250 results about "Command center" patented technology

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 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 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 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 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 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 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 provides a multi-dimensional perception-driven field large-scale scene intelligent detection method and system, and relates to the technical field of scene intelligent detection. According to the method, a closed-loop system covering multi-source sensing, edge preprocessing, three-dimensional space-time fusion inference, alarm linkage response and continuous model optimization is constructed. By arranging a compound eye imaging sensor, an inertia-GNSS sensor, a millimeter wave radar sensor and an electrical parameter and environment sensor on site, synchronous acquisition and transmission of multi-modal data are realized; and de-noising, standardization and calibration processing is carried out on edge nodes, and combined identification of a target state, an event category and a risk level is completed based on a deep fusion network. When a detection result meets a preset condition, alarm information is generated, and the command center, the wearable terminal and the execution mechanism are linked to respond in time; meanwhile, feedback is periodically collected and disposed, the model is driven to be self-updated, the detection accuracy and response adaptability are continuously improved, and the method is suitable for intelligent safety monitoring of complex operation scenes such as mines, electric power and ports.

The invention relates to the technical field of anti-riot vehicles, and discloses a police anti-riot command vehicle which comprises a vehicle chassis, a compartment body arranged on the vehicle chassis and a command communication system arranged in the compartment body, and further comprises an anti-riot net laying device integrated on the top of the compartment body and used for rapidly launching and unfolding an anti-riot net towards the outside of the vehicle; the emergency supporting wheel mechanism is arranged on the vehicle chassis, corresponds to vehicle tires installed on the side face of the vehicle chassis and is used for providing emergency supporting when the vehicle tires fail. The anti-riot net laying device comprises a launching cylinder, an anti-riot net contained in the launching cylinder and a driving mechanism providing power for launching of the anti-riot net, and the launching cylinder is arranged at the top of the compartment through a mounting base. Through an integrated anti-riot net laying device and a centralized control system, a non-fatal interception means and a command center are deeply fused, and seamless connection from situation awareness to rapid disposal is achieved.

The utility model provides an intelligent scheduling command platform with integrated scheduling, and effectively solves the problem that the scheduling work is influenced because an interphone and a camera in the prior art are lack of effective means of effective electric quantity. The dispatching command platform comprises an electric quantity monitoring module, the electric quantity monitoring module comprises a primary diagnosis circuit and a secondary diagnosis circuit, the primary diagnosis circuit detects a current signal of a battery in dispatching equipment during use by using a current sensor, obtains a reminding signal and an early warning signal based on the current signal, and sends the reminding signal and the early warning signal to the secondary diagnosis circuit; the reminding signal and the early warning signal are output to a command center; the primary diagnosis circuit is connected with one end of the secondary diagnosis circuit, and the other end of the secondary diagnosis circuit is connected with the command center.

The invention discloses a forest fire unmanned aerial vehicle video monitoring system and method. The system comprises a data acquisition unit arranged on an unmanned aerial vehicle and responsible for acquiring multi-source monitoring data and spatial attitude data of a target area; the data processing unit is arranged on a ground station and is used for receiving and processing the data and generating fused situation data containing the position and situation of the fire behavior through a fire behavior recognition algorithm; the dynamic path planning unit is used for automatically generating a cruising or path tracking instruction according to the fused situation data, the geographic information and the state of the unmanned aerial vehicle; and the command decision-making unit is arranged in a ground command center and is responsible for visualized display, spatial analysis and emergency command of the fire behavior and issuing a path instruction to the unmanned aerial vehicle for execution so as to realize a monitoring and disposal closed loop. According to the invention, multi-source data efficient processing, fire accurate identification, dynamic path planning and emergency command efficient linkage can be realized, the monitoring coverage range and the response speed are improved, the labor cost is reduced, and the fire loss is reduced.

Embodiments of the disclosed is a system comprising a wearable command center. One such embodiment comprises a case clip top portion; a chest mount bottom portion; a hinge member assembly; a connector cartridge assembly; a case; and at least one structural guide rail.

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 ecological environment real-time monitoring method based on the Internet of Things technology, and the method comprises the steps: obtaining a monitoring strategy and task distribution data from a central command center through a layered command architecture, determining an intelligent equipment selection scheme, and obtaining optimal equipment configuration parameters. And deploying sensor network nodes, predicting a pollution diffusion trend by using the pollution diffusion model, and verifying and analyzing abnormal data. When the abnormal event feature exceeds a threshold value, an emergency response linkage process is triggered, and a dense monitoring mode is started. Equipment health state data is transmitted through an Internet of Things communication link, fault diagnosis and parameter adjustment are carried out, the transmission bandwidth is optimized, and adaptive speed limit control is realized. And finally, reconstructing a network topology structure through a network topology adaptive adjustment algorithm, and realizing real-time continuous coverage monitoring of the ecological environment. Through dynamic adjustment and intelligent optimization, the real-time performance, the accuracy and the system stability of environment monitoring are remarkably improved, and the method is suitable for complex and changeable environment monitoring scenes.

The application discloses a traffic management platform construction method and device and a traffic management method and system, acquires traffic basic data and carries out digital analysis to construct a traffic management semantic library, constructs a traffic management element periodic table from the semantic library, and the traffic management element periodic table is composed of various preset traffic management elements and traffic basic data corresponding to each type of traffic management element; the traffic management element is randomly combined to generate a corresponding traffic management scene library; the traffic management scenes in the traffic management scene library are randomly combined to generate a traffic management business library; and the traffic management platform for digital traffic management is constructed according to the traffic management semantic library, the traffic management element periodic table, the traffic management scene library and the traffic management business library, so that the programmable and calculable traffic management full chain can be realized, and templates and demonstrations can be provided for the construction of traffic management command centers in various places.

The invention relates to a water quality emergency scheduling method based on multi-platform linkage, and the method comprises the steps: enabling an emergency monitoring vehicle to drive to a preset emergency response point along the bank of a water area after a satellite remote sensing system captures a water quality abnormal signal; an unmanned aerial vehicle carrying a hyperspectral lens flies to an abnormal water area according to a planned route to collect spectral data, and an abnormal range is interpreted and narrowed to a worst pollution area in real time through a data processing server; then, the unmanned ship goes to the area according to a planned route to monitor water quality parameters in real time, the data processing server determines an optimal water sampling point, and the unmanned ship automatically completes water sampling; finally, the data processing server generates a water quality report and reports the report to a command center, and the command center starts an emergency disposal scheme.

The invention discloses a nuclear power plant production command center management system, which relates to the technical field of nuclear power and comprises a data storage device, an equipment management platform, a decision management platform and an operation management platform. Wherein the equipment management platform comprises an equipment remote monitoring module and an intelligent early warning module; the decision management platform comprises an intelligent decision center module; the operation management platform comprises an intelligent dispatching module; the equipment remote monitoring module realizes real-time acquisition of equipment operation parameters through an intelligent sensor network, and the intelligent early warning module performs anomaly detection based on a dynamic threshold model, so that the problem of lagging of traditional fixed threshold early warning is solved; the intelligent decision-making center module responds to the early warning information, carries out deep knowledge reasoning by combining historical operation data and a nuclear power plant group reactor knowledge graph, generates a scientific decision-making scheme, and solves the limitation of artificial experience decision-making; and the intelligent dispatching module automatically generates the operation task based on the decision scheme and matches the operation team, so that the operation efficiency is improved.

The invention discloses a mine emergency data relay transmission method based on LoRa and 4G fusion, and belongs to the technical field of mine communication. The method comprises the steps that a communication node monitors sensor data in real time, and when key emergency data is recognized, 4G signal strength is automatically detected; when the 4G signal strength is lower than a set threshold value, starting a LoRa multi-hop relay transmission mode, and selecting an optimal relay node through a dynamic relay node discovery and comprehensive preferential algorithm; the key data is transmitted to an exit node with 4G connection capability through a one-hop or multi-hop LoRa link, and is finally uploaded to a command center through a 4G network. According to the invention, through advantage complementation of LoRa and 4G, a hybrid communication network adaptive to a complex mine environment is constructed, and the technical problem of reliable transmission of key data in a communication blind area is effectively solved.

The invention discloses an unmanned aerial vehicle patrol and security monitoring linkage management method. According to the system, urban geographic information data and key monitoring area coordinates are acquired, hierarchical grid division is realized by using a quadtree spatial index algorithm, and a patrol task distribution basic data structure is established; solving an approximate optimal solution of the patrol path of the unmanned aerial vehicle by adopting an improved greedy strategy, and performing optimization adjustment according to technical parameters and weather conditions of the unmanned aerial vehicle; the unmanned aerial vehicle collects video data in real time through high-definition camera equipment in the patrol process, target detection is conducted through a deep learning model, and potential safety hazards such as personnel gathering and vehicle abnormity are recognized; detecting violent conflicts and illegal intrusion behaviors in combination with a time sequence analysis algorithm, and generating an abnormal event report; cooperative work of the unmanned aerial vehicle, the ground robot and the command center is realized; and a patrol scheme is dynamically adjusted according to meteorological conditions, and robot scheduling is optimized through energy consumption management.

The invention discloses a distributed seat system operation state and fault monitoring method, which is suitable for scenes such as a command center and an enterprise conference room, and is used for solving the problems that hidden faults are difficult to find, fault response is lagged and the system stability is insufficient due to lack of a node local display device, single fault prompting mechanism and limited monitoring dimension of the existing system. According to the method, a low-power-consumption touch screen is configured at each node to synchronously display equipment states and signals, and multi-protocol compatible decoding is combined with load balancing to schedule the signals; constructing a hierarchical fault prompt mechanism and linking the operation and maintenance mobile terminal; an operation and maintenance management platform is built, multi-dimensional monitoring of equipment, links, machine room environment and power utilization is achieved, and edge calculation decoding, signal timing switching and equipment fault prediction are also supported. The method can improve the fault positioning efficiency, enhance the system operation stability, shorten the fault response time, realize full-scene management and control, and guarantee the continuous development of key businesses.

The invention provides a chemical accident emergency response method and system under real-time monitoring, and relates to the technical field of emergency response, and the method comprises the steps: carrying out the time alignment through collecting multi-source heterogeneous data in real time, and generating multi-source synchronous data; extracting multi-modal features of the multi-source synchronous data to carry out chemical accident identification; accident scene parameters are called, accident response analysis is carried out based on an accident identification result, an emergency response scheme is formulated, resource scheduling analysis is carried out, and a resource scheduling network diagram is constructed; and performing accident monitoring and early warning according to the resource scheduling network diagram in combination with the multi-source synchronous data, generating a real-time decision instruction, and pushing the real-time decision instruction and an emergency response scheme to an emergency command center. According to the method and the device, the technical problems of low chemical accident identification accuracy and response flow lag caused by lack of a multi-source heterogeneous data fusion and real-time linkage mechanism in the prior art are solved, and the technical effects of improving the chemical accident identification precision and the emergency response speed are achieved.

The application discloses an intelligent road system for vehicle-road cooperation safety warning and relates to the technical field of vehicle-road cooperation warning, and comprises a communication evaluation module, an optimal communication path is input into a communication mapping model, a space matching layer is used for fusing road geometry and communication topology, a state mapping layer is used for marking signal strength and stud node state, and a communication quality heat map is generated; a risk decision module is used for evaluating the risk level of each region based on the communication quality heat map and outputting priority transmission parameters; and an information transmission module is used for starting an audible and visual alarm according to the priority transmission parameters, acquiring an execution state report, and feeding back the execution state report to a command center. Through the construction of the communication mapping model and the dynamic generation of the priority transmission parameters, the application improves the precision of communication state evaluation, realizes efficient cooperative processing of multi-source alarm information and intelligent allocation of priorities.

The invention discloses a water regimen AR video fusion management system, which relates to the technical field of fusion management and comprises a hydrological data acquisition module, a video acquisition module, a geographic information acquisition module, a dynamic calibration module, an AR fusion module and an intelligent decision module. Multi-source data of the water level value H, the flow velocity value V and the rainfall value R are fused with a single risk index, and AR alarm is driven; the dynamic calibration module integrates a heterogeneous data source (hydrological sensor / video / GIS), Beidou RTK positioning data (XRTK, YRTK) and a GIS elevation model Z (X, Y) are fused into a three-dimensional space point, the intelligent decision-making module carries out graded early warning and linkage AR visual early warning based on a hydrological early warning value F and a submerging depth D (x, y), and meanwhile, a mobile terminal, AR glasses and a command center large screen are supported to synchronously display an AR fusion scene. Collaborative annotation data is encrypted and stored by adopting a block chain technology, and is shared in real time through a 5G private network, so that the timeliness of emergency command is improved.

To provide a tailor-made remote cell-activation system and its application method.SOLUTION: Provided are a remote cell-activation system and its application method configured to work with a computer or a smartphone capable of internet access, sound recording, photographing, executing mobile apps, and updating applications, wherein, by utilizing features of the computer and the smartphone, three different electromagnetic fields are generated in equipment, and quasi-like quantum entanglement pair technology transmits an electric field message after final conversion to a target object in a radio and wireless manner, the technology being applied to the remote cell-activation system 2, a mobile app and an application acting as a command center that issues instructions, and the computer or the smartphone being designed to execute equipment, whereby, by seamlessly combining AI medical diagnosis systems and AI robots, more accurate mobile medical services can be provided for human beings or other living organisms.SELECTED DRAWING: Figure 1

The application provides a firefighter fatigue detection method and device based on a dynamic region attention mechanism. The method collects continuous frame videos through a fire helmet camera, and calculates the target region occlusion degree during preprocessing. Accordingly, the dynamic region attention mechanism is used in the backbone network, the target region is divided into discrete sections according to the occlusion degree, and the sampling multiple is adjusted in the up-sampling layer to enhance feature extraction and improve the positioning accuracy of the small target region of the face and joints. The method effectively improves the real-time performance and accuracy of fatigue detection in complex fire environments, provides accurate decision support for the command center, ensures the safety of firefighters, and improves the rescue efficiency.

A system for inspecting an offshore wind farm having one or more wind turbines includes an unmanned autonomous vessel. The unmanned autonomous vessel includes a positioning module for navigating the unmanned autonomous vessel to a target wind turbine in the offshore wind farm and positioning the unmanned autonomous vessel near the target wind turbine, an onboard data acquisition module with one or more sensors for collecting local data regarding the health of the target wind turbine, and a controller with at least one processor. The processor is configured to perform a number of operations, including, for example, receiving the local data from the one or more sensors and forwarding the local data to a remote command center via a satellite communication link.