2579 results about "Emergency rescue" patented technology

A dynamic evaluation method for an extreme rainstorm waterlogging disaster risk for disaster prevention and reduction. The method comprises: investigating and surveying urban system data and disaster prevention and reduction data, using GIS technology to divide disaster-bearing objects into refined risk units on the scale of urban buildings and road networks, and determining the spatial distribution of the disaster-bearing objects; on the basis of an extreme rainstorm waterlogging scene, simulating the disaster influence of a dynamic change process of a flood ponding depth on the disaster-bearing objects; developing refined dynamic evaluation on a waterlogging risk by combining the two methods of waterlogging process simulation and an indicator system; using a spatial complex network and a shortest path plan to calculate a traffic capacity and emergency service accessibility of a road network system; and on this basis, taking into comprehensive consideration the rational allocation of disaster prevention emergency drainage and emergency rescue services to a high-risk area, and proposing dynamic evaluation technology for a waterlogging risk that integrates a disaster evolution process and a disaster prevention response process, and ultimately realizing the dynamic evaluation of the waterlogging risk of each disaster-bearing unit during the waterlogging disaster evolution.

The invention belongs to the technical field of emergency management, and discloses a natural disaster emergency rescue system based on multi-source sensing information fusion. The system is composed of a multi-source sensing data acquisition module, a data preprocessing and space-time registration module, a cross-modal feature extraction module, a multi-modal information fusion and conflict resolution module, a disaster type identification and grade discrimination module, a disaster influence range prediction and diffusion modeling module, and a dynamic emergency path planning and response plan generation module. A rescue scheduling and command control module; and an emergency feedback and closed loop dynamic correction module. Through multi-source sensing data fusion, cross-modal feature extraction and deep information fusion technologies, a full-space-time and full-process natural disaster emergency rescue system is constructed, comprehensive sensing, accurate recognition and dynamic plan generation of a disaster site are realized, the rescue response speed and decision scientificity are remarkably improved, and the intelligent level of emergency rescue is comprehensively improved.

The invention relates to the technical field of unmanned aerial vehicle perception, and discloses a visual navigation method and system of a six-rotor full-drive unmanned aerial vehicle, a terminal and a storage medium. A navigation framework integrating dynamic visual perception and full-drive control characteristics is constructed, and a visual encoder is adopted to extract multi-scale environment characteristics; according to the method, time sequence information is processed in combination with a long-short-term memory network, efficient feature extraction and motion trail prediction of an image sequence under high-speed rotation and violent attitude change of the unmanned aerial vehicle are achieved, the problem of feature tracking loss of a traditional algorithm in a high-dynamic scene is solved, global correlation modeling of environment features is enhanced through an attention mechanism, and the tracking accuracy of the unmanned aerial vehicle is improved. According to the six-rotor-wing full-drive unmanned aerial vehicle navigation method, the navigation precision and robustness of the unmanned aerial vehicle in a complex dynamic environment are remarkably improved by combining control instruction generation of dynamics constraints, high-precision inertial navigation compensation is not needed, and an efficient and reliable navigation solution is provided for application of the six-rotor-wing full-drive unmanned aerial vehicle in emergency rescue, high-speed inspection and other scenes.

The invention provides a miner safety early warning system based on UWB and AI cameras, and relates to the technical field of mine safety, the miner safety early warning system comprises a positioning module, a video monitoring and analysis module, a data fusion and processing module and an early warning and communication module, the positioning module is composed of a plurality of UWB base stations arranged in a mine and UWB positioning cards worn by miners, and the video monitoring and analysis module is connected with the early warning and communication module. The centimeter-level real-time positioning of miners is realized through ultra-wideband pulse signals; the UWB technology is applied, the positioning precision is improved to the centimeter level, the positions of miners can be accurately mastered, precious time is won for emergency rescue, intelligent recognition and analysis of personnel behaviors and environmental risks are achieved through the AI camera, the defects of traditional monitoring are overcome, potential safety hazards can be found in advance, and through multi-source data fusion and real-time processing, the safety of the miners is improved. The system can give an early warning at the first time when a danger occurs, thereby effectively avoiding the occurrence of an accident or reducing the harm degree of the accident.

The invention relates to the technical field of emergency management, in particular to an emergency rescue management optimization method based on an AI algorithm. The method comprises the following steps: obtaining the corresponding number and position of various rescue resources and the corresponding state and performance of various rescue devices through an emergency disaster area, carrying out rescue resource capability evaluation, and predicting the emergency rescue resource demand corresponding to each emergency rescue task; based on the emergency rescue resource demand quantity corresponding to each emergency rescue task, performing emergency priority sorting analysis on each emergency rescue task, and generating a corresponding emergency rescue priority sequence in the current area; and carrying out emergency rescue allocation management optimization on the corresponding emergency rescue priority sequence in the current area by taking the maximum rescue effect as a target and combining the corresponding emergency rescue resource capability in the current area so as to generate a corresponding emergency rescue resource allocation management decision suggestion. According to the invention, the response speed and rescue effect of emergency rescue can be improved.

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 discloses a disaster emergency rescue nursing skill training system based on virtual reality, and relates to the technical field of virtual reality. A high-simulation virtual disaster scene is constructed based on real data, diversified injury condition virtual objects matched with the scene are generated, a secondary disaster risk diffusion effect and emergency prompt information are overlaid in real time, physiological state changes such as blood pressure and respiration generated by nursing operation differences in the rescue process of wounded personnel are dynamically simulated, and the rescue effect of the wounded personnel is improved. The problems of single scene and fixed injury condition in traditional training are solved, real-time and multi-modal feedback of student operation is realized through accurate comparison and hierarchical identification of multi-dimensional operation characteristics, the defects of guidance lagging and general are overcome, a personalized and adaptive training scheme is generated according to a comprehensive evaluation result, the progress is dynamically adjusted, and the training efficiency is improved. And scene simulation, operation practice, accurate feedback and personalized improvement are integrated.

The invention provides a major accident-oriented rescue resource demand quantity prediction and dynamic supply method, which relates to the technical field of emergency rescue, and comprises the following steps: acquiring accident site multi-source data information for situation awareness, performing long-term prediction on rescue demand quantity based on a symplectic geometric structure and Hamiltonian dynamic mapping, and determining the rescue demand quantity; and the supply network is dynamically optimized by using the Riemannian curvature flow to generate the rescue resource supply scheduling scheme, so that the resource demand can be accurately predicted, the supply path can be optimized, the rescue efficiency can be improved, the resource waste can be reduced, and the accurate delivery of the rescue resources can be realized.

The invention relates to the technical field of rescue path planning, and discloses a low-altitude traffic emergency rescue path planning method and system based on geographic information space-time analysis, and the method comprises the steps: obtaining geographic information data collected by different data sources, and carrying out the fusion of the same kind of data of the different data sources; based on the fused geographic information data, adding timestamps and time interval attributes to construct four-dimensional spatio-temporal data; determining a preliminary rescue path based on the four-dimensional spatio-temporal data through an improved A * algorithm; on the basis of the preliminary rescue path, local or global path optimization is carried out according to the real-time change of geographic information in the flight process, and the accuracy, timeliness and safety of low-altitude emergency rescue path planning are improved.

The invention is applicable to the technical field of emergency rescue, and relates to an optimal path planning method based on a fire rescue road network directed graph, which comprises the following steps: reconstructing the road network directed graph according to a road priority principle by using multi-source data such as an open street map road network, road conditions, survey data, real-time road conditions and the like and fusing remote sensing image data; on the basis, based on a dynamic weight model, an optimal path planning algorithm based on a fire rescue road network directed graph is further constructed. The application of the method can effectively make up for the deficiency of online map path planning used in the existing research, so that the path planning better fits the path planning requirement in a real fire rescue scene, and the driving path of fire rescue can be accurately calculated, so that the path is more reasonably planned, and the efficiency of fire rescue is improved.

The invention relates to a multi-dimensional transmission data compression sensing method and system for urban emergency rescue, and the method comprises the steps: obtaining multi-modal data, carrying out the normalization processing and sparse representation, and obtaining the sparse coefficient of each modal; constructing a block diagonal random matrix for each modal sparse coefficient to perform independent compression sampling, generating a low-dimensional observation value before coding, and performing arithmetic coding and low-density parity check code error correction coding to generate an anti-interference code stream; and performing low-density parity check code decoding and arithmetic decoding on the anti-interference code stream to obtain a decoded low-dimensional observation value, performing iteration by using an orthogonal matching pursuit algorithm, recovering sparse coefficients of each mode, performing reconstruction to obtain text, image and audio features, and projecting the text, image and audio features to a shared semantic space to obtain a shared semantic space. And calculating a joint semantic weight through a cross-modal attention mechanism, and generating a multi-modal fusion result with consistent semantics. The method disclosed by the invention provides an efficient, robust and semantic collaborative end-to-end solution for urban emergency rescue.

The invention provides a mountain area highway emergency rescue path planning method and system. The method comprises the following steps: collecting traffic flow data, meteorological data and field state data of a disaster site; generating a dynamic risk map according to the meteorological data, the field state data and the traffic circulation data; determining rescue constraint conditions of the rescue bodies in the emergency rescue process according to the dynamic position information of the rescue bodies near the disaster site and the rescue body types of the rescue bodies; performing hierarchical scheduling on each rescue body based on the dynamic risk map and all rescue constraint conditions to obtain a space-time conflict matrix; and performing multi-target real-time path planning on each rescue body according to the space-time conflict matrix, and generating a space-time conflict-free collaborative rescue path set. By adopting the scheme of the invention, efficient cooperation of multiple rescue bodies can be realized in the multi-disaster-chain coupling evolution environment of the highways in the mountainous area so as to generate a global optimal rescue path without conflicts in time and space.

The invention provides an interphone emergency rescue method and system based on ultra-low power consumption remote wakeup, and relates to the technical field of interphone emergency rescue, and the method comprises the steps: switching a normal working mode to an ultra-low power consumption mode according to a mode switching instruction generated by triggering a target emergency event; in the ultra-low power consumption mode, performing signal monitoring on a preset communication frequency band according to a preset monitoring strategy so as to receive a wake-up signal broadcasted by a first search and rescue user on the preset communication frequency band through a first search and rescue end interphone; when it is determined that the wake-up signal is received from the preset communication frequency band, performing security verification on the wake-up signal to switch the ultra-low power consumption mode to a normal working mode; and in the normal working mode, executing the target help-seeking operation. The technical problem that the emergency rescue efficiency of the interphone in the ultra-low power consumption mode is low in the prior art is solved, and the technical effect of improving the emergency rescue efficiency of the interphone in the ultra-low power consumption mode is achieved.

The invention belongs to the technical field of low-altitude navigation safety monitoring, and particularly relates to a low-altitude navigation multi-source heterogeneous data adaptive fusion method for multiple scenes, which is a low-altitude navigation multi-source heterogeneous data adaptive fusion method for multiple scenes such as urban air traffic, low-altitude logistics and emergency rescue. Efficient integration of multiple types of monitoring data and position output of the trusted aircraft can be achieved, and accurate data support is provided for low-altitude navigation anomaly recognition and risk deduction. The method comprises the following specific steps: constructing a low-altitude navigation scene classification system and fusion demand mapping, collecting and preprocessing multi-source heterogeneous data, quantifying data credibility and resolving conflicts, constructing a hierarchical adaptive fusion framework and outputting a fusion result. According to the method, efficient and accurate fusion of multi-source data in different scenes is realized by constructing a layered scene adaptation framework and a credibility fusion model, and finally, a high-credibility aircraft position is output, so that reliable data support is provided for low-altitude navigation anomaly recognition and risk management and control.

The invention discloses a full-aviation life intelligent detection and emergency rescue decision-making method and system. The method comprises the following steps: dividing emergency rescue scene gridding partitions; identifying the disaster degree and the number of affected people; combining an identification result with the gridding partition map to form a red, yellow, blue and green post-disaster gridding partition map; a full-aviation transient electromagnetic method life detector, an optical personnel detection device and a microwave radar life detection device are sequentially adopted to carry out step-by-step detection on the potential affected area, and a final replacement result of red, yellow, blue and green gridding target marking is formed; determining the priority level of ground rescue entering search and rescue according to the gridding partition map and the final replacement result; searching and inputting rescue result information of ground rescue entering search and rescue, and forming box counting statistics of grid information; a rescue decision suggestion is automatically generated according to a box counting statistical result, and efficient cooperation with a ground rescue team is formed; the method can effectively overcome the limitation of a single detection method in complex terrains and extreme environments.

The invention discloses a perception and communication detection platform and method in a complex weak communication environment. According to the detection platform, a high-simulation multi-physical field coupling test environment is constructed by integrating a weak illumination perception mechanism and capability test module, an anti-interference communication mechanism and capability test module, a complex environment detection mechanism and capability test module, a data acquisition and analysis system, a multi-scene coupling controller and a full-experiment-area weak electromagnetic shielding case. The adaptive test efficiency of the unmanned system in weak illumination, strong interference and complex terrain environments is remarkably improved, the method can be widely applied to the fields of underground exploration, emergency rescue and intelligent inspection, and the field test cost and risk are reduced.

Disclosed herein are embodiments of an electric suction device for emergency airway obstruction removal and anti-choking, relating to the field of emergency rescue technology. One embodiment comprises a face mask, with an electric suction mechanism set on the surface of the face mask. The electric suction mechanism includes an oral support that is movably installed inside the face mask. The face mask is pressed tightly against the face and adjusted to form a sealed space. Activating the electric suction mechanism switch triggers the control circuit board to power the one-way suction module via the battery. This controls the one-way suction module to extract air, creating negative pressure in the sealed space.Consequently, the obstructing object is suctioned out of the airway due to continuous negative pressure. When the patient is unconscious or unable to cooperate, the oral support can be inserted into the patient's mouth to ensure that the patient's mouth is open and the device can be used. This device is easy to operate, safe and stable. The suction of this device can be controlled and there are different types of masks that can be configured to meet different people. It can be used independently by the patient without third-party assistance, or by a rescuer when the patient is unable to perform self-rescue.

The invention discloses a method for simulating the dam break flood process of an earth and rockfill dam containing upstream and downstream reservoir areas and application, DEM data is adopted as a calculation structure grid, breach evolution is achieved by updating the DEM data, and related formulas are established by considering factors such as seepage in the breach evolution. Iteration of each time step length is realized by adopting a mode of directly updating and calculating a grid DEM, a dam body area grid participates in model calculation, driving water depth and flow velocity values of breach evolution adopt corresponding water depth and flow velocity values obtained by directly calculating the last time step length at the breach, and changes of reservoir area water quantity are reflected through reservoir area water depth in each time step length. According to the method, the breach scouring and the upstream and downstream hydrodynamic processes are fully considered, the simulation precision and the calculation efficiency are improved, and powerful support can be provided for dam break prediction and emergency rescue.

The invention relates to an emergency rescue method and device based on driver health monitoring, a vehicle and a medium. The method comprises the following steps: acquiring real-time health state data and a current driving scene type of a driver in a vehicle driving process, and performing weight distribution on each monitoring dimension of the real-time health state data based on the current driving scene type to obtain a monitoring data group corresponding to the current driving scene type; determining a current alarm level under the condition that the driver is judged to be in a preset abnormal state based on the monitoring data group, and selecting a corresponding auxiliary driving strategy and a corresponding emergency rescue strategy based on the current alarm level and the current driving scene type; the current vehicle is controlled to run based on the corresponding auxiliary driving strategy, and / or emergency rescue is carried out on the driver based on the corresponding emergency rescue strategy. Therefore, the problem that traffic accidents occur due to the fact that the abnormal state of the driver is not monitored in time in the prior art is solved, and driving safety is improved.

The invention discloses a flood control and emergency rescue plan generation method, which comprises the steps of S1, collecting flood control and emergency rescue original data, performing preprocessing and feature extraction, and labeling and confirming extracted feature data to serve as a training set; s2, performing LoRA fine tuning of a low-rank decomposition matrix on the basis of a pre-trained large language model, and performing large language model training operation through the training set; s3, constructing a flood control and emergency rescue field ontology model, learning distributed representation of the knowledge graph by adopting a graph neural network technology, and dynamically updating the knowledge graph and executing reasoning query according to real-time dangerous case information by establishing a dynamic reasoning mechanism; and S4, constructing a multi-modal information fusion framework which is used for carrying out information fusion processing on the knowledge graph reasoning result and then guiding the big language model to generate an emergency plan as a control signal. According to the method, the technical bottlenecks of low plan generation quality, difficulty in knowledge updating, insufficient multi-source information fusion and the like of a traditional method in a complex dangerous case scene are effectively solved.

The invention discloses an emergency rescue data privacy protection and collaborative analysis system based on federated learning, and belongs to the technical field of emergency rescue data privacy protection and collaborative analysis. A dynamic trust evaluation module; the federated learning privacy protection engine module is used for realizing cross-domain data collaborative training by adopting a secure multi-party computing model; and the block chain intelligent contract module is used for deploying a data access control strategy and a credible auditing rule. According to the method, a global trusted environment is established through an end-side cloud three-level trust chain, the reliability of equipment is quantified through dynamic trust evaluation, data collaboration of privacy protection is realized through federated learning, an auditing strategy is automatically executed through an intelligent contract, an efficient encryption technology for guaranteeing safety and effectively reducing resource consumption is adopted, and the urban emergency data safety problem is solved.

The invention discloses an emergency rescue resource scheduling method based on the Internet of Things, and the method comprises the steps: collecting disaster area environment parameters, images and personnel distribution data through Internet of Things equipment, and associating historical disaster cases to construct a multi-source heterogeneous data set; extracting disaster characteristics through preprocessing, dynamically distributing data source weights, and generating a disaster assessment matrix; outputting a resource demand peak value based on the time sequence prediction model and performing dynamic correction; constructing a deep reinforcement learning model optimization decision strategy, and generating a scheduling scheme in combination with priority matching and an improved A * algorithm; according to the method, the disaster sensing precision and the demand prediction accuracy are improved, the scheduling decision adaptability is enhanced, the response time of a high-priority region is shortened, and the efficient demand of emergency rescue in a complex disaster is met.

The embodiment of the invention provides a dike breach blocking method and system, electronic equipment and a storage medium, and belongs to the technical field of automatic emergency rescue. The method comprises the following steps: performing virtual three-dimensional space reconstruction according to collected water surface flow data in a breach area to obtain a three-dimensional flow field model; performing target feature extraction on the three-dimensional flow field model to obtain a flow field feature matrix; a first target function is used as an optimization target, throwing decision optimization is carried out according to the flow field characteristic matrix, the regional throwing state data and the available material data, an optimal throwing scheme is obtained, and the first target function represents at least one of the minimum flow velocity energy or the minimum material loss amount; and carrying out transportation decision optimization according to the optimal throwing scheme and the transportation resource data by taking a second target function as an optimization target, so as to obtain an optimal transportation scheduling scheme, carrying resource scheduling is carried out according to the optimal transportation scheduling scheme, and the second target function represents maximum transportation efficiency. The dike breach plugging efficiency can be improved.

The invention discloses a field emergency rescue medical big data management system, and relates to the technical field of medical data management. The system comprises a data acquisition module, a data transmission module, a data storage module, an analysis processing module and a rescue decision support module, wherein the acquisition module acquires physiological and environmental data by using a multi-modal sensor array and performs edge preprocessing; the transmission module constructs a multi-link communication architecture and encrypts transmission; the storage module adopts distributed encryption and block chain storage; the analysis processing module combines depth migration and federal learning to mine data; the decision support module provides a scheme based on a knowledge graph and reinforcement learning, and VR / AR auxiliary decision is fused. The system comprehensively and accurately collects data, stably transmits and stores data in various field environments, deeply mines data values to assist in accurate decision making, supports remote cooperation, realizes functions of intelligent early warning, equipment management, authority control and the like, and comprehensively improves the medical efficiency and accuracy of field emergency rescue.

The invention relates to the technical field of emergency rescue resource scheduling, in particular to an annealing algorithm improved genetic algorithm-based resource scheduling scoring method, which comprises the following steps of: S1, pre-constructing a resource information database; s2, obtaining a final resource set meeting the emergency demand of the current user; s3, constructing a target function, generating a plurality of initial populations of the resource scheduling scheme, and performing global optimization calculation on the initial populations in combination with a genetic algorithm and a simulated annealing algorithm; and S4, obtaining an optimal resource scheduling scheme based on a global optimization calculation result. Through modular design and genetic algorithm optimization, high efficiency and applicability of resource scheduling are guaranteed, and the emergency rescue response speed and the resource utilization efficiency are remarkably improved. The genetic algorithm is combined with the simulated annealing algorithm, the resource scheduling scheme is quickly generated, the emergency response time is shortened, and the scheduling efficiency is improved; according to the genetic algorithm, advantages and disadvantages of a scheduling scheme are clearly measured through a fitness function, and quantitative indexes are provided to guide scheduling decisions.

The invention relates to the technical field of emergency linkage, and discloses an urban fire emergency linkage command system and method based on digital twinning, and the system comprises a multi-source heterogeneous data collection module which obtains the multi-source heterogeneous data of multiple departments in real time; the dynamic digital twinborn body construction module is used for generating a three-dimensional fire scene twinborn body with a unified space-time reference; the intelligent decision-making module is used for coupling a fire behavior diffusion prediction result of the fluid dynamic equation and a building risk prediction result of the finite element analysis model and generating a fire-fighting power dispatching instruction, a medical aid distribution instruction and a traffic control instruction; and the multi-department linkage execution module is used for sending a fire-fighting power dispatching instruction to the fire-fighting terminal, sending a medical aid distribution instruction to the medical terminal and sending a traffic control instruction to the traffic terminal so as to realize cross-department dynamic collaborative dispatching. According to the method, the emergency response speed and the decision accuracy are improved, efficient cooperation of urban fire emergency rescue is realized, and the rescue efficiency and the capability of coping with complex fire scenes are remarkably enhanced.

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 relates to the technical field of data mining, in particular to an elevator emergency rescue station site selection decision optimization method, system and device and a medium, and the method comprises the steps: obtaining elevator related data of a target area, and carrying out the preprocessing of the elevator related data; based on the preprocessed elevator related data, space density distribution of the elevators in the target area is extracted; constructing a quantitative evaluation model, and extracting a rescue difficulty quantitative result of the target area based on spatial density distribution; and constructing a site selection decision model based on stochastic programming, and solving an emergency rescue station site selection decision result. The invention aims to improve the rationality and rescue efficiency of site selection of the elevator emergency rescue station.

The invention discloses a simulation method for urban flood emergency rescue path planning, and the method comprises the steps: carrying out the modeling of an urban road network based on an urban topographic map, rainfall data, existing water distribution and key position information; mIKE simulation software is used for establishing a hydrodynamic model to simulate the rainfall and flood spreading process of the city, and flood dynamic information, including the depth and flow velocity of the flood, at each position point in the flood disaster scene model is obtained; respectively constructing objective functions according to the shortest maximum time of arrival of the disaster relief point, the lowest driving risk of the rescue vehicle and the shortest total weighted rescue time; setting constraint conditions to ensure that all disaster relief points are covered, and preventing vehicles from being excessively distributed; based on the flood dynamic information, the objective function and the constraint condition, adopting an NSGA-II non-dominated sorting genetic algorithm to solve a Pareto solution set; and performing weighted analysis on a result in the Pareto solution set to obtain an optimal solution, and outputting an urban flood emergency rescue path plan.

The invention relates to a cross-domain collaborative chain processing task decomposition and distribution method, which comprises a distributed intelligent planning architecture oriented to task decomposition and distribution, a dynamic knowledge injection mechanism of disaster situation awareness and a large language model and an HTN-MCTS algorithm based on absolute pruning. Emergency rescue theory excerpts and field professional knowledge are effectively integrated, dynamic task characteristics and resource conditions can be processed, and abstract task decomposition can be efficiently completed. The resource allocation is quickly and efficiently responded according to the urgency, advantages and disadvantages of the task and the danger level of the target under the high dynamic property. According to the method, full-right decisions from rapid decomposition and distribution of abstract cross-domain emergency rescue task requests to final formation of an end-to-end agile cross-domain rescue chain are realized, three major pain points of slow decisions, weak strain and poor collaboration of a traditional cross-domain rescue system are overcome, and a full-process second-level closed loop from task instruction receiving to rescue chain readiness is realized. And aiming at the problem that the resource search space is too large, the convergence speed is accelerated through absolute pruning, and agile disaster response is realized.