346 results about "Fire behavior" patented technology

The invention discloses a forest fire detection and disappearance method and system, and relates to the technical field of forest fire prevention and data processing, and the method comprises the steps: carrying out the fire inspection of a planned forest region through a plurality of inspection unmanned planes, and transmitting an image and airborne sensor data back to a command center in real time; identifying a fire behavior by using an artificial intelligence method, and performing fire behavior judgment and fire hazard grade division; the command center screens fire points according to the thermal images and updates the positions of the fire points in real time; the fire scene spreading trend is judged according to the returned data, and a basis is provided for the dispatching task of throwing the fire extinguishing bombs by the fire extinguishing unmanned aerial vehicle; using an MAPPO multi-agent reinforcement learning algorithm to train an optimal dynamic fire point collaborative disappearance regulation strategy; and after the open fire is extinguished, the inspection unmanned aerial vehicle continues to inspect to identify a re-ignition point or a smoke point, and secondary large-area fire is prevented. According to the method, efficient collaborative fire extinguishing, dynamic environment adaptation and resource optimization configuration can be achieved, and robustness is kept when part of intelligent agents fail.

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 provides a tunnel fire behavior inversion method based on multi-modal fusion and physical constraint, and aims to solve the problem that the position and power of a fire source are difficult to invert accurately in real time in traditional fire behavior monitoring. According to the method, data, temperature distribution images and physical parameters of distributed temperature sensors in a tunnel are collected, and a spatial-temporal feature fusion network is constructed; designing an information leakage prevention training mechanism, and adopting a modal random discarding and sensor shielding technology to avoid overfitting of the model to a specific input mode; a physical constraint loss function is introduced, and the temperature gradient, the maximum temperature rise and the longitudinal attenuation law are combined to ensure the physical rationality of an inversion result; a coarse-fine two-stage position prediction framework is adopted, and meter-scale precision positioning of the position of a fire source is achieved. According to the invention, the power and position of the fire source can be inversed accurately in real time, and reliable technical support is provided for intelligent monitoring and emergency rescue of tunnel fire.

The invention relates to the technical field of fire safety, and discloses a partition controller linkage method, device and equipment and a storage medium. The method comprises the following steps: acquiring original fire sensing data acquired by a plurality of fire-fighting sensors in each independent partition, and performing preprocessing of a plurality of sensing types; extracting space-time dimension features from the preprocessed data, generating fire behavior space-time feature vectors, and performing multi-source evidence weight fusion; performing fire abnormal mode identification and evaluation on the fused fire spatio-temporal feature vector to obtain a partition preliminary fire evaluation result, transmitting the partition preliminary fire evaluation result to a main controller, and performing global fire situation fusion based on a building physical structure and a partition connection relationship to obtain an overall fire situation evaluation result; and generating a multi-partition cooperative fire extinguishing execution scheme based on the overall fire situation assessment result, and controlling fire fighting equipment in each partition to perform linkage fire fighting. According to the invention, multi-source data fusion and cross-partition collaborative linkage of building fire are realized, and the fire detection accuracy and the fire-fighting response efficiency are improved.

The invention discloses a fire alarm linkage system for fire engineering based on the Internet of Things. The operation process of the system specifically comprises the following steps: generating a dynamic risk probability distribution diagram based on a building three-dimensional point cloud model and multi-source data, and deploying a differential sensor array; environment multi-physical field parameters are collected in real time through a differential sensor array, and a multi-mode fire behavior sensing signal set is generated; building a fire situation credibility map: calling a multi-criterion decision module to calculate a linkage equipment weight distribution matrix based on the fire situation credibility map, and generating a multi-stage linkage control instruction set in combination with the building topological structure model and the personnel distribution thermodynamic diagram; and performing multi-cross-system cooperative execution and closed-loop optimization. The method has the following advantages and effects that the inherent limitation of a traditional system can be broken through by constructing an intelligent prevention and control framework combining risk quantification, situation deduction and decision closed loop, the personnel evacuation efficiency is effectively improved, and damage caused by major accidents such as detonation is reduced.

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 concrete filled steel tube structure fire early warning method and device based on multi-agent cooperative detection, and belongs to the technical field of concrete filled steel tube structure fire early warning. The invention discloses a concrete filled steel tube structure fire early warning method and device based on multi-agent cooperative detection. The method comprises the following steps that S1, a fire early warning threshold value is set; s2, collecting real-time physical state data of the concrete-filled steel tube structure; s3, performing cross validation on the fire signal; s4, comparing the composite fire behavior index with a set fire early warning threshold value; and S5, sending out corresponding fire early warning information. According to the invention, the problem that a fire detection system for detecting a single parameter in the prior art cannot accurately distinguish a real fire source from environmental interference so as to cause false alarm is solved, compared with single-point monitoring, early fire characteristics such as local temperature abnormity and a smoke diffusion path can be accurately captured, the false alarm rate is obviously reduced, and the system is suitable for popularization and application. And the accuracy of fire early warning is ensured.

The invention provides an unmanned aerial vehicle inspection method, system and device and a storage medium, and relates to the technical field of unmanned aerial vehicle inspection, and the method comprises the steps: dividing a to-be-inspected fire region into a plurality of sub-regions, and determining the number of unmanned aerial vehicles required by each sub-region and a first inspection route according to the region area and the region feature of each sub-region; according to the fire behavior data of each sub-region, predicting a fire behavior spreading range of each sub-region in a preset duration, and determining a newly added to-be-inspected sub-region of each sub-region; determining a second inspection route of each unmanned aerial vehicle by combining the target region area and the target region feature of the newly added sub-region to be inspected and the residual electric quantity and the target position of each unmanned aerial vehicle; and sending the first inspection route and the second inspection route to each unmanned aerial vehicle, so that each unmanned aerial vehicle performs inspection according to the first inspection route and the second inspection route. The technical effect of the invention is that the monitoring requirement of dynamic spreading of forest fire can be effectively met.

The invention relates to the technical field of urban fire safety rescue, in particular to a low-altitude fire fighting system and method based on urban CIM and Beidou positioning. According to the system and the method, full space-time accurate positioning is realized through the Beidou differential base station and the UWB indoor positioning equipment; integrating the urban information model system and unmanned aerial vehicle cluster data, and constructing a multi-source heterogeneous data set; a coordinate system is unified based on a space-time reference calibration module, and fire behavior prediction, path planning and resource scheduling are realized through AI computing nodes; the unmanned aerial vehicle task distribution module is used for realizing multi-vehicle cooperative rescue; and iteratively optimizing system parameters through a closed-loop adaptive optimization module. The method is suitable for fire emergency rescue in an urban complex building environment, and the rescue response speed, the decision-making precision and the cooperative combat capability are remarkably improved.

The utility model discloses a control cabinet with an isolation structure, and relates to the technical field of control cabinets, the control cabinet comprises a control cabinet body, the front surface of the control cabinet body is rotatably connected with a cabinet door, and the top end of the inner wall of the control cabinet body is provided with an isolation assembly. A pair of fire extinguishing tanks extending into the control cabinet body is mounted on the rear surface of the control cabinet body; the isolation assembly comprises a storage frame fixed to the inner wall of the top end of the control cabinet body. The control cabinet on fire is blocked through the isolation assembly, fire is prevented from spreading towards the two sides to burn other control cabinets or articles, the operation space on the front side of the control cabinet is guaranteed, internal components can be disassembled and assembled manually in the follow-up process, meanwhile, people do not need to get close to operate the blocking assembly to open the control cabinet, and operation is convenient. And after blocking, the fire extinguishing tank is controlled to spray dry powder into the cabinet body, so that expansion of the fire behavior is inhibited, and sufficient time is provided for subsequent fire extinguishing of firefighters.

The invention relates to the technical field of image recognition, in particular to a fire behavior recognition method and system based on video monitoring. The technical problem that the early warning reliability of a video monitoring system on fire smoke is insufficient is solved. The method comprises the following steps: acquiring a monitoring video stream of a monitoring area and time sequence data acquired by a sensor in the monitoring area; determining an evaluation value of the to-be-detected area based on the image feature and the morphological change of the to-be-detected area; determining a confidence factor based on the form change trend of the to-be-detected region and the change trend of the time series data; determining a smoke authenticity value based on the evaluation value and the confidence factor; and adjusting an alarm threshold value of the smoke alarm based on the smoke authenticity value. The method is used for fire smoke early warning and monitoring scenes.

The invention provides an intelligent fire extinguishing strategy control method for an autonomous flight fire extinguisher, and belongs to the technical field of intelligent navigation fire extinguishment. The method comprises the following steps: firstly, acquiring fire scene data through a multi-source sensor, and constructing a fire behavior positive and negative development matrix; then, route planning is carried out based on a pre-trained deep learning model, the model adopts a special convolution kernel structure to extract fire scene features, and a decision is optimized through a mathematical calculation module; and the system updates a fire matrix in real time, dynamically adjusts a fire extinguishing strategy, and finally completes a precise fire extinguishing task through a time sequence aligned control instruction. According to the method, efficient control over the autonomous flight fire extinguisher in the complex environment is achieved through data driving and intelligent decision making, and the technical problem that in the prior art, an autonomous flight fire extinguisher is difficult to achieve precise fire extinguishing path planning and fire extinguishing strategy control in the complex fire environment is solved.

When the intelligent fire-fighting unmanned aerial vehicle cluster system works, the method comprises the following steps that 1, an intelligent fire-fighting unmanned aerial vehicle cluster detects a fire scene and searches a water source near the fire scene, and an optimal route is searched between the water source and the fire scene to lay a pressurizing water pump and a fire hose; 2, the intelligent fire-fighting unmanned aerial vehicle cluster controls a fire-fighting nozzle to conduct fire extinguishing operation, and the positions of a pressurizing water pump and a fire hose are adjusted according to fire behavior changes of a fire scene; and 3, the intelligent fire-fighting unmanned aerial vehicle cluster performs handover control on a fire-fighting nozzle, a pressurizing water pump and a fire-fighting hose in turn, and fuel oil is supplemented to the pressurizing water pump until fire extinguishing operation is finished. A fire-fighting water supply channel can be laid between a water source and a fire scene at an ultra-fast speed, the fire extinguishing operation speed is high, manual intervention is not needed, and nearly infinite fire-fighting water can be continuously provided.

An indoor fire source positioning method based on an infrared thermogram of the outer surface of a glass curtain wall comprises the following steps: database construction, which mainly comprises construction of a fire data set, temperature distribution of the outer surface of the glass curtain wall, and image extraction and processing; a Resnet deep learning model is constructed and trained; and carrying out fire source positioning by using a Resnet deep learning model. In the early stage of fire disaster development, when fire behavior reconnaissance of a super high-rise building fire disaster is carried out, a reconnaissance unmanned aerial vehicle carrying an infrared thermal imager is controlled to fly out of a glass curtain wall of a fire floor, and the position of the reconnaissance unmanned aerial vehicle is adjusted to obtain a complete glass curtain wall outer surface infrared thermal image of the fire floor; an infrared thermal image of the outer surface of the glass curtain wall acquired by the thermal infrared imager is input into the trained Resnet-50 deep learning model, the model analyzes the infrared thermal image to give a position number of a fire source, the position of the fire source can be accurately recognized in the early stage of fire development, the real-time performance and reliability are high, and the fire early warning capacity and rescue efficiency of the super high-rise building are improved.

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 is suitable for the technical field of mountain fire disaster monitoring and early warning, and provides a power distribution network mountain fire disaster state monitoring and early warning system, which comprises a multi-source data processing module, a space-time coupling monitoring module, an intelligent response module and a remote management platform, the multi-source data processing module is used for integrating and processing satellite remote sensing data, meteorological data, topographic data and power distribution network topology data; the space-time coupling monitoring module is connected with the multi-source data processing module and is used for dynamically analyzing the space-time characteristics of the fire behavior; the intelligent response module is connected with the space-time coupling monitoring module and is used for executing hierarchical prevention and control operation according to a fire behavior space-time characteristic analysis result; the remote management platform is connected with the space-time coupling monitoring module and the intelligent response module and used for outputting a forest fire disaster early warning scheme according to the fire behavior space-time characteristic analysis result and the graded prevention and control operation process, the emergency evacuation efficiency can be improved, and power grid facility damage and economic loss caused by fire behavior diffusion are reduced.

The utility model relates to the technical field of fire fighting equipment, in particular to a fire extinguishing device for an unmanned mine car, which comprises a fire extinguisher with a self-starting function, a temperature detection device, a pipeline and a plurality of sprayers, the spray head is connected with the fire extinguisher with the self-starting function through the pipeline; the plurality of nozzles are respectively aligned with a wiring harness, an oil pipe and an engine exhaust pipe area of the unmanned mine car; the temperature detection device is mounted in the areas of a wiring harness, an oil pipe and an engine exhaust pipe of the unmanned mine car and is electrically connected with the fire extinguisher with the self-starting function; when the temperature detection device detects that the temperature exceeds a preset value, a signal is fed back to the fire extinguisher with the self-starting function, the fire extinguisher with the self-starting function starts the fire extinguishing function and sprays a fire extinguishing agent outwards through the spray head, and the sprayed fire extinguishing agent immediately extinguishes the ignition part in the spray head installation area. Therefore, the purposes of extinguishing flames and controlling fire behaviors are achieved.

The invention discloses an automatic patrol intelligent fire extinguishing method and control system based on data analysis, and relates to the technical field of intelligent fire extinguishing control, and the method comprises the steps: obtaining multi-dimensional data through a multi-dimensional data integration platform, and carrying out the preprocessing; calculating a multi-dimensional risk assessment index based on the preprocessed data, performing nonlinear standardization, constructing a multi-dimensional risk assessment feature vector, and performing clustering analysis on all the to-be-patrolled areas based on the multi-dimensional risk assessment feature vector according to a distance metric function; according to the clustering analysis result, comprehensive risk score calculation is carried out on all the to-be-patrolled areas, a priority to-be-patrolled list is generated, automatic patrolling is carried out on the to-be-patrolled areas, and when a fire behavior is detected, fire extinguishing equipment in the areas is started to extinguish fire. Key elements of fire occurrence and spreading are comprehensively described through multi-dimensional risk assessment, and risk scoring and grading are performed on all to-be-patrolled areas after clustering analysis, so that dynamic priority patrolling of high-risk areas is realized, and the patrolling efficiency is effectively improved.

The invention relates to the technical field of comprehensive pipe galleries, and provides a comprehensive pipe gallery cable fire intelligent identification and prevention and control linkage system. In the system, fire simulation is carried out on a comprehensive pipe gallery cable through a cable fire simulation device; the fire behavior of the cable in the pipe gallery is monitored in real time through the image acquisition unit, and the acquired simulated fire image information is transmitted to the deployed fire identification model in real time for fire identification, so that the fire identification result of the fire identification model is judged through the deployed fire early warning model. A fire extinguishing instruction or an early warning instruction is sent out according to the judgment result; further, the fire extinguishing linkage device responds after receiving the fire extinguishing instruction, and a self-made fire resisting shutter with a flexible steel brush is firstly started to block a fire point area; and then a telescopic end of an electric push rod mounted at the top of the pipe rack quickly extends out to crush a temperature sensing glass ball of the suspension type fire extinguisher, so that quick linkage prevention and control of the pipe rack cable fire are realized.

The invention discloses a superfine dry powder automatic fire extinguishing method and system, and the method comprises the following steps: collecting multi-source parameters of a monitoring area according to a preset time interval; based on the multi-source parameters, whether an ignition point exists in the monitoring area or not is judged, and if yes, the first environment temperature rising rate, the smoke concentration change gradient and the first flame energy ratio are calculated; according to the temperature rising rate, the smoke concentration change gradient and the flame energy ratio, the fire behavior grade of the ignition point is judged; based on the fire behavior grade, a superfine dry powder spraying device is controlled to conduct graded spraying fire extinguishing; after graded jet fire extinguishing is conducted, the second temperature rising rate and the second flame energy ratio of the ignition point are calculated according to the preset time interval; and whether the ignition point has a reburning risk or not is judged based on the second temperature rising rate and the second flame energy ratio, and if yes, the superfine dry powder jetting device is controlled to conduct supplementary jetting.

The invention relates to the technical field of fireproof safety, in particular to a cable type linear independent temperature sensing terminal which comprises a cable type temperature sensing cable module, a data processing module, a self-adaptive fire behavior detection module, a fire behavior analysis and judgment module, a fire extinguishing device control module and a power failure guarantee module. Wherein the cable type temperature sensing cable module is used for detecting temperature data of different positions; the data processing module is used for formatting the temperature data; the self-adaptive fire detection module is used for dynamically adjusting a fire detection threshold value according to environmental conditions; the fire analysis and judgment module is used for judging whether a fire exists or not; the fire extinguishing device control module is used for starting a fire extinguishing device to execute fire extinguishing operation; and the power-off guarantee module is used for providing a standby power supply. According to the invention, through self-adaptive fire behavior detection, accurate fire behavior analysis and judgment, and starting and power-off guarantee of the automatic fire extinguishing device, the accuracy and response speed of fire monitoring of the electrical cabinet are improved, and the loss caused by the fire is effectively reduced.

The invention relates to the technical field of image processing, in particular to a fire early warning method based on video analysis, and the method comprises the steps: obtaining images containing open fire and smog and wind speed data in various scenes, constructing a data set, training a fire recognition network, and marking the open fire and smog in the current frame image; calculating the flame intensity by using the size of a flame target frame extracted by the fire identification network and the gray value of pixel points in the target frame; combining the smoke target frame, the flame intensity and the wind speed data to determine the smoke diffusion degree of the scene corresponding to the current frame image; the fire possibility is evaluated by analyzing the variation trend of the flame intensity degree and the smoke diffusion degree, and whether a fire alarm is given or not is judged. The fire behavior is comprehensively judged through the size and position change of the flame target frame and the area and diffusion degree of the smoke target frame in combination with the wind speed data, false alarms are reduced, and the detection accuracy is improved.

The invention relates to the technical field of computer vision, and discloses a flame recognition and fire extinguishing system for indoor fire fighting, comprising: a binocular infrared imaging module for acquiring a thermal imaging image; the monocular visible light imaging module is used for acquiring a visible light image; the infrared stereoscopic vision module is used for carrying out processing and feature extraction on the thermal imaging images, carrying out feature aggregation to obtain an aggregated feature map, carrying out parallax optimization on the aggregated feature map, and carrying out calculation according to a parallax optimization result to obtain depth information of the thermal imaging images at different visual angles; the multi-mode stereoscopic vision fusion module is used for fusing the thermal imaging image with the depth information and the visible light image; the flame identification and fire behavior prediction module is used for performing flame detection according to the fused image, predicting a bounding box, confidence and a category label of the flame in the fused image, and predicting a future diffusion position of the flame, a diffusion scale of the flame and a diffusion trend of the flame; and the self-adaptive water gun spraying control module controls the water gun to execute spraying operation.

The invention discloses a dynamic fire extinguishing strategy generation method and system based on fire behavior development stage grading, belongs to the technical field of artificial intelligence, and aims to solve the problems of rapid fire behavior spreading and toxic and harmful flue gas retention in a fire disaster in a closed space of a multi-layer underground parking lot. The target tracking device firstly uses image identification to position a fire point, then uses the fire source detection device to collect a fire type and a fire behavior degree, and generates triple data; the data are input into a fire behavior stage grading model, and the fire behavior is divided into an incubation period, an accelerated spread period and a deflagration period according to a combustion entropy threshold value. According to the current stage, the corresponding fire extinguishing strategy is loaded from the blocking priority rule base, and in the detonation period, the aerogel flame retardant is only allowed to be put into the top ventilation opening in the fire diffusion direction. And then the fire scene control instruction drives the fire behavior blocking robot to release the flame retardant on time at a fixed point, and environment parameters after release are collected and fed back to the model. And if the combustion entropy value crosses the stage threshold value, the model triggers the blocking strategy to be dynamically switched.

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 relates to the technical field of fire-fighting management, and discloses an intelligent fire-fighting management method and system based on a multi-modal large model, and the method comprises the steps: 1, collecting multi-modal perception data in a field environment, and transmitting the multi-modal perception data as input data to a multi-modal semantic recognition module; and 2, performing modal analysis and semantic fusion on the input data by using the multi-modal semantic recognition module, and generating a unified semantic description containing fire state elements. According to the invention, a multi-modal perception data semantic fusion mechanism and a multi-modal large model-driven fire behavior recognition framework are adopted, and data of different modals from a camera, a temperature and humidity sensor, a smoke detector and combustible gas monitoring equipment are input into a unified semantic recognition module, so that unified fire behavior state semantic description is constructed; and the technical effects of multi-source data complementation and semantic-level collaborative recognition of the fire state are achieved.

The invention discloses a building fire safety management and control method based on a digital twinborn technology, and the method comprises the steps: constructing sensor-middle platform-model bidirectional mapping, and reconstructing a dynamic scene through employing a neural radiation field technology; fusing the cross-domain desensitization data based on federal transfer learning, and constructing a building total-factor dynamic digital mirror image; through a spectrum analysis algorithm, a fire source is positioned in real time, and a flame spreading track is predicted; performing fire simulation in linkage with a total-factor dynamic digital mirror image, and optimizing a fire-fighting resource scheduling path through a multi-target particle swarm optimization algorithm; a multi-target rescue scheme is generated, an asynchronous block chain is used for evidence storage of a fire-fighting decision instruction, a rescue key area is plotted, and an optimal evacuation route is planned; and converging federal node data to quantify the data contribution degree, reproducing a historical fire behavior and deducing a new scene to carry out iterative optimization. According to the method, the problems of data sensing fragmentation, difficulty in cross-domain fusion, fire prediction lag, underscientific resource scheduling, slow drill scheme iteration and the like in traditional management and control are solved.

The invention relates to the technical field of alarm devices, and discloses a building monitoring management system based on the Internet of Things, which is characterized in that when an alarm sensor generates an early warning signal, a side evidence confirmation module captures power grid harmonic data and compares the power grid harmonic data with a benign equipment feature library, and whether to trigger an alarm or not is determined according to a matching result; according to the invention, through a time sequence mutual identification mechanism of power grid harmonic waves and alarm signals, real fire behavior and equipment operation interference are fundamentally distinguished, and the alarm accuracy is significantly improved; meanwhile, passive positioning is achieved through the multi-branch harmonic intensity difference, the error suppression risk in a large building is eliminated, the equipment health state is monitored through the harmonic entropy change trend, and a complete safety closed loop from early warning to prevention is formed.

This application relates to the technical field of utility tunnels, and provides an intelligent identification and prevention and control linkage system for cable fires in utility tunnels. In this system, a cable fire simulation device is used to simulate cable fires in the utility tunnel; an image acquisition unit is used to monitor the cable fire behavior in the tunnel in real time, and the collected simulated fire image information is transmitted to the deployed fire identification model in real time for fire identification, so as to judge the fire identification results of the fire identification model through the deployed fire warning model, and issue a fire extinguishing command or a warning command according to the judgment results; furthermore, after receiving the fire extinguishing command, the fire extinguishing linkage device responds, and the self-made fireproof rolling shutter with flexible steel brushes is first activated to block the fire point area; subsequently, the telescopic end of the electric push rod installed on the top of the tunnel quickly extends to break the heat-sensitive glass ball of the suspended fire extinguisher, realizing the rapid linkage prevention and control of cable fires in the tunnel.

The invention is suitable for the technical field of computers, and provides a multi-modal fire rescue detection method and system, and the method comprises the steps: obtaining the related information collected by a rescue area, carrying out the multi-modal feature extraction, and selecting the multi-modal feature fusion; performing deconvolution and up-sampling operation on the prior information, and outputting a target position search prompt; multiplying the fire behavior temperature distribution characteristic Fuc by a calibrated temperature range to obtain an actual temperature at the next moment so as to assist rescue; according to the method, voice features, infrared features and visual features are combined, and sufficient feature fusion is performed, so that the accuracy and recall rate of detecting and recognizing the position information of the trapped person are improved; and meanwhile, audio modality is added, so that the limitation that the visual modality cannot be detected due to building shielding objects, smoke and other reasons can be avoided, and the detection effect is more robust.