1106 results about "Fire spread" patented technology

The invention provides a smoke and fire detection method and system based on deep reinforcement learning and electronic equipment, and relates to the technical field of fire fighting. The method comprises the following steps: acquiring thermal imaging data of a forest area through a thermal imager, obtaining temperature distribution conditions of different positions, and determining position coordinates, the number and specific temperature values of temperature abnormal points for an area with abnormal temperature rise; if the temperature value of the temperature abnormal point exceeds a preset temperature threshold value, judging that the temperature abnormal point is a suspected fire point, and collecting a visible light video image of the area through a visible light camera according to the position of the suspected fire point; smog detection processing is carried out on the collected visible light video image, whether smog exists in the image is judged by analyzing the color, texture, motion and other characteristics of the image, and the concentration, morphological characteristics and diffusion speed of the smog are obtained; the meteorological parameters such as the wind speed and the wind direction of a fire occurrence area are obtained through the meteorological sensor, the meteorological parameters are input into the fire spreading model, and the spreading direction and the spreading range of the fire under the current wind field condition are simulated.

The invention discloses a forest defense method and system based on digital twin and intelligent sensors, and the method comprises the steps: collecting and monitoring environment data, and carrying out the integration processing through data fusion; a big data analysis technology is adopted to analyze a potential risk area where a fire occurs, a high-risk area is identified by evaluating a risk level, and a fire spreading trend is predicted; constructing a three-dimensional virtual model of the forest region by adopting a digital twinborn technology; the spreading conditions of the fire at different time and spatial positions are simulated; according to the predicted fire spreading trend, when a potential fire risk is detected, an early warning mechanism is started; automatic generation and screening of the emergency plans are realized, and the emergency plans are generated. The invention provides an emergency protection system integrating the functions of multi-source sensing data fusion, intelligent early warning analysis, dynamic emergency plan generation and the like. In addition, the problem that a traditional emergency plan is static and cannot be dynamically adjusted according to actual conditions is solved.

The invention relates to the technical field of fire monitoring and prediction, in particular to a multi-source fire data fusion and fire analysis and prediction system which comprises a data acquisition module, a data preprocessing module, a data fusion module, a fire analysis module and an early warning module. Wherein the data acquisition module is used for acquiring fire data from various sources; the data preprocessing module is used for preprocessing the fire data; the data fusion module is used for carrying out fusion processing on the multi-source data output by the data preprocessing module; the fire analysis module is used for identifying the current situation of the fire and the position of a fire source and predicting the spreading direction of the fire; and the early warning module is used for sending out an early warning signal in time. According to the invention, through the multi-source fire data fusion and intelligent analysis and prediction technology, the occurrence, spreading and risk level of the fire can be accurately monitored in real time, so that the timeliness and accuracy of fire emergency response are effectively improved.

The invention discloses a scheduling information management method and system based on fire fighting of a fire fighting truck, and relates to the technical field of intelligent fire fighting scheduling, and the method comprises the steps: receiving fire alarm information, and collecting real-time fire scene data based on a preliminary fire behavior evaluation result; combining the collected real-time fire scene data with historical fire data, and analyzing a fire spreading trend through an AI fire prediction model; according to the fire behavior spreading trend and the equipment state of the fire fighting truck, dynamically allocating fire fighting truck resources, and planning an optimal driving route; the driving state of the fire fighting truck is monitored in real time, dynamic adjustment is performed based on road conditions and equipment information, and task allocation of the fire fighting truck is updated according to the real-time fire scene situation; in the fire extinguishing process, resources are dispatched in real time for supply according to the material consumption condition of the fire fighting truck. By monitoring the material consumption condition of the fire fighting truck in real time, the supply resources are intelligently dispatched, and the continuity and high efficiency of the fire extinguishing action are ensured.

The invention belongs to the technical field of intelligent management, and particularly discloses and provides an unmanned aerial vehicle group collaborative fire extinguishing intelligent management system, which comprises a flame position analysis module, a fire scene image is acquired by screening target unmanned aerial vehicles, and a flame area is identified to determine a fire source position. The fire behavior evaluation module divides a fire scene area according to the position of a fire source, monitors the wind speed, the combustible density and the flame temperature, analyzes a fire behavior spreading degree index, and screens out a fire behavior spreading area. The launching path analysis module screens fire extinguishing unmanned aerial vehicles based on unmanned aerial vehicle functions, and analyzes flight paths in combination with fire spreading areas, maps and unmanned aerial vehicle position information of a fire scene. The fire extinguishing agent throwing module collects data such as vertical temperature distribution, analyzes the target height and throwing distance of the fire extinguishing unmanned aerial vehicle, judges whether the target height and throwing distance are qualified or not and conducts adjustment. And the coverage area qualification judgment module is used for collecting a put fire extinguishing agent image, analyzing a coverage area qualification degree index, judging whether the fire extinguishing agent is qualified or not and performing early warning.

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 present invention discloses a fire monitoring method and system based on three-dimensional laser scanning technology, which relates to the field of fire monitoring technology, including collecting a fire scene structure diagram for path planning, deploying sensors on a robot for real-time path navigation and obstacle avoidance; performing three-dimensional laser scanning and collecting data after reaching the target point, processing the collected data and performing three-dimensional modeling. The present invention combines three-dimensional laser scanning technology with a robot intelligent navigation system, utilizes high-precision three-dimensional point cloud data and sensor fusion technology, realizes comprehensive monitoring of the fire scene, and through the robot's autonomous path planning and obstacle avoidance, can dynamically collect data at the fire scene and perform three-dimensional modeling, analyze heat source distribution and smoke diffusion trajectory, and then predict the fire spread path, and generate a real-time updated three-dimensional fire scene map, which can provide efficient and accurate fire information in a complex environment, and provide an important basis for decision support and emergency rescue at the fire scene.

The invention discloses a fire safety detection system based on edge-cloud collaboration, and belongs to the technical field of fire safety, the fire safety detection system comprises an edge end and a cloud end, the edge end comprises a sensor module and a fire response module, the cloud end comprises a fire analysis module and an auxiliary traceability module, and the sensor module is connected with the auxiliary traceability module. Comprising a smoke sensor, a light scattering sensor and an infrared sensor and is used for receiving field data in real time, transmitting the field data to the edge end for judgment and transmitting a control signal into the fire-fighting response module based on a judgment result of the edge end. According to the fire safety detection system based on side cloud cooperation, on the basis of the side cloud cooperation technology, the edge end is responsible for field monitoring and emergency alarm, the cloud end is responsible for data integration, analysis, information transmission and auxiliary alarm, data support is provided for subsequent fire decision making, meanwhile, the fire spreading trend and the fire grade are analyzed and predicted in real time, and the fire safety detection efficiency is improved. And the fire treatment efficiency can be improved.

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.

A fire suppression parking barrier to prevent the spread of a vehicle fire is disclosed, including at least one barrier frame assembly and a fire suppression material slidingly engaged over the at least one barrier assembly. A cover slidingly engages over the fire suppression material. The fire suppression parking barrier is capable of preventing the propagation of a fire to other nearby vehicles in a parking area.

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 relates to the technical field of fire monitoring and alarming, in particular to an intelligent household fire automatic alarming and escape guidance system, which comprises a time-sensitive escape window evaluation module, a time-sensitive escape window evaluation module, an escape window evaluation module and an escape guidance module, wherein the time-sensitive escape window evaluation module is based on fire source temperature, smoke concentration, humidity and oxygen content collected by a fire detection sensor network in combination with a fire source position; the severity of a current fire and the influence of the current fire on an escape window are evaluated in real time, and preliminary escape time early warning is provided; the fire spreading trend prediction module is used for predicting a fire spreading path based on fire detection sensor network data and a machine learning algorithm and generating a dynamic risk map; and the self-adaptive escape path optimization module is used for generating a plurality of escape paths with different priorities, optimizing the paths in real time according to the fire change, and ensuring that the escape paths are always in a low-risk area. According to the invention, it is ensured that family members can obtain timely alarm and action guidance in an escape time window, and the escape success rate is improved.

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 an underground comprehensive pipe gallery electric power cabin plugging selection method based on a fire situation, and relates to the technical field of urban underground management. According to the method, FDS fire dynamics simulation software is utilized to construct a blocked underground utility tunnel electric power cabin full-size model and a non-blocked underground utility tunnel electric power cabin full-size model, fire spreading conditions under the two models are simulated, extinguishing time and fire spreading images are recorded, and fire evolution under different conditions is determined; based on the extinguishing time and the fire spreading image, whether plugging is carried out or not is selected, the safety and fireproof performance of the underground comprehensive pipe gallery power cabin are improved, further spreading of the fire is stopped in time, the resident safety is improved, social resources are guaranteed, follow-up reconstruction is facilitated, and resource waste is reduced.

The utility model discloses a steel heat insulation fireproof door, which belongs to the technical field of fireproof doors, and comprises a frame, a door plate is hinged in the frame, a plurality of U-shaped fixing plates are fixedly connected to the surface of the top end of the frame, and the U-shaped fixing plates are linearly and symmetrically distributed. The top end of the U-shaped fixing plate is fixedly connected with an L-shaped fixing plate, the other end of the L-shaped fixing plate is fixedly connected with the frame, and a bidirectional heat insulation water curtain mechanism is arranged between the L-shaped fixing plate and the U-shaped fixing plate. By arranging the bidirectional heat insulation water curtain mechanism, the water curtain can absorb heat through evaporation, reduce the temperature of a fire area and reduce the temperature of the steel fireproof door directly contacted with flames, so that the door body is prevented from excessively fast thermal expansion and deformation in a fire, and the water curtain not only can reduce the temperature, but also can effectively isolate a fire source, so that the service life of the steel fireproof door is prolonged. Direct contact of flames to the surface of the fireproof door is reduced, and fire spreading speed is inhibited.

The invention discloses a fire spreading prediction method based on a time-space point process, and the method comprises the steps: extracting multi-dimensional features through observation of each time point, and enabling the features to be embedded into a ConvLSTM network, and forming time-space sequence data of fire spreading; local spatio-temporal features are extracted through a ConvLSTM network, and local dependency capture is achieved; a self-attention mechanism is introduced, the dependency relationship between grids is calculated, fire behavior interaction in a remote area is carried out, and remote dependency capture is achieved; and after processing of the ConvLSTM network and the self-attention mechanism, outputting a prediction result of the fire behavior at the future moment. According to the method, the local fire dynamic state is captured through the convolutional long-short-term memory network, and the remote space-time correlation is processed through the self-attention mechanism, so that the prediction precision of fire spreading is improved; the problems that in the prior art, local and global space-time dependence capture is insufficient, the model generalization ability is poor, the calculation cost is high, and the real-time performance is poor can be effectively solved.

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 power distribution room remote monitoring and fire-fighting inspection system based on a cloud platform, and relates to the technical field of fire-fighting safety monitoring. The system comprises a remote monitoring module, a fire safety monitoring module and an inspection task scheduling module. And the remote monitoring module acquires and stores the running state data of the power distribution equipment in real time to realize continuous monitoring. The fire safety monitoring module obtains environment data of a power distribution room through an environment sensing unit, establishes a fire prediction model through a random forest algorithm in combination with an equipment operation state, and generates a fire prediction index. And the early warning unit simulates a fire spreading process based on the fire prediction index and predicts a fire spreading direction and an influence area. And the inspection task scheduling module intelligently distributes inspection tasks and adjusts task execution strategies in real time according to the fire risk assessment result in combination with the geographic position and the working load of the inspection personnel. The fire risk is accurately predicted and the inspection task is dynamically scheduled, so that the fire-fighting potential safety hazard of the power distribution room can be timely found and eliminated.

The utility model relates to the field of automobile parking space fire fighting equipment, and particularly discloses an intelligent fire extinguishing device for an automobile parking space, which comprises a fireproof cover, a support, a fire fighting nozzle, a temperature sensor, a smoke sensor and a lifting assembly, the fireproof cover is fixedly mounted right above the parking space through the support, and an opening is formed in the bottom of the fireproof cover; the fire-fighting sprayer, the temperature sensor and the smoke sensor are all installed in the fireproof cover, the lower end of the fireproof cover is sleeved with a first fixing frame, the first fixing frame is connected with the lifting assembly and moves up and down under the action of the lifting assembly, when the first fixing frame makes contact with or gets close to the support, the fireproof cover is completely folded, and when the first fixing frame makes contact with the parking space, the first fixing frame moves up and down. The fireproof cover is unfolded, and a closed space is formed between the fireproof cover and the parking space. The fire-proof cover can be used for isolating a vehicle on fire from surrounding vehicles or equipment, fire spreading is avoided, meanwhile, a water pool can be formed in the fire-proof cover to immerse a battery, and the final fire extinguishing purpose is achieved.

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 field of fire safety, relates to a data analysis technology, is used for solving the problem that a fire safety monitoring system in the prior art cannot automatically screen a fire behavior control processing decision according to a field environment, and particularly relates to an intelligent building fire safety monitoring system based on artificial intelligence, which comprises a safety monitoring platform, the safety monitoring platform is in communication connection with a safety monitoring module, a risk analysis module, a decision processing module and a database, and the risk analysis module is also in communication connection with an instant control module; the safety monitoring module is used for carrying out fire safety monitoring analysis on the intelligent building; according to the method, the spreading coefficient can be obtained through calculation in combination with the multiple risk parameters about the fire point in the risk data set, the fire spreading trend of the floor where the fire point is located is evaluated according to the spreading coefficient, then the most appropriate control means is adopted for fire control according to the evaluation result, and the fire handling efficiency is improved.

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 present invention relates to the technical field of power cable manufacturing, and discloses a low-smoke halogen-free flame-retardant polyolefin sheathed power cable. The power cable outer sheath composite material comprises the following raw materials: metallocene linear low-density polyethylene, ethylene-vinyl acetate copolymer, high-density polyethylene, flame-retardant additives, high-temperature resistant components, antioxidants, cross-linking agents, and lubricants; by improving the flame retardant and high-temperature resistant properties of the polyethylene material, the prepared power cable has excellent mechanical properties, toughness, flame retardant properties, and high-temperature resistant properties, can work continuously and stably in a high-temperature environment, reduce the occurrence of fire accidents, and effectively prevent the spread of fire even in the event of a fire, and does not generate toxic hydrogen halide gas and thick smoke during combustion.