761 results about "Fire spread" patented technology

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 discloses a forest-town junction region fire dynamic early warning method based on multi-source data assimilation, and the method comprises the following steps: inputting collected multi-source observation data into a fire risk prediction model for training, and outputting a fire risk grid map covering the whole forest-town junction region for monitoring a high-risk building group; constructing a fire spreading numerical model covering multi-material, multi-scale and multi-physical mechanism coupling; a fire propagation characteristic quantitative model is constructed, and the building heat influence is evaluated; and constructing a data assimilation and fire dynamic prediction model, and dynamically predicting and outputting fire spreading parameters and a spreading trend chart. According to the method, a forest-building-oriented complex scene is constructed, and propagation behaviors of flames under multiple mechanisms of convection, radiation and conduction are effectively described; through the modes of risk identification, dynamic simulation, data assimilation, visual early warning and the like, the precision, response speed and engineering applicability of forest-town boundary region fire prediction are remarkably improved.

The invention provides an intelligent fire-fighting fire prediction method and system, a medium and a program product, and relates to the technical field of electric digital data processing. The method comprises the following steps: firstly, acquiring real-time smoke monitoring data of a smoke alarm sensor in a target building, and once the data reaches a preset threshold value, immediately determining fire occurrence and locking a target fire source range; thirdly, calculating a fire risk value of the range by means of a fire risk assessment model trained based on multiple factors of a target building and a machine learning algorithm, and determining that a high-risk fire source point exists when the fire risk value is higher than a threshold value; then, combining meteorological data to obtain multi-dimensional environment characteristic data, and inputting the high-risk fire source point and the meteorological data into a fire spreading prediction model trained by a deep learning algorithm to obtain a fire spreading prediction condition; and finally, the situation is sent to a management end for alarming, and according to the method, rapid and accurate pre-judgment of the fire situation is achieved by means of multi-source data and an intelligent model.

The invention provides a fire-fighting escape guiding method based on a sensor, and the method comprises the steps: calculating a safe evacuation path and evacuation facilities through a graph theory algorithm according to a building structure model and the position information of escapers in combination with a fire spreading trend, a fire spreading speed and a fire spreading direction; according to the fire development situation and a preset trigger threshold value, the updating frequency of fire induction and evacuation alarms is dynamically adjusted, and it is ensured that real-time alarms transmitted to escapers have perspectiveness and accuracy; fire induction information and evacuation alarms are dynamically pushed to escapers at different positions through electronic display equipment or sound prompts, and evacuation paths and facilities which should not go to or be used at present are informed; according to the real-time position of the escaper and the fire development condition, the induction direction and the evacuation path are continuously optimized, and the accuracy and the real-time performance of user safety induction and evacuation alarm are ensured.

The embodiment of the invention relates to the technical field of fire spreading prediction, and particularly discloses a fire spreading trend AI prediction method and system based on a high-rise building. According to the embodiment of the invention, fire alarm information is received; acquiring smoke monitoring data of the target fire building, and performing smoke spreading prediction on the smoke monitoring data; selecting an auxiliary monitoring building; flame monitoring data transmitted by the auxiliary monitoring building are acquired, and flame spreading prediction is carried out; aI prediction of fire hazards and visual display of the fire spreading trend are carried out. Smoke monitoring data of a target fire building can be acquired, auxiliary monitoring analysis is performed, an auxiliary monitoring building is selected, flame monitoring data transmitted by the auxiliary monitoring building is acquired, and AI prediction of fire hazards and visual display of a fire spreading trend are performed by integrating a smoke prediction result and a flame prediction result. The defect of single data acquisition is overcome, and the accuracy of fire spreading trend prediction is effectively ensured in combination with flame monitoring of an auxiliary monitoring building.

The invention discloses an intelligent forest fire prevention method and system, and aims at solving the problems of monitoring failure, information updating lag and low prediction precision of a traditional method in a severe environment by integrating multi-source real-time data and adopting deep learning and a dynamic probability model to realize accurate identification of a fire disaster and fire spreading prediction. Through an intelligent path planning algorithm and an unmanned aerial vehicle autonomous fire extinguishing technology, real-time response to dynamic changes of a fire scene and flexible adjustment of a fire extinguishing strategy are realized, the fire extinguishing efficiency and safety are improved, a fire extinguishing effect data acquisition and feedback mechanism is established, and the defect that a traditional system lacks effect evaluation after fire extinguishing is overcome. And a reliable basis is provided for subsequent model optimization and decision improvement, so that the forest fire early warning and emergency response capabilities are integrally improved.

The invention discloses an intelligent building fire identification and simulation early warning method and system, belongs to the technical field of building informatization and disaster prevention and control, and aims to solve the technical problems of how to realize fire early identification, fire intelligent prediction and evacuation path dynamic planning, improve fire identification accuracy and response speed, and improve the safety and reliability of a building. According to the technical scheme, the method comprises the steps of BIM modeling, wherein a high-precision three-dimensional space model is established based on building information modeling, and the high-precision three-dimensional space model is deeply coupled with an FDS fire numerical simulation engine; multi-modal data acquisition: performing data acquisition by adopting a visual, environmental and spatial multi-modal sensor, and performing feature fusion on the acquired data by using a multi-channel deep convolutional network to generate unified space-time fire characterization; a video-sensing-geometric data collaborative sensing network is constructed on the basis of space-time fire characterization, so that the recognition robustness in a complex environment is improved; intelligent identification and decision making; performing early warning control linkage; and post-disaster assessment feedback.

The invention provides an unmanned aerial vehicle fire monitor fire source positioning system based on infrared thermal imaging, and the system comprises a fire scene situation collection module which obtains thermal image data and high-precision point cloud data; the fire diffusion model building module is used for generating a radiation intensity distribution diagram; the thermal image processing module is used for generating a structured fire source risk feature image; the LSTM time sequence model processing module is used for generating a smooth diffusion thermodynamic diagram to predict the spreading direction and speed; the combat map generation module is used for realizing data visualization; and the unmanned aerial vehicle flight path planning module realizes comprehensive coverage of a fire monitor striking path. Aiming at the problem that the prior art depends on static fire source data and is difficult to capture time-space dynamic evolution of a fire behavior, the method comprises the following steps: constructing a multi-dimensional fire behavior diffusion model, and fusing fire scene air flow vector projection analysis, thermal radiation background concentration dynamic superposition and LSTM time sequence modeling modes; accurate prediction of the diffusion path of the fire from the low-risk area to the high-risk area is realized, and instant support is provided for fire extinguishing action.

The invention discloses an intelligent fire-fighting AI collaborative early warning system and method fusing GIS and multi-source data, and relates to the technical field of fire-fighting safety, and the system comprises a GIS space modeling module which is used for constructing a digital twinborn model through integrating a building BIM model, fire-fighting facility distribution, a population density thermodynamic diagram, sensing equipment layout and real-time environment data; the multi-source data fusion module is used for integrating sensing equipment data, real-time environment data, meteorological information, manually reported hidden dangers and a historical fire case library, and outputting the data after standardization processing; the AI collaborative early warning engine module is used for accessing standardized data, realizing building fire dynamic risk assessment and outputting graded warning information; the 3D simulation drilling platform is used for calling the digital twinborn model, receiving graded alarm information and supporting fire spreading simulation, emergency drilling and plan optimization; and the block chain evidence storage module is used for storing alarm information and drill records. According to the invention, risk assessment and accurate prediction of the fire hazard can be realized.

The invention discloses an unmanned aerial vehicle-mounted GNSSINS visual combination fire detection method, system and device and a medium, belongs to the technical field of unmanned aerial vehicles, and aims to solve the technical problem of how to improve the positioning precision and fire recognition capability of an unmanned aerial vehicle in a complex environment. Setting a dynamic temperature threshold value, and calibrating the threshold value in real time in combination with the environment temperature; identifying a fire source diffusion trend by adopting a temperature gradient analysis method, and excluding isolated high-temperature points; an image is collected through an RGB camera and converted into an HSV color space, flame features are extracted, and the flame shape is detected in real time through a YOLOv5 model; detecting a smoke area based on a U-Net segmentation network, outputting a binary mask, carrying out space-time alignment on the binary mask and the wind speed and wind direction of the meteorological data, and predicting the fire spreading direction; thermal imaging, visible light and smoke detection results are fused through the D-S evidence theory, and when the confidence coefficients of the thermal imaging, visible light and smoke detection results are all larger than 80%, it is judged that a fire exists.

The invention discloses a virtual reality fire drill and training method and system, and the method comprises the steps: building a three-dimensional fire scene based on a BIM model and fluid dynamics, resolving the fire spreading rate and the smoke concentration in real time, and generating a dynamic disaster evolution model in combination with explosive parameters; collecting the heart rate variability and the action track of the user through the wearable device, and calculating a physiological stress index and a device operation deviation degree; smoke suppression, explosion delay and fire behavior correction instructions are triggered based on fire behavior and physiological data association; a cooperative avoidance strategy is generated in combination with the path overlap ratio and the fire-fighting role and is fed back to the fire behavior correction module; aligning the spatio-temporal data to evaluate the contribution degree and the cooperative influence weight of the fire extinguishing operation on fire behavior inhibition, and outputting a multi-dimensional evaluation matrix; generating a three-dimensional defect thermodynamic diagram by using a space-time convolutional network, marking a high-risk area and feeding back the high-risk area to a disaster model, and realizing adaptive difficulty iteration; according to the invention, through multi-source data fusion and dynamic regulation and control, the drill authenticity and the emergency disposal efficiency are improved.

The invention discloses a coal mine goaf fire monitoring method and system based on multi-source data fusion, and relates to the technical field of coal mine goaf fire monitoring, and the method comprises the steps: collecting the concentration, concentration and air pressure of each wireless sensing node in a coal mine goaf in real time; according to the concentration of each node, a dual-parameter dynamic coupling gradient field traceability algorithm of fusion / gas expansion and chemical reaction mechanism is adopted to calculate a fire source coordinate; performing anomaly detection according to the concentration of each node, and positioning an air leakage point by adopting a three-dimensional oxygen concentration gradient field positioning algorithm and combining air pressure compensation for an oxygen concentration anomaly point; based on goaf point cloud data, a goaf three-dimensional grid model is constructed, and a fire source spreading path, an air leakage channel and gas concentration distribution are dynamically and visually displayed in combination with multi-source monitoring data and fire source and air leakage point positioning results. The goaf fire prevention and control system can achieve all-around prevention and control of goaf fire.

The invention discloses a garden fire early warning system based on GIS Internet, relates to the technical field of environmental protection, and comprises a terrain analysis unit, a node division unit, a fire judgment unit, an early warning classification unit and an early warning notification unit; the invention obtains garden distribution data from GIS Internet, calculates the fire spread coefficient according to terrain height data and vegetation distribution density data, and then delineates different monitoring areas according to the degree of fire spread, obtains real-time sensor data through a sensor group arranged at a monitoring node, generates a fire occurrence signal according to the real-time sensor data, calculates the fire spread rate in combination with the fire spread coefficient of the fire occurrence coordinates and real-time weather data, and arranges the monitoring nodes according to the distribution characteristics of the garden, thereby ensuring the effectiveness of monitoring while reducing the cost, accurately judging the fire spread rate when a fire occurs so as to take corresponding rescue measures, ensuring safety and being able to effectively regulate firefighting resources.

The invention belongs to the technical field of forest disaster monitoring and early warning, and particularly discloses and provides a forest fire spreading prediction method based on multi-dimensional features, which comprises the following steps: dividing a target area into grid units, collecting an infrared thermal imaging data sequence through an unmanned aerial vehicle, dynamically evaluating fire intensity indexes of the grid units, and predicting the fire intensity indexes of the grid units. Identifying each fire spreading path, evaluating the spatial proximity of each grid unit relative to the path, marking a fire occurrence area, and determining the path intersection density in each grid unit; fusing the fire intensity index, the path space proximity and the path intersection density, calculating to obtain a comprehensive fire spreading risk index of each grid unit, and generating a forest fire spreading danger level zoning map based on the index; according to the method, the fire spreading risk of each grid unit is comprehensively evaluated by fusing the fire intensity index, the path space proximity and the path intersection density, and refined and three-dimensional evaluation of the risk of the unburned area is realized.

The invention relates to a bio-based degradable UV-curable coating material for a microcapsule fire extinguishing agent, the microcapsule fire extinguishing agent and a preparation method and application of the bio-based degradable UV-curable coating material for the microcapsule fire extinguishing agent. The bio-based degradable UV-curable coating material for the microcapsule fire extinguishing agent is prepared from the following components in parts by weight: 100 parts of bio-based hyperbranched polyurethane / acrylate prepolymer; 10-150 parts of a reactive flame-retardant monomer, 0.1-5 parts of a photoinitiator and 0-70 parts of a solvent. The coating material for the microcapsule fire extinguishing agent is a thermal response type material, when the coating material is prepared into a shell layer of the microcapsule fire extinguishing agent and the environment temperature reaches a preset threshold value, the shell layer is rapidly broken due to thermal expansion coefficient difference and chemical bond fracture, internal fire extinguishing liquid is released, the process can be completed within 3 seconds or less, rapid response in the initial stage of a fire disaster is ensured, and fire extinguishing efficiency is improved. The thermal response speed is high, the microcapsule fire extinguishing agent can be rapidly broken in the early stage of a fire, rapid release of fire extinguishing liquid is achieved in the early stage of the fire, efficient fire extinguishing is achieved, a fire source is controlled in time, and fire spreading is effectively prevented.

The invention discloses a subway tunnel fire behavior spreading prediction method, which comprises the steps of 1, fire source type digital modeling, 2, fire scene initialization, 3, dynamic fire source loading and ignition triggering, 4, fire behavior spreading multi-physics field coupling calculation, 5, ventilation system dynamic response, 6, visual risk thermodynamic diagram generation, and 7, fire behavior spreading prediction. Step 7, carrying out real-time early warning on the safety margin; the method has the beneficial effects that a total factor modeling capability is realized, multi-dimensional parameter input from fire source characteristics to a tunnel environment is supported, a scene range covering a typical subway fire disaster is expanded, solving is realized through a multi-physics field simultaneous equation, a fire spreading error is reduced, smoke diffusion simulation precision is improved, and a dynamic ventilation adjustment and safety early warning mechanism is realized. And more buffer time is provided for emergency response.

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 belongs to the technical field of artificial intelligence, and discloses a fire spreading path dynamic prediction method and system based on artificial intelligence. The method comprises the following steps: acquiring image data, sensor data, meteorological data, fire spreading rate and burnt area of a fire scene; performing feature extraction on the image data to obtain image features; performing feature extraction on the sensor data to obtain environment features; performing feature extraction on the meteorological data to obtain meteorological features; calculating correlation weights among the different modal features, and performing weighted fusion on the different modal features based on the correlation weights to obtain aligned feature vectors; dynamically adjusting a model prediction time step length based on a reinforcement learning mechanism to obtain a dynamic time step length; performing fire hazard path dynamic prediction based on a path prediction model according to the dynamic time step length; according to the method, the change of the fire spreading path can be carefully captured, so that the prediction accuracy is improved.

The invention discloses a scene preprocessing method for fire simulation, and relates to the technical field of building fire simulation, and the method comprises the steps: calculating a three-dimensional thermal weight through employing a fire propagation dynamics model, and generating a fire dangerous region thermal diagram; through a tensor field generation algorithm, fire behavior main diffusion direction and each axial anisotropic parameter are extracted, and fire behavior grid parameters are generated; through a hybrid grid generator, performing hexahedron dominant grid construction and increasing the grid density of a fire behavior dangerous area to obtain a fire behavior optimization hybrid grid; performing Reynolds number verification and boundary layer matching on the fire behavior optimization hybrid grid through a fire behavior feature adaptive algorithm, and performing iterative correction to generate a fire simulation correction grid; according to the invention, through the hybrid grid generator, the self-adaptive distribution of the grid density of the fire hazard area and the smooth connection of the transition area are realized, so that the grid distribution of the fire hazard area is accurately matched with the fire spreading characteristics.

The invention discloses a fire spreading prediction method, a server and a storage medium, and the method comprises the following steps: 1, collecting fire related data from a sensor layer and a block chain layer, and carrying out the preprocessing of the fire related data; and 2, inputting the preprocessed fire related data into a fire spreading prediction model for prediction to obtain a fire spreading trend. According to the method, the change of the fire along with the time is accurately grasped through the LSTM, the GCN accurately predicts the spreading path of the fire in the space, the spatial-temporal characteristics can be integrated through the fusion of the LSTM and the GCN, and the fire spreading probability of each room is given. The method is suitable for fire-fighting early warning of various buildings such as shopping malls, office buildings and residences, effectively assists fire-fighting decision making, plans rescue paths and resource allocation in advance, and reduces fire hazard and loss.

The invention discloses a fire simulation method, device, equipment and medium for a new energy vehicle roll-on and roll-off place, and the method comprises the steps: building an accurate fire risk simulation evaluation model, setting a roll-on and roll-off place vehicle mixed transportation and partition transportation fire scene model, and carrying out the simulation of a new energy vehicle on the basis of temperature distribution, thermal radiation intensity and other key data. According to the method, the fire spreading condition of the electric vehicle under different transportation strategies is simulated, then the effectiveness of the transportation strategies is evaluated, the roll-on-roll-off ship transportation strategies are formulated according to the vehicle power mode, a scientific basis is provided for formulating reasonable roll-on-roll-off site transportation strategies and emergency response measures, and therefore the safety of the new energy vehicle roll-on-roll-off site is improved.

The invention discloses a fire identification method and system based on a smoke analysis algorithm, belongs to the technical field of forest fire identification, and is used for solving the problems that the existing forest fire identification algorithm is easily interfered by multiple aspects in a forest complex environment, so that the misjudgment rate is increased, and the forest fire identification efficiency is increased. And a potential fire point and a fire spreading trend cannot be quickly locked when a fire occurs. Comprising the steps of collecting multi-dimensional monitoring data of a monitoring forest region; performing cell division on the monitoring forest region based on the multi-dimensional monitoring data, and generating a dynamic smoke threshold value of each cell; constructing a cell dynamic association library according to the multi-dimensional monitoring data of each cell; performing smoke identification on the multi-dimensional monitoring data, and determining a target cell where a fire occurs based on a dynamic smoke threshold value; performing spreading dynamic simulation on the multi-dimensional monitoring data of the target cell to obtain spreading simulation data; and obtaining an associated cell of the target cell in the cell dynamic association library, determining the associated cell as a potential fire area, and generating a thermodynamic diagram of the potential fire area.

The invention provides an intelligent building fire safety early warning system based on intelligent fire protection, and relates to the field of fire safety, and the system comprises a distributed data collection module which is used for achieving data real-time collection and network disconnection local processing through heterogeneous sensor networking and dual-mode communication; the edge processing module is used for carrying out edge processing on the output standardized environment data flow by adopting a fire behavior triple verification model and a dynamic weight algorithm, and carrying out cross-node model sharing in combination with a federated learning framework so as to obtain a fire risk score and a fire source positioning coordinate; the decision execution module is used for dynamically planning an evacuation path; the feedback module is used for performing real-time rendering fluid dynamics fire spreading simulation on the evacuation path and generating multi-terminal early warning; and the dynamic evacuation optimization module simulates and optimizes the exit position and the path planning through fluid dynamics to obtain the optimized path planning. The method and the device are used for overcoming the defects of cloud processing delay and failure during network disconnection in the prior art.

The invention provides a chemical industrial park fire spreading prediction method and system. The method comprises the following steps: dividing a grid chart structure of a target chemical industrial park space structure into a plurality of function partition sub-graphs; determining a fire propagation flux of a shared node in an overlapping region between every two adjacent function zone sub-graphs, converting each function zone sub-graph into a macro-scale sub-graph, and determining a fire propagation macro-situation of the target chemical industrial park; according to the fire propagation flux and the fire propagation macroscopic situation, determining a fire front edge envelope line of each area, thereby constructing a fire propagation prediction model of the target chemical industry park, inputting fire initial environment data into the fire propagation prediction model, and outputting a fire propagation prediction result. And automatically triggering a fire alarm signal of the target park according to a fire spreading prediction result. By adopting the scheme of the application, the fire spreading of the target chemical industrial park can be predicted by combining the dynamic fire interaction among the areas in the target chemical industrial park.

The invention relates to the technical field of data management, in particular to a digital twinning-based smart park visual management method, which comprises the following steps of S1, acquiring real-time data through a multi-source sensor, formulating a uniform data format specification and an interface protocol, performing data access conversion, and outputting uniform data; s2, an integrated three-dimensional digital twinborn model is established according to the unified data, and a simulation engine and an event linkage rule engine are introduced for real-time deduction. During use, by establishing the park integrated three-dimensional digital twinborn model, when an emergency situation such as a fire alarm occurs, real-time deduction can be carried out; the method comprises the following steps: automatically deducing simulation animations of entrance guard opening and personnel evacuation in a digital twin interface, synchronously turning off ventilation systems of related floors at the same time to form a linkage reaction, further predicting the fire spreading direction and time through a simulation engine, and intuitively presenting a future change trend through a visual means, so as to improve the fire spreading effect. And the cognition and response speed of a manager to potential risks and resource demand changes can be improved.

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.

Disclosed is a digital twin platform provision system for detecting and responding to a fire in an installation region of electrical equipment in a nuclear power plant, which includes: a digital twin build unit for building an initial digital twin by digitally modeling target objects including equipment and subsidiary materials related to fire outbreak and damage spread; an attribute information application unit for applying fire reactivity information received from an outside and serves as attribute information about fire outbreak and spread factors to the initial digital twin, thereby building a digital twin; and a simulation information provision for unit generating simulation information, which is information fire outbreak about prediction, fire spread simulation upon fire break, and fire response and evacuation scenarios upon the fire break, by using the digital twin according to a user input and outputting the simulation information to a user terminal.

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.

The invention relates to the technical field of radar fire source positioning, in particular to a light quantum radar fire source identifying and positioning method and system for a fire extinguishing robot. Acquiring radar point cloud data, temperature time sequence data and smoke concentration time sequence data of a fire scene; comparing the radar point cloud data with preset radar point cloud data, identifying smoke data points, analyzing motion characteristics of the smoke data points to determine a smoke diffusion path, and analyzing changes of temperature and smoke concentration time sequence data to determine a fire spreading path; comparing the two and combining temperature and smoke concentration change characteristics, identifying a real fire behavior evolution trend, and screening suspected fire source positions; and at each suspected fire source position, the initial power and the resolution of the light quantum radar are adaptively and intelligently adjusted according to indexes such as the area to be measured, the environmental complexity and the smoke concentration, fire source identification and positioning are carried out with the optimal performance, and the accuracy and the stability are improved. The range is dynamically reduced, radar parameters are adaptively adjusted, and accurate positioning of a fire source is facilitated.

The invention relates to an emergency evacuation path generation method, system and device under multi-target conflict and a medium. The method comprises the following steps: acquiring video monitoring data and environment sensing data of a target building, and performing fire disaster detection according to the video monitoring data to obtain a fire detection result; in response to the fire detection result that the fire disaster exists, performing fire evolution prediction according to the environment sensing data based on the environment topological graph of the target building to obtain fire evolution parameters; performing risk assessment and latest passable time marking on each space unit node in the environment topological graph according to the fire evolution parameters to obtain a risk graph layer; and in response to the obtained positions of the to-be-evacuated persons, generating an exclusive emergency evacuation path of each to-be-evacuated person in combination with the environment topological graph and the risk map layer. According to the method, fire detection and fire spreading deduction are carried out through continuous video image frames, time sequence judgment is carried out on traffic effectiveness, and path design is prevented from lagging behind risk change.