1468 results about "Fire safety" patented technology

The invention belongs to the technical field of fire safety, and discloses a fire-fighting equipment detection early warning method and system based on a visual camera, and the method comprises the following steps: obtaining multi-focal-length image frames of a fixed spray head and a fire extinguisher edge region, judging the continuous change of gray scale in the continuous image frames, and carrying out the detection early warning of the fire-fighting equipment based on the visual camera. Comparing the gray level distribution difference under the long focus and the short focus, identifying the dynamic trajectory of the contour line angular point of the fire-fighting equipment association structure, analyzing the delay of the function action response, marking as an abnormal region, and generating a fire-fighting equipment collaborative early warning information set; according to the invention, by extracting and analyzing the multi-focal-length image frames of the edge areas of important facilities such as a fixed spray head and a fire extinguisher, fine changes of the fire-fighting facilities under differentiated focal lengths can be captured, working states and potential faults of the fire-fighting facilities can be judged, functional abnormalities caused by equipment aging or damage can be recognized in advance, early warning can be carried out in real time, and the safety of the fire-fighting facilities can be improved. And a higher guarantee level is brought to fire safety.

The present invention discloses an intelligent control system for fire safety management, which relates to the field of safety management technology, including a multimodal sensor module and a digital twin modeling module, wherein the multimodal sensor module and the digital twin modeling module are connected and communicated through a data transmission network, and the digital twin modeling module includes an edge computing node in the region and a central data processing server, and constructs a three-dimensional digital twin model of a building and its environment by receiving and fusing data from the multimodal sensor module and utilizing real-time data processing and model updating algorithms. The present invention realizes the function of constructing and continuously updating a digital twin model of a building and its environment by designing a multimodal sensor module and a digital twin modeling module, and reflects the internal structure of the building, environmental parameters and personnel flow status in real time, solves the problems of data dispersion, lack of real-time performance and static model in traditional systems, and ensures the accuracy and timeliness of fire risk assessment.

The invention relates to the technical field of fire safety, and provides a smart campus multi-dimensional fire safety monitoring method and system. The method comprises the following steps: collecting multi-source security data of a campus building; extracting features based on a preset risk dimension, and generating a fire risk feature vector; constructing a risk model according to historical fire cases, and scoring the feature vectors to obtain a real-time risk score; when the score exceeds a dynamic threshold value, triggering a grading early warning instruction; an emergency scheme is generated according to the early warning, and fire fighting equipment and a personnel evacuation system are linked to execute operation. The technical problem that an existing campus fire safety monitoring system lacks a multi-dimensional, real-time and comprehensive risk assessment means and is difficult to accurately judge different fire risks and deal with the fire risks in real time is solved, and accurate fire risk early warning and efficient emergency response are achieved through multi-source data fusion and intelligent analysis. And the campus fire safety management level is improved.

The invention provides a method for constructing a differential diffusion small flame model for buoyancy-driven plume, and the method is applied and expanded to a pool fire combustion process in the field of fire safety. According to the method, the buoyancy driven plume is solved by using the small flame model, the solving number of component equations of the buoyancy plume is greatly reduced through coordinate conversion dimensionality reduction processing, and the main characteristics of the buoyancy plume can be reproduced with relatively high precision and a faster calculation rate. According to the method, high-precision numerical solution of buoyancy plume is realized, and pool fire combustion of gas fuel and liquid fuel and numerical solution of all plume driven by buoyancy can be processed.

The invention relates to the technical field of fire safety monitoring, in particular to a firework identification system and method based on multi-modal fusion perception, and the core of the scheme is a visible light, multispectral and temperature three-modal framework: feature extraction optimization of each modal, improved YOLOv8s for visible light branches, dynamic background modeling and flame color screening, and multi-modal fusion perception. False positive is rejected by a multispectral branch depending on a waveband ratio and an index, an error compensation algorithm is introduced into a thermopile branch, and finally, a final smoke and fire area and the confidence coefficient thereof are determined by associating a three-mode area through collaborative decision. According to the scheme, the complex environment adaptability and the recognition reliability can be improved, the false alarm risk is reduced, the extremely-early smoke and fire detection capability is enhanced, good real-time performance and deployment flexibility are achieved, and the method is suitable for various types of fire safety monitoring scenes.

The invention relates to the technical field of fire safety, in particular to an intelligent fire-fighting electrical fire monitoring method, device and equipment and a medium, and the method comprises the steps: obtaining electrical parameters; according to the electrical parameters, a fire hazard identification model is established by using an LSTM algorithm and a CNN algorithm, the operation state of the electrical equipment is predicted according to the fire hazard identification model, an operation state trend prediction result is obtained, and a potential fire hazard type is identified; according to a fire hazard type identification result, in combination with a use environment of electrical equipment and a threshold determination algorithm, performing quantitative evaluation on a fire hazard risk to obtain a corresponding risk level, and when the risk level exceeds a set multi-layer threshold, automatically starting a linkage control mechanism; therefore, the problems of response lagging, high labor cost, high intermittent fault omission ratio and the like in the prior art are solved.

The invention discloses an energy storage power station fire early warning method and system based on multi-parameter fusion, and the method comprises the following steps: collecting the temperature, characteristic gas concentration, cell expansion force, voltage fluctuation and environment temperature and humidity data of a lithium battery of an energy storage power station in real time through a distributed sensor, and carrying out the cleaning, denoising and standardization processing of the collected parameters, temperature and gas concentration monitoring values are corrected through an environment temperature and humidity compensation algorithm, abnormal data caused by environment interference are eliminated, the preprocessed data are input into a preset intelligent early warning module, and the model is based on a random forest algorithm. Through multi-parameter fusion and intelligent algorithm deep analysis, in combination with environment compensation, interference elimination, early warning accuracy improvement, graded early warning and linkage response, full-stage accurate disposal is achieved, timeliness is enhanced, sensor redundancy, multi-cabin cooperation and other mechanisms guarantee reliability, a closed loop from monitoring to disposal is formed, and the fire risk and loss are effectively reduced.

The invention discloses an intelligent AI detection method based on an infrared thermogram and automobile diagnosis, according to the technical scheme, the fireproof safety detection efficiency of an electric automobile is remarkably improved through multi-modal data fusion and intelligent analysis, and a multi-dimensional data basis is constructed through synchronous acquisition of dual-band infrared and vehicle operation parameters; secondly, a dynamic correlation model realizes accurate triggering of abnormal current on heat map enhancement, partition gradient processing is combined with dynamic threshold adjustment to optimize detection sensitivity for thermal characteristics of different parts, three-dimensional thermal field reconstruction breaks through surface detection limitation, internal potential overheat points can be identified, and the detection sensitivity is improved; and finally, closed-loop diagnosis is formed through case library intelligent matching, so that the fault positioning precision reaches a component level, and the whole scheme is coordinated through a multi-level technology, so that the problems of low infrared thermal image contrast and relatively poor detail distinguishing capability due to the fact that electric vehicle fireproof safety detection is carried out only by depending on thermal infrared images in the prior art are solved.

The invention relates to the technical field of highway tunnel safety monitoring, and discloses a highway tunnel intelligent fire safety early warning system, which comprises a data acquisition and preprocessing module used for acquiring video monitoring data, environment sensor data and vehicle positioning data in a tunnel in real time; the dynamic risk assessment module is used for constructing a risk field model based on vehicle trajectory and smoke diffusion space-time coupling; the emergency resource elastic adaptation module is used for automatically adjusting the induction screen and the fire fighting equipment according to the risk intensity; according to the method, the limitation of traditional threshold alarm is avoided, fire early warning nodes are greatly advanced through multi-source data dynamic fusion, long-term stability of a monitoring benchmark is guaranteed by utilizing an optical flow compensation and pollution self-repairing mechanism, and the self-adaptive migration of a calculation task is realized by utilizing the optical flow compensation and pollution self-repairing mechanism. And the initiative and reliability of tunnel safety prevention and control are obviously improved.

The invention belongs to the technical field of fire monitoring, and particularly relates to an early warning system and method based on fire safety. According to the method, the multi-modal environment data of the monitoring area is comprehensively analyzed, a confidence evaluation function and a dynamic weight distribution mechanism are introduced, the accuracy and reliability of early warning are improved, and the early warning accuracy and reliability are improved by calculating and analyzing the characteristic parameters such as the forward change rate and the historical fire occurrence probability of each sub-environment data. The confidence of the sub-environment data is obtained by combining a confidence evaluation function, an important basis is provided for subsequent data processing, fine processing of the sub-environment data is realized through independent analysis of the sub-environment data, the sensitivity and accuracy of early warning are further improved, and the accuracy of early warning is improved through weighted fusion of the sub-environment data. According to the method, the fire safety early warning index is obtained, the risk grade of the monitoring area is evaluated according to the index, the corresponding early warning signal is output, and the real-time early warning of the fire safety state of the monitoring area is realized.

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 belongs to the technical field of safety protection, and particularly relates to an energy storage equipment safety protection early warning system applied to an industrial park, which adopts a module-cluster-cabin three-level architecture to realize real-time monitoring and dynamic evaluation of thermal runaway risk, the architecture integrates multi-source data, and when the risk exceeds a preset threshold value, the energy storage equipment safety protection early warning system is used for early warning the thermal runaway risk. The system automatically starts graded fire extinguishing measures and a fire-fighting linkage mechanism, and meanwhile, secondary analysis is carried out on an early warning result through a cloud platform to optimize model parameters, so that the accuracy and the efficiency of the system are ensured; the system constructs an integrated monitoring, response and self-correction prevention and control process, and effectively overcomes the problems of early warning delay, high false alarm rate, single protection means, data islanding and the like in the prior art through a multi-parameter fusion early warning, accurate recognition, graded fire extinguishing and intelligent linkage mechanism. And a solid guarantee is provided for fire safety in a high-density energy storage environment.

The invention relates to the technical field of intelligent fire safety linkage control, in particular to an intelligent locking linkage control system and method based on fire monitoring, and the system comprises an acquisition module, a modeling module, a simulation engine module, a decision center module and an execution module. The acquisition module acquires physical quantity data of a key area of a building, wherein the physical quantity data comprises high-temperature radiation spectrum offset, aerosol particle swarm distribution characteristics and local heat convection intensity. The modeling module generates an environmental interference confidence index through convolutional neural network fusion features, and starts an incremental clustering algorithm to update an interference knowledge base when the confidence is insufficient. And the execution module dynamically compresses the delay window according to the risk map, and triggers a cross-level linkage mechanism through a people flow density threshold. And the environment sampling frequency adjustment coefficient is fed back to the acquisition module, the execution state data reverse drive modeling module iteratively updates the knowledge base, a Bayesian optimizer is combined to screen high-value characteristics to reconstruct simulation parameters, and full-link closed-loop learning and continuous evolution of the false alarm suppression capability are realized.

The invention discloses an intelligent fire-fighting risk prediction and dynamic early warning method and system based on multi-source data fusion, and relates to the technical field of intelligent fire-fighting risk prediction, and the method comprises the steps: collecting multi-source fire-fighting data, and constructing a fire-fighting safety state multi-dimensional data matrix; constructing a risk prediction model based on the fire safety state multi-dimensional data matrix to carry out real-time risk scoring; and executing dynamic early warning through a risk prediction result. According to the method, through the multi-source data acquisition and fusion module, multi-type fire-fighting data are comprehensively acquired and standardized, a structured and multi-dimensional fire-fighting safety state matrix is constructed, and the problems of data dispersion and information splitting are solved. In combination with a risk collaborative prediction and scoring module, the risk level of each region is dynamically output based on multi-factor analysis, and the accuracy and foresight of risk prediction are improved. Through a dynamic early warning generation and linkage module, real-time grading early warning and linkage of a fire fighting system are realized, and rapid response and intelligent prevention and control of a high-risk area are realized.

The invention belongs to the technical field of fire-fighting supervision, and particularly relates to an intelligent fire-fighting alarm system and method based on regionalized monitoring, and the system comprises a regionalized monitoring network module, an intelligent data analysis module, an early warning information issuing module, an emergency evacuation plan module, a fire-fighting facility linkage module, and a regional fire-fighting supervision terminal. Environmental parameters in a target area are comprehensively collected in real time through the regionalized monitoring network module, the intelligent data analysis module identifies a fire disaster based on the collected data, quick response and emergency evacuation are performed after the fire disaster is identified, loss caused by the fire disaster is effectively reduced, and the safety of the fire disaster is improved. After fire early warning is removed, fire hazards are accurately analyzed and fed back in time, regional fire control management personnel can master the severity degree of each fire in detail, and regional fire control safety supervision is enhanced in time by comprehensively evaluating and analyzing the regional fire control potential safety hazard degree; the regional fire-fighting hidden danger is obviously reduced; and the regional fire-fighting management difficulty is reduced.

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, which relates to the technical field of fire safety, discloses a multi-modal intelligent identification method for fire-fighting hidden troubles based on a large model, comprising the following steps: S1, acquiring multi-source heterogeneous feature data through a sensor network deployed in a fire-fighting water pump room to obtain an initial feature set; s2, performing unified scale conversion on the initial feature set, calculating heterogeneous bridging parameters according to the environmental parameters and the equipment operation data, constructing a fusion feature vector, inputting the fusion feature vector into a preset neural network for feature weight adaptive adjustment, and outputting an adjusted weight vector; according to the fire-fighting hidden danger intelligent identification method based on the large-model multi-mode, intelligent closed loop from hidden danger identification to prevention and control decision making is realized, and the intelligent, dynamic and precise management level of a fire-fighting safety system is comprehensively improved.

The invention relates to the field of urban building fire-fighting management, and discloses an urban building fire-fighting safety intelligent management platform based on BIM and GIS multi-source fusion, and the platform comprises a multi-dimensional sensing module which is used for accessing BIM building detail data and GIS geographic space data, and collecting the multi-dimensional data of a building in real time; the data fusion module is used for performing space-time alignment and feature fusion on the BIM building detail data, the GIS geographic space data and the multi-dimensional data by adopting a space-time attention mechanism, and performing standardization processing to obtain fused data; and the coupling calculation module is used for utilizing a multi-physics field coupling algorithm. Through comprehensive acquisition and access of BIM building detail data, GIS geographic space data and real-time multi-dimensional data, space-time alignment and feature fusion of multi-source data are completed by means of a space-time attention mechanism, and a fire dynamic model including interaction of a temperature field, a structural mechanical field and a smoke diffusion field is constructed by using a multi-physics field coupling algorithm.

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 invention belongs to the technical field of fire safety early warning, and discloses a fire detection alarm method and system. The method comprises the following steps: monitoring the environmental smoke concentration in real time through a smoke detector arranged in a battery compartment to obtain smoke parameters; synchronously monitoring the environment temperature change through a temperature sensing detector to obtain a temperature parameter; comparing the smoke parameter with a preset smoke threshold value, and comparing the temperature parameter with a preset temperature threshold value; determining an alarm signal grade according to a comparison result, and triggering a corresponding alarm signal based on the alarm signal grade; and after the alarm signal is triggered, corresponding alarm measures and corresponding fire extinguishing measures are executed according to the grade of the triggered alarm signal. Through the above mode, composite grading alarm can be carried out, the accuracy of fire alarm is improved, targeted fire extinguishing measures are taken for different alarms, and the fire extinguishing efficiency is also improved.

The invention relates to the technical field of fire safety management, and discloses a fire safety management supervision platform system. The system comprises a building information acquisition module for acquiring building structure data and environment monitoring data of a target building in real time; the risk area division module is used for dividing a plurality of independent fire risk areas according to the building structure data and distributing area identifiers; the historical data indexing module is used for indexing a historical fire accident data set and a fire-fighting facility maintenance record set of each region according to the region identifier; the dynamic risk analysis module fuses the environment monitoring data and the historical fire accident data set to generate a real-time fire risk coefficient sequence; the fire-fighting resource scheduling module is used for generating a fire-fighting resource allocation scheme based on the real-time fire risk coefficient sequence and the facility maintenance record set; and the emergency response decision module generates a multi-stage fire emergency response strategy according to the resource allocation scheme. The system improves the timeliness and pertinence of fire safety management.

The invention discloses a real-time judgment method for roof collapse caused by a fire between nuclear power station oil storage tanks, and relates to the technical field of fire safety design of roof structures between nuclear power station oil storage tanks. Acquiring time sequence temperature data of the grid nodes; establishing a three-dimensional heat conduction model of the roof structure; top plate structure heating surface temperature field mapping is realized; carrying out three-dimensional heat transfer simulation on the top plate structure; analyzing the instability critical condition of the roof structure. According to the real-time judgment method for the roof collapse caused by the fire between the oil storage tanks of the nuclear power station, time sequence temperature field mapping of the heated surface of a complex roof structure between CFD numerical simulation software and FEM software in different fire scenes between the oil storage tanks of the nuclear power station can be realized; real-time structure response behaviors of the nuclear power station oil storage tank roof structure in different fire scenes are simulated, and the method can be used for fire safety design and post-disaster damage evaluation of the nuclear power station oil storage tank roof structure.

The invention belongs to the technical field of fire safety, and particularly relates to a control method of a fire detection alarm. Firstly, a distributed sensor network is deployed to collect temperature and smoke data, self-calibration is carried out, and abnormal data is eliminated. Then, through three-level progressive anomaly screening, namely, first-level preliminary screening monitoring mutation features and second-level feature verification, a space-time matrix is constructed, CNN analysis is used for the space-time matrix, third-level scene adaptation is combined with historical data to calculate the probability, and an anomaly screening signal is output. A visual camera is used for collecting images to generate a visual evidence matrix, a sensor data vector and an abnormal screening signal are combined to calculate a comprehensive confidence coefficient, and an alarm signal is triggered if the comprehensive confidence coefficient is larger than a threshold value; and finally, through time window sliding verification taking one minute as a period, determining an alarm when an alarm signal is greater than or equal to three periods. According to the method, the data accuracy is improved, fire hazards are accurately identified, the false alarm rate is reduced, and the alarm timeliness and accuracy are guaranteed.

The invention discloses a fire safety intelligent evaluation system and a closed-loop management and control method, and the method comprises the steps: analyzing national standard and local standard texts through a natural language processing technology, disassembling terms into a three-stage quantifiable index system, and constructing a dynamic index library comprising at least 200 subdivisions; a dynamic rule base is generated based on a BERT-NER model, a standard parameter threshold value is automatically extracted, and version difference comparison and real-time updating are supported; deploying a fire-fighting special BERT model to analyze an unstructured document, extracting violation events and converting the violation events into structured evaluation factors, aggregating multi-source sensor data and video streams through an edge computing gateway, and adding space-time tags to realize millisecond-level real-time monitoring; generating a comprehensive score in combination with the static weight and the dynamic weight, constructing a risk prediction model based on an Attention-LSTM network, inputting historical hidden danger data, environment variables and enterprise operation data, and outputting future risk probability distribution; according to the invention, compliance management is efficient, assessment accuracy is improved, risk response is real-time, and a management and control process is digital.

The invention relates to the technical field of fire safety inspection, in particular to a fire safety inspection method and system based on machine vision recognition. The method comprises the following steps: carrying out inspection equipment deployment on an inspection area to obtain a camera deployment scheme and a sensor network deployment scheme; performing multispectral dynamic sensing according to the camera deployment scheme to obtain a time sequence spectral flow; performing multispectral channel motion estimation on the time sequence spectral flow, and performing motion vector noise suppression to obtain a filtered motion vector diagram; performing spectral characteristic-based motion enhancement on the filtered motion vector diagram to obtain a spectral enhanced motion vector; and performing motion amplification algorithm application on the time sequence spectrum flow according to the spectrum enhanced motion vector, and constructing an enhanced motion vector field to obtain the enhanced motion vector field. According to the invention, through multi-modal information fusion, context awareness and capturing of early fine features, early and accurate fire hazard identification and early warning are realized.

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 invention discloses a preparation method of modified self-extinguishing insulating oil with flame-retardant and self-repairing functions. Wherein the insulating liquid is mixed oil of mineral oil and palm oil-based modified natural ester, and the inherent high flash point characteristic of the natural ester improves the fireproof safety of the insulating oil. The modified hexagonal boron nitride (h-BN), the magnesium hydroxide nano material and the microcapsule repairing agent are added into the insulating oil, and the h-BN can capture free electrons in the oil, so that the formation and expansion of electric arcs are inhibited, and the breakdown voltage is improved. Magnesium hydroxide is heated to decompose and absorb heat, the fault temperature is reduced, and therefore the arc self-extinguishing effect is achieved. Under the action of a high electric field and a high temperature, the capsule wall of the microcapsule repairing agent is broken, meanwhile, the repairing material is released, a chemical reaction is carried out, and the insulating property of the insulating oil is repaired. The modified insulating oil prepared by the invention has high insulating strength and high flame retardance, and also has a performance self-repairing function, so that the service life of the insulating oil is prolonged.

The invention discloses a building fire-fighting automatic verification and evacuation path verification system based on a rule engine, and relates to the technical field of building fire-fighting intellectualization. Comprising the steps that a rule generation module analyzes a fire-fighting standard text and generates an executable rule set; the model analysis module is used for extracting component attributes and a spatial topological relation from the building information model; the real-time sensing module collects environment state data. The rule engine module matches the component attributes with the executable rule set to generate a first verification result; spatial topology and real-time sensing data are fused, the dynamic passing weight of each path segment is calculated, and an evacuation path network model is constructed. The path verification module verifies the safety of a path from a preset point to an exit based on the model, and generates a path verification result. And the result generation module outputs fire-fighting compliance data. According to the invention, through the dynamic optimal evacuation path planning from the static fire-fighting standard examination of the building design to the occurrence of the disaster, the guarantee capability and the emergency response efficiency of the building fire-fighting safety are improved.

The invention provides an AI-based security risk analysis method, and relates to the technical field of data processing, and the method comprises the steps: dynamically determining three spatial reference positions through a spatial topological relation analysis algorithm based on spatial coordinates in a business data result; generating a dynamic risk partition based on the spatial reference position; executing a space grid division operation on the dynamic risk partition to form a discretized space analysis unit; calculating a grid deformation gradient tensor as a risk distribution adjustment value based on the geometric deformation parameters of the spatial analysis unit; and generating spatial risk thermodynamic data points describing spatial risk distribution according to the structured semantic information, the knowledge enhancement context, the business data result and the risk distribution adjustment value. According to the method, the risk analysis target, the key entity and the spatial constraint condition can be accurately extracted, and the convenience of man-machine interaction and the accuracy of semantic understanding are improved.

The invention relates to an intelligent fire-fighting potential safety hazard evaluation system and evaluation method, and relates to the technical field of fire-fighting safety management, and the system comprises a multi-dimensional sensing module, a state vectorization module, a regional risk quantification module, a global risk evaluation module and a model optimization module. Multi-dimensional data is converted into a unified state vector through the multi-dimensional sensing module and the state vectorization module, and the unified state vector is compared with a dynamic normal state, so that the accuracy of hidden danger recognition is improved. The regional risk quantification module calculates the internal risk index of each region, and the global risk assessment module integrates the indexes to form a comprehensive risk assessment result. The model optimization module dynamically adjusts model parameters based on historical data and real-time feedback, and the prediction accuracy is improved. According to the invention, comprehensive monitoring and intelligent assessment of fire risks are realized, the efficiency and practicability of fire safety work are significantly improved, and it is ensured that potential fire risks are effectively coped with in a complex and changeable environment.