Fireproof data monitoring method, device, equipment and medium

Abstract

The embodiment of the invention provides a fireproof data monitoring method and device, equipment and a medium. The method comprises the steps of obtaining building information of a to-be-monitored building, and constructing a fire risk portrait of the to-be-monitored building based on the building information; deploying a dynamic sensing system of the to-be-monitored building based on the fire risk portrait, wherein the dynamic sensing system comprises a smoke sensor, an electrical fire detector and an image acquisition device; obtaining multi-dimensional sensing data corresponding to the dynamic sensing system, and determining a risk monitoring result of the to-be-monitored building based on the multi-dimensional sensing data; and generating a corresponding risk early warning strategy in response to the risk monitoring result, and optimizing the dynamic sensing system based on an execution result of the risk early warning strategy. According to the embodiment of the invention, active and passive fire prevention capabilities can be evaluated in combination with fire-fighting facilities, a multi-dimensional fire risk portrait is finally constructed, and accurate quantification and dynamic visual management and control of building fire risks are realized.

Description

Technical Field

[0001] This application relates to the field of building fire protection technology, specifically to a fire protection data monitoring method, device, equipment, and medium. Background Technology

[0002] Building fires are one of the major disasters that seriously threaten people's lives and property. Existing building fire monitoring technologies mainly rely on traditional automatic fire alarm systems. These systems typically deploy several point sensors such as smoke detectors and heat detectors within the building. When the smoke concentration or ambient temperature in the detected area exceeds a preset fixed threshold, an alarm signal is triggered. This alarm mode, based on a single parameter and a fixed threshold, constitutes the main technical means of current building fire prevention.

[0003] However, in practical applications, traditional technical solutions have obvious limitations and defects. Point sensors must wait for the smoke or heat generated by the fire to reach the detector body before they can respond. By this time, the fire may have already entered its development stage, missing the best opportunity to extinguish the initial fire and threatening the safe evacuation of personnel. Furthermore, automatic fire alarm, automatic fire extinguishing, emergency lighting, and smoke control systems often operate independently, lacking effective data exchange and intelligent linkage, making it difficult to achieve coordinated and efficient emergency response, resulting in poor fire monitoring and an inability to accurately assess fire risks. Summary of the Invention

[0004] To address the aforementioned technical problems, embodiments of this application provide a fire data monitoring method and apparatus, an electronic device, a computer-readable storage medium, and a computer program product.

[0005] According to one aspect of the embodiments of this application, a fire prevention data monitoring method is provided, comprising: acquiring building information of a building to be monitored, and constructing a fire risk profile of the building to be monitored based on the building information; deploying a dynamic sensing system of the building to be monitored based on the fire risk profile, the dynamic sensing system including a smoke sensor, an electrical fire detector, and an image acquisition device; acquiring multi-dimensional sensing data corresponding to the dynamic sensing system, and determining a risk monitoring result of the building to be monitored based on the multi-dimensional sensing data; generating a corresponding risk warning strategy in response to the risk monitoring result, and optimizing the dynamic sensing system based on the execution result of the risk warning strategy.

[0006] According to one aspect of the embodiments of this application, the building information includes building materials, fire protection facilities, and the building age. The step of constructing a fire risk profile of the building to be monitored based on the building information includes: determining the building risk coefficient of the building to be monitored based on the building materials and the building age; determining the active fire protection capability and passive fire protection capability of the building to be monitored based on the fire protection facilities; and determining the fire risk profile of the building to be monitored based on the building risk coefficient, the active fire protection capability, and the passive fire protection capability.

[0007] According to one aspect of the embodiments of this application, the method further includes: determining, based on the fire protection facilities, the active fire protection system corresponding to the building to be monitored, as well as the number and installation location of the active fire protection system, wherein the active fire protection system includes an automatic fire alarm system, an automatic fire extinguishing system, and the fire load of the building to be monitored; and determining the active fire protection capability of the building to be monitored based on the number and the safe location.

[0008] According to one aspect of the embodiments of this application, the method further includes: determining the passive fire protection system of the building to be monitored based on the building information, wherein the passive fire protection system includes fire compartments, fire separation distances, fireproofing, fire extinguishers, evacuation routes, and smoke exhaust systems of the building to be monitored; and determining the passive fire protection capability of the building to be monitored based on the passive fire protection system.

[0009] According to one aspect of the embodiments of this application, the deployment of the dynamic sensing system for the building to be monitored based on the fire risk profile includes: determining the risk points of the building to be monitored based on the fire risk profile; configuring the corresponding sensor device type and parameter configuration of the sensor device based on the risk level corresponding to the risk point; and determining the deployment of the dynamic sensing system for the building to be monitored based on the location information of the risk point, the sensor device type, and the configuration parameters of the sensor device.

[0010] According to one aspect of the embodiments of this application, the step of acquiring multi-dimensional sensing data corresponding to the dynamic sensing system and determining the risk monitoring result of the building to be monitored based on the multi-dimensional sensing data includes: standardizing the multi-dimensional sensing data to form a standardized multi-dimensional data stream carrying spatiotemporal labels; extracting features from the standardized multi-dimensional data stream to obtain fire feature signals corresponding to the risk points, wherein the fire feature signals include fire temperature parameters, delay parameters, personnel activity characteristics, flame characteristics, and visible smoke; and determining the risk monitoring result of the building to be monitored based on the fire feature signals.

[0011] According to one aspect of the embodiments of this application, the step of generating a corresponding risk warning strategy in response to the risk monitoring result and optimizing the dynamic perception system based on the execution result of the risk warning strategy includes: determining a risk warning strategy based on the risk level corresponding to the risk monitoring result and executing the risk warning strategy; during the execution of the risk warning strategy, obtaining a warning feedback result, the warning feedback result including on-site confirmation result, fire situation determination result, and strategy execution result; and optimizing the dynamic perception system based on the warning feedback result.

[0012] According to one aspect of the embodiments of this application, a fire prevention data monitoring device is provided, comprising: a construction module, configured to acquire building information of a building to be monitored, and construct a fire risk profile of the building to be monitored based on the building information; a deployment module, configured to deploy a dynamic sensing system of the building to be monitored based on the fire risk profile, the dynamic sensing system including a smoke sensor, an electrical fire detector, and an image acquisition device; a determination module, configured to acquire multi-dimensional sensing data corresponding to the dynamic sensing system, and determine the risk monitoring result of the building to be monitored based on the multi-dimensional sensing data; and a response module, configured to generate a corresponding risk warning strategy in response to the risk monitoring result, and optimize the dynamic sensing system based on the execution result of the risk warning strategy.

[0013] According to one aspect of the embodiments of this application, an electronic device is provided, including: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the electronic device to perform the method described above.

[0014] According to one aspect of the embodiments of this application, a computer-readable storage medium is provided that stores computer-readable instructions thereon, which, when executed by a computer's processor, cause the computer to perform the method described above.

[0015] According to one aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps in the method described above.

[0016] In the technical solution provided by the embodiments of this application, a fire risk profile is constructed by acquiring the building information of the building to be monitored, which can accurately grasp the fire risk characteristics and potential hidden dangers of the building, providing a solid foundation for subsequent work; a dynamic sensing system containing multiple devices is deployed based on the fire risk profile, which can acquire fire-related data in the building from all directions and multiple angles, improving the comprehensiveness and accuracy of fire monitoring; the risk monitoring results are determined by using the acquired multi-dimensional sensing data, which can timely and accurately detect fire risk conditions; a risk warning strategy is generated in response to the risk monitoring results, and the dynamic sensing system is optimized based on the execution results, forming a closed loop of dynamic adjustment and continuous improvement, which can continuously improve the efficiency and accuracy of fire monitoring, effectively reduce the risk of fire in buildings, and protect the safety of people's lives and property.

[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings: Figure 1 This is a schematic diagram illustrating the implementation environment of fire protection data monitoring, as shown in an exemplary embodiment of this application. Figure 2 This is a flowchart illustrating a fire data monitoring method in an exemplary embodiment of this application; Figure 3 This is a flowchart illustrating a fire data monitoring method, as shown in another exemplary embodiment of this application; Figure 4 This is a flowchart illustrating a fire data monitoring method, as shown in another exemplary embodiment of this application; Figure 5 This is a flowchart illustrating a fire data monitoring method, as shown in another exemplary embodiment of this application; Figure 6 This is a flowchart illustrating a fire data monitoring method, as shown in another exemplary embodiment of this application; Figure 7 This is a flowchart illustrating a fire data monitoring method, as shown in another exemplary embodiment of this application; Figure 8 This is a flowchart illustrating a fire data monitoring method, as shown in another exemplary embodiment of this application; Figure 9This is a block diagram illustrating a fire data monitoring device in an exemplary embodiment of this application; Figure 10 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown. Detailed Implementation

[0019] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0020] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0021] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0022] In this application, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0023] First, it should be noted that fire data monitoring in buildings is a comprehensive and crucial safety measure. It involves the rational deployment of various monitoring devices within the building, such as smoke sensors, temperature sensors, electrical fire detectors, and image acquisition devices, to continuously collect various data closely related to fire occurrences in real time. This includes information such as smoke concentration, ambient temperature, abnormal fluctuations in electrical circuit current and voltage, and on-site visual data. This data is then transmitted to an intelligent analysis system, which uses advanced algorithms and pre-set fire characteristic models for rapid and accurate analysis. Once abnormal data is detected or fire warning conditions are met, an alarm mechanism is immediately triggered, promptly notifying relevant personnel to take appropriate measures. Simultaneously, it provides detailed and reliable data support for subsequent fire investigations and the optimization of fire prevention strategies, thereby achieving early detection, early warning, and early response to building fire risks, minimizing the likelihood and severity of fires.

[0024] Figure 1 This is a schematic diagram illustrating an implementation environment for fire protection data monitoring, as shown in an exemplary embodiment of this application. Figure 1 As shown, server 120 acquires building information corresponding to building 110 to be monitored and constructs a fire risk profile of the building based on the building information. Then, server 120 deploys a dynamic sensing system for the building based on the fire risk profile. The dynamic sensing system includes smoke sensors, electrical fire detectors, and image acquisition devices. Next, server 120 acquires multi-dimensional sensing data corresponding to the dynamic sensing system and determines the risk monitoring results of the building based on the multi-dimensional sensing data. Finally, server 120 generates a corresponding risk warning strategy in response to the risk monitoring results and optimizes the dynamic sensing system based on the execution results of the risk warning strategy. This achieves fire prevention data monitoring and fire risk warning for the building to be monitored.

[0025] in, Figure 1 The server 120 shown can be, for example, a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. There are no restrictions on these options.

[0026] In practical applications, traditional technical solutions have obvious limitations and defects. Point sensors must wait for the smoke or heat generated by the fire to reach the detector body before they can respond. By this time, the fire may have already entered the development stage, missing the best opportunity to extinguish the initial fire and threatening the safe evacuation of personnel. Furthermore, automatic fire alarm, automatic fire extinguishing, emergency lighting, and smoke control systems often operate independently, lacking effective data exchange and intelligent linkage, making it difficult to achieve coordinated and efficient emergency response, resulting in poor fire monitoring and an inability to accurately assess fire risks.

[0027] To address these issues, embodiments of this application propose a fire data monitoring method, a novel fire data monitoring device, an electronic device, a computer-readable storage medium, and a computer program product, which will be described in detail below.

[0028] Please see Figure 2 , Figure 2 This is a flowchart illustrating a fire data monitoring method in an exemplary embodiment of this application. This method can be applied to... Figure 1 The implementation environment shown is specifically executed by server 120 within that implementation environment. It should be understood that this method can also be applied to other exemplary implementation environments and executed by devices in other implementation environments; this embodiment does not limit the implementation environment to which the method is applicable.

[0029] like Figure 2 As shown, in an exemplary embodiment, the fire data monitoring method includes at least steps S210 to S240, which are described in detail below: Step S210: Obtain building information of the building to be monitored, and construct a fire risk profile of the building to be monitored based on the building information.

[0030] For example, collecting data from multiple sources covers basic structural information about the building, such as its height, number of floors, and structural type (brick-concrete, frame, or steel structure, etc.). Different structures exhibit significant differences in fire resistance and combustion characteristics during a fire. For instance, steel structures are prone to losing strength at high temperatures, while brick-concrete structures are relatively fire-resistant but may have hidden dangers such as wall cracks. The building's floor plan is also crucial, including the distribution of functional areas, such as densely populated shopping malls and office areas, warehouses storing flammable materials, and the location and width of evacuation routes and safety exits. A reasonable layout facilitates rapid evacuation and firefighting during a fire, while a poor layout may exacerbate the spread of the fire and increase casualties. Information on the building's interior decoration materials is equally important. Different decoration materials have different combustion performance ratings; for example, flammable foam plastic decoration materials can accelerate the spread of fire, while flame-retardant materials can effectively slow down the development of a fire. Furthermore, it is necessary to understand the building's fire protection facilities, including whether the fire water supply is sufficient, the distribution and quantity of fire hydrants and fire extinguishers, and whether the automatic sprinkler system and automatic fire alarm system are operating normally and meet the required standards.

[0031] After obtaining this detailed building information, professional fire risk assessment methods and models are used, combined with historical fire data and industry experience, to conduct a comprehensive analysis and assessment of the building's fire risk. The assessment considers multiple dimensions, such as the likelihood of a fire, the speed and extent of fire spread, the difficulty of evacuation, and the potential losses caused by the fire. This process constructs a comprehensive and accurate fire risk profile that reflects the fire risk characteristics of the building to be monitored, providing a scientific basis for subsequent fire prevention, monitoring, and emergency response.

[0032] Step S220: Deploy a dynamic sensing system for the building to be monitored based on the fire risk profile. The dynamic sensing system includes smoke sensors, electrical fire detectors, and image acquisition devices.

[0033] For example, the various risk characteristics and key elements revealed by the fire risk profile should be fully considered. For smoke sensors, based on the fire-prone areas identified in the fire risk profile, such as densely populated conference rooms and restaurant kitchens with a large amount of combustible materials, or equipment rooms with complex electrical wiring and heavy loads, the installation location and number of sensors should be rationally planned in these key areas. Regarding installation height, the natural upward movement of smoke should be followed, typically installing them at a certain distance from the ceiling to ensure timely detection of smoke signals. Simultaneously, appropriate sensor spacing should be determined based on the area area and spatial layout to ensure effective coverage of the entire area and avoid monitoring blind spots. Electrical fire detectors are mainly deployed in areas with prominent electrical fire hazards in the fire risk profile, such as distribution boxes, cable trays, and areas with concentrated electrical equipment. Residual current type electrical fire detectors installed in distribution boxes can monitor the residual current in electrical circuits in real time. When the residual current exceeds a set threshold, an alarm can be issued promptly to prevent fires caused by leakage. Temperature-measuring electrical fire detectors installed at cable trays can monitor temperature changes on the cable surface; once the temperature rises abnormally, potential electrical fire risks can be quickly detected. The deployment of image acquisition devices should be combined with the analysis of potential fire scenarios and spread paths in fire risk profiling. High-definition cameras should be installed at key locations such as building entrances, evacuation routes, and stairwells to monitor personnel evacuation and the unobstructedness of passageways in real time. In areas prone to fire spread, such as large warehouses and atriums, cameras with wide-angle views and night vision capabilities should be installed to capture early signs of fire such as smoke and flames from all directions and around the clock. Simultaneously, cameras installed near fire-fighting facilities can monitor their operational status and usage in real time, ensuring they function properly during a fire. Through this precise and comprehensive deployment, smoke sensors, electrical fire detectors, and image acquisition devices can collaborate and complement each other, forming an efficient and reliable dynamic sensing system capable of accurately and in real time detecting fire risk information within buildings.

[0034] Step S230: Obtain multi-dimensional sensing data corresponding to the dynamic sensing system, and determine the risk monitoring results of the building to be monitored based on the multi-dimensional sensing data.

[0035] For example, the process of acquiring multi-dimensional sensing data corresponding to a dynamic sensing system and determining the risk monitoring results of the building to be monitored requires real-time collection of data such as smoke concentration and particulate matter distribution in various areas of the building through smoke sensors, acquisition of abnormal electrical parameters such as current, voltage, residual current, and temperature of electrical circuits through electrical fire detectors, and capture of visual features such as flame patterns, smoke diffusion trajectories, and abnormal personnel activities in the scene using image acquisition devices. This multi-dimensional sensing data is transmitted in real-time to a central data processing platform through wired or wireless communication networks. In the platform, data fusion technology is used to perform correlation analysis, spatiotemporal alignment, and feature extraction on the data from different sensors and devices. Combined with the risk thresholds, pattern recognition rules, and intelligent algorithm models set in the pre-constructed fire risk profile, the system comprehensively judges whether the smoke concentration exceeds the safety limit, whether there are abnormal fluctuations in electrical parameters, and whether flame or smoke features appear in the image. When any dimension of data triggers a preset fire warning condition or multiple dimensions of data collaboratively indicate an increased fire risk, the system will comprehensively determine the risk monitoring results, clarify the risk level, specific location, and possible development trend, providing accurate basis for subsequent risk warning and emergency response.

[0036] Step S240: Generate a corresponding risk warning strategy in response to the risk monitoring results, and optimize the dynamic perception system based on the execution results of the risk warning strategy.

[0037] For example, when generating corresponding risk warning strategies in response to risk monitoring results, it is necessary to formulate graded and classified warning strategies based on the risk level, specific location and development trend clearly defined in the monitoring results, combined with the fire risk profile of the building and historical warning data. For example, for low-risk situations, local area alarms and enhanced real-time monitoring can be implemented, while for medium- and high-risk situations, measures such as activating multi-channel alarms, notifying the fire department and evacuation guidance personnel can be taken. At the same time, the warning strategy must include detailed execution procedures, responsible parties and time limits to ensure that the warning information can be quickly and accurately transmitted to relevant personnel and trigger corresponding actions. During the execution of the early warning strategy, it is necessary to collect execution result data in real time, including the reception of early warning information, personnel response speed, the effectiveness of emergency measures, and the elimination of fire hazards. This data should be tracked and analyzed to evaluate the effectiveness and applicability of the early warning strategy. If problems such as untimely response, inadequate measures, or false alarms or omissions are found in the early warning strategy, the dynamic sensing system should be optimized and adjusted based on the feedback of the execution results. For example, the deployment location and density of sensors should be corrected according to the actual fire scene, the threshold setting of electrical fire detectors should be optimized, and the recognition algorithm of the image acquisition device should be improved to improve the accuracy of smoke and flame detection. At the same time, the fire risk profile should be updated in combination with new risk characteristics in the execution results, so that the dynamic sensing system can perceive risks more accurately and trigger early warnings more efficiently. Through a continuous execution-feedback-optimization cycle, the system's ability to monitor and warn of building fire risks and its emergency response efficiency can be continuously improved.

[0038] In the embodiments provided in this application, a fire risk profile is constructed by acquiring building information and a dynamic perception system is deployed. Combined with multi-dimensional perception data, accurate risk monitoring and graded early warning are achieved. Finally, the system is continuously optimized based on execution feedback, forming a closed-loop management of the entire process from risk identification to early warning and disposal, which significantly improves the intelligence level of building fire prevention and control and the efficiency of emergency response.

[0039] Furthermore, based on the above embodiments, please refer to... Figure 3 In one exemplary embodiment provided in this application, the aforementioned building information includes building materials, fire protection facilities, and the building's age. The specific implementation process of creating a fire risk profile of the building to be monitored based on the aforementioned building information may further include steps S310 to S330, which are detailed below: Step S310: Determine the building risk coefficient of the building to be monitored based on the building materials and the building age.

[0040] Step S320: Determine the active fire protection capability and passive fire protection capability of the building to be monitored based on the fire protection facilities.

[0041] Step S330: Determine the fire risk profile of the building to be monitored based on the building risk coefficient, active fire protection capability, and passive fire protection capability.

[0042] For example, when determining the building risk coefficient of a building to be monitored based on building materials and building age, it is necessary to comprehensively consider the combustion performance rating of building materials (such as flammable, combustible, flame-retardant, and non-combustible materials) and their distribution ratio in the building, combined with the building design codes and fire protection standards corresponding to the building age, to analyze the potential risks brought about by old buildings due to material aging, structural defects, or non-compliance with current fire protection requirements. For example, early buildings may have problems such as the lack of fire-resistant barriers and electrical wiring without conduit protection. By quantitatively assessing the fire resistance limit of materials, the stability of building structures, and age-related safety hazards, the building risk coefficient reflecting the inherent fire risk of the building is calculated. When determining active and passive fire protection capabilities based on fire protection facilities, active fire protection capabilities focus on the active intervention effectiveness of fire protection facilities when a fire occurs, such as the response time, coverage, and reliability of automatic sprinkler systems, the sensitivity and false alarm rate of automatic fire alarm systems, and the quantity and accessibility of fire extinguishers, fire hydrants, and other fire-fighting equipment. These facilities can detect the fire in time and initiate fire-fighting measures in the early stages of a fire. Passive fire protection focuses on the fire-resistant partitions of the building structure itself, the use of fire-resistant materials, and evacuation design, such as the fire resistance rating of firewalls, fire doors, and fire-resistant roller shutters, the width, length, and unobstructedness of evacuation routes, and whether the combustion performance of interior decoration materials meets the requirements of the regulations. These designs can delay the spread of fire and ensure the safe evacuation of personnel during a fire. Finally, by comprehensively analyzing the building risk coefficient, active fire protection capabilities, and passive fire protection capabilities, and using methods such as weighted scoring, fuzzy comprehensive evaluation, or machine learning models, the influence of the three on fire risk is integrated to form a comprehensive fire risk profile that reflects the probability of fire occurrence, the speed of fire spread, the difficulty of personnel evacuation, and the potential loss of the building under monitoring. This provides a scientific and accurate basis for subsequent fire prevention, monitoring and early warning, and emergency response.

[0043] In the embodiments provided in this application, the building risk coefficient is quantified by comprehensively considering building materials and building age, and the active and passive fire prevention capabilities are assessed by combining fire protection facilities. Finally, a multi-dimensional fire risk profile is constructed to achieve accurate quantification and dynamic visual management of building fire risk.

[0044] Furthermore, based on the above embodiments, please refer to... Figure 4 In one exemplary embodiment provided in this application, the specific implementation process of the above-mentioned fire data monitoring method may further include steps S410 and S420, which are described in detail below: Step S410: Based on the fire protection facilities, determine the active fire protection system corresponding to the building to be monitored, as well as the number and installation location of the active fire protection system. The active fire protection system includes an automatic fire alarm system, an automatic fire extinguishing system, and the fire load of the building to be monitored. Step S420: Determine the active fire protection capability of the building to be monitored based on the number and safe location.

[0045] For example, when determining the active fire protection system, its quantity, and installation location based on fire protection facilities and assessing its active fire protection capabilities, it is necessary to clarify that the active fire protection system includes three elements: automatic fire alarm system, automatic fire extinguishing system, and fire load. For the automatic fire alarm system, the type, quantity, and installation location of detectors (such as smoke and heat detectors) must be determined based on the building's floor plan, functional zoning, and fire risk level to ensure detector coverage of all critical areas and that spacing meets regulations. For example, detectors should be densely deployed in high-risk areas such as evacuation routes and equipment rooms. Wiring and signal transmission paths should be optimized based on the building's age and structural characteristics. For the automatic fire extinguishing system, the required number of sprinklers, extinguishing agent reserves, and coverage area must be calculated based on the fire load (i.e., the type, quantity, and distribution characteristics of combustibles within the building). For example, in areas with high fire loads such as warehouses and electrical rooms, fast-response sprinklers should be used, and sprinkler spacing should be appropriately set to ensure that the extinguishing agent can quickly and evenly cover the fire source. The fire load itself is an important basis for system design. The combustion characteristics and potential heat release rate of combustibles must be clarified through on-site surveys and material testing to deduce the activation threshold and response time of the automatic fire extinguishing system. Ultimately, by comprehensively evaluating the detection sensitivity, false alarm rate, and linkage control capabilities of the automatic fire alarm system, the fire extinguishing efficiency, coverage, and reliability of the automatic fire extinguishing system, as well as the actual impact of fire load on the system design, and combining whether the installation location meets safety standards such as evacuation safety distance and fire compartment requirements, the active fire protection capability of the building to be monitored is quantitatively determined, forming a closed-loop logic from system design to capability assessment, providing precise support for building fire risk prevention and control.

[0046] In the embodiments provided in this application, by specifying the number and installation location of the active fire protection systems (automatic fire alarm system, automatic fire extinguishing system and fire load) corresponding to the fire protection facilities, the active fire protection capability of the building to be monitored is accurately quantified, providing a scientific and dynamic assessment basis for fire risk prevention and control.

[0047] Furthermore, based on the above embodiments, please refer to... Figure 5 In one exemplary embodiment provided in this application, the specific implementation process of the above-mentioned fire data monitoring method may further include steps S510 and S520, which are described in detail below: Step S510: Determine the passive fire protection system of the building to be monitored based on the building information. The passive fire protection system includes the fire compartments, fire separation distances, fire-resistant sealing, fire extinguishers, evacuation routes, and smoke exhaust systems of the building to be monitored. Step S520: Determine the passive fire protection capability of the building to be monitored based on the passive fire protection system.

[0048] For example, when determining the passive fire protection system of a building to be monitored based on building information, a comprehensive analysis of the building's structural layout and functional characteristics is required. Fire compartments must be divided into independent fire-resistant units according to building height, area, and usage, with each compartment separated by firewalls, fire doors, or fire-resistant roller shutters to ensure effective fire control within the compartment. Fire separation distances must be determined by considering the surrounding environment and adjacent buildings to ensure a safe distance between the building and external facilities and other buildings, reducing the risk of external fire sources affecting or spreading the fire. Fire sealing requires the strict sealing of through-holes such as cable trays, pipe shafts, and ventilation ducts within the building, using fire-resistant putty, fire-resistant boards, or other materials to prevent smoke and flames from spreading through these openings. Fire extinguishing equipment must be configured according to the fire risk level of different areas within the building. For example, wheeled fire extinguishers should be provided for flammable and explosive areas, while portable fire extinguishers should be provided for general areas. It is also essential to ensure that the type of equipment matches the type of potential fire source; for example, dry powder fire extinguishers should be used for Class A fires, and carbon dioxide fire extinguishers for electrical fires. Evacuation routes must be designed in conjunction with the building's floor plan and personnel density, ensuring that the width and length of the routes meet regulations and are unobstructed. Clear evacuation signs and emergency lighting must be installed to ensure rapid and safe evacuation in the event of a fire. Smoke extraction systems must be designed according to the characteristics of the building space, using either natural or mechanical methods to ensure timely smoke removal and maintain the visibility of evacuation routes and safety exits during a fire. Finally, by comprehensively evaluating the effectiveness of fire compartment separation, the compliance of fire separation distances, the tightness of fireproofing, the rationality of fire extinguisher configuration, the unobstructed nature of evacuation routes, and the smoke extraction efficiency of the smoke extraction system, combined with the building's structural fire resistance rating, functional characteristics, and personnel evacuation needs, the passive fire protection capabilities of the building under monitoring are quantified. This forms a complete logical chain from system composition to capability assessment, providing precise support for passive fire protection in building fire risk prevention and control.

[0049] In the embodiments provided in this application, by integrating passive fire protection elements such as fire compartments and fire separation distances in building information, the passive fire protection capability of the building to be monitored is comprehensively and quantitatively evaluated, providing reliable protection for fire spread control and safe evacuation of personnel.

[0050] Furthermore, based on the above embodiments, please refer to... Figure 6 In one exemplary embodiment provided in this application, the specific implementation process of deploying the dynamic sensing system for the building to be monitored based on the fire risk profile may further include steps S610 to S630, which are described in detail below: Step S610: Determine the risk points of the building to be monitored based on the fire risk profile.

[0051] Step S620: Configure the corresponding sensor type and sensor parameter configuration based on the risk level of the risk point.

[0052] Step S630: Determine the deployment of a dynamic sensing system for the building to be monitored based on the location information of the risk points, the type of sensing device, and the configuration parameters of the sensing device.

[0053] For example, when determining risk points in a building to be monitored based on a fire risk profile, it is necessary to comprehensively analyze multi-dimensional information such as building structure, material characteristics, usage functions, fire protection facility status, and historical fire data to identify areas with a high probability of fire occurrence, rapid spread, or significant potential losses, such as electrical distribution rooms with dense electrical wiring, warehouses storing flammable materials, and densely populated shopping mall atriums. These areas are marked as risk points due to risk characteristics such as electrical faults, accumulation of combustibles, or difficulties in personnel evacuation. Subsequently, the corresponding type of sensor device is configured according to the risk level of the risk point (e.g., high, medium, low). High-risk points require the deployment of highly sensitive, multi-parameter fusion sensors, such as composite sensors that simultaneously possess smoke detection, temperature monitoring, and electrical parameter analysis functions. Medium- and low-risk points can use sensors with a single parameter but wide coverage, such as smoke sensors or temperature sensors. At the same time, the parameter configuration of the sensor device is adjusted in conjunction with the risk level. For example, smoke sensors at high-risk points need to be set with lower concentration thresholds and shorter response times, and electrical fire detectors need to optimize residual current and temperature alarm thresholds to reduce false alarms and missed alarms. Ultimately, based on the specific location information of risk points (such as floor, room number, and spatial coordinates), the type of sensing device (such as composite or single type), and configuration parameters (such as threshold and response time), the installation location and wiring scheme of the sensing devices are planned through 3D modeling or digital twin technology. This ensures that the sensors cover all risk points without any blind spots. At the same time, the data transmission path and power supply scheme are optimized in combination with the characteristics of the building structure, forming a closed-loop logic from risk identification to sensor deployment. This constructs a dynamic perception system that accurately adapts to the fire risk profile and dynamically responds to changes in risk, providing solid technical support for the early detection, rapid warning, and efficient handling of building fires.

[0054] In the embodiments provided in this application, risk points are accurately located by fire risk profiling and matched with differentiated sensing devices and parameters, so as to achieve deep adaptation between the dynamic perception system and building fire risk, and significantly improve the accuracy and response efficiency of early fire warning.

[0055] Furthermore, based on the above embodiments, please refer to... Figure 7 In the embodiments provided in this application, the specific implementation process of obtaining multi-dimensional sensing data corresponding to the dynamic sensing system and determining the risk monitoring results of the building to be monitored based on the multi-dimensional sensing data may further include steps S710 to S730, which are described in detail below: Step S710: Standardize the multidimensional sensing data to create a standardized multidimensional data stream carrying spatiotemporal labels.

[0056] Step S720: Extract features from the standardized multi-dimensional data stream to obtain fire feature signals for the corresponding risk points. The fire feature signals include fire temperature parameters, delay parameters, personnel activity characteristics, flame characteristics, and visible smoke.

[0057] Step S730: Determine the risk monitoring results of the building to be monitored based on fire characteristic signals.

[0058] For example, when standardizing multidimensional sensor data, the raw data from different types of sensors, such as smoke sensors, electrical fire detectors, and image acquisition devices, must first be cleaned and denoised to eliminate outliers and noise caused by environmental interference, equipment failure, or signal transmission errors. Then, normalization or standardization methods are used to unify data of different dimensions and ranges to a comparable scale. Simultaneously, precise spatiotemporal labels (such as specific location coordinates and timestamps) are added to each data point, forming a standardized multidimensional data stream carrying spatiotemporal information. Next, feature extraction is performed on this data stream. For temperature parameters, features such as temperature rise rate and high-temperature duration are extracted from raw temperature data collected by devices such as thermocouples and infrared sensors. For smoke parameters, features such as smoke diffusion speed and smoke particle size distribution are extracted from smoke concentration data collected by devices such as optical scattering and ion sensors. For personnel activity features, behavioral features such as personnel density, movement trajectory, and abnormal aggregation are extracted using video analysis technology. For flame features, visual features such as flame color, shape, and flicker frequency are extracted using image processing technology. For visible smoke, features such as smoke concentration gradient and diffusion pattern are extracted using image recognition. Finally, based on the extracted fire feature signals, a pre-set fire risk assessment model (such as a rule-based expert system or a machine learning-based intelligent algorithm) is used, combined with the risk thresholds and pattern matching rules set in the fire risk profile, to comprehensively analyze single or combined features such as abnormal temperature rise, excessive smoke concentration, appearance of flame features, and abnormal personnel activity. When the feature signals reach the pre-set fire warning conditions, it is determined to be a high-risk state and a risk monitoring result containing risk level, specific location, and development trend is generated, providing accurate data support for subsequent risk warning and emergency response.

[0059] In the embodiments provided in this application, multi-dimensional sensor data is processed in a standardized manner to form a standardized data stream carrying spatiotemporal labels. Key fire characteristic signals such as temperature, smoke, and human activity are extracted, and the risk monitoring results of the building to be monitored are finally accurately determined, so as to achieve efficient and accurate control of fire risk from data collection to monitoring results.

[0060] Furthermore, based on the above embodiments, please refer to... Figure 8 In one exemplary embodiment provided in this application, the specific implementation process of generating a corresponding risk warning strategy based on the response risk monitoring result and optimizing the dynamic perception system based on the execution result of the risk warning strategy may further include steps S810 to S830, which are described in detail below: Step S810: Determine the risk warning strategy based on the risk level corresponding to the risk monitoring results, and execute the risk warning strategy.

[0061] Step S820: During the execution of the risk warning strategy, obtain the warning feedback results, which include on-site confirmation results, fire situation determination results, and strategy execution results.

[0062] Step S830: Optimize the dynamic perception system based on the early warning feedback results.

[0063] For example, when determining and implementing a risk warning strategy based on the risk level corresponding to the risk monitoring results, a tiered response strategy must first be formulated according to the risk level (e.g., low, medium, high) clearly defined in the monitoring results. For instance, at low risk, local area alarms and enhanced real-time monitoring might be activated; at medium risk, multi-channel alarms might be triggered, and the fire department and evacuation guidance personnel might be notified; at high risk, fire-fighting facilities might be automatically activated, and the entire building might be evacuated. Simultaneously, the warning strategy must include detailed execution procedures, responsible parties, and time limits to ensure rapid and accurate information transmission. Specifically, real-time monitoring of warning feedback is necessary, including on-site personnel's confirmation of the alarm, the fire department's assessment of the fire situation upon arrival (e.g., location of the fire, fire scale), and the effectiveness of the strategy implementation (e.g., evacuation time, fire-fighting facility activation efficiency). The effectiveness and applicability of the warning strategy can be evaluated by tracking and analyzing this feedback data. If problems such as response delays, inadequate measures, or false alarms / missed alarms are found, the dynamic sensing system needs to be optimized and adjusted based on the feedback results. For example, the deployment location and density of sensors should be corrected according to the actual fire scenario, the threshold settings of electrical fire detectors should be optimized, and the recognition algorithm of image acquisition devices should be improved to enhance the accuracy of smoke and flame detection. At the same time, the fire risk profile should be updated based on the new risk characteristics exposed in the feedback. Through a continuous execution-feedback-optimization cycle, the system's ability to monitor and warn of building fire risks and its emergency response efficiency can be continuously improved, ultimately forming a closed-loop management mechanism from risk monitoring to strategy execution to system optimization.

[0064] In the embodiments provided in this application, a graded early warning strategy is determined and implemented based on the risk level of the risk monitoring results. Combined with on-site confirmation, fire identification and strategy implementation feedback results during the implementation process, the dynamic perception system is continuously optimized, forming a closed-loop management mechanism from monitoring and early warning to system optimization, which significantly improves the accuracy of building fire prevention and control and the effectiveness of emergency response.

[0065] Figure 9 This is a block diagram illustrating a fire data monitoring device according to an exemplary embodiment of this application. The device can be applied to… Figure 1 The implementation environment shown is specifically configured in server 120. This device can also be applied to other exemplary implementation environments and specifically configured in other devices. This embodiment does not limit the implementation environment to which the device is applicable.

[0066] like Figure 9 As shown, the exemplary fire data monitoring device includes: a construction module 910, used to acquire building information of the building to be monitored and construct a fire risk profile of the building to be monitored based on the building information; a deployment module 920, used to deploy a dynamic sensing system of the building to be monitored based on the fire risk profile, the dynamic sensing system including a smoke sensor, an electrical fire detector and an image acquisition device; a determination module 930, used to acquire multi-dimensional sensing data corresponding to the dynamic sensing system and determine the risk monitoring result of the building to be monitored based on the multi-dimensional sensing data; and a response module 940, used to generate a corresponding risk warning strategy in response to the risk monitoring result and optimize the dynamic sensing system based on the execution result of the risk warning strategy.

[0067] According to one aspect of the embodiments of this application, the above-mentioned construction module 910 is further configured to: determine the building risk coefficient of the building to be monitored based on the building materials and the building age; determine the active fire protection capability and passive fire protection capability of the building to be monitored based on the fire protection facilities; and determine the fire risk profile of the building to be monitored based on the building risk coefficient, active fire protection capability and passive fire protection capability.

[0068] According to one aspect of the embodiments of this application, the above-mentioned construction module 910 is further configured to determine the active fire protection system corresponding to the building to be monitored, as well as the number and installation location of the active fire protection system, based on the fire protection facilities. The active fire protection system includes an automatic fire alarm system, an automatic fire extinguishing system, and the fire load of the building to be monitored; and determine the active fire protection capability of the building to be monitored based on the number and safe location.

[0069] According to one aspect of the embodiments of this application, the above-mentioned construction module 910 is further configured to determine the passive fire protection system of the building to be monitored based on the building information, wherein the passive fire protection system includes fire compartments, fire separation distances, fireproof sealing, fire extinguishing equipment, evacuation routes and smoke exhaust systems of the building to be monitored; and determine the passive fire protection capability of the building to be monitored based on the passive fire protection system.

[0070] According to one aspect of the embodiments of this application, the deployment module 920 is further configured to: determine the risk points of the building to be monitored based on the fire risk profile; configure the corresponding sensor device type and sensor device parameter configuration based on the risk level corresponding to the risk points; and determine the deployment of a dynamic sensing system for the building to be monitored based on the location information of the risk points, the sensor device type, and the configuration parameters of the sensor devices.

[0071] According to one aspect of the embodiments of this application, the determination module 930 is further configured to: standardize the multidimensional sensing data to form a standardized multidimensional data stream carrying spatiotemporal labels; extract features from the standardized multidimensional data stream to obtain fire feature signals for the corresponding risk points, the fire feature signals including fire temperature parameters, delay parameters, personnel activity characteristics, flame characteristics, and visible smoke; and determine the risk monitoring results of the building to be monitored based on the fire feature signals.

[0072] According to one aspect of the embodiments of this application, the response module 940 is further configured to: determine a risk warning strategy based on the risk level corresponding to the risk monitoring result, and execute the risk warning strategy; during the execution of the risk warning strategy, obtain warning feedback results, including on-site confirmation results, fire situation identification results, and strategy execution results; and optimize the dynamic perception system based on the warning feedback results.

[0073] It should be noted that the fire data monitoring device and the fire data monitoring method provided in the above embodiments belong to the same concept. The specific operation methods of each module and unit have been described in detail in the method embodiments and will not be repeated here. In practical applications, the fire data monitoring device provided in the above embodiments can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. This is not a limitation here.

[0074] Embodiments of this application also provide an electronic device, including: one or more processors; and a storage device for storing one or more programs, which, when executed by one or more processors, cause the electronic device to implement the fire data monitoring method provided in the above embodiments.

[0075] Figure 10 A schematic diagram of a computer system suitable for implementing the embodiments of this application is shown. It should be noted that... Figure 10 The computer system 1000 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0076] like Figure 10As shown, the computer system 1000 includes a Central Processing Unit (CPU) 1001, which can perform various appropriate actions and processes, such as executing the methods described in the above embodiments, based on programs stored in Read-Only Memory (ROM) 1002 or programs loaded from storage portion 1008 into Random Access Memory (RAM) 1003. The RAM 1003 also stores various programs and data required for system operation. The CPU 1001, ROM 1002, and RAM 1003 are interconnected via a bus 1004. An Input / Output (I / O) interface 1005 is also connected to the bus 1004.

[0077] The following components are connected to I / O interface 1005: an input section 1006 including a keyboard, mouse, etc.; an output section 1007 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 1008 including a hard disk, etc.; and a communication section 1009 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to I / O interface 1005 as needed. Removable media 1011, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 1010 as needed so that computer programs read from them can be installed into storage section 1008 as needed.

[0078] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1009, and / or installed from removable medium 1011. When the computer program is executed by central processing unit (CPU) 1001, it performs various functions defined in the system of this application.

[0079] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0080] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0081] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0082] Another aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the fire data monitoring method described above. This computer-readable storage medium may be included in the electronic device described in the above embodiments, or it may exist independently and not assembled into the electronic device.

[0083] Another aspect of this application provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the fire data monitoring method provided in the various embodiments described above.

[0084] The above description is merely a preferred exemplary embodiment of this application and is not intended to limit the implementation of this application. Those skilled in the art can easily make corresponding modifications or alterations based on the main concept and spirit of this application. Therefore, the scope of protection of this application should be determined by the scope of protection claimed in the claims.

Claims

1. A method for monitoring fire prevention data, characterized in that, include: Obtain building information of the building to be monitored, and construct a fire risk profile of the building to be monitored based on the building information; Based on the fire risk profile, a dynamic sensing system is deployed for the building to be monitored. The dynamic sensing system includes smoke sensors, electrical fire detectors, and image acquisition devices. Acquire multi-dimensional sensing data corresponding to the dynamic sensing system, and determine the risk monitoring result of the building to be monitored based on the multi-dimensional sensing data; The system generates a corresponding risk warning strategy in response to the risk monitoring results, and optimizes the dynamic perception system based on the execution results of the risk warning strategy.

2. The method as described in claim 1, characterized in that, The building information includes building materials, fire protection facilities, and the building's age. The fire risk profile of the building to be monitored, constructed based on the building information, includes: The building risk coefficient of the building to be monitored is determined based on the building materials and the building age. The active fire protection capability and passive fire protection capability of the building to be monitored are determined based on the fire protection facilities. The fire risk profile of the building to be monitored is determined based on the building risk coefficient, the active fire protection capability, and the passive fire protection capability.

3. The method as described in claim 2, characterized in that, The method further includes: Based on the fire protection facilities, the active fire protection system corresponding to the building to be monitored, as well as the quantity and installation location of the active fire protection system, are determined. The active fire protection system includes an automatic fire alarm system, an automatic fire extinguishing system, and the fire load of the building to be monitored. The active fire protection capability of the building to be monitored is determined based on the quantity and the safe location.

4. The method as described in claim 2, characterized in that, The method further includes: The passive fire protection system of the building to be monitored is determined based on the building information. The passive fire protection system includes the fire compartments, fire separation distances, fireproofing, fire extinguishers, evacuation routes and smoke exhaust systems of the building to be monitored. The passive fire protection capability of the building to be monitored is determined based on the passive fire protection system.

5. The method according to any one of claims 1 to 4, characterized in that, The dynamic sensing system for deploying the building to be monitored based on the fire risk profile includes: Based on the fire risk profile, the risk points of the building to be monitored are determined; Configure the corresponding sensing device type and parameter configuration based on the risk level of the risk location; The dynamic sensing system for the building to be monitored is deployed based on the location information of the risk points, the type of the sensing device, and the configuration parameters of the sensing device.

6. The method as described in claim 5, characterized in that, The step of acquiring multi-dimensional sensing data corresponding to the dynamic sensing system and determining the risk monitoring result of the building to be monitored based on the multi-dimensional sensing data includes: The multidimensional sensing data is standardized to make the standardized multidimensional data stream carrying spatiotemporal labels; Feature extraction is performed on the standardized multi-dimensional data stream to obtain fire feature signals for the corresponding risk points. The fire feature signals include fire temperature parameters, delay parameters, personnel activity characteristics, flame characteristics, and visible smoke. The risk monitoring results of the building to be monitored are determined based on the fire characteristic signals.

7. The method as described in claim 6, characterized in that, The step of generating a corresponding risk warning strategy in response to the risk monitoring results, and optimizing the dynamic perception system based on the execution results of the risk warning strategy, includes: A risk warning strategy is determined based on the risk level corresponding to the risk monitoring results, and the risk warning strategy is executed. During the execution of the risk warning strategy, warning feedback results are obtained, including on-site confirmation results, fire situation determination results, and strategy execution results. The dynamic sensing system is optimized based on the early warning feedback results.

8. A fire prevention data monitoring device, characterized in that, The device includes: A construction module is used to acquire building information of the building to be monitored and construct a fire risk profile of the building to be monitored based on the building information; The deployment module is used to deploy a dynamic sensing system for the building to be monitored based on the fire risk profile. The dynamic sensing system includes a smoke sensor, an electrical fire detector, and an image acquisition device. The determination module is used to acquire multi-dimensional sensing data corresponding to the dynamic sensing system, and determine the risk monitoring result of the building to be monitored based on the multi-dimensional sensing data; The response module is used to generate a corresponding risk warning strategy in response to the risk monitoring results, and to optimize the dynamic perception system based on the execution results of the risk warning strategy.

9. An electronic device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, cause the electronic device to perform the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores computer-readable instructions that, when executed by the computer's processor, cause the computer to perform the method of any one of claims 1 to 7.

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