466 results about "Command center" patented technology

The invention discloses a forest fire detection and disappearance method and system, and relates to the technical field of forest fire prevention and data processing, and the method comprises the steps: carrying out the fire inspection of a planned forest region through a plurality of inspection unmanned planes, and transmitting an image and airborne sensor data back to a command center in real time; identifying a fire behavior by using an artificial intelligence method, and performing fire behavior judgment and fire hazard grade division; the command center screens fire points according to the thermal images and updates the positions of the fire points in real time; the fire scene spreading trend is judged according to the returned data, and a basis is provided for the dispatching task of throwing the fire extinguishing bombs by the fire extinguishing unmanned aerial vehicle; using an MAPPO multi-agent reinforcement learning algorithm to train an optimal dynamic fire point collaborative disappearance regulation strategy; and after the open fire is extinguished, the inspection unmanned aerial vehicle continues to inspect to identify a re-ignition point or a smoke point, and secondary large-area fire is prevented. According to the method, efficient collaborative fire extinguishing, dynamic environment adaptation and resource optimization configuration can be achieved, and robustness is kept when part of intelligent agents fail.

The invention relates to the technical field of unmanned aerial vehicle assistance, and discloses an unmanned aerial vehicle assisted fire scene real-time monitoring and commanding method, which comprises the following steps: acquiring fire disaster situation data of a fire scene in real time through equipment such as a high-definition camera and a red thermal imager of an unmanned aerial vehicle, and outputting the fire disaster situation data to a commanding center; analyzing the fire behavior development direction, the fire source position and the smoke concentration of the fire disaster situation data; evaluating a fire scene scale and a dangerous area according to an analysis result, forming a rescue scheme according to an evaluation result, and commanding firefighters and a fire extinguishing unmanned aerial vehicle based on the rescue scheme; dynamically adjusting a rescue scheme according to the fire disaster situation data of the fire scene collected by the unmanned aerial vehicle in real time; when the fire is extinguished, the blind fire area is continuously monitored, and if abnormity occurs, an alarm is given out immediately; the unmanned aerial vehicle serves as an air base station for communication. According to the invention, instant and comprehensive fire scene information is provided for a command center, and rapid decision making is facilitated.

The invention discloses an event early warning efficient management method and system based on park management, and relates to the technical field of safety management, and the method comprises the steps: constructing a hexagonal cellular unit layout, generating an equipment registry and a network topology structure, and forming a structured data set through data alignment and sliding window verification; the edge server loads an initial weight, calculates a dynamic weight matrix based on the LSTM network, and generates a high-order feature vector set in combination with the graph neural network; inputting the high-order feature vector set into a space-time prediction model to generate an environment evolution trend prediction value, fusing network topology and BIM model parameters to calculate a dynamic risk index, and triggering graded early warning; the command center analyzes the early warning signal to generate a fusion visual interface, historical cases are matched through federal learning, a resource allocation scheme is optimized, and an optimal disposal strategy is output through Monte Carlo simulation. By dynamically adjusting the weight of the sensor, the weight of the infrared sensor in the high-temperature-sensitive area is increased, and the abnormality capturing efficiency is improved.

The invention discloses a multi-mode city security video abnormal behavior real-time detection system and method, and belongs to the technical field of artificial intelligence and city security, and the system comprises an edge node module which is used for collecting a local video stream and sensor data, and executing local model training and real-time abnormal detection; the central coordination server module is used for federal model parameter aggregation, global model distribution and dynamic resource coordination; the multi-modal data fusion module is used for realizing cross-modal feature fusion through space-time alignment and an attention mechanism; the dynamic federation strategy module is used for calculating a load and a network state according to an edge node and adaptively adjusting a model parameter aggregation frequency; and the alarm linkage module triggers a local sound-light alarm when an abnormal behavior is detected, and encrypts and transmits event information to a command center. According to the method, the problems of privacy leakage, bandwidth pressure and multi-modal data collaboration in the prior art can be solved, and on the premise that data privacy is guaranteed, calculation overhead is minimized, and heterogeneous equipment is adapted.

The invention relates to the technical field of unmanned aerial vehicle scheduling, and discloses an emergency scene unmanned aerial vehicle task allocation method based on multi-objective optimization, and the method comprises the steps: obtaining a task parameter set of an unmanned aerial vehicle in real time through a standardized task interface, and obtaining a state data set of the unmanned aerial vehicle in real time through an unmanned aerial vehicle management platform; secondly, calculating an optimal task allocation scheme by adopting a multi-target particle swarm optimization algorithm and an improved PSO algorithm, and dynamically adjusting sudden emergency tasks and priority changes in combination with a task preemption mechanism; three task allocation plans including a time optimal scheme, a resource optimal scheme and a parameter optimal scheme are provided to ensure that tasks can be completed in the shortest time or executed at the lowest cost, and the final scheme is provided for a command center for decision making. According to the invention, the intelligence and flexibility of unmanned aerial vehicle scheduling are improved, and rapid response and global optimal resource configuration of unmanned aerial vehicle scheduling in an emergency scene are realized.

The invention discloses a multispectral satellite fire prevention method and system based on data identification, a multispectral satellite optical sensor array scans a target area for 30 minutes, the acquisition precision is guaranteed through a high-precision attitude system and a formula to obtain data, and the quality is guaranteed through adaptive filtering and multi-source data correction. A dynamic threshold value and wavelet transform are used for extracting fire features to construct vectors, the vectors are input into a fusion model to discriminate a fire in real time, early warning information including positions, fire behaviors and the like is transmitted to a ground command center within 8 minutes, data are updated every 10 minutes during the fire, the fire behaviors are evaluated according to multiple indexes in combination with a GIS and a time sequence model, strategies are adjusted, and the data are stored. The system is fast in data acquisition and processing, early warning is performed within 8 minutes, the accuracy rate exceeds 92%, the fire behavior is pre-judged 15 minutes in advance, the system is stable, data is efficiently processed, and ecological and life and property safety is protected.

The invention provides an unmanned aerial vehicle cruise pre-warning method and monitoring system applied to high-speed traffic monitoring, and the method comprises the steps: collecting the dynamic monitoring data of a target road segment in real time through a plurality of hovering monitoring platforms disposed along a highway, and recognizing an abnormal event in the target road segment based on the dynamic monitoring data; generating a multi-level early warning signal according to the event type of the abnormal event, transmitting the multi-level early warning signal to a command center to generate an unmanned aerial vehicle dispatching instruction matched with the event type, and controlling the target unmanned aerial vehicle to move to a target position corresponding to the abnormal event based on the path planning parameter; and an early warning operation corresponding to the event type is executed through a loudspeaker module of the target unmanned aerial vehicle, the monitoring range of the hovering type monitoring platform is adjusted according to the continuous state of the abnormal event, and a flow adjusting instruction is sent to a service area control system of the vehicle in the target direction. According to the invention, the timeliness of accident early warning and the systematicness of a disposal scheme can be improved, the occurrence rate of a secondary accident is effectively reduced, and the utilization efficiency of emergency resources is optimized.

The invention discloses a dynamic task distribution system based on multi-source data fusion, belongs to the technical field of intelligent task scheduling, and aims to solve the problems of response delay and execution failure caused by undifferentiated rule verification, fuzzy resource matching logic and inaccurate real-time state evaluation in a traditional task distribution system. According to the system, a task request is obtained through a task receiving module, multiple indexes are converted through a data standardization processing module, a rule matching engine carries out multi-rule verification and outputs a matching degree score, a real-time capability evaluation module calculates a current capability value of an executor, and a dynamic decision module dynamically adjusts double weights according to a task emergency degree and generates a comprehensive score. And time, resource and skill conflicts are eliminated through the conflict detection unit, and finally the optimal executor is selected by the task allocation unit to issue the task. The system is suitable for various fields requiring efficient and accurate task allocation, such as grid command center order distribution, emergency response, logistics distribution, maintenance service and the like.

The invention discloses a tunnel fire extinguishing robot emergency command system and a use method. The system comprises an inspection robot, a fire extinguishing robot, a visual command center, an industrial internet platform and corollary equipment. The inspection robot is in communication connection with the visual command center through the industrial internet platform; the visual command center is provided with a dispatching module for dispatching the fire extinguishing robot and a navigation module; and the fire extinguishing robot is in communication connection with the visual command center through the industrial internet platform. A high-definition infrared camera, multiple types of sensors and a laser scanner are carried, and conditions in a tunnel are monitored in real time; an automatic fire extinguishing device is carried, and the fire spraying angle can be adjusted through remote control for accurate fire extinguishing; by analyzing monitoring data and alarm information, the robot can be remotely commanded to perform emergency response; the system can upload monitoring data and transmit instructions of the command center to the fire extinguishing robot in real time.

The invention relates to the field of unmanned aerial vehicle control, and discloses a police unmanned aerial vehicle management and control system for handling emergencies, which comprises a sensing module, a distribution module, a planning module, a control module, a tracking module and a feedback module. The sensing module is used for collecting environment data in real time and generating a three-dimensional environment model; the distribution module optimizes an unmanned aerial vehicle task distribution scheme; the planning module dynamically plans the optimal flight path of the unmanned aerial vehicle according to the task allocation result and the three-dimensional environment model; the control module dynamically adjusts the attitude and flight height of the unmanned aerial vehicle; the tracking module tracks the target position in real time and predicts the motion trail of the target; and the feedback module transmits the execution condition of the unmanned aerial vehicle, the target tracking result and the field real-time picture back to the command center. Through cooperative work of all the modules, rapid response and efficient disposal of emergencies are achieved, the system is particularly suitable for police service tasks in complex and dynamic environments, and the system has the advantages of being high in response efficiency, high in environmental adaptability and high in resource utilization rate.

The invention discloses a safe operation system and a safe operation method of a space-ground integrated rescue vehicle, which are used for the rescue vehicle working in a complex disaster environment and ensure stable and reliable two-way communication connection between the rescue vehicle and a command center by establishing an intelligent switching mechanism of a low-orbit satellite main link and a ground network standby link. Real-time transmission of key instructions and field information is guaranteed, and a foundation is laid for safe operation. Advanced risk early warning is achieved through a space-ground cooperation mechanism, dynamic decision making and path planning are carried out by integrating satellite information and local sensor data, and the global adaptive capacity of the rescue vehicle to the complex disaster environment is improved. Satellite pre-sensing information is combined with a local decision, and a pre-control instruction is generated to act on a drive-by-wire chassis, so that the rescue vehicle can smoothly deal with hidden or developmental risks in advance, and the driving safety and stability are improved.

The invention discloses an emergency command system and method based on satellite communication, and particularly relates to the technical field of radio transmission. On-site information of a disaster area is obtained in real time, the information is transmitted to an emergency command center through a satellite communication channel, dynamic command decision and resource optimization are achieved, in the signal transmission process of the system, the phase noise and the inter-carrier interference ratio of satellite signals are monitored and analyzed in real time, whether the signals are distorted or not is judged, and when the signals are distorted, the emergency command center is started. The system is automatically switched to a standby satellite communication channel to ensure that information transmission is not interrupted; besides, the satellite communication link monitoring system can adjust the signal quality in real time and carry out fault-tolerant processing, continuous operation of the command system is ensured, emergency response failure caused by communication interruption is avoided, the stability of satellite signals in various environments is effectively improved, and efficient operation of the emergency command system is ensured.

The invention relates to a multi-unmanned aerial vehicle maritime cooperative reconnaissance method based on an Archimedes algorithm and hierarchical scheduling, and the method comprises the steps: defining a patrol task region and task targets, and constructing a topological model of an unmanned aerial vehicle cluster for each task target; according to the cooperation characteristic of the unmanned aerial vehicle cluster, Archimedes patrol path planning is carried out on various unmanned aerial vehicles; based on the performance of the unmanned aerial vehicle, factors such as path length, flight time, unmanned aerial vehicle scanning range and search efficiency are comprehensively considered, and the path of the unmanned aerial vehicle is optimized, so that the unmanned aerial vehicle has relatively high execution efficiency and stability; when the leader unmanned aerial vehicle finds a target during patrol, the cluster dispatches the investigation unmanned aerial vehicle to perform a tracking task; and the investigation data is returned to the command center, and next task planning is carried out. The cooperative reconnaissance capability of the unmanned aerial vehicle cluster in complex tasks can be effectively improved.

The invention provides a mine emergency rescue command system, and aims to solve the problems of untimely emergency response, incomplete information, low command and dispatch efficiency and the like in the prior art. The system comprises a mine environment data acquisition module, a wireless transmission module, a data processing module, a risk early warning module, a command and dispatch module and a rescue auxiliary module. The environment data acquisition module acquires gas concentration, temperature and humidity, dust concentration and personnel position information in a mine in real time through a sensor; the wireless transmission module transmits the data to a ground command center; the data processing module analyzes and generates a comprehensive safety score by using an algorithm; when the danger value exceeds the threshold value, the risk early warning module automatically triggers an alarm; and the commanding and dispatching module remotely dispatches rescue workers according to the real-time information, and generates an optimal rescue path by using the rescue auxiliary module. The system has real-time performance, intellectualization, information integration and remote command capability, and can quickly respond to mine accidents, improve rescue efficiency and reduce accident loss.

The invention discloses a mobile application scene monitoring method and system based on audio and video, and relates to the technical field of intelligent monitoring. The method is executed by an edge computing node and comprises the following steps: S1, constructing a three-level edge computing network architecture; s2, performing multi-stage noise reduction processing on the wearable device layer, performing adaptive noise suppression based on a 200ms time window, and extracting a pure voice signal; s3, heterogeneous network bandwidth resources are allocated through a dynamic priority transmission protocol, and urgency grading is performed on the audio signal Saudio and the video frame Vframe; S4, processed audio and video data are input into a double-flow neural network for space-time alignment, and a fusion feature vector is generated; and S5, uploading the fusion feature vector and the metadata to a command center cloud platform of a center cloud layer through a secure transmission protocol. According to the invention, through a three-level edge computing network architecture, distributed processing of data is realized, the computing pressure of a central cloud layer is reduced, and the data processing efficiency is improved.

The invention discloses a fire water tanker emergency intelligent scheduling method and system based on a cloud platform, and relates to the technical field of intelligent scheduling management. According to the method, based on a multi-dimensional real-time database constructed by a cloud platform, multi-disaster data and priority data in a to-be-dispatched vehicle data dynamic acquisition and classified storage process are acquired, and preliminary dispatching distribution of to-be-dispatched vehicles is synchronously completed, so that a dispatching response initial period is shortened; after preliminary scheduling distribution, candidate scheduling schemes are generated, and meanwhile, an optimal scheduling scheme is screened out so as to accurately match emergency requirements of each target area; after the optimal scheduling scheme is obtained, based on a received scheduling instruction, a driving route and task allocation are dynamically adjusted, and scheduling information is synchronously pushed to a command center and each task scheduling site, so that rescue delay caused by information lag is avoided. Full-process optimization of data processing, scheme screening and collaborative scheduling in a multi-disaster-situation concurrent scene is realized, so that the timeliness of emergency scheduling of the fire water tanker is effectively improved.

The invention discloses a customs remote intelligent patrol system based on a 5G + unmanned aerial vehicle technology, and relates to the technical field of unmanned aerial vehicle patrol. An unmanned aerial vehicle module is responsible for performing field data acquisition and primary processing according to application scene requirements; the wireless communication terminal provides a high-speed and low-delay data transmission channel through a 5G communication network; the customs command center is responsible for gathering, analyzing, commanding and deciding the collected application scene data. The data analysis module is matched with a high-definition camera to enable collected remote sensing data to be further close to a real image, so that customs supervision work management can be more accurate and stable, an intelligent inspection route is continuously optimized by carrying a path navigation model based on an improved ant algorithm, and the intelligent inspection efficiency is improved. And the intelligent inspection efficiency is improved.

The invention discloses a quadruped robot system for indoor fire rescue. The quadruped robot system comprises a quadruped robot body, a main control unit carried by the robot, a sensing unit, a navigation unit, an execution unit and a motion control unit. The main control unit comprises two high-performance industrial personal computers which respectively process a motion control algorithm and a visual perception algorithm. The industrial personal computer communicates with other sensors through an IP and a serial port, and wirelessly communicates with the rear end of the fire-fighting command center through a TCP. After the fire-fighting command center issues a rescue task to the quadruped robot, the robot constructs a global map through the laser radar, and searches a fire source and trapped persons through the depth camera. When the robot recognizes the target, the robot sends the target position to the rear end of the fire-fighting command center, automatically avoids obstacles, and navigates to the target position to execute fire extinguishing and rescue work. The firefighter can be helped to quickly find a fire source and trapped persons, determine the positions of the trapped persons in the map, and guide the firefighter to reach the area to carry out rescue.

The invention discloses a collision sensing intelligent guardrail system and method based on Beidou positioning, and the method comprises the following steps: S1, collecting sensor data along a guardrail, and carrying out the preprocessing; s2, transmitting the preprocessed sensor data to an edge server, and forwarding the preprocessed sensor data to a cloud server through a cellular network; s3, constructing a gated convolutional network based on two channels, and inputting the state vector sequence into the gated convolutional network; s4, performing multi-layer nested coding and decoding operation on the collision feature vector, constructing a collision judgment function, and judging whether collision abnormity is triggered or not; s5, generating a collision early warning data packet when the collision level label is in an activated state; and S6, transmitting the collision alarm data packet to a road traffic command center for road maintenance personnel to quickly respond and deal with the collision alarm data packet. According to the invention, high-precision real-time perception and intelligent early warning of the collision state of the road guardrail are realized, and the automation level and response efficiency of traffic safety monitoring are obviously improved.

The invention discloses an intelligent water conservancy monitoring system and method based on air and underwater cooperation, and relates to the technical field of water conservancy projects, and functional modules of the system comprise an air platform, an underwater platform and a command center; comprising the following steps of: modeling a dynamic task demand based on multi-dimensional environment collaborative awareness; an air-horizontal platform task allocation mechanism based on collaborative path-load optimization; a multi-source data space-time coding and platform embedded sensing guide sampling mechanism; edge node multi-source observation collaborative fusion and local anomaly recognition; carrying out risk trend prediction and regional priority reconstruction based on a dynamic evolution network; and generating an intelligent response strategy based on risk dynamic reconstruction. According to the method, a cooperative working mechanism of an air platform and an underwater platform is constructed, and technologies of multi-source data fusion, a multi-platform linkage response strategy and the like are combined, so that systematic enhancement of a water conservancy project area in multiple dimensions of full space coverage, high time frequency, strong risk identification, response schedulability and the like is realized.

The invention discloses an unmanned aerial vehicle emergency control management method and system based on digital twinning, and belongs to the technical field of unmanned aerial vehicle control. The system comprises an unmanned aerial vehicle data acquisition module which acquires image data in an emergency area and parameter records of an unmanned aerial vehicle; the virtual scene construction module is used for constructing a virtual scene by using a digital twinning technology, and mapping and dividing a three-dimensional grid in real time; the emergency route analysis module is used for planning a feasible route for each unmanned aerial vehicle in the virtual scene and screening out key routes; the execution scheme planning module is used for analyzing each scheme according to the key route planning scheme so as to set a communication scheme; and the operation visualization module is used for supervising each unmanned aerial vehicle to fly according to the communication scheme and displaying a virtual scene in real time through a visualization page of the command center. According to the invention, through digital twin-driven multi-source sensing fusion, dynamic grid adaptation and nonlinear anti-interference path planning, the environment modeling precision and communication link reliability of the unmanned aerial vehicle group in a disaster environment are improved.

The invention provides an emergency response terminal system with image data return capability, which relates to the technical field of emergency response terminals and comprises an emergency response terminal management subsystem, an emergency response terminal, a multi-mode communication network, an image data return channel and an equipment state monitoring system. The emergency call terminal management subsystem is deployed on an emergency management platform and is used for generating and auditing an early warning task, dynamically selecting a communication link, interacting with a terminal through a satellite network and receiving a field image and equipment state data returned by the terminal; through the satellite, Beidou and 4 / 5G multi-link redundancy design, it is ensured that early warning information can be reached under the three-disconnection scene of network disconnection, power failure and disconnection, the problem of communication failure of a traditional system is solved, low-delay and wide-coverage transmission of the early warning information is achieved, the encrypted image return function is adopted for providing real-time disaster situation pictures for a command center, the rescue decision accuracy is improved, and the rescue cost is reduced. And the decision support capability is improved.

The invention discloses a photovoltaic panel ground cleaning control system and method based on an unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicle control, and the system comprises a cleaning unmanned aerial vehicle, a ground control center system, a command center system and corresponding functions. Through modular design and multi-system cooperation, intelligentization, high efficiency and precision of photovoltaic panel cleaning operation are achieved.

Disclosed are a method, system, and apparatus of a corrections officer tactical gear using computer vision to notify of an ambient threat. In one embodiment, a personal protective equipment includes a responsive device integrated in a tactical gear and a visual sensor of the tactical gear to identify an inmate using an inmate artificial intelligence model. The responsive device notifies a wearer of the tactical gear when the visual sensor identifies an ambient threat to the wearer and / or the inmate. A geo-location device may identify a present location of the wearer when the visual sensor identifies the inmate. When the visual sensor identifies the inmate, a present location of the wearer may be transmitted from the tactical gear to a command center of a correctional facility (e.g., may also identify a distance away and / or a location of the inmate from the present location of the wearer).

The invention discloses an intelligent road system for vehicle-road cooperation safety alarm, and relates to the technical field of vehicle-road cooperation alarm, and the system comprises a communication evaluation module which inputs an optimal communication path into a communication mapping model, a space matching layer carries out the fusion of road geometry and communication topology, a state mapping layer marks the signal intensity and spike node states, and a state analysis module which carries out the analysis of the optimal communication path; generating a communication quality thermodynamic diagram; the risk decision module is used for evaluating the risk level of each region based on the communication quality thermodynamic diagram and outputting priority transmission parameters; and the information transmission module starts sound-light alarm according to the priority transmission parameters, obtains an execution state report, and transmits the execution state report back to the command center. According to the method, the communication mapping model is constructed and the priority transmission parameters are dynamically generated, so that the accuracy of communication state evaluation is improved, and efficient cooperative processing and intelligent priority distribution of multi-source alarm information are realized.

The invention relates to the technical field of communication engineering, in particular to a high-precision charge-discharge balanced intelligent positioning system integrating Beidou and ultra-wideband technologies, which integrates the Beidou and ultra-wideband technologies, introduces AI artificial intelligence, provides data support for intelligent safety management and control of engineering field personnel based on big data, and improves the safety of the engineering field personnel. The engineering site safety management level is improved; comprising a fusion type single base station which is installed and deployed in a place needing positioning and is used for receiving positioning signals and transmitting data; the solar energy complementing multimode positioning tag is worn by a constructor and is used for intelligently switching a positioning mode, complementing energy, monitoring a state and returning data; and the AI intelligent analysis system is deployed in an engineering command center or a monitoring center and is used for receiving the data and carrying out intelligent analysis, management and decision-making assistance.

The invention belongs to the technical field of robot fire rescue navigation, and particularly relates to an autonomous navigation method and system for a fire rescue quadruped robot, and the method comprises the following six main steps: environment scanning and mapping, target identification and positioning, communication and instruction receiving, map conversion and repositioning, path planning and obstacle avoidance, and fire extinguishing and rescue. The first robot is responsible for entering a fire scene to conduct environment scanning and mapping, a three-dimensional point cloud map is obtained, and trapped persons and a fire source are accurately recognized and positioned through the depth camera. And then, the first robot sends the information to a fire-fighting command center and a second robot, and the command center issues a fire extinguishing instruction. And the second robot converts the three-dimensional point cloud map into a two-dimensional grid map and carries out repositioning. And then, the second robot performs path planning according to the fire source position information and finally arrives at the fire source to perform fire extinguishing work. Effective rescue of the quadruped robot on a fire scene is achieved, and rescue efficiency and safety are improved.

The invention discloses an automatic emergency management method for intelligent industrial production, and relates to the field of industrial management, and the method comprises the steps: calculating the production capacity range of a production line; constructing a real-time command platform; the production capacity of the production line is monitored in real time, the real-time production capacity is obtained, whether the real-time production capacity belongs to the production capacity range or not is judged, and operation environment state data of the abnormal production line are obtained; determining production capacity abnormity reasons of the abnormal production line; determining the emergency level of the abnormal production line; outputting an alarm signal of a corresponding degree; and smooth communication among the command center, field personnel and related departments is judged. The method has the advantages that the abnormal reason of the abnormal production line is rapidly determined through the digital twinborn model, an emergency measure execution scheme for historically processing the reason is given, closed-loop feedback is completed, meanwhile, the real-time command platform detects signals in the emergency operation execution process, smooth communication of all departments is guaranteed, and the emergency operation execution efficiency is improved. And the collaboration efficiency of all departments is improved.

The invention discloses a self-optimizing intelligent work order scheduling method and system, belongs to the technical field of work order scheduling, and solves the problems that a traditional scheduling method is poor in dynamic adaptability due to static rules, single in optimization target and dependent on artificial experience, and a model cannot be self-optimized online. According to the technical scheme, the method comprises the steps that work order features and resource state data are collected in real time and input into a pre-trained deep reinforcement learning model to generate a scheduling scheme, a scheduling deviation value is calculated based on actual feedback data to trigger model iterative optimization, and dynamic updating of a scheduling strategy is achieved; the method is mainly used for work order automatic distribution and scheduling optimization in scenes such as a grid command center, a logistics distribution platform and a customer service center.

The invention discloses a fire extinguishing robot control method and system based on multi-modal sensing and autonomous navigation, and the method comprises the steps: collecting environment temperature data according to a preset frequency through a thermal imager, and triggering early warning when an abnormal threshold value is reached; after early warning, the depth camera obtains a depth image, the depth image is processed through mirror reflection filtering and smoke filtering algorithms and input into a flame form recognition model to judge whether flame features exist or not, and if yes, a fire disaster is judged. And after the fire is confirmed, constructing a real-time model, planning an obstacle avoidance path and guiding the robot to a fire source according to a pre-stored three-dimensional / two-dimensional map in combination with a synchronous positioning and map construction technology. After reaching, adjusting the spraying angle of the fire extinguishing mechanism, and extinguishing fire by water mist / dry powder. During fire extinguishing, the real-time video of the fire scene and the fire source position data are uploaded to a fire-fighting command center in real time. The problems that in the prior art, autonomous fire extinguishing cannot be achieved, environment perception is poor, and early warning and fire extinguishing efficiency is low are solved.