1283 results about "Fire prevention" patented technology

A device, system and method comprising computer vision techniques for fire prevention / detection and risk assessment, as well as for determining deviations from an ideal operational state. The present invention includes for example systems and methods which leverage data collected by camera systems composed of infrared and visible light sensors to detect and / or prevent a fire from starting, and additionally, use this data to determine a risk assessment for the building. The present invention also provides for example a system and method for monitoring and controlling safety risks in indoor industrial environments by determining deviations from an ideal operational state using computer vision techniques and game-theoretic competitive ranking frameworks.

The invention relates to the technical field of fire-fighting early warning, and discloses a fire-fighting early warning system based on image data relevance. The system comprises a multi-source image acquisition module used for acquiring fire-fighting scene multi-source heterogeneous image data; the correlation feature analysis module is used for performing cross-data-source correlation analysis on the data to generate feature vectors; the spatio-temporal dynamic modeling module is used for constructing a multi-dimensional feature fusion space to generate an associated spatio-temporal feature tensor; the resource optimization scheduling library is used for constructing a double-layer collaborative library; and the intelligent early warning control module generates a real-time fire early warning instruction and an emergency response decision through a hierarchical reinforcement learning framework. The system also has the functions of building structure deformation detection, smoke diffusion prediction and the like. Through cooperation of multiple modules, accurate fire-fighting early warning and efficient emergency response are realized, the fire prevention and control capability is improved, and life and property safety is effectively guaranteed.

The invention relates to the technical field of regional fire-fighting analysis, in particular to a regional fire-fighting risk analysis method and system based on multi-modal AI analysis. The method comprises the following steps: collecting a multi-modal fire-fighting related sensing source in an area, carrying out cross-modal fusion processing and abnormal event detection, and identifying a fire-fighting risk mutation point; carrying out risk propagation trend evolution on the fire risk mutation points, and carrying out fire source high-dimensional traceability analysis to obtain regional fire risk traceability points; performing risk evolution time estimation on the regional fire-fighting risk tracing point, and then performing fire risk situation evolution prediction to obtain a fire-fighting simulation situation map; and performing dynamic risk level change tracking according to the fire-fighting simulation situation map, and performing comprehensive emergency demand adjustment to obtain comprehensive risk intervention decision parameters. Through refined resource matching, the utilization rate of fire-fighting resources is improved, and the regional fire prevention and control quality and safety efficiency are improved.

The invention discloses a fire-fighting early warning system and method based on artificial intelligence, and relates to the technical field of intelligent fire-fighting early warning, and the system comprises an environment sensing module which comprises a multispectral sensor, a temperature sensor, a smoke sensor and a high-definition camera, and is used for collecting fire characteristic spectral data and transmitting the data to a data analysis module; the data analysis module comprises an edge calculation unit and a data fusion unit, and is used for performing feature extraction and anomaly detection on the fire feature spectrum data through a deep learning model to generate a fire risk assessment result; the early warning decision module comprises a risk assessment unit, an early warning grading unit and a communication unit, and is used for determining an early warning grade according to a fire risk assessment result and triggering equipment of the execution feedback module; and the execution feedback module comprises a spraying system, an emergency lighting system and an alarm and is used for executing fire emergency measures according to the instruction of the early warning decision module. According to the invention, comprehensive improvement of fire prevention and control efficiency is realized through cooperative work of multiple modules.

The invention relates to the technical field of fire prevention and control, in particular to a BIM and AI algorithm-combined fire spreading path evaluation system, which comprises a multi-source data fusion module, a fire source positioning module, a spreading path prediction module, a risk evaluation module and an intelligent linkage module. A three-dimensional dynamic model is generated by fusing sensor data and BIM data, accurate fire source positioning and fire spreading path prediction are achieved, the regional risk level is quantified in combination with building information, and a control instruction is sent to fire fighting equipment to isolate a high-risk region and delay fire spreading. The fire source positioning precision, the fire behavior prediction reliability and the emergency response efficiency can be improved, and scientific decision support is provided for building fire prevention and control.

The invention relates to the technical field of intelligent forestry management, and particularly discloses a forest farm intelligent comprehensive management and control system, which comprises a space-air-ground collaborative sensing module, a fire danger dynamic modeling module and an intelligent decision execution module. The method comprises the following steps: acquiring temperature field data through multispectral satellite remote sensing, constructing a high-precision terrain model through a laser radar, extracting vegetation features through hyperspectral imaging, extracting a thermal anomaly structure by adopting topological continuous coherence analysis and a Morse-Smal complex method, and establishing an adaptive fire danger model in combination with a quantum annealing optimizer. The system can generate a fire danger thermodynamic diagram in real time and divide risk levels, and drives the unmanned aerial vehicle to perform priority patrol and obstacle avoidance path planning. The problems of difficulty in pseudo hot area identification, low fire danger prediction precision, non-intelligent path planning and the like in a complex environment are solved, and the intelligent level of forest farm fire prevention and control is improved.

The invention relates to the technical field of unmanned aerial vehicle inspection, and provides an unmanned aerial vehicle-based forest fire prevention inspection and disposal method, device and system. When an inspection unmanned aerial vehicle equipped with a multi-modal sensor is deployed to cruise according to a preset route, a visible light camera of the inspection unmanned aerial vehicle continuously collects forest region videos and transmits the videos to edge computing equipment of an inspection airport; fire hazards are analyzed in real time through a target recognition algorithm, and when a fire source is detected, position information is reported to a background terminal immediately; the system automatically dispatches the nearest fire extinguishing airport to dispatch the fire extinguishing unmanned aerial vehicle, and secondary accurate positioning is performed on a fire source by using the airborne infrared vision module, so that accurate throwing of the fire extinguishing bomb is ensured. The whole system enhances the real-time analysis capability through the edge computing device, breaks through the single-machine computing power limitation, also realizes the full-process automation from fire behavior recognition to fire extinguishing treatment, and significantly improves the response efficiency and treatment safety of forest fire prevention.

The invention discloses a fire monitoring controller with a self-adaptive alarm threshold adjustment function, and belongs to the technical field of fire monitoring. Comprising a data acquisition module used for acquiring visible light and infrared double-spectrum video streams of a monitoring area and environment temperature and humidity; the data processing module is used for executing scene classification, fire feature analysis, dynamic alarm threshold calculation and alarm decision according to the video stream and the environment data; the feedback learning module is used for optimizing the fire analysis model according to the false report and / or missing report data; and the alarm execution module triggers sound-light alarm and fire-fighting equipment linkage according to the alarm decision. According to the invention, adaptive adjustment of the alarm threshold is realized, the problems of poor threshold adaptation, poor environmental adaptability, high false alarm / missing alarm rate, response lag and the like of the device in the prior art are solved, and a high-reliability solution is provided for multi-scene fire prevention and control.

The invention provides an intelligent fire prevention and control fire-fighting management system and method for a lithium battery energy storage power station, and relates to the technical field of data processing, and the method comprises the steps: arranging a multi-level temperature sensor, a gas detector and a smoke detector in and outside a battery module, and collecting and forming multi-source monitoring data; performing time sequence rate analysis, and if a preset condition is met, generating early warning data; in combination with sensor matrix distribution in the battery module, spatial cross comparison is executed to obtain abnormal positioning data, and false anomalies are eliminated through multi-point consistency verification; generating a directional processing instruction corresponding to the injection unit, and setting injection data in the processing instruction; the spraying unit is controlled to release an atomized fire extinguishing medium, so that the medium forms a permeation flow field in the gaps of the battery cells, and treatment feedback data is acquired and formed; performing trend analysis, and if the trend is not enough to recover to the preset safety range, generating a secondary processing instruction; according to the invention, the autonomy and accuracy of fire control management are improved.

The invention discloses a fire prevention and control method and system for battery energy storage equipment. The method comprises the following steps: collecting real-time fire characteristic parameters of the battery energy storage equipment; based on the real-time fire characteristic parameters and a preset fire control strategy, making a fire control decision and generating a fire control instruction; obtaining effect feedback after the fire-fighting instruction is executed; based on the real-time fire characteristic parameters and effect feedback, optimizing and updating a fire-fighting strategy; and applying the optimized and updated fire-fighting strategy to a subsequent fire-fighting decision of the battery energy storage equipment. According to the method, through real-time monitoring, digital twinborn simulation and a closed-loop optimization mechanism, the accuracy and adaptive capacity of fire prevention and control of the battery energy storage equipment are remarkably improved, dynamic adjustment and low-risk verification of a fire-fighting strategy are achieved, and safety and reliability are effectively enhanced.

The invention relates to the technical field of fire-fighting simulation, and discloses a fire-fighting fire dynamic simulation system based on multi-physics field coupling. The system collects temperature field distribution data, smoke concentration gradient data, airflow velocity field data and building structure heat conduction parameters of a fire scene; establishing a bidirectional coupling model of a temperature field and a smoke diffusion field, realizing dynamic correction of a smoke convection effect by a temperature gradient through real-time data exchange, constructing a correlation model of an airflow velocity field and a heat conduction parameter of a building structure, and adjusting a velocity field vortex coefficient according to heat flow intensity; integrating the bidirectional coupling model and the correlation model to form a multi-physical field joint calculation framework, and propelling a simulation process by adopting a discrete time slicing mode; and outputting a three-dimensional dynamic simulation map including a temperature field evolution track, a smoke diffusion path and an airflow disturbance range. The system can accurately restore the fire scene multi-physics field synergistic effect process, and provides effective support for fire rescue decision and building fire protection design.

The invention relates to the technical field of forest steppe fire emergency command, and discloses a forest steppe fire comprehensive monitoring and emergency command method and system. The method comprises the following steps: acquiring multi-source monitoring data of a satellite, an unmanned aerial vehicle and a ground sensor, and constructing a fire scene multi-dimensional feature vector through cooperative training and feature fusion; inputting the feature vectors into a physical simulation model to generate fire scene spreading speed and temperature gradient data; analyzing a terrain obstacle coefficient based on the spreading speed data and generating a helicopter no-fly zone coordinate and a passing attenuation factor; and solving and outputting a rescue unit deployment instruction through the scheduling matrix, and projecting a holographic image by using an augmented reality terminal to realize dynamic closed-loop feedback. Through deep fusion of a physical mechanism and reinforcement learning, the problem of separation of traditional fire prediction and resource scheduling is solved, intelligent decision-making of fire accurate prediction and emergency response is realized, and the accuracy and timeliness of fire prevention and control are remarkably improved.

The invention relates to the technical field of coal mine fire prevention and control, and discloses a coal mine fire disaster prevention and control system and method based on artificial intelligence. A data preprocessing module of the system cleans and converts the data to obtain high-quality data; the fire prevention knowledge base construction module constructs a coal mine fire prevention ontology knowledge base in combination with the preprocessed data and a preset fire prevention knowledge text; the risk map construction module constructs a risk knowledge map containing risk nodes, attribute edges and relation edges based on the knowledge base and historical disaster data; a risk factor extraction module extracts fire risk factors from real-time monitoring data, and a risk mapping module maps the fire risk factors to a risk knowledge graph to obtain risk association nodes; and the risk reasoning module performs reasoning analysis on the risk association nodes according to the risk knowledge graph and a preset fireproof rule to form a preliminary risk assessment result, so that the comprehensiveness and effectiveness of coal mine fireproof disaster prevention and control can be improved.

The invention relates to the technical field of forest fire monitoring and power grid safety prevention and control, and discloses a fire scene spreading time sequence reconstruction method based on Doppler weather radar mountain fire echoes, which comprises the following steps: acquiring original data of the Doppler weather radar mountain fire echoes and carrying out quality control processing to obtain radar echo data; performing automatic segmentation of a smoke plume area on radar echo data by adopting an optimized Otsu-Unet network model, and extracting a centroid coordinate of a mountain fire echo area; a Kalman filtering algorithm is used and combined with external three-dimensional wind field data to predict a future motion trend of centroid coordinates of a forest fire echo region so as to reconstruct a continuous fire scene spreading time sequence voxel sequence; performing 3DTiles slicing processing on the fire scene spreading time sequence voxel sequence, and performing real-time rendering display on a power grid monitoring platform by using a WebGL technology; and obtaining an external expansion boundary of fire scene spreading based on the fire scene spreading time sequence voxel sequence, and calculating the distance between the external expansion boundary and the power transmission line GIS data in real time. The fire prevention and control capability of the power transmission line of the power grid is improved.

The invention is suitable for the technical field of fire prevention and control, and relates to a regional fire risk assessment method based on a fire risk prevention and control unit, which is based on a specific risk prevention and control unit, integrates static risk assessment and dynamic risk adjustment, and can realize refined assessment and visual display of regional fire risks. Compared with an existing assessment method, the method can more accurately reflect the distribution characteristics of specific risk points, makes up for the defect that the overall assessment result of a region cannot reflect details in a traditional method, and effectively solves the problem that assessment unit division is disjointed from actual fire-fighting management work. According to the assessment method based on the risk prevention and control unit, the efficiency and precision of regional fire risk assessment are remarkably improved, and fire risk prevention and control work can be carried out more scientifically and efficiently.

The invention discloses a fire behavior identification method, system and device suitable for power grid inspection and a medium, and belongs to the technical field of mountain fire monitoring, and the method comprises the steps: obtaining multi-mode video data of a to-be-monitored region, and obtaining a synchronized multi-mode video frame according to the multi-mode video data; determining a baseline model of preliminary training convergence based on the synchronized multi-modal video frame and a preset forest fire recognition model; obtaining an optimized baseline model by obtaining unlabeled video data and combining the baseline model; and performing fire behavior identification based on the optimized baseline model and the synchronized multi-mode video frame to obtain a fire behavior identification result. The method has the beneficial effects that the accuracy and reliability of fire identification are improved, continuous and stable detection under the actual background condition across day and night is realized, and accurate and timely fire early warning guarantee is provided for power grid inspection and forest fire prevention.

The invention provides a fire prevention and control method and system using computer vision, and relates to the technical field of computer vision, and the method comprises the steps: firstly obtaining a monitoring scene visual flow containing visible light and infrared thermal imaging images, and carrying out the visual flow segment correlation modeling of the monitoring scene visual flow to obtain a correlation chain cluster; a fire evolution feature set is obtained through feature linkage evolution analysis, a fire prevention and control response instruction containing prevention and control operation guidance information is generated based on the fire evolution feature set, the fire prevention and control response instruction is sent to an execution terminal, feedback is received, and comprehensive monitoring and effective prevention and control of the fire are achieved. Fire prevention and control efficiency and reliability are improved, and fire loss is reduced.

A vehicle battery fire prevention system includes: a housing configured to provide an accommodation space in which a battery module is accommodated; a chamber configured to store a fire extinguishing gas to be sprayed into the housing in the form of fire extinguishing liquid; a fire extinguishing tube connected to the chamber, and extended into the housing along a predetermined path; and a control unit configured to control the spraying of the fire extinguishing gas through the fire extinguishing tube; wherein the control unit performs control so that spraying corresponding to a plurality of predetermined conditions for spraying into the accommodation space can be performed.

The invention provides fire extinguishing spraying equipment which comprises a stator and a rotor arranged outside the stator, a water flow channel is designed in the stator, a connector capable of rotating around the stator is movably connected to the lower end of the stator, a nozzle is connected to the connector, and the connector or the nozzle is in transmission connection with the rotor. And the rotor can drive the nozzle to rotate in a rotating state. Spraying equipment is designed to be of a rotatable positioning water outlet structure, original fixed blasting type fire extinguishing spraying is innovated and upgraded, more accurate fire extinguishing is achieved, the spraying equipment is improved, the fire spreading risk is reduced, the fire prevention and extinguishing capacity of a defense area is greatly improved through application of the technology, and the device is simple in structure, good in durability and high in practicability. And the practicability and the chemical degree are high.

The invention provides an unmanned aerial vehicle nest fire monitoring, prevention and control system based on an intelligent electric pole, and relates to the technical field of mobile data communication services, and the system comprises a real-time monitoring component which carries out the real-time monitoring and collection of a target region through the intelligent electric pole; the information classified storage component is used for calling a plurality of collaborative databases and carrying out classified storage on the multi-source fire monitoring information flow; the risk dynamic evaluation component is used for performing data preliminary screening and risk dynamic evaluation based on the initial fire information; and the instruction execution component is used for linking the unmanned aerial vehicle nest to execute self-adaptive route inspection according to the graded early warning signal, and activating a fire extinguishing instruction to perform intelligent fire prevention and control. According to the intelligent electric pole linkage unmanned aerial vehicle nest, the technical problem that in the prior art, fire monitoring and prevention and control generally depend on a fixed camera and are easily interfered by natural light, so that fire recognition difficulty is increased, response is delayed, and fire prevention and control efficiency is affected can be solved; and the fire prevention and control efficiency and accuracy are improved.

The invention discloses a safety and disinfection integrated system based on AI analysis linkage control electromagnetic valves, and relates to the technical field of intelligent fire fighting, and the safety and disinfection integrated system comprises a flame detection camera, a network input and output module, a safety and disinfection integrated machine, an execution module and an acousto-optic alarm bell. According to the security and disinfection integrated system for linkage control of the electromagnetic valve based on AI analysis, the advanced AI visual recognition technology and an electromagnetic valve linkage control mechanism are deeply fused, the efficiency and the precision degree of fire safety management are greatly improved, flame characteristics are precisely recognized by means of a deep learning model, and the safety and disinfection effect is improved. The limitation that traditional fire behavior detection is easily influenced by environmental factors is broken through, the accuracy and reliability of fire behavior recognition are greatly enhanced, the system supports multi-modal data fusion, the confidence coefficient of fire behavior judgment is further improved, adjacent electromagnetic valves can be automatically started according to the position of a fire behavior in the linkage control link, an effective fire extinguishing isolation belt is constructed, and the fire extinguishing efficiency is improved. And fire spreading is effectively restrained.

A firewall system isolating a fire zone of an engine (2) from a hanger (1) located in a non-fire zone, comprising: a vertical firewall (3) arranged at a front end of a frame of the hanger, on which a support structure (13) is arranged for mounting the hanger and a fairing of the engine; and a bottom firewall (7) which is provided so as to extend rearward from the vertical firewall, is provided so as to cover the suspended frame from below, has a bottom plate (71), a left side plate (72), and a right side plate (73), and has an isolated space formed by the vertical firewall, the bottom firewall, and the suspended frame. Fireproof sealing isolation of an aircraft engine can be achieved, meanwhile, arrangement of multiple systems such as fuel oil, hydraulic pressure, an air source, fire prevention, power and EWIS is achieved, influences between the systems are avoided, and structural weight reduction can be achieved.

The invention discloses a community fire risk dynamic assessment method and system based on AI prediction, and belongs to the technical field of fire prevention and control, and the method comprises the steps: S1, collecting and preprocessing multi-source data of a community, and constructing a comprehensive risk factor database; s2, constructing a risk prediction model, taking the preprocessed multi-source data as input, identifying a key risk factor, and outputting a fire risk probability; s3, calculating the dynamic weight of each index by fusing the static expert experience and the real-time risk contribution degree; s4, based on the dynamic weight and the risk probability, calculating a comprehensive risk value and dividing risk levels; s5, constructing a prevention and control strategy library based on the risk level and the key risk factor; according to the community fire risk dynamic assessment method and system based on AI prediction, the change rule of the fire risk factors in the community can be captured in real time, potential fire hazards can be predicted in advance, and a targeted prevention and control strategy can be automatically generated.

The invention provides an unmanned aerial vehicle forest fire prevention smoke intelligent early warning method, device and equipment and a medium, and the method comprises the steps: detecting a smoke concentration value in a target inspection region at a current moment, when the smoke concentration value is greater than a preset concentration value, acquiring a multi-frame image sequence in a first preset time period and acquiring a multi-frame image sequence in a second preset time period; smog feature analysis is carried out on the multi-frame image sequence in the first preset time period and the multi-frame image sequence in the second preset time period to obtain smog multi-dimensional features; a thermal imaging data sequence in a second preset time period is collected, and flame multi-dimensional features are extracted; based on the smog multi-dimensional features and the flame multi-dimensional features, a fireproof early warning grade is judged; if the fireproof early warning level is greater than the preset early warning level, fusing the fire source navigation positioning information and the fire source dead reckoning information to obtain a fire source position coordinate; and generating a fireproof early warning prompt based on the fire source position coordinates, and sending the fireproof early warning prompt to a ground control center. Therefore, the forest fire prevention efficiency is effectively improved.

The invention relates to the technical field of fire prevention, and discloses a high-and-low-voltage power distribution room fire prevention early warning system based on potassium ion aerosol fire extinguishing, which comprises a smoke fire detection module used for detecting fire related data inside and outside a high-and-low-voltage power distribution room; the fire related data comprises smoke data and temperature data; the comprehensive evaluation module is used for judging whether an adopted evaluation model is a temperature evaluation model or a smoke evaluation model according to the fire related data; the fireproof grade classification module is used for grading fireproof grades in the high and low voltage power distribution room according to the screened evaluation model; the fire prevention measure implementation module is used for starting the potassium ion aerial fog fire extinguishing equipment in the corresponding fire prevention subareas to extinguish fire according to different grades; the electrical characteristic monitoring module is used for monitoring the load current and arc signal intensity of electrical equipment in the high-low voltage power distribution room and the temperature change rate of key nodes in real time; according to the invention, multi-dimensional accurate monitoring and graded prevention and control of the fire risk of the high and low voltage power distribution room are realized.

The embodiment of the invention provides an integral toilet module which is mainly composed of a concrete chassis, a structural framework, a built-in system and an electromechanical system which are integrally formed in a pouring mode and can be matched with a steel structure fabricated building. The chassis is prefabricated by concrete and is integrally sealed and waterproof. And the structural framework is fixed on the chassis and is provided with the light enclosure wallboards, so that the overall weight of the module is effectively reduced, the transportation and construction cost is reduced, and the assembly efficiency is improved. The enclosure wallboards can be made of light materials such as foaming ceramics and have the properties of heat preservation, heat insulation, fire prevention, water prevention and the like. According to the module, pre-integration of all structures, built-in systems and electromechanical systems is completed in a factory, the module can be used only by being hoisted in place and connected with a main body structure on site, and rapid, efficient and reliable assembly type construction is achieved.

The invention relates to the technical field of fire prevention and control, and discloses an unmanned aerial vehicle cooperative control fire extinguishing operation method and system, and the method comprises the steps: determining the target geographic position parameter of a fire source region according to the observation parameters corresponding to a tower monitoring device and / or an investigation unmanned aerial vehicle when a fire behavior is monitored in a target region; fire extinguishing operation parameters for the fire source area are determined according to the target geographic position parameters and the fire scene image data of the fire source area; the fire extinguishing unmanned aerial vehicle is controlled to fly to the fire source area so as to perform networking operation with the investigation unmanned aerial vehicle, and after networking is completed, the fire extinguishing unmanned aerial vehicle is controlled to perform fire extinguishing operation on the fire source area through the investigation unmanned aerial vehicle and according to the fire extinguishing flight control parameters and bomb dropping parameters of the fire extinguishing unmanned aerial vehicle, so that manual control in the fire extinguishing operation process is reduced, and the fire extinguishing efficiency is improved. And an effective cooperative combat system between the unmanned aerial vehicles is formed, and the overall fire extinguishing operation efficiency is improved.

The invention belongs to the technical field of coal mine fire prevention and extinguishing, and particularly provides a coal mine goaf fire simulation experiment device and method. Comprising an experiment table groove body, a working face channel, an air inlet way, an air return way, a ventilation system, a goaf groove body, a water bath heating and heat preservation system, a goaf temperature simulation system, a distributed temperature acquisition system, a goaf gas environment simulation system and a gas acquisition system. According to the invention, the inclination pitching angle, the coal rock porosity, the goaf ignition position, the internal gas components and the like of the goaf can be simulated according to the actual conditions of different working surfaces of each coal mine, and the evolutionary process of the spontaneous ignition accident of the goaf is realized. According to experimental data, development and change states of internal temperature, gas components and the like of the goaf of each coal mine can be determined, key fire prevention and control areas of the goaf in each period of coal mining are found out, early warning is performed in advance, and life and property safety of underground personnel is guaranteed.

The invention discloses a method and a system for realizing intelligent prevention and control of an electrical fire in an enclosed space, relates to the technical field of intelligent monitoring and prevention and control of fire, and aims to solve the problems of insufficient environmental protection property, hysteresis quality and intelligence in the prevention and control of the electrical fire in the enclosed space. The method comprises the following steps: acquiring multi-modal sensing data and preprocessing the multi-modal sensing data to generate a feature vector; based on the vector, early warning of the fire hazard is realized through a warning model; when early warning is triggered, the positioning model is used for accurately positioning a fire source and evaluating the risk; according to an evaluation result, determining an optimal fire extinguishing strategy through a decision model; and the fire-extinguishing execution module is driven to release fire-extinguishing agents. The system comprises a multi-mode sensing module, a data processing and early warning module, a positioning and evaluating module, a fire extinguishing decision module and a fire extinguishing execution module. According to the technical scheme, full-chain intelligent and automatic prevention and control can be achieved, the intelligent, precise and environment-friendly efficiency of fire prevention and control is improved, and the fire risk and loss are reduced.

The utility model relates to the field of building safety, in particular to a building fire alarm device which comprises a base, a shell and a protective cover, a controller is installed at the bottom of the base, a photoelectric sensor is installed on one side of the front face of the controller, and a networking module is installed on the other side of the front face of the controller; the base is provided with a photoelectric sensor and a controller, the front surface of the controller is provided with an ion type sensor, the bottom of the base is provided with an ionization chamber through the controller, the ionization chamber is covered with a shell, and the bottom of the shell is provided with a protective cover. The detection sensitivity and accuracy are improved, the false alarm rate is reduced, the built-in networking module supports multiple communication protocols, butt joint with various fire control systems and safety management systems is facilitated, remote monitoring and instant alarm are achieved, and the fire prevention and control efficiency and response speed are improved.