163results about How to "Improve emergency response efficiency" patented technology

The invention relates to the technical field of natural disaster early warning, in particular to a natural disaster intelligent early warning system based on image processing. Comprising a multi-modal sensor data acquisition module, an image and data preprocessing module, a deep learning and confrontation generative network identification module, a virtual reality disaster situation simulation module, a disaster prediction and trend analysis module, an alarm and notification module, a decision support and emergency response module, and a data storage, management and feedback optimization module. The multi-modal sensor data acquisition module is used for acquiring and fusing various sensor data; the image and data preprocessing module is used for processing multi-source data and aligning and fusing multi-modal data. Through fusion of a multi-modal sensor and a deep learning algorithm, the system improves the recognition capability in a complex environment, can maintain high-precision disaster monitoring under severe conditions, reduces false alarm and missing alarm, and remarkably improves the reliability of an early warning system.

The invention provides an intelligent forest fire prediction and early warning system which integrates satellite remote sensing, unmanned aerial vehicle patrol, ground monitoring and other technologies and intelligently identifies ecological behaviors by using a deep learning algorithm. The system is composed of four core modules: a multi-source data acquisition module, an ecological behavior identification module, a machine learning prediction model module and an intelligent early warning and emergency response module. The forest environment is comprehensively monitored, ecological data is analyzed, the fire risk is accurately predicted, early warning information is automatically generated, and the system is closely linked with an emergency system. The system effectively solves the problems of single traditional early warning means, poor timeliness and insufficient precision, significantly improves the accuracy and response speed of forest fire early warning, and provides powerful technical support for forest resource protection and ecological environment safety.

The invention discloses a reservoir dam safety monitoring abnormity early warning method and system, and belongs to the technical field of safety monitoring, and the method specifically comprises the steps: installing a sensor array at a spillway, a dam body, a dam foundation and a dam shoulder part of a reservoir dam, collecting dam physical parameter data in real time, and transmitting the data to a monitoring center in a wireless manner; after receiving the data, the monitoring center preprocesses and analyzes the data, calculates parameters such as deformation, settlement and displacement of the dam, and compares the parameters with preset safety thresholds; if the dam is in an unsafe state, the system automatically sends out an early warning signal, and a worker acts according to an emergency plan; the method further comprises the steps of field inspection, treatment measure implementation and result recording and feedback, safe operation of the dam is ensured, and the early warning and emergency response efficiency is improved.

The invention discloses an ecological environment commanding and dispatching system and method based on audio and video fusion, and relates to the technical field of ecological environment dispatching. The commanding and dispatching platform is in communication connection with a data acquisition module, a data preprocessing module, an event detection and identification module, a severity evaluation module, a commanding and dispatching module and a resource management module, and all the modules are in electric signal connection; the data acquisition module is used for collecting real-time audio and video data from various sensors and monitoring equipment which are deployed in advance. According to the invention, through real-time monitoring and automatic detection technologies, abnormal events are identified at the first time, and an early warning mechanism is started immediately, so that compared with traditional manual inspection, the time for finding the abnormal events can be shortened, in addition, the automation characteristic of the system reduces delay caused by human factors, and the system is more convenient to use. Therefore, resources and personnel can be quickly mobilized in emergency, and the influence of events can be effectively controlled and relieved.

The invention relates to a water body automatic extraction method and device fusing optical remote sensing data, synthetic aperture radar (SAR) data and unmanned aerial vehicle images. Preprocessing such as radiometric calibration, atmospheric correction and geometric correction is carried out on multi-source remote sensing data, an improved DeepLabv3 + model is used for processing an optical image, a UNet model is used for processing an SAR image, and accurate extraction of a water body area is achieved. And the system fuses optical and SAR data extraction results to generate a high-precision water body recognition result. The method is suitable for flood disaster monitoring and emergency response, and the recognition precision and timeliness of the flood inundation range are improved.

The invention discloses a road traffic accident monitoring and alarming method and system, and relates to the technical field of data processing. The method comprises the following steps: acquiring vehicle speed values, vehicle distance values and driving tracks of a plurality of vehicles on a road to be monitored; calculating a speed change rate according to the vehicle speed value of each vehicle, calculating a distance change rate according to the vehicle distance value of each vehicle, and calculating a vehicle transverse offset according to each driving track; when the speed change rate, the distance change rate or the vehicle lateral offset exceeds the corresponding standard threshold value, determining that a traffic accident occurs on the road to be monitored; receiving the lane occupancy rate, the traffic flow density and the average passing speed of the road to be monitored; and determining an accident grade corresponding to the traffic accident based on the lane occupancy rate, the traffic flow density and the average passing speed, and generating alarm information of the accident grade corresponding to the traffic accident. By implementing the technical scheme provided by the invention, the effect of improving the road traffic accident monitoring and alarming efficiency is achieved.

The invention relates to the technical field of breach image processing, in particular to a breach rapid situation awareness method and system based on multi-source data. The method comprises the following steps: acquiring dam monitoring station data; performing hydrological sensor network setting on the dam monitoring station data to obtain dam hydrological sensor network data; performing ultrasonic water level change trend analysis on the dam hydrological sensor network data to generate an ultrasonic water level change trend chart; performing breach node sensing on the dam hydrological sensor network data according to the ultrasonic water level change trend chart to generate breach node data and breach prediction node data; and according to the breach node data, macroscopic disaster risk analysis is carried out on the breach area, and a breach area macroscopic disaster risk schematic diagram is generated. According to the invention, through real-time data integration, comprehensive risk assessment, unmanned aerial vehicle monitoring, dynamic prediction model and multi-party cooperative response, the accuracy and response speed of breach rapid situation awareness are improved.

The invention discloses a traffic transportation emergency command and dispatch system based on big data resources, which is constructed based on the big data resources and mainly comprises a data acquisition module, a big data processing and analysis module, an event early warning and prediction module, an emergency command and dispatch module, an information display and interaction module and the like. Various devices (a sensor, a camera, a GPS and the like) are utilized to comprehensively collect data such as traffic flow, road conditions, weather, events and the like. Acquisition has the characteristics of high frequency and high precision, supports a plurality of data transmission modes and protocols, and can integrate and format the acquired data to guarantee data quality and convenience of subsequent processing. According to the system, effective utilization of traffic data is realized through collaborative operation of all the modules, and the traffic transportation emergency management capability is improved from multiple aspects, including improvement of management efficiency, enhancement of emergency response capability, improvement of decision support, enhancement of information transparency, optimization of resource allocation, reduction of economic loss and improvement of public safety.

The invention relates to the technical field of storage tank safety monitoring, in particular to a visual real-time monitoring method and system for a digital floating disc of a storage tank. The method comprises the following steps: carrying out real-time floating disc signal acquisition on a full liquid receiving floating disc to obtain real-time floating disc sensing signal data, and carrying out data filtering preprocessing on the real-time floating disc sensing signal data to obtain floating disc sensing signal data; performing Kalman filtering data fusion on the floating disc sensing signal data to obtain real-time floating disc sensing fusion data; performing floating disc abnormal state detection on the real-time floating disc sensing fusion data to obtain floating disc abnormal detection data; floating disc early warning information integration is carried out according to the floating disc anomaly detection data, so that an abnormal floating disc alarm strategy is obtained; data of the full-liquid-receiving floating disc auxiliary mechanism is obtained, prevention and control strategy analysis is carried out, an abnormal floating disc prevention and control strategy is obtained, and the abnormal floating disc prevention and control strategy is uploaded to a controller to execute a floating disc prevention and control task. The safety of the storage tank can be improved.

The invention relates to the technical field of water conservancy projects, in particular to a water conservancy project digital management method based on a BIM model. The method comprises the following steps: acquiring real-time monitoring data; carrying out high-precision topographic data acquisition on a water conservancy project area, and carrying out data preprocessing to obtain preprocessed data; according to the preprocessed data, hydrological information integration modeling is carried out by utilizing a BIM platform, and a hydrological information integration model is obtained; performing multi-dimensional terrain dynamic updating on the hydrological information integration model by using the real-time monitoring data to obtain digital terrain data; performing flood simulation calculation based on the digital topographic data to obtain a flood simulation calculation result; and performing flood scene simulation according to the flood simulation calculation result to obtain flood simulation data. Through real-time monitoring, accurate prediction and timely early warning of the risk of the water conservancy project, a more effective technical means is provided for flood control and disaster reduction and safety management of the water conservancy project.

The invention belongs to the technical field of emergency resource allocation, and particularly relates to an emergency resource modular allocation method capable of achieving rapid and accurate early warning response. The method comprises the following steps: firstly, collecting emergency event related information by using a multi-source data acquisition channel, and carrying out data cleaning preprocessing; secondly, evaluating a risk level by using an enhanced random forest algorithm, and triggering an early warning mechanism; then, based on historical data and current information, using a multilayer perceptron (MLP) to predict emergency resource types and quantity, and dividing the emergency resources into different modules for deployment; and finally, planning an optimal resource transportation path by using a genetic algorithm. The method can effectively improve the data quality and prediction accuracy, accurately judge the risk level, reasonably deploy resources, optimize the transportation path, improve the emergency response efficiency, and guarantee the safe and stable operation of a power grid.

The invention provides a building security alarm system based on the Internet of Things. The building security alarm system based on the Internet of Things comprises a sensor module used for collecting safety related data including environmental parameters and safety events in a building, an edge calculation unit connected with the sensor module and used for analyzing and processing the collected data in real time by adopting a preset quick response algorithm model, and a communication module connected with the edge calculation unit and used for sending the data to the communication module. And the alarm module is used for transmitting analysis results and alarm information to the central control platform and related personnel terminals. According to the building security alarm system based on the Internet of Things, the Internet of Things and an edge computing technology are introduced into the building security alarm system, and a preset quick response algorithm model is adopted, so that real-time analysis and processing of safety related data are realized; mathematical formulas of data fusion, anomaly detection, alarm judgment, response time optimization and the like are utilized, so that the data processing flow is simplified, and the system complexity is reduced.

The invention discloses a smart archival repository intelligent early warning method and system based on the Internet of Things, and relates to the technical field of archival repository early warning, and the smart archival repository intelligent early warning method comprises the steps: transmitting the pre-collected spatial layout data and environment monitoring data of an archival repository to a central management platform through the Internet of Things communication technology; dividing the spatial layout of the archival repository based on the spatial layout data, and judging an archival storage type in each archival storage space; identifying environment monitoring characteristics corresponding to each file storage space based on the environment monitoring data, and judging file storage conditions in each file storage space in combination with the environment monitoring characteristics; and establishing a partition early warning mechanism by combining the file storage type and the file storage condition in each file storage space. According to the invention, environment regulation and control can be effectively carried out according to storage requirements of archives in different areas, and resource waste and environment inadaptation caused by unified regulation and control are avoided.

The embodiment of the invention discloses a forest fire point positioning method and device for a power transmission line, equipment and a storage medium, and the method comprises the steps: obtaining the image data of the power transmission line, the image data being used for reflecting the current environment of the power transmission line; and inputting the image data into a pre-trained Kanbambala distance learning model for forest fire point positioning processing to obtain a forest fire point positioning result of the power transmission line, the forest fire point positioning result being used for reflecting whether a forest fire point exists in the current environment of the power transmission line, the Kanbazier distance learning model is obtained based on historical image data training of a plurality of power transmission lines with forest fire points; and when the forest fire point positioning result reflects that the forest fire point exists in the current environment of the power transmission line, outputting a forest fire prompt including the geographic position information of the forest fire point and the fire information of the forest fire point. The method can quickly respond to the forest fire event, improves the emergency response efficiency, and reduces the damage of the forest fire to the power transmission line. The method can be widely applied to the power transmission line safety monitoring and maintenance field.

The invention relates to the field of digital archives, in particular to an alarm information processing method and system based on a block chain technology. A traditional monitoring system mainly carries out real-time monitoring according to data of a sensor and gives an alarm, and data may be tampered, so that emergency response and afterward responsibility investigation and determination work are affected; the invention aims to provide the alarm information processing method and system based on the block chain technology for a scene that alarm data is easy to tamper in the field of safety production, the method is improved on the basis of the existing Internet of Things technology, the block chain technology is added into the alarm processing system, and the alarm information processing efficiency is improved. The non-tampering and traceability of the data are realized based on the block chain technology, the integrity and transparency of the data are comprehensively considered in the risk monitoring process, the data security can be ensured, and the data security can be ensured for storing and tracing complete and real alarm notification and disposal process records. And powerful evidence support is provided for responsibility investigation and responsibility determination of subsequent accidents.

The invention provides a building group seismic loss probability assessment method based on seismic oscillation intensity random field simulation, and belongs to the technical field of seismic loss assessment. The method provided by the invention comprises the following steps: firstly simulating seismic oscillation of a region by adopting a seismic oscillation intensity random field simulation technology to obtain seismic oscillation intensity spatial distribution of different sites, and then estimating loss probability distribution of each building by utilizing a building anti-seismic performance model and a building vulnerability database. According to the method, the occurrence probability of extreme earthquake loss of a large-scale building group can be evaluated more quickly and accurately, and important support is provided for earthquake risk evaluation and post-disaster emergency decision, so that the disaster resistance and recovery capability of a city are enhanced, and the overall toughness of the city is improved.

A sequential control simulation method and system of a centralized control station simulation system comprises the following steps: establishing a primary wiring diagram and an interval diagram through the simulation system, and collecting data information; establishing an equipment switch disconnecting link association table; associating equipment of the simulation system with a switch and a disconnecting link associated with the equipment, and establishing an index; decomposing the operation state of the equipment according to the association of the equipment, the switch and the disconnecting link to obtain the operation state of the switch; based on a switch operation state, establishing an indexed equipment switch disconnecting link association table, and modeling a scheduling instruction ticket; on the basis of the obtained scheduling instruction ticket model, the simulation system automatically generates an operation instruction ticket according to the initial state and the target state according to the equipment state recorded by the equipment switch disconnecting link association table with the established index; analyzing the operation instruction ticket according to a time sequence to form an event set, and inserting a to-be-executed event list of the simulation system; and the simulation system carries out analysis according to the time sequence and feeds back corresponding states including operation success or operation failure, and one-key sequential control is completed.

The invention relates to a method for evaluating the risk of road damage caused by seismic landslide under different seismic motions, and the method comprises the steps: building a probability multi-factor influence model of seismic landslide occurrence through employing a Bayesian probability method and a machine learning model, and building a sample set according to the historical co-seismic landslide data in a region, taking the sample set as the input of a seismic landslide occurrence probability multi-factor influence model, expanding and applying the seismic landslide occurrence probability multi-factor influence model to a seismic landslide region, taking different seismic oscillation peak accelerations as seismic landslide trigger factors, and calculating the seismic landslide occurrence true probabilities under the different seismic oscillation peak accelerations; and obtaining seismic landslide area road data, and generating a risk level distribution diagram of road damage caused by landslide through spatial analysis by combining the seismic landslide area road data with the seismic landslide occurrence true probabilities under different seismic oscillation peak accelerations. According to the invention, rapid and accurate post-earthquake landslide road damage risk assessment is realized.

The invention discloses a rail transit emergency information generation method and device, equipment and a medium. The method comprises the steps of obtaining fault parameter items corresponding to rail transit fault types and fault parameter data corresponding to the fault parameter items; acquiring system monitoring parameter items, system monitoring parameter data corresponding to the system monitoring parameter items, and sensing data; comparing the system monitoring parameter data corresponding to the system monitoring parameter items with the fault parameter data of the fault parameter items corresponding to the system monitoring parameter items to obtain risk parameter items and risk parameter data corresponding to the risk parameter items; calculating to obtain a predicted fault type according to the obtained data; obtaining resource supply information corresponding to the predicted fault type; and generating rail transit emergency information according to the predicted fault type and the resource supply information corresponding to the predicted fault type. According to the technical scheme of the embodiment of the invention, the accuracy and efficiency of rail transit emergency information generation can be improved.

The embodiment of the invention discloses a forest fire spreading trend prediction method and device, equipment and a storage medium. The method comprises the steps of obtaining preprocessed landform data and meteorological data of a target region; extracting feature information related to fire spreading from the feature information, and constructing an initial feature set; evaluating the S transformation mathematical model through a feature importance evaluation method, identifying feature information having important influence on fire spreading, dividing the obtained processed data set into a training set, a verification set and a test set, and training the constructed S transformation mathematical model of fire spreading; and based on landform data and meteorological data of a to-be-detected target region, predicting and obtaining a fire spreading path and speed through the trained S transformation mathematical model. The scheme has important application prospects in the field of power grids, the early warning capability of power grid mountain fire prevention and control can be improved, the damage of fire disasters to power transmission lines is reduced, and the stability and safety of power grid operation are ensured.

The invention relates to underground space'prevention-breaking-installation 'integrated intelligent emergency equipment and an application method, and the equipment comprises a walking and deployable device, a sensing module and an intelligent control module which are arranged in the walking and deployable device, and a breaking device and an installation device which are arranged at the top of the walking and deployable device. The forcible entry device and the mounting device are arranged adjacently; the method comprises the following steps: 1, deploying and starting; 2, sensing and evaluating; 3, performing three-dimensional reconstruction; 4, decision making and planning; 5, executing first-aid repair; 6, monitoring and adjusting in real time; 7, finishing operation and withdrawing; according to the invention, forcible entry, installation and monitoring are integrated, the whole process of emergency repair can be covered, various conditions after an underground space disaster can be effectively handled, data can be automatically collected and analyzed, three-dimensional reconstruction and decision optimization can be carried out, and dependence on manpower is reduced. Many tasks such as forcible entry, supporting, monitoring and repairing are executed, and meanwhile real-time risk assessment and intelligent early warning are achieved.

The invention belongs to the technical field of scheduling optimization, and particularly relates to a crude oil storage and transportation global commanding and scheduling optimization system, which comprises a crude oil quality judgment module, an optimal adaptive transportation equipment comparison module, an optimal transportation path comparison module, an operation state evaluation value acquisition module and a transportation equipment operation state judgment module. The quality of the crude oil to be transported can be assessed and judged, it is ensured that the quality of the crude oil meets the transportation requirements and standards, and according to the basic information data set of the crude oil to be transported, different transportation devices are compared to find the most adaptive transportation device and the optimal transportation path, so that the transportation cost, time and risk are reduced, and the transportation efficiency is improved; the operation state of the most adaptive transportation equipment under the optimal transportation path is evaluated and monitored, whether the operation state of the transportation equipment is qualified or not is judged, and when the operation state of the transportation equipment is not qualified, a corresponding emergency solution is provided to guarantee the safety and stability of the transportation process.

The invention relates to the technical field of power generation equipment data monitoring, in particular to a new energy power generation equipment accurate monitoring and operation data analysis method. Comprising the following steps: data acquisition and storage: deploying sensors at key nodes to acquire data; evaluating a running state, extracting key indexes such as equipment efficiency, energy consumption and environmental adaptability, and quantifying a scoring standard; an evaluation function is constructed, an analytic hierarchy process and an entropy weight method are combined to determine a weight, and a normalized weight value and a comprehensive evaluation value are calculated; carrying out anomaly detection and early warning, defining an early warning level based on the comprehensive evaluation value, and carrying out mean shift detection; early warning operation and emergency response are carried out, a feedback mechanism is established, and emergency measures under different early warning levels are formulated. According to the method, the equipment operation state monitoring accuracy, the data evaluation scientificity and the abnormity processing timeliness and effectiveness are improved, and stable operation and efficient power generation of the new energy power generation equipment are guaranteed.

The invention relates to an urban rail train main track fault emergency disposal method, device and equipment and a storage medium. The method comprises the steps that all traction key conditions of an urban rail train are obtained; configuring the logic of each traction key condition, and determining an emergency disposal step corresponding to each traction key condition; and monitoring the signal data of the target urban rail train in real time, and when the signal data of the target urban rail train is matched with the logic of the traction key condition, determining the emergency disposal step of the target urban rail train according to the matched traction key condition. By monitoring the signal data of the target urban rail train in real time, the fault causing that the train cannot be pulled to run can be mastered in time, so that the corresponding emergency disposal steps are determined quickly and accurately, the emergency disposal time of the main track fault of the urban rail train is shortened, the emergency disposal efficiency is improved, and the safety of the urban rail train is improved. And the probability of rescue and delay caused by incapability of moving the car is effectively reduced.

The invention relates to an extremely early fire extinguishing scheme for a ship cargo hold transporting a new energy automobile, and belongs to the technical field of ship fire extinguishing systems. The problem that when a ship transports a new energy automobile, it is difficult to find and extinguish fire in the early stage in time is solved. When the new energy automobile in the cargo hold of the ship has a fire risk, the gas telemetering imaging early warning system can detect and identify risk gas and give an alarm. A commander carries out comprehensive assessment according to field conditions, directs sailors to cover a vehicle with risks with a fire blanket, arranges a fire retardant plate and uses a fire extinguishing agent special for a handheld lithium battery. If open fire occurs, the crew uses a fire blanket, a fire-retardant plate and a lithium battery special fire extinguishing agent to extinguish fire, and after it is confirmed that the fire behavior is basically extinguished, the firefighter carries out further treatment after the ship arrives at the shore; and if open fire does not occur, the fire blanket and the fire retardant plate are removed after the alarm is released, and the vehicle can automatically drive away after approaching the shore. The scheme of the invention has the advantages of finding fire in time and effectively preventing fire spreading.

This application relates to a flood control emergency response method, device, and electronic equipment for a valley-type dry ash storage yard. The method includes: responding to a preset emergency condition where the water level of the downstream drainage well's tail-end dammed lake meets the required emergency conditions, initiating emergency drainage measures to excavate a flood discharge channel and construct a flood control work surface; using a combination of hydraulic flushing and slurry pumping to clean the surrounding sediment deposits of the upstream drainage well; and after the drainage functions of both the downstream and upstream drainage wells are restored, reshaping the ash surface morphology of the entire valley-type dry ash storage yard based on the flood control work surface to construct a flood discharge system with the drainage wells as the lowest control points within the yard. This solves the problems in related technologies where heavy rain causes drainage wells to be buried by sediment, leading to drainage system failure, rapid rise in water level within the storage yard, and a lack of systematic emergency response measures, resulting in a sharp shortening or even disappearance of the dry beach in front of the dam, posing a risk of ash water overflow and dam collapse.

The embodiment of the invention discloses a forest fire monitoring method, device and equipment based on a deep learning algorithm and a medium, and the method comprises the steps: capturing image data of heat and spectral information of the surrounding environment of a forest fire through an infrared camera or a thermal imaging camera installed in a power grid; carrying out processing and feature extraction on the image data to obtain a feature vector; analyzing the feature vector through a deep learning model, and recognizing a forest fire target; ranging and positioning are carried out according to the forest fire target, and forest fire position information of an infrared camera or a thermal imaging camera and the forest fire target is obtained; and predicting the spreading speed and direction of the forest fire according to the forest fire position information and the landform data. The scheme provides a scientific basis for power grid forest fire prevention and control work, improves emergency response efficiency, reduces loss caused by fire, and can be widely applied to the field of power grid transmission line forest fire prevention.

The utility model relates to the technical field of heating furnace door opening and closing air cylinder control pipelines, and particularly discloses a furnace door air cylinder emergency control system which comprises an air cylinder and an air source pipeline, an electromagnetic valve is installed on the air source pipeline, and the rear portion of the electromagnetic valve is connected with an air inlet pipeline and an air return pipeline. An air inlet of the air cylinder is further connected with an emergency pipeline, and the other end of the emergency pipeline is connected with an air source pipeline. After the air source straight-through control pipeline is additionally arranged, connection with the air cylinder can be directly disconnected no matter an electromagnetic valve breaks down or an air source triple piece on the front portion breaks down, straight-through air source operation is achieved, intervention of an air source control system is not needed, emergency disposal efficiency is improved, and safe operation of production is guaranteed; when a control pipeline breaks down, a worker does not need to enter a site for emergency danger handling operation, the emergency handling process of the worker is eliminated, intrinsic safety of operation is achieved, and spare part consumption of the electromagnetic valve is reduced.

This utility model relates to the field of electronic lock technology, specifically an unlocking mechanism and a passive intelligent lock for power plant equipment maintenance and isolation. It includes a lock body, a lock rod movably disposed inside the lock body, and a battery disposed inside the lock body; an engaging assembly including a drive component disposed inside the lock body, a lifting component movably disposed on the outer wall of the drive component, and a locking component movably disposed on the outer wall of the lifting component. This utility model, by setting up the engaging assembly, enables a motor to drive a cam to rotate, causing the lifting rod to descend under the action of a first elastic component, and further contraction of a second elastic component to disengage the protrusion from the groove, thus completing the unlocking action and enabling rapid release in emergency situations. Furthermore, it achieves remote control of the lock via a Bluetooth connection between a mobile app and the key, effectively preventing unauthorized intrusion, enhancing security, and allowing for rapid unlocking in emergency situations, improving emergency response efficiency.

The application relates to the field of intelligent cabinet management, in particular to a safety data management system and method based on an emergency rescue intelligent cabinet, which comprises a material grading module, a permission management module, a distribution planning module, a space supervision module and an emergency identification module, the material grading module is used for establishing a material grading system, the permission management module is used for determining the opening permission of a high-grade material storage compartment, the distribution planning module is used for constructing a gridding model and determining the optimal layout of the intelligent cabinet, the space supervision module is used for setting the positions of common cabinets and supervision points, and the emergency identification module is used for determining the core area of an emergency event; the application can reduce the setting cost of the intelligent cabinet, optimize emergency resource management, balance the convenience and safety of the intelligent cabinet, shorten the material deployment time, improve the emergency response speed, realize event detection and dynamic adjustment mechanism based on a material flow mode, and provide rapid and effective material guarantee for emergencies.