete equipment failure, severe pipeline leakage, and power outages, audible and visual alarms are immediately triggered, and the faulty equipment is locked to prevent the fault from escalating.

[0028] The offline linkage control submodule is pre-programmed with three levels of emergency linkage logic. It is on standby in real time during normal operation, and automatically switches to local offline working mode when a network interruption or cloud connection is detected. If an abnormal increase in local temperature or excessive smoke concentration is detected, a level one warning is triggered, and on-site audible and visual alarms and voice evacuation prompts are activated. If an open flame or flammable gas leak is confirmed, a level two linkage is triggered, automatically activating the corresponding area's sprinkler and smoke exhaust equipment, closing fire dampers, and turning on emergency evacuation indicator lights. If a large-scale fire or multiple area alarms are detected, a level three emergency response is triggered, activating the fire extinguishing, smoke exhaust, and evacuation systems in the entire area, while simultaneously locking fire compartments to prevent the spread of fire, achieving fully autonomous emergency control even in the event of a network outage.

[0029] The encrypted network transmission module employs dual-link redundant transmission of 5G wireless and wired Ethernet. Under normal operating conditions, both links work simultaneously and serve as backups for each other, ensuring stable data transmission. In the event of a single link failure, it automatically switches to the other link to avoid transmission interruption. The protocol adaptation unit automatically identifies the communication protocols of various brands of fire protection equipment, completes protocol conversion and data interoperability, and solves compatibility issues among multiple devices. All uplink data and downlink operation and maintenance control commands are encrypted using the AES-256 algorithm and undergo triple verification of identity, permissions, and integrity to prevent unauthorized command manipulation and data security risks.

[0030] The cloud-based remote operation and maintenance management platform builds a 3D digital twin model of the commercial complex, restoring the location and information of fire protection equipment on each floor and in each fire compartment in a 1:1 ratio. It displays the operating status, data parameters, and fault information of all equipment in real time. Managers can intuitively view the overall fire protection operation status through the cloud platform and realize visualized remote inspection.

[0031] The end-to-end remote operation and maintenance submodule is the core application unit of this system. Administrators can perform remote operation and maintenance of all fire protection equipment through the cloud platform without on-site work. It supports remote modification of equipment alarm thresholds, linkage parameters, and calibration parameters; remote program upgrades and firmware updates for single or batch devices; remote reading of equipment operation logs, fault logs, and maintenance logs; remote fault reset, equipment restart, and function debugging. For diagnosed faults, the system automatically generates maintenance work orders, assigns them to the corresponding maintenance personnel, and automatically archives the records after maintenance, forming a complete operation and maintenance loop. Simultaneously, the platform supports hierarchical permission management. The super administrator has full operation permissions, ordinary maintenance personnel only have fault handling and parameter viewing permissions, and supervisory personnel only have data query and alarm viewing permissions, ensuring the system operation is safe, controllable, and traceable.

[0032] The intelligent analysis and early warning submodule continuously collects operational and environmental data from storage devices. Through big data algorithms, it constructs equipment aging models and fire risk prediction models, analyzes equipment operating time, failure frequency, and parameter fluctuation patterns in real time, predicts the remaining service life of equipment in advance, and pushes replacement reminders to equipment that is about to age and fail, thus achieving preventive maintenance. At the same time, it analyzes the changing trends of ambient temperature, smoke, and gas concentration to identify hidden fire hazards, achieve early warning, and prevent fire accidents.

[0033] The terminal execution linkage module accurately executes corresponding operations based on instructions issued from the edge and cloud: under normal conditions, it keeps the equipment in standby mode and provides real-time feedback on its own operating status; under early warning conditions, it activates audible and visual alarms, voice broadcasts, and pushes alarm information to mobile devices; under fire conditions, it activates layered and zoned linkage operations such as sprinkler fire suppression, smoke exhaust and ventilation, emergency evacuation, and pipeline pressure stabilization, accurately controlling the equipment in the corresponding area, avoiding ineffective activation of equipment across the entire area, improving the accuracy of emergency response, and reducing energy consumption and equipment wear.

[0034] All system operation data, alarm records, fault information, operation and maintenance logs, and linkage records are stored in real time to a cloud-based distributed database, permanently preserved, and can be queried, exported, and traced at any time. This meets the archiving and traceability requirements of fire safety supervision and realizes digital, intelligent, standardized, and closed-loop control of the entire fire management process.

[0035] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A modular intelligent fire management system capable of remote operation and maintenance, characterized in that: It includes a front-end perception module group, an edge computing operation and maintenance module, an encrypted network transmission module, a cloud-based remote operation and maintenance management platform, and a terminal execution linkage module; the front-end perception module group, the edge computing operation and maintenance module, the encrypted network transmission module, the cloud-based remote operation and maintenance management platform, and the terminal execution linkage module are sequentially connected in communication. The front-end sensing module group is a distributed data acquisition terminal, including a fire detection submodule, an equipment status monitoring submodule, an environmental security monitoring submodule, a pipeline network condition monitoring submodule, and a power supply status monitoring submodule, which are used to collect multi-dimensional data such as fire characteristics, fire-fighting equipment conditions, on-site environment, pipeline network parameters, and power supply status. The edge computing operation and maintenance module is deployed in the local fire protection zone and includes a data preprocessing submodule, a device self-diagnosis submodule, a local operation and maintenance submodule, an offline linkage control submodule, and a data caching submodule, which are used to realize local data processing. The encrypted network transmission module adopts a dual-link redundant transmission architecture and has a built-in protocol adaptation unit, data encryption unit, and instruction verification unit to realize multi-protocol device adaptation, bidirectional encrypted data transmission, and secure instruction verification. The cloud-based remote operation and maintenance management platform includes a digital twin visualization operation and maintenance sub-module, a full-process remote operation and maintenance sub-module, an intelligent analysis and early warning sub-module, a multi-level linkage scheduling sub-module, a data storage and archiving sub-module, and an access security management sub-module, which are used to realize visualized remote inspection, remote operation and maintenance, intelligent risk early warning and hierarchical access control. The terminal execution linkage module includes an alarm prompting submodule, a fire extinguishing execution submodule, and a ventilation and smoke exhaust submodule, which are used to receive control commands and complete the linkage execution of fire alarm, fire extinguishing, and smoke exhaust operations.

2. The modular intelligent fire management system capable of remote operation and maintenance according to claim 1, characterized in that: The data preprocessing submodule incorporates a Kalman filter algorithm and a data standardization algorithm to perform noise reduction, filtering, format unification, and abnormal data removal on multi-source heterogeneous data from the front end, thereby improving the accuracy of data collection. The data caching submodule adopts a power-loss protected storage design, caching local data when the network is interrupted and automatically synchronizing it to the cloud after the network is restored.

3. The modular intelligent fire management system capable of remote operation and maintenance according to claim 1, characterized in that: The device self-diagnosis submodule has a built-in device fault feature database and status judgment model, which can autonomously diagnose device offline, abnormal parameters, component damage, and operational lag faults, accurately locate the fault location and fault type, and classify the faults into three levels: minor parameter abnormality, general operation fault, and serious failure fault, and generate corresponding differentiated operation and maintenance solutions such as automatic reset, operation and maintenance reminders, and emergency alarms.

4. The modular intelligent fire management system capable of remote operation and maintenance according to claim 1, characterized in that: The offline linkage control submodule is pre-set with multi-level emergency linkage logic. Under network interruption or cloud connection failure, it can independently complete fire level determination, alarm triggering, equipment linkage, and emergency start-up and shutdown operations, realizing local autonomous emergency control without cloud intervention.

5. A modular intelligent fire management system capable of remote operation and maintenance according to claim 1, characterized in that: The encrypted network transmission module uses the AES-256 encryption algorithm to achieve bidirectional encrypted transmission of data and instructions. Through a triple verification mechanism of identity verification, permission verification, and instruction integrity verification, it intercepts illegally tampered or hijacked control instructions, ensuring the security of system transmission and management.

6. The modular intelligent fire management system capable of remote operation and maintenance according to claim 1, characterized in that: The full-process remote operation and maintenance submodule supports remote device parameter configuration, remote program upgrade, remote fault reset, remote device calibration, remote start-up and shutdown debugging, and remote log reading. It also has a built-in operation and maintenance work order system that automatically generates, assigns, records, and archives operation and maintenance tasks, realizing closed-loop management of the operation and maintenance process, and supports batch remote operation and maintenance of multiple devices.

7. A modular intelligent fire management system capable of remote operation and maintenance according to claim 1, characterized in that: The intelligent analysis and early warning submodule has built-in equipment aging model and fire risk prediction model. Through long-term operation data trend analysis, it can predict the remaining service life of equipment, push equipment replacement reminders in advance, and identify hidden fire hazards, so as to realize the early warning of risks and equipment operation and maintenance.

8. A modular intelligent fire management system capable of remote operation and maintenance according to claim 1, characterized in that: The digital twin visualization operation and maintenance submodule builds a three-dimensional digital twin model of the building fire protection scene, which maps the location, operating status, data parameters, fault points and risk areas of fire protection equipment in real time, realizing the visualization of the fire situation and remote inspection and operation and maintenance management of the entire area.

9. A modular intelligent fire management system capable of remote operation and maintenance according to claim 1, characterized in that: Each module is an independent and decoupled structure, uniformly configured with RS485, Ethernet, and wireless universal interfaces, supporting independent plug-and-play installation, replacement, and functional expansion of a single module.

10. A modular intelligent fire management system capable of remote operation and maintenance according to claim 1, characterized in that: The permission security management submodule sets up a multi-level permission hierarchy system to distinguish the operation permissions of administrators, operation and maintenance personnel, supervisors, and ordinary users.

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