1458 results about "Emergency rescue" patented technology

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 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 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 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 discloses an emergency rescue real-time human body detection method and device based on time sequence motion feature enhancement, and the method comprises the steps: obtaining visible light and infrared image sequences of a rescue region and environment parameters (including smoke concentration and illumination intensity) in real time, and carrying out the spatial registration preprocessing; respectively carrying out frame difference processing on the two types of image sequences, generating a binary motion mask, calculating an optical flow amplitude, and carrying out adaptive fusion according to smoke concentration to obtain a multi-scale motion energy field; human body micro-motion frequency band energy is extracted through time-frequency transformation, a frequency domain dynamic attention mask is generated, and a saliency motion target area is extracted in combination with a multi-scale motion energy field; constructing a double-branch neural network, extracting time sequence motion features and multi-modal appearance features, dynamically distributing weights and fusing the weights, and outputting a human body bounding box and detection confidence; and calculating environment complexity according to the environment parameters, determining a dynamic confidence threshold, verifying a detection result by combining the average temperature of the human body bounding box region, and generating alarm information if a condition is met. The method aims at solving the problems that a traditional method is high in omission ratio and unstable in recognition in a complex environment.

The invention relates to the technical field of emergency rescue intelligent decision, and discloses an emergency rescue management system and method based on rescue timeliness. The method comprises the following steps: constructing a space-time three-dimensional grid by fusing multi-source information, and performing dynamic scene reconstruction by using a multi-level mapping rule to obtain preliminary and deep rescue scenes. And after combined anomaly diagnosis is carried out on the double scenes, a task topological structure is driven to dynamically evolve according to a diagnosis report, and a rescue task sequence is generated. And then cross-dimension resource adaptation is executed, a resource list is formed, key bottleneck nodes are predicted and identified in combination with real-time feedback, and finally a rescue instruction chain is generated. According to the method, deep fusion and structured analysis of field information in a space-time dimension are realized, a closed-loop decision-making mechanism with task and resource dynamic cooperation and adaptive optimization is established, and timeliness and overall toughness of rescue actions in a complex disaster environment are enhanced.

The invention discloses a multi-dimensional flood risk assessment method and system oriented to personnel, traffic and economy. The method comprises the following steps: acquiring multi-source data, and generating flood spatio-temporal evolution data through hydrodynamic simulation; constructing a time-dependent traffic network driven by flood power, wherein the road traffic capacity is dynamically attenuated along with hydrodynamic parameters; on the basis of a space-time racing mechanism, calculating the time difference between the personnel danger arrival time and the shortest evacuation time consumption, and constructing an evacuation time margin and evacuation success probability model so as to dynamically correct the static personnel exposure risk and obtain a personnel safety risk index; and in combination with physical state attenuation and asset exposure characteristics, traffic operation and economic loss risk indexes are calculated respectively, and multi-dimensional fusion evaluation is carried out. According to the method, the problem that dynamic interaction between flood routing and personnel evacuation is neglected in traditional static assessment is solved, accurate calculation of personnel trapped probability and critical road section rush-through marginal contribution is realized, and scientific decision support is provided for flood control command and emergency rescue.

The invention relates to the related field of a peacetime and urgency dual-purpose communication technology, in particular to an interphone peacetime and urgency dual-purpose dual-mode parallel communication method. According to the invention, dual-mode parallel communication is carried out through a private network emergency channel and short message communication of a Beidou satellite communication system, the two modes operate independently and do not interfere with each other, when one communication mode is limited, the other communication mode can continue to work, parallel transmission of voice and data is realized, the problem that single communication fails in a complex environment is effectively solved, and the communication efficiency is improved. The continuity and reliability of communication in an emergency scene are ensured, key information is ensured not to be lost, and the development of emergency rescue work is facilitated.

The invention discloses a mobile robot autonomous search navigation method based on a visual language large model. The method comprises the steps of receiving a natural language instruction of a user, and synchronously collecting an RGB image and a laser point cloud; two-stage visual language reasoning is adopted, and target semantic analysis and existence judgment are completed in sequence; when the target does not exist, autonomous exploration is executed based on the point cloud data and is parallel to target judgment, and an exploration-judgment closed loop is formed; after determining that the target exists, switching to a visual language navigation model, generating an incremental motion instruction, and guiding the robot to approach the target; target state monitoring is continuously carried out during navigation, if the target is lost, a dynamic backtracking mechanism is triggered, the robot is driven to return to the historical state of the recently confirmed target, and navigation is restarted. The method does not need to depend on a prior map, can execute efficient and robust autonomous search and navigation tasks on edge equipment through task collaboration, model quantification and state backtracking, and is suitable for complex scenes such as industrial inspection and emergency rescue.

The invention discloses an unmanned aerial vehicle group temporary communication network construction method based on visual self-organization. The method comprises the following steps: establishing an unmanned aerial vehicle node system and a security audit management system to realize flight control and message encryption exchange; airborne perception is realized through a visual candidate site identification system, and multi-modal data fusion and site scoring are carried out; domain autonomy and weighted election are realized by using a distributed voting and election system, and relay nodes are determined; scheduling, monitoring and self-adaptive reconstruction of a multi-hop path are completed based on a multi-hop relay and route maintenance system; and target detection, positioning and emergency document reporting are executed through the search and rescue positioning and situation return system. According to the method, voice and data links can be quickly recovered when ground communication facilities are damaged or unavailable, and under the condition of limited communication and energy, an unmanned aerial vehicle group can autonomously identify a safe position in a distributed manner and negotiate to establish a reliable multi-hop communication network, so that emergency rescue and positioning services are supported.

The invention relates to the technical field of emergency rescue, in particular to a movable emergency rescue conveyor which comprises a conveying truck, a hoisting machine is fixedly connected to the top of the conveying truck, a conveyor angle control seat is fixedly connected to the rear side of the top of the conveying truck, and a rescue conveyor is arranged on the front side of the conveyor angle control seat. According to the movable emergency rescue conveyor, by arranging the conveying truck, the hoisting machine, the conveyor angle control base and the rescue conveyor, rapid unfolding and flexible adjustment of the movable emergency rescue conveyor on a rescue site are achieved, and the movable emergency rescue conveyor can be accurately controlled through an electric push rod within a short time; lifting of the conveyor body and height difference adjustment among the conveyors are achieved, so that the material conveying requirements in different rescue scenes are met, meanwhile, the structural strength and stability of the conveyor in the unfolded state are ensured through the unique supporting structure design, and reliable guarantee is provided for rescue actions.

The invention belongs to the technical field of dike breach emergency rescue, and discloses a dike breach breach potential intelligent deduction and submerging probability visualization system and method and a medium. The engineering intervention deduction engine is constructed on the basis of a physically guided neural operator, takes a two-dimensional multi-physical reconstruction field containing pile body positions, material distribution, a flow velocity field and terrains as input, and directly outputs a water flow velocity-water depth physical field time history in a future time period; the online self-evolution engine is used for triggering fine adjustment of the model by comparing a deduction result with the deviation of real-time monitoring data; and the uncertainty quantification visual interface is used for dynamically displaying the deduction result in the form of a probabilistic submerging thermodynamic diagram. According to the method, a deduction framework integrating physical constraints and neural operators is created for the first time, the technical problems that traditional numerical simulation calculation is low in efficiency and pure data driving methods are physically inconsistent are solved, the unification of minute-level deduction speed and physical rule following is achieved, and real-time and reliable scientific decision support is provided for dike breach emergency rescue.

A method for previewing the terrain in front of an emergency rescue vehicle in a geometric feature degradation scene relates to the technical field of road surface recognition, realizes accurate alignment of LiDAR point cloud and IMU data through timestamp synchronization and linear interpolation, and combines a spherical projection model and a degradation perception complementary feature selection algorithm to realize the previewing of the terrain in front of the emergency rescue vehicle. Converting the three-dimensional point cloud into a robust intensity image and extracting gradient significant features; based on a double-observation secondary filter frame, a motion state is predicted by utilizing IMU forward propagation, a point cloud geometric residual error and an intensity image luminosity residual error are synchronously fused, timestamp deviation is compensated through back propagation, and a multi-source observation model under a global coordinate system is constructed. Finally, the error state is iteratively optimized to realize collaborative output of the high-precision odometer and the three-dimensional terrain map, and the problems of data asynchronism, feature degradation and dynamic interference in a complex scene are effectively solved.

The invention discloses an unmanned aerial vehicle rescue scheduling optimization method and device based on semantic translation modeling, and relates to the technical field of unmanned aerial vehicle emergency rescue intelligent scheduling, and the method comprises the steps: obtaining emergency rescue task description information; a natural language rule in the task description information is converted into a standardized constraint expression, and a response time target, a coverage range target, resource parameters and network structure parameters are recognized; constructing an initial scheduling model, and solving the initial scheduling model through an improved multi-objective optimization algorithm to obtain an initial scheduling scheme of the unmanned aerial vehicle; and when an interference event in the execution process of the initial scheduling scheme is detected, constructing a dynamic re-optimization model by taking the initial scheduling scheme as a disturbance reference, solving the dynamic re-optimization model by taking the scheme disturbance cost and the arrival late time as optimization targets, and outputting a repair scheduling scheme and an interpretable decision result. And the accuracy, the real-time performance and the decision credibility of emergency rescue scheduling are obviously improved.

The invention belongs to the field of unmanned aerial vehicle visual perception and intelligent control, and provides an unmanned aerial vehicle reinforcement learning target tracking method and device.According to the unmanned aerial vehicle reinforcement learning target tracking method and device, human body feature representation is reinforced through a dual-path fixed weight attention fusion module, and the detection precision of targets at different distances is optimized in combination with a multi-scale adaptive detection head; and meanwhile, direct mapping from visual detection to flight control is realized by adopting a depth deterministic strategy gradient algorithm. By reconstructing a target detection framework and deeply integrating a reinforcement learning control strategy, the end-to-end real-time control capability is realized on the premise of ensuring the tracking precision. Along with the wide application of the unmanned aerial vehicle technology in the fields of emergency search and rescue, security monitoring and the like, the intelligent tracking algorithm combining deep learning and reinforcement learning can be widely applied to the fields of disaster rescue, public safety and sports event shooting, and the autonomous tracking and intelligent decision-making ability in a complex scene is improved.

The invention relates to the technical field of emergency rescue, and discloses a cooperative control system for disaster sensing and emergency rescue. According to the system, a disaster situation sensing unit collects field data through a multi-mode sensor network and generates a real-time situation map; a rescue resource scheduling unit performs hierarchical coding on rescue resources according to the situation map, establishes a resource distribution thermodynamic diagram and performs superimposed analysis on the resource distribution thermodynamic diagram and disaster partitions; the multi-target decision-making unit receives the thermodynamic diagram and the situation map, generates a rescue task sequence through a priority algorithm and outputs a decision-making instruction set; the dynamic path planning unit performs topology reconstruction on a rescue path based on an instruction set, and generates an obstacle avoidance navigation path set in combination with terrain obstacle data; and the emergency response execution unit drives the rescue equipment to execute standardized operation according to the path set, and feeds back execution state data to the sensing unit to form closed-loop updating. According to the system, the whole-process cooperative control of disaster sensing, resource scheduling and rescue execution is realized.

The invention provides a road dangerous chemical transportation system risk coupling assessment method based on FRAM-ISM-NK, and belongs to the technical field of road transportation safety. Comprising the following steps: identifying functional composition of a dangerous chemical transportation system based on a functional resonance analysis method (FRAM), determining risk functional elements of three core stages of transportation preparation, accident occurrence and emergency rescue, and analyzing variability; constructing a hierarchical structure relationship of risk function elements of each stage based on an interpretation structure model (ISM), and determining an action hierarchical relationship and weight between the elements; quantifying a coupling relationship between risk function elements in different stages by combining an NK model, and revealing a risk coupling mechanism; and based on the analysis result, establishing a risk transfer quantitative model, and identifying key risk function elements and risk control paths in each stage. The system depicts the multi-stage risk factor coupling relation of road hazardous chemical substance transportation, quantitatively identifies the risk transmission path and the key control link, and provides effective technical support for improving the safety of the transportation system.

The invention provides a new energy automobile high-voltage accident grading response and emergency rescue operation guiding method and system, and is applied to the technical field of data processing. Multi-source data of voltage, current and battery states of a high-voltage system are collected, a standardized association sequence is generated after denoising, then the standardized association sequence is converted into a three-dimensional risk map, electric leakage, overvoltage and thermal runaway scenes are analyzed and subdivided through a fault tree, and a classified accident grading model is constructed. Extracting hazard weight factors to establish a dynamic evaluation matrix, and cooperatively calculating multi-source data to obtain key response indexes; parameters are extracted according to accident stages, response levels are divided, and a feature matrix is generated; real-time data and historical data are compared, and correction factors are generated by means of the accident curve slope. And in combination with vehicle types, architecture and environment grouping, key factors are screened by using a support vector machine, a personalized rescue model is established by fusing multiple constraints, and finally, a real-time graded response instruction and scene-divided rescue guidance are output.

The invention relates to a water surface floating type flying water pump system for large-flow long-time operation, and belongs to the technical field of special operation unmanned aerial vehicles and fluid conveying. The system integrates a multi-rotor flying platform, a buoyancy stabilizing device, a large-flow water pump module, a high-strength flexible water conveying pipeline and an intelligent control system. The core of the system is that the system can land on an open water surface, stable floating is achieved through the buoyancy stabilizing device, and a water inlet of the water pump module is submerged into water to directly pump water. By means of the floating water taking mode, the flying platform does not need to hover during operation, energy consumption is greatly reduced, ultra-long operation time is achieved, the limitation of the liquid carrying amount of the unmanned aerial vehicle is broken through, and continuous high-flow water pumping can be conducted through a high-power water pump. The system supports independent operation of a single device or networking collaborative operation of multiple devices, dynamically distributes water supply tasks, can be used as an aerial extension arm of a ground fire fighting truck, and is mainly applied to emergency rescue scenes such as high-rise building fire fighting and forest fire fighting.

The invention discloses an air-ground task intersection prediction method for emergency rescue, and belongs to the technical field of unmanned aerial vehicle control. In order to solve the problem of accurately predicting an air-ground task intersection with reachability and energy efficiency requirements, the method comprises the following steps: predicting an unmanned aerial vehicle path; predicting a ground vehicle path; generating candidate intersection points; calculating the time cost of the rescue task, the energy consumption cost of flight and the environmental risk cost; constructing a comprehensive cost function; constructing a confidence factor through the terrain height difference, the path node complexity and the communication shielding score, and carrying out risk correction on the comprehensive cost function to obtain a corrected comprehensive cost function; and introducing factors such as a ground slope angle, a wind speed value, a ground trafficability score and an unmanned aerial vehicle flight distance to carry out punishment correction, and extracting an optimal air-ground task intersection point coordinate for emergency rescue. The method is suitable for various emergency rescue, multi-platform cooperation and intelligent task scheduling, and has wide application prospect and popularization value.

The invention discloses a thermal environment and air quality self-adjusting intelligent emergency rescue cabin and method, and relates to the technical field of emergency rescue. The core of the method is that firstly, heat loss characteristics of the rescue cabin are learned through a simulated environment, and a standard loss rate is established; then, a target temperature interval is set, and based on comparison between the temperature loss rate monitored in real time and a standard value, hierarchical temperature control modes such as dormancy, low-power-consumption maintenance or dynamic balance are dynamically selected. Furthermore, by integrating vital sign monitoring, the target temperature can be dynamically adjusted according to parameters such as the core body temperature, blood oxygen and blood pressure of a patient, medical intervention modes such as active cooling and shock rewarming are started, and safe rewarming is achieved in the shock rewarming mode in the mode that a core area is heated through directional radiation. The system is also internally provided with a multi-rule priority arbitration mechanism. The cabin body comprises a sensor, an air conditioner, vital sign monitoring equipment and a directional heating plate. Unification of energy conservation, temperature stabilization and precise medical intervention is achieved, and the intelligent level and the safety guarantee capacity of emergency rescue are remarkably improved.

The invention relates to the technical field of wireless communication, in particular to a low-frequency special data link communication system fusing a central networking and an ad hoc network. According to the technical scheme, the system comprises a central networking communication module, an ad hoc network communication module, a special data link module, a low-frequency communication optimization module, a clock synchronization module and a fault self-healing module. Through dynamic cooperation of the central networking and the ad hoc network, low-frequency signal special optimization, industry customization of a special data link and multi-module cooperation of precise clock synchronization and efficient fault self-healing, the problems of incomplete communication coverage, easy transmission interruption, poor industry adaptability and high information security risk in a complex environment are solved; the system is large in communication coverage range, stable in operation and accurately adaptive to different industry scenes, meanwhile, the real-time performance and safety of data transmission are guaranteed, the scene requirements of emergency rescue, industrial control monitoring, remote area communication guarantee and the like are met, and the stability and reliability of communication are effectively improved.

The invention relates to the technical field of target positioning, in particular to a cross-view object-level geographic positioning method and system based on heterogeneous space contrast loss, and the method comprises the steps: inputting a query image and a reference image into a geographic positioning model, and obtaining the position of a target object in the reference image in the query image through the geographic positioning model; according to the geographic positioning model, a double-branch pseudo-twin network is adopted to extract global features of an input query image and local features of a reference image, fusion features are focused on a local area of a target object in feature fusion through space attention, and the position of the target object on the reference image is output by generating a prediction frame. And the geographic positioning model adopts a heterogeneous space contrast loss constraint model training process. According to the invention, the method achieves the precise positioning of the position of the target of interest through combining with the fine-grained features in the image, effectively improves the cross-view object-level geographic positioning precision, and provides technical support and position information support for the application fields of urban planning monitoring, emergency rescue scheduling and the like.

The invention provides a high-altitude phased array communication blind area electric power emergency unmanned aerial vehicle route planning method and system, and relates to the technical field of electric power emergency communication, and the method comprises the steps: 1, collecting environment data through a phased array communication device and an airborne environment perception sensor of an unmanned aerial vehicle, and constructing an environment information library; step 2, based on the environment information base, filling and boundary completion are carried out on irregular invalid areas in the polygon of the communication blind area, a continuous effective coverage boundary is formed, the dynamic communication blind area is identified and positioned, and communication characteristic parameters are extracted; and step 3, combining the communication characteristic parameters with preset phased array beamforming capability, unmanned aerial vehicle performance parameters and communication coverage requirements, and constructing a route planning model. According to the invention, the unmanned aerial vehicle can adaptively sense the change of a communication blind area in real time in a dynamic and complex power emergency rescue terrain environment, and the emergency response speed and the power emergency rescue efficiency are improved.

The invention discloses a heterogeneous communication network queuing time delay violation probability prediction method based on a yoke theory. The method is suitable for an emergency scene emergency communication system cooperatively constructed by an unmanned aerial vehicle and a high-altitude platform. The method comprises the following steps: modeling links from an unmanned aerial vehicle to a high-altitude platform and from the high-altitude platform to a ground command center in a communication network into a two-hop heterogeneous queuing service system; secondly, modeling a dynamic evolution process of data arrival and channel service by adopting a Markov Monte Carlo method; and finally, constructing a multi-hop heterogeneous network joint arrival-service yoke process based on a yoke theory, and deducing a violation probability boundary expression of end-to-end queuing time delay. The invention provides a time delay violation probability prediction method in cooperative emergency rescue communication of an unmanned aerial vehicle and a high-altitude platform. The service reliability of a system under given time delay constraint is accurately quantified.

The invention discloses an emergency rescue method and related equipment after a vehicle collision based on a mobile terminal, and relates to the technical field of automobile electronic technologies, and the method comprises the steps: determining a target feature value of a vehicle collision event based on real-time monitoring data of the mobile terminal in a vehicle; wherein the target characteristic value is used for representing the severity of the vehicle collision event; and executing a corresponding rescue action based on a preset level interval in which the target feature value is located. According to the method, whether the vehicle has the collision accident or not is detected and the accident collision level is determined only by using the data collected by the mobile terminal, so that corresponding rescue strategies are intelligently implemented based on different accident collision levels, and finally, the safety of a vehicle owner and passengers is protected, and the vehicle owner and the passengers are prompted and rescued in time.

The invention discloses a marine environment simulation and search and rescue formation method and system, and a computer program product, and belongs to the technical field of virtual reality technology and marine emergency rescue, and the method comprises the steps: designing a mixed data cleaning model of a space-time Kriging difference method and a long-short term memory network, and building a multi-modal dynamic environment database; establishing a marine meteorological data prediction model; combining the multi-modal dynamic environment database with the predicted marine meteorological data model to generate a dynamic marine environment; establishing a multi-agent training framework, and constructing a search and rescue formation strategy; and designing a hybrid planning model of a fast random tree algorithm and a long-short term memory network, realizing real-time path planning and path correction, and adjusting a search and rescue formation strategy according to the real-time path planning and path correction result. According to the invention, the problems of scene staticization and decision experience in traditional search and rescue training are solved, and the environment simulation precision, dynamics and decision accuracy are improved.