3311 results about "Emergency situations" patented technology

An Internet-of-Things-based intelligent safety monitoring method and system for power plant operation. The method comprises: deploying sensors and collecting monitoring data in real time; transmitting the collected data to a central server, performing data processing, integrating the monitoring data, calculating a comprehensive environmental index, and preliminarily assessing an environmental monitoring condition; and comprehensively determining a device fault condition, remotely monitoring device status, starting a device emergency response mechanism, and performing intelligent safety monitoring of power plant operation. Power plant devices and environment parameters are monitored in real time, so that device anomalies and potential safety hazards are promptly captured to achieve rapid response. The stability of the power plant is improved, and a video monitoring system is integrated in combination with image recognition technology to monitor anomalous events in the power plant area. The level of safety management is enhanced, and decisions can be quickly made in emergency situations, improving flexibility and efficiency and enhancing management effectiveness and the accuracy and stability of the monitoring system.

The invention relates to the technical field of communication command, in particular to an intelligent emergency command system and method based on scene twinning. Comprising a data acquisition module, a scene twinborn management module, an emergency situation analysis module, an emergency response decision module and a resource scheduling command module. Multi-source data of an emergency scene are collected through a sensor network, a scene twinning model is constructed by using augmented reality and digital twinning technologies, and real-time rendering of a virtual scene is realized. According to the method, emergency situation analysis, risk detection and trend prediction are performed in combination with a random matrix theory and a graph neural network algorithm, an emergency response strategy is generated by using a decision tree based on an analysis report, resources are scheduled and allocated through a multi-objective optimization algorithm, and an optimal emergency command scheme is ensured. According to the invention, the efficiency and scientificity of emergency command are improved, and the rapidity and accuracy of emergency response are enhanced.

The present invention discloses a disaster prevention, early warning and production decision support method and system for a power distribution network, and relates to the technical field of the power distribution network. Various data is fused, a maximum wind load, a lightning trip-out rate, a maximum carrying capacity at a highest operation temperature and an average failure frequency and time under an environmental factor are calculated, and a power outage risk is evaluated and classified; and after an emergency, a power grid topology is analyzed, and a device outage probability is calculated to obtain a load power outage probability and risk and provide disaster early warning, monitoring and rush repair decision support.

The invention relates to the technical field of structure health monitoring, in particular to a basement prestress bottom plate health monitoring system based on the internet of things, which comprises a stress distribution analysis module, a defect diffusion analysis module, a damage characteristic evaluation module and a safety monitoring evaluation module. According to the method, accurate stress data collection and real-time monitoring are realized by capturing spatial position information and node stress values, so that stress change is carefully tracked and evaluated, stress conduction and edge weight between monitoring points are analyzed, the internal stress distribution state of the structure is accurately revealed, the defect diffusion range and path are simulated, and the damage trend is predicted in time; according to damage characteristic evaluation, through analysis of stress mutation and material strain, key data support is provided, maintenance decision making and maintenance plan optimization are effectively guided, threshold value classification and early warning implementation of safety monitoring evaluation are effectively guided, the recognition capacity of an overproof stress concentration area is improved, and the reliability of the system is improved. And the overall safety and stability of the structure are ensured.

The invention discloses a Beidou short message communication transmission method applied to the electric power field, relates to the technical field of electric power communication, and aims to solve the technical problems that the current communication transmission technology cannot meet the communication transmission requirements of electric power equipment under extreme conditions and cannot ensure that key information is preferentially transmitted in an interfered environment under emergency conditions. Comprising the following steps: communication guarantee and short message communication in a non-signal area: installing a high-performance Beidou short message communication module for power equipment in the non-signal area such as a mountainous area and a depopulated area, monitoring the running state of the equipment in real time through the high-performance Beidou short message communication module, and periodically sending parameter information to a monitoring center; according to the method, communication guarantee is provided for the power equipment in the non-signal area by taking the power equipment as a relay node, short message transmission is optimized after a natural disaster occurs and in a special scene, smooth communication is guaranteed, and priority transmission of key information in an interfered environment is guaranteed in an emergency.

The invention belongs to the technical field of aircraft navigation, guidance and control, and provides a satellite exploration control system and method based on deep reinforcement learning, and the system comprises a sensing layer, a decision layer, and an execution layer. The sensing layer is used for integrating equipment data and performing primary processing; the decision-making layer is used for deploying a deep reinforcement learning model and regularly carrying out data training and model updating; the execution layer is used for controlling satellite attitude and orbit adjustment and performing autonomous fault diagnosis and recovery operation; according to the method, effective control under different environments and emergencies is realized through continuous learning and optimization, the adaptive capacity and the autonomous control capacity are relatively high, and an efficient and accurate control strategy can be realized in a complex and changeable space environment through gradual optimization and iteration, so that the method is suitable for large-scale popularization and application. And the autonomous operation capability and the task execution efficiency of the satellite are greatly improved.

The invention discloses an industrial environment information wireless monitoring system based on the Internet of Things and a control method thereof, and relates to the technical field of industrial management, and the system comprises an intelligent edge calculation module, a data visualization module, a self-healing network management module, a precise energy consumption management module, an environment anomaly detection module and a wireless network optimization module. According to the industrial environment information wireless monitoring system based on the Internet of Things and the control method thereof, real-time analysis and decision are realized at a data source by using an intelligent edge computing module, data transmission delay is reduced, response can be quickly made in an emergency, potential faults are predicted through a time sequence abnormity self-learning network model, and the monitoring accuracy of the industrial environment information wireless monitoring system based on the Internet of Things is improved. And network self-healing is actively carried out before a problem occurs, so that the network downtime is effectively reduced. In addition, due to the introduction of a low-power-consumption ad hoc network protocol, the energy consumption optimization management of the sensor nodes is realized, and the service life of equipment is prolonged.

The present invention relates to an automated driving system for switching between automated driving mode and manual driving mode in an automated driving situation, and a fallback method for an automated driving failure situation in the automated driving system. According to the present invention, the method comprises the steps of predicting whether, on a route a vehicle is traveling, the vehicle will deviate from an operational design domain (ODD) in which automated driving is possible; and when deviation is predicted, performing a minimal risk maneuver (MRM) process for controlling the vehicle to respond to an automated driving failure situation at a deviation point. According to the present invention, the stability of the automated driving system in emergency situations may be increased, and by proposing a stable mode-switching method for the automated driving system, the best response method may be provided.

The present invention relates to an intelligent, context-aware battery management system embedded within a mobile device that dynamically allocates power resources based on real-time user behavior, system state, and environmental context. It incorporates a smart recognition engine that analyzes sensor-derived telemetry data to compute behavioral deviation scores, enabling the system to anticipate abnormal or emergency-prone conditions. A continuous activity classification module contextualizes user motion and geolocation to inform power policy decisions. Upon detecting significant behavioral anomalies or critically low battery conditions, an emergency mode subsystem is triggered, restricting device operations to essential functionalities while preserving energy for critical communication and navigation tasks. The system also establishes a secure, lightweight emergency communication tunnel for relaying essential metadata, including GPS and behavioral indicators, to predefined response servers.

The invention relates to the technical field of path planning, in particular to a multi-unmanned aerial vehicle oil depot storage tank inspection intelligent optimization method based on a layering strategy. The method comprises the following steps: constructing an equivalent terrain mathematical model according to oil depot storage tank characteristics, and establishing a multi-objective optimization objective function; performing global path planning inspection of multiple unmanned aerial vehicles by using an improved wolf pack optimization algorithm; abnormities are monitored through a carried sensor, and abnormal information is uploaded to a terminal; the terminal issues the target abnormal point to the single unmanned aerial vehicle; performing single-machine local path optimization by adopting an improved particle swarm optimization algorithm; and updating the state of the inspection task. According to the method, global path planning and local path optimization are effectively combined through a layered inspection strategy, the defects of a traditional method in inspection full coverage and local emergency response are overcome, the intelligent and efficient level of an unmanned aerial vehicle inspection system is improved, and the method is suitable for complex oil depot storage tank inspection tasks and emergency disposal scenes.

The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle task automatic planning and situation display system based on artificial intelligence. Comprising a task demand identification and priority dynamic adjustment module, a multi-task path optimization module, a multi-dimensional situation awareness and data fusion module, a three-dimensional situation display module, a task dynamic adjustment and feedback control module, a task data storage and historical analysis module and an emergency task response and environment interference adaptation module. By collecting task requirements and environment parameters in real time, the system can dynamically generate a task priority queue and optimize path planning based on priorities, it is ensured that the unmanned aerial vehicle has efficient response ability when executing tasks such as reconnaissance, monitoring, searching and rescue, the system combines a multi-source data fusion technology, the three-dimensional situation of the task environment is displayed in real time, and the system has good application prospects. Visual support is provided for decision making; the self-optimization capability and the adaptability to emergency situations lay a foundation for long-term intelligent development of unmanned aerial vehicle tasks.

The invention provides an intelligent traffic dynamic green wave control method and system, a storage medium and a program product, and relates to the field of traffic control systems.The method comprises the steps that real-time traffic data of all lanes and emergency data published by a traffic management department are obtained; obtaining traffic flow prediction results of different directions of each road section in a future preset time based on a neural network model; outputting the congestion level and the congestion duration of each road section in combination with the emergency situation data and a traffic flow theoretical model, and further determining an adjustment sequence; and on the basis of the traffic flow prediction result, calculating the optimal green wave bandwidth of the signal lamp at each intersection in each target road section by using a particle swarm optimization algorithm to obtain an optimal timing combination scheme of the signal lamp in each target road section, and performing real-time timing control. By implementing the method, the traffic flow can be dredged more efficiently, the parking frequency and delay time of vehicles on the road are reduced, the overall traffic capacity of the urban road is improved, and energy consumption and environmental pollution are reduced.

The invention discloses a power distribution system and method for a modular power supply, and aims to optimize power distribution through an intelligent means, improve the operation efficiency and stability of the system, and control a unit to check the states of all power supply modules, and evaluate the required total power output according to the load demand. Then, based on the capability of each module and a redundancy planning principle, an appropriate module combination is selected to meet the load requirement, and necessary voltage or current adjustment is carried out to ensure stable power supply. In the operation process, the control system continuously monitors the state and the overall performance of each module, and once a fault or an abnormal condition is detected, measures such as automatic switching to a standby module are taken immediately, so that the continuity and the safety of the system are ensured. In addition, through analysis and learning of historical data, the system can continuously optimize a power distribution strategy, and efficiency and reliability are further improved. And the ability of the system to deal with emergency situations is also enhanced.

The invention relates to the technical field of space governance, and discloses a multi-agent space collaborative governance method which comprises the following steps: processing multi-source heterogeneous data such as satellite images and sensor readings, establishing cross-type semantic association through a geographic space data embedding technology, generating a unified structured text after optimizing the satellite images through vLLM, and synchronizing the unified structured text to a central database; an agent role portrait is dynamically generated by the central server large language model based on a preset Prompt template, and generation does not depend on a fixed rule; then, selecting a target node in the edge-center architecture, disassembling a total task into sub-tasks, establishing semantic mapping, calculating a matching probability, and performing optimal distribution by a reward borrowing function; generating a governance scheme in a perception layer-decision layer-execution layer framework, and outputting a coded operation instruction; based on an execution feedback updating strategy, a multi-level mechanism is set, roles are automatically redistributed, and the governance continuity is guaranteed. According to the invention, the overall efficiency and reliability of space governance can be improved in the face of dynamic scenes or emergency situations.

The present invention relates to a warning system and in particular to a warning system that is movable to a monitoring zone. The invention has been developed primarily for use for early notification of danger by approaching vehicles to a monitored zone such as an emergency in an emergency lane of a roadway. The warning system of the invention comprises at least two forms of detectors for detecting and tracking vehicles and obtaining characteristics of the tracked vehicle relative to the monitored zone a determinator for receiving the characteristics of the tracked vehicle relative to the monitored zone and assessing the expected relative impact of the vehicle on the monitored zone and an alarm system for providing an alarm action according to a predetermined danger of the assessed expected relative impact of the vehicle to the monitored zone.

The invention discloses an intelligent traffic data processing method and system based on a 5G communication system, and relates to the technical field of traffic data processing, and the method comprises the steps: collecting data based on a 5G communication network; preprocessing the collected traffic data through an edge computing node; real-time prediction and risk assessment are carried out on traffic flow based on the cloud platform; sending real-time traffic information and optimization suggestions to a traffic management center and related vehicles; when an emergency occurs, a rapid response mechanism is triggered through a 5G network, and traffic resources are scheduled. The system collects, processes and analyzes traffic data in real time through the characteristics of high bandwidth and low delay of the 5G communication network and the distributed processing capability of edge calculation, achieves the real-time prediction and management of traffic flow and accident risks, and can improve the road utilization efficiency, reduce traffic accidents and improve the traffic safety through the intelligent decision and optimization control strategy. And the emergency response capability is improved, so that a more intelligent solution is provided for urban traffic management.

The invention discloses a park safety operation and maintenance management method based on a digital twinborn technology, and relates to the technical field of park safety operation and maintenance management, and the method comprises the following steps: S1, obtaining park information which comprises park structure information, environment information and real-time operation and maintenance data; and S2, constructing a digital twinborn model of the park based on the obtained park structure information. According to the park safety operation and maintenance management method based on the digital twin technology, the conditions after different emergency measures are implemented are simulated, and different evacuation routes and guide modes are simulated for multiple times to evaluate the advantages and disadvantages of the scheme, so that the optimal evacuation scheme is selected, the safety of personnel in an emergency is improved, and the safety of the personnel is improved. The response efficiency and effect when the security event occurs are improved, so that the security event can be timely and effectively controlled when the security event occurs, and greater loss is avoided.

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 discloses a multi-sensor fusion unmanned aerial vehicle environment monitoring and early warning system, and relates to the technical field of environment monitoring and early warning, and the system comprises the following components: an unmanned aerial vehicle platform which is used as a carrying basis of sensors and data processing equipment and has excellent flight stability and strong cruising ability; according to the invention, by introducing a task planning mechanism based on autonomous learning, the unmanned aerial vehicle can continuously learn and optimize the flight strategy when executing the monitoring task, the innovation point significantly improves the efficiency of task execution, and the unmanned aerial vehicle can perform real-time monitoring according to the actual environment feedback and historical task data. The unmanned aerial vehicle can automatically adjust the parameters of the flight path, speed and height to avoid adverse factors and select the optimal path, and meanwhile, the unmanned aerial vehicle is endowed with strong scene adaptability by the autonomous learning ability, so that the unmanned aerial vehicle can quickly respond to a complicated and changeable natural environment or a sudden emergency, and smooth completion of a task is ensured.

The invention discloses a comprehensive transportation junction emergency scene simulation deduction system based on digital twinning, which relates to the technical field of digital simulation and comprises a data processing unit, a simulation deduction unit and a visual display unit, the data processing unit is used for acquiring emergency scene basic data of the target digital twin comprehensive transportation hub, performing multi-source integration on the basic data and constructing a model data environment; the simulation deduction unit calls a simulation deduction algorithm to construct a simulation deduction algorithm model according to the emergency scene model data, and carries out emergency situation deduction and scheduling processing based on the simulation deduction algorithm model; and the visual display unit is used for carrying out distribution management on user permissions, carrying out deduction data plotting based on GIS map basic information, and carrying out query and visual display on the deduction data according to a query instruction of a user. According to the method, a digital twinborn platform is built based on a simulation deduction algorithm model and dynamic data, so that the deduction process is more accurate, and visual display is realized in combination with GIS map data.

The invention discloses an emergency situation intelligent decision-making method, device and system based on deep learning, and the method comprises the steps: firstly collecting multi-modal data of an affected area, carrying out the fusion processing of the multi-modal data into a unified embedded vector, carrying out the time and space dimension feature extraction of the unified embedded vector through a space-time perception neural network, and constructing a state sequence containing a space-time evolution characteristic; constructing a dynamic causal graph based on the sequence to identify a potential causal relationship, and predicting a future emergency situation development trend according to the potential causal relationship; and finally, generating an emergency decision strategy accurately adaptive to the actual condition of the affected area in combination with historical disposal experience and the current resource constraint condition. According to the invention, accurate perception of disaster situations, evolution prediction and intelligent decision generation under resource constraint can be realized.

The invention relates to the technical field of path planning, and discloses a path planning method and system of an AGV (Automatic Guided Vehicle) for a silver electrolysis process workshop. The method comprises the following steps: carrying out environment characteristic acquisition and electronic map construction on a silver electrolysis process workshop to obtain a silver electrolysis process workshop electronic map; calculating an initial optimal path of the AGV from the current position to the target workstation; detecting the actual driving resistance in the execution process of the initial optimal path to obtain a path correction parameter; performing local adjustment to obtain an energy-saving safe path; and in the process that the AGV executes the energy-saving safe path, the front moving obstacle and the electrolyte leakage area are monitored in real time, and a temporary detour path is generated. According to the application, the path planning is more suitable for the actual environment characteristics of the silver electrolysis workshop, the emergency situation of the silver electrolysis workshop can be timely handled, the equipment safety and the production continuity are guaranteed, the no-load rate of the AGV is reduced, and the overall logistics efficiency of the silver electrolysis workshop is improved.

The invention relates to the technical field of remote control, in particular to an intelligent device remote cooperative control method and system based on the Internet of Things, and the method comprises the following steps: monitoring and adjusting the CPU utilization rate and memory usage of an intelligent device based on an Internet of Things platform, optimizing the data collection and network resource distribution, and improving the intelligent device remote cooperative control efficiency. By analyzing equipment performance and a network load balance index, equipment connection priority ranking and task load management are realized, and task execution and connection frequency is dynamically adjusted, so that real-time task requirements are met, and system efficiency is improved. According to the method, the performance index of the equipment is monitored in real time, the data transmission interval is dynamically adjusted, the data processing speed is remarkably increased, resource waste is reduced, efficient use of network resources is ensured through real-time load analysis and optimization of network nodes, the problem of data delay caused by network congestion is avoided, and in the aspect of equipment connection management, the data transmission efficiency is improved. An intelligent priority decision mechanism allows the key device to quickly access the network in an emergency.

The invention belongs to the technical field of power distribution network equipment, and relates to an interlocking device with an emergency unlocking function and an environment-friendly ring main unit, and the interlocking device comprises an isolation interlocking assembly, a circuit breaker interlocking assembly and a chamber door interlocking assembly. The isolation interlocking assembly comprises an isolation interlocking plate, and one side of the isolation interlocking plate is provided with a shielding part; the circuit breaker interlocking assembly comprises a closing interlocking group which is arranged on the isolation interlocking plate and is used for locking and unlocking a closing release in the ring main unit; the chamber door interlocking assembly comprises a chamber door interlocking piece suitable for movably unlocking a cable chamber door on the ring main unit; the chamber door interlocking piece is provided with a rod abutting part connected with the chamber door interlocking piece through a fixing bolt. The protection functions that the circuit breaker cannot be switched on first when the disconnecting switch is switched off, the grounding switch is switched on in an electrified mode after the circuit breaker is switched on, and a cable chamber door cannot be opened when the circuit breaker is switched on are achieved through interlocking. And meanwhile, under the emergency condition of interlocking failure caused by interlocking clamping stagnation or other unforeseen circumstances, the fixing bolt can be disassembled to unlock and open the cable chamber door emergently.

A coupling device for conveying cryogenic fluid which is separable in the event of an emergency and is automatic-closing, the device comprising: two pipes for conveying fluid that extend in a longitudinal direction and each comprise, at a connection end, a valve mechanism that is configured to automatically close the pipe when the connection ends are separated and to allow the pipe to open when the connection ends are coupled; an outer tube that is arranged around each conveying pipe and defines an evacuated space for thermally insulating the conveying pipe; a quick-connection mechanism for quickly connecting the two pipes which comprises cooperating mechanical fastening members that are located at each of the two connecting ends, respectively; an emergency separation system that is configured to allow the two pipes to be separated when the connection ends are coupled via the quick-connection system, wherein the emergency separation system is located at a connection end of a first pipe and comprises a set of connecting parts that are movable between a first configuration, which provides a rigid mechanical connection between the connection end that is equipped with one or more fastening members of the first pipe and the rest of the first pipe, and a second, split configuration in which the connection end of the first pipe that is equipped with one or more mechanical fastening members of the quick-connection mechanism is separated from the rest of the first pipe.

A system for protecting occupants of a vehicle during aa catastrophic event includes at least one safety pod that encloses one or more seats within the vehicle. The pod is constructed of a material that is fire proof, waterproof, bomb proof, crash proof, and / or capable of withstanding any other physical or environmental hazards that might be expected during the catastrophic event, and includes a sliding, electrically powered doors that seals the pod when closed. The pod may be configured to be ejected from the vehicle when the catastrophic event occurs or is imminent. When the vehicle is a passenger airplane, pods may be provided for each row of passenger seats, the pods being mounted to tracks by brackets and latched in a stationary position until an emergency occurs. When an emergency that requires ejection from the airplane occurs, the pods are propelled towards the rear of the airplane, and at least a portion of the rear section of the airplane is detachable to provide a space through which the pods are ejected. Sealing of the pods protects the occupants from hazards such as fire and smoke, and provides a waterproof flotation chamber in case of ejection over water.

The invention discloses a UWB-based multifunctional integrated vehicle-mounted safety control method and system, and the method comprises the following steps: collecting the dynamic environment data around and in a vehicle in real time based on a plurality of sensors, carrying out the path adjustment and driving mode optimization through generating a multi-level three-dimensional environment model, and carrying out the control of the driving mode. The system performs risk assessment and dynamic adjustment by using external data such as obstacles, road conditions, weather and the like collected by a sensor and combining a behavior mode of a driver and a health state of a passenger, and in a collision prediction and protection mechanism, the system gradually activates a protection system by analyzing factors such as vehicle speed and acceleration, so that the safety is guaranteed, and the safety is ensured. The system optimizes the energy distribution of a key system through an energy scheduling model, improves the energy efficiency, and preferentially guarantees the operation of a safety system in an emergency. According to the invention, a self-adaptive learning algorithm and a multi-scene optimized driving assistance function are integrated, and self-adaptive adjustment and safety control of the vehicle in different driving environments are realized.

An integrated system for detecting dam breaches, as an early warning system and for evacuation assistance, consisting of: A geoinformatics analysis module comprising a modeling processor with a graphics processing unit, configured to: analyze spatial, hydrological, and topographic data of a dam and its downstream area; generate hydrological models using probable maximum rainfall (PMP) data to determine probable maximum flood discharge (PMF); generate hydraulic models to simulate flood propagation and determine flood depth, flood extent, flow velocity, and flood arrival time; create flood vulnerability models, vulnerability models, and flood hotspot models using a multi-criteria decision-making (MCDM) framework; and generate evacuation plans for high-risk zones based on the models. A sensor monitoring subsystem includes: a distributed fiber optic sensor (DFOS) configured to monitor the structural load and deformation of a dam, and a radar level gauge configured to measure the water level in the reservoir; a microcontroller unit configured to receive and process sensor data from the sensor monitoring subsystem, to detect dam breaches based on abnormal structural movements detected by the DFOS or sudden drops in water level below predefined thresholds detected by the radar level gauge; a communication module configured to transmit warning messages when dam breaches are detected; a warning system configured to: send SMS notifications to residents in downstream high-risk zones via a GSM communication module, generate real-time alerts via an IoT platform on user devices, and activate siren systems in villages to issue loud alarms and voice announcements; and an evacuation assistance platform configured to provide real-time evacuation assistance in emergencies due to dam breaks, displaying site maps with nearby emergency shelters, evacuation routes, hospitals, government buildings and aid centers, showing hydrological layers including flood extent, water depth, flow velocity and arrival time of the water, and enabling real-time location tracking in relation to safety zones and flood-prone areas.

The invention discloses an intelligent emergency control system of an arrangement ship steering oar, and belongs to the technical field of arrangement ship steering oar control. An intelligent emergency control system of an arrangement ship steering oar comprises a main control module, a steering oar driving module and a steering oar control module. The problem that in the prior art, when a main steering system breaks down, a ship is prone to being out of control, colliding or other safety accidents are caused is solved, the steering oar driving module is used for conducting driving operation on the arrangement ship steering oar in an emergency mode, the state of the arrangement ship steering oar is monitored in real time, and the safety of the arrangement ship steering oar is improved. When potential problems and fault trends exist in the arrangement ship steering oar, a control instruction of the arrangement ship steering oar is adjusted so as to ensure safe operation of the arrangement ship steering oar, quick response can be made and an emergency mode can be started in emergency, dangerous situations such as out-of-control of the ship can be effectively avoided, remote monitoring and management can be achieved, and the safety of the arrangement ship steering oar is improved. Safety and management efficiency of the ship are improved, and safe driving of the ship is effectively guaranteed.

The invention discloses a travel emergency state judgment method and device based on semantic analysis and a storage medium, and relates to the technical field of classification models. Comprising the following steps: extracting speech characteristic parameters such as speech speed, volume, speech signal spectrum entropy and the like by collecting speech data of an independent user with known emotion and target intention, and calculating a speech judgment coefficient; and based on the voice text data, performing voice recognition by using a knowledge perception network model, and generating a danger feature comprehensive vector. And using the vector to train a neural network model, taking the danger feature comprehensive vector as input, and predicting a corresponding emotion and a target intention. And monitoring voice data of the independent user in real time, obtaining a corresponding danger feature comprehensive vector, calculating a comprehensive emergency state judgment index by combining the voice judgment coefficient and the environment data, comparing the index with a risk threshold value, and outputting an emergency state instruction. The method can effectively predict the emergency situation of the user in travel, and provides support for safety emergency.