941 results about "Electronic map" patented technology

The invention provides an intelligent warehouse management system and method based on big data, and relates to the technical field of warehouse logistics, and the system comprises a data collection module which is used for collecting the electronic tag information, goods location coordinates and environment data of materials in a warehouse in real time through a radio frequency identification reader-writer and a wireless sensor network node, and uploading the information to a central server; the inventory early warning module is used for dynamically classifying the materials in the warehouse in the central server, calculating safety inventory intervals of various materials through historical turnover rate data, and correcting an inventory threshold value in combination with a real-time correction factor; and the positioning navigation module is used for acquiring the real-time positions of the materials according to the new safe inventory interval, and generating a goods allocation electronic map and final path navigation. According to the invention, the warehouse management efficiency and accuracy are effectively improved, the warehouse space utilization is optimized, the warehouse-in and warehouse-out operation level is improved, and visual and intelligent management is realized.

The invention belongs to the technical field of smart tourism management, and relates to an AI-based smart tourism recommendation method and system, and the method comprises the steps: obtaining instantaneous aggregation density data collected by a plurality of hidden monitoring nodes in a scenic spot in real time; generating a dynamic environment grade set according to the instantaneous aggregation density data, the real-time weather elements and the traffic control information; generating a user physical exhaustion level, and generating an interest preference label through an electronic map zooming operation track; identifying space-time synchronization features between the associated mobile terminals to generate a group type identifier, and binding the group type identifier with a strategy recommendation template; performing peak shifting recommendation sorting in combination with the dynamic environment level to form an initial recommendation scheme set; and comparing the matching degree between the initial recommendation scheme and the interest preference label, triggering the secondary optimization of the recommendation content based on the group type identifier when the matching degree is lower than a set range, and injecting an emergency risk avoiding path to complete a closed-loop recommendation decision chain. The problem that in the prior art, due to the fact that the data collection dimension is single, recommendation strategies lack group adaptability is solved.

The invention relates to the technical field of path planning, in particular to a path planning method and system for an inspection robot, and provides the following scheme: executing an inspection task through an initial electronic map, collecting first image data and pose information, recognizing an inspection target, completing image registration, and generating second image data; inverting and calibrating the optimal observation direction based on the structural sensitivity distribution of the local visual features and the illumination variation trend, and determining the shooting position and angle to form a path node; a multi-objective optimization model is adopted, the path length, the view angle continuity and the illumination interference are comprehensively considered, and an optimal inspection path is generated; the method is suitable for outdoor inspection scenes with complex structures and non-uniform target distribution.

The invention discloses a land investigation quality monitoring system for remote sensing image intelligent segmentation and ground feature recognition, and relates to the technical field of remote sensing, and the system comprises an image recognition module, a label comparison module and a monitoring module, and specifically carries out the remote sensing image acquisition of a to-be-monitored land through a remote sensing sensor, and carries out the structural complexity analysis and image region division. The method comprises the steps of forming a non-uniform region set, analyzing and acquiring category probability vectors of pixel positions of all regions in the formed non-uniform region set to construct a tag map of a whole remote sensing image, comparing pixel-by-pixel categories on a current tag map and a reference tag map to form a change mask map, identifying a structural change region according to the change mask map, and identifying a structural change region through sequential analysis. And determining whether the corresponding candidate tag inconsistent region under different time phase conditions is still a structural change region, so as to obtain a judgment result, and updating the electronic map based on the judgment result.

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 discloses a robot dog inspection path intelligent planning and dynamic adjustment method, system and device and a medium, and belongs to the technical field of robot path planning, and the method comprises the steps: calculating a task emergency degree index according to a weight coefficient of an inspection point and a time constraint, and determining a task priority; constructing a hierarchical electronic map containing the terrain difficulty coefficient and the moving cost; performing global path planning through a comprehensive cost function by adopting an A star algorithm; environment information is collected in real time through multiple sensors, and the dynamic obstacle layer is updated; performing real-time trajectory optimization by adopting a local path planning mode; selecting local path correction or global path re-planning according to the path execution state score; energy needed for completing the remaining tasks is predicted, and a charging path is planned when necessary. According to the invention, multi-target adaptive optimization of path planning is realized, a coordination mechanism of global planning and local adjustment is established, and the execution efficiency and reliability of inspection tasks are improved.

The invention discloses a base station coverage anomaly detection method based on big data analysis, and belongs to the technical field of base station coverage detection in the technical field of communication. Aiming at the problems that the existing base station coverage anomaly detection is insufficient in accuracy and cannot adapt to dynamic environment change, the method comprises the following steps of: acquiring operation data such as received signal strength indication values of all base stations in a target area for continuous 1-30 days and 10-60 minutes, performing dimension reduction processing, and calculating a coverage characteristic value obtained by multi-dimensional index linear weighting; the method comprises the following steps: acquiring a coverage anomaly probability value, inputting the coverage anomaly probability value into an isolated forest model which is trained by historical data and can be dynamically updated, outputting the coverage anomaly probability value, and when the coverage anomaly probability value is in an interval greater than 0.7 and less than or equal to 0.9, marking a corresponding base station position on an electronic map as a coverage anomaly area. The method can accurately position the abnormal coverage area of the base station, is suitable for real-time monitoring and abnormity identification of the coverage state of the base station in communication network maintenance, and improves the network optimization efficiency and the service quality.

The invention relates to the technical field of position tracking, in particular to an intelligent bracelet real-time position tracking visualization method and system. The method comprises the following steps: acquiring multi-dimensional sensing monitoring parameters of a user based on a smart bracelet, performing real-time motion state evaluation of the user, and performing adaptive adjustment of a position acquisition frequency to generate an adaptive position acquisition frequency; performing real-time position positioning acquisition based on the adaptive position acquisition frequency, and performing frequency-by-frequency spatial position positioning calculation to obtain a high-precision compensation reconstruction trajectory; the method comprises the following steps: acquiring public electronic map information, performing scene key element identification, and performing key attribute cognitive marking to obtain a plurality of scene attribute memory anchor points; and performing relative position distribution analysis on the high-precision compensation reconstruction trajectory based on a plurality of scene attribute memory anchor points, and constructing an anchor point space trajectory visual mapping graph. According to the invention, high-precision real-time position tracking of the user is realized, and clear and visual multi-level map information rendering is presented.

The invention relates to an active train obstacle detection method and apparatus based on a positioning technique. The active train obstacle detection method comprises the following steps: S1, acquiring an electronic map; S2, correcting initial parameters; S3, performing parameter calibration of a video camera; S4, detecting a train obstacle; and S5, outputting an obstacle recognition result. The apparatus comprises a positioning module, a laser radar detection module, a video recognition module, an operational host and an interface module, wherein the operational host is connected to the positioning module, the laser radar detection module, the video recognition module and the interface module respectively. Compared with the prior art, the invention can increase the obstacle detection rate and reduce report failures and errors.

The invention relates to the technical field of Internet of Things, and provides an obstacle avoidance method of an unmanned sweeper based on V2X communication and related equipment thereof. Space-time alignment and map initialization are carried out on satellite positioning information and real-time V2X communication data to obtain a reference electronic map, and rasterization fusion is carried out on the reference electronic map and laser radar point cloud data to obtain a dynamic obstacle probability map. Performing dynamic path planning on the dynamic obstacle probability map according to an A * algorithm to obtain an initial obstacle avoidance global path, and performing dynamic optimization on the initial obstacle avoidance global path according to real-time V2X communication data through a vehicle motion model to obtain a local optimization track; and performing motion analysis and instruction synthesis on the local optimization track through a differential driving model to obtain a driving control instruction. According to the invention, through multi-source information fusion, efficient probability mapping, double-layer path optimization and feedforward-feedback control compensation, the obstacle avoidance precision, the response speed and the driving smoothness in a complex dynamic environment are improved.

The invention discloses an intelligent parking navigation system based on image recognition and the Internet of Things, and relates to the technical field of intelligent parking navigation, the system draws a three-dimensional electronic map of a parking lot, divides the parking lot into monitoring areas, deploys sensors and cameras to collect image data, and transmits the image data to a cloud through the Internet of Things. The intelligent regulation and control model module uses a convolutional neural network CNN to carry out parking space recommendation and path guidance. And the vehicle monitoring module monitors vehicles entering the parking lot in real time, calculates a geometric environment adaptation coefficient and evaluates a traffic risk. And the vehicle guiding analysis module calculates the traffic flow and the parking space idle index, and recommends a proper parking area for the vehicle. The parking space recommendation analysis module evaluates the comfort level of the parking space, ensures the safety of backing and parking, and avoids the risk of traffic jam or traffic accident through strategy adjustment. The system improves the parking efficiency and safety, and optimizes the parking experience.

The invention discloses an airport runway FOD inspection and operation safety guarantee system in the field of airport runway safety detection. A ground control platform receives three-mode image data of an unmanned aerial vehicle platform and sends flight control data; the unmanned aerial vehicle platform receives the flight control data, executes flight actions, collects three-mode image data and sends the three-mode image data to the ground control platform; the ground control platform comprises an FOD detection module, a map module and a task scheduling module; the FOD detection module receives the three-mode image data and performs video image recognition to generate image recognition data; a gridding electronic map is arranged in the map module, and the FOD detection module superposes the image recognition data on the gridding electronic map to generate map obstacle data; and the task scheduling module sends the flight control data to the unmanned aerial vehicle platform. According to the invention, three-mode image recognition is carried out on the airport scene through the unmanned aerial vehicle platform to enhance the FOD inspection detection accuracy, and the unmanned aerial vehicle platform is utilized to increase the monitoring range, so that emergencies can be found in time.

The invention discloses a path planning method and system based on Beidou satellite positioning, and relates to the technical field of Beidou satellite positioning, and the method comprises the steps: carrying out the high-precision positioning and error correction of Beidou satellite signals through employing a multi-source sensor fusion method, and obtaining the position information; matching the electronic map data with the position information by adopting an electronic map matching method to obtain electronic map data corresponding to the current position; constructing a traffic flow prediction model based on the position information and a machine learning algorithm, and inputting the position information into the traffic flow prediction model to obtain a traffic condition prediction result; based on the traffic condition prediction result, planning a path from the current position to the destination by adopting a path search algorithm to obtain a preliminary path; performing personalized adjustment on the initial path according to user preference setting to obtain a recommended path; and monitoring the final recommended path by adopting a real-time monitoring and feedback mechanism, evaluating the position change and traffic condition in the path, and obtaining a final path planning strategy.

The invention relates to the technical field of agricultural intelligent equipment, in particular to a field sowing grain distance detection system and method based on computer vision, and the method comprises the steps that an image collection module collects 4KRGB and near-infrared data of a sowing area; the image processing module is used for processing and correcting the acquired image in real time; the grain distance feature deep learning analyzer strengthens seed feature extraction through an attention mechanism based on an improved YOLOv5 algorithm, accurately distinguishes weeds from seeds, and calculates a center distance deviation value of adjacent seeds based on a preset target grain distance; the positioning fusion module fuses Beidou positioning data and a visual odometer track, generates seed longitude and latitude and burial depth coordinates by using a high-precision farmland surface elevation model, and maps the seed longitude and latitude and burial depth coordinates to a farmland electronic map; and the dynamic regulation and control execution mechanism adjusts the rotating speed of the seeder or the seeding gap according to the grain distance deviation value and a priority strategy, and dynamically corrects the grain distance. Therefore, the problems of high detection error rate, single detection algorithm, poor data relevance and the like in the prior art are solved.

The invention relates to the technical field of railway communication, and provides a train message information transmission method and system, and the method comprises the steps: constructing an electronic map, and storing the ID, type and position information of each transponder on a railway; when the train is powered on for the first time, the initial position of the train is obtained, transponder IDs on the two sides of the train are determined in the electronic map according to the initial position, the ID of the next transponder is selected according to the running direction of the train, and the type of the transponder is obtained; when the train runs, the ID of the passing transponder is recorded in real time, and the type of the next transponder is predicted according to the ID of the recently passing transponder; and adjusting a receiving mode of a train transponder receiving module according to the predicted transponder type, and adaptively receiving message information sent by the next transponder. According to the invention, the train control system does not need to add sidelobe management and transponder suppression functions, and can meet the communication requirements of two transponders.

The invention provides an intelligent marine emergency equipment automatic positioning method and system. Wherein multiple distress signals are received and fused, and optimal geographical location information and timestamps are generated; determining a distress area on a preset sea area electronic map, correcting a distress position, evaluating probability distribution of each potential distress area, and generating a primary search target with the highest probability; a thermal imaging and optical sensing system on the rescue unmanned aerial vehicle is started for scanning, and a high-accuracy potential survivor position is generated; the search and rescue path is dynamically adjusted and optimized, the search strategy is adjusted, the optimal flight path is updated in real time, and an economical and efficient search and rescue path plan is generated; and timely feeding back the accurate coordinates of the position of the potential survivor to the nearest rescue coordination center, and guiding first-aid equipment to go along the optimal path to implement rescue. According to the technical scheme provided by the invention, the search and rescue efficiency and accuracy are improved, and the position of a potential survivor can be quickly and accurately positioned.

The invention discloses an action management identification method based on earthquake site disaster investigation, and relates to the technical field of data processing, and the method comprises the steps: determining a to-be-acted earthquake site region, and planning a disaster search task corresponding to a plurality of unmanned aerial vehicles in the to-be-acted earthquake site region; issuing the disaster situation search task to multiple unmanned aerial vehicles, controlling the unmanned aerial vehicles to execute the disaster situation search task, and obtaining an actual disaster situation investigation result corresponding to the disaster situation search task; according to an actual disaster situation investigation result, generating disaster situation points on the electronic map corresponding to the earthquake field area to be moved, and obtaining a disaster situation investigation map; and finally, the disaster situation investigation map is fed back to equipment specified by a commander to guide disaster relief actions of the commander, so that the earthquake site disaster situation investigation efficiency is improved, comprehensive disaster situation data can be formed, the commander can comprehensively understand the disaster situation, the commander is assisted to quickly form a global and optimal action scheme, and the disaster relief efficiency of the commander is improved. And the disaster disposal efficiency is improved.

The invention provides a geographic data search method and device, and the method comprises the steps: obtaining a geographic data search request of a user, and the geographic data search request comprises geographic knowledge keywords; and in response to the geographic data search request, recalling target geographic data. The target geographic data is searched based on the geographic knowledge keyword and a geographic knowledge database, and the target geographic data comprises geographic knowledge, a POI identifier related to the geographic knowledge and geographic data of the POI. And displaying the target geographic data on an electronic map interface. According to the geographic data search method provided by the invention, the application scene of the electronic map can be expanded, and the use requirement of a user on the map in the education field is met.

An AI-connected-electrified (ACE) heavy truck system equipped with an intelligent multi-mode hybrid (iMMH) powertrain system and a vehicle supervision control strategy based on machine learning (ML) or reinforcement learning (RL) paradigm are presented. This system ensures industry-leading power and braking performance of the ACE heavy truck while automatically optimizes both energy saving and emission reduction based on the vehicle's dynamic driving data and 3D electronic map information of roads for any transport event. In this application, the conventional analog electronic control (AEC) method is replaced by a novel digital pulse control (DPC) method on the instantaneous power function of the engine. The DPC method converts the complex surface working conditions of the AEC engine of the hybrid vehicles into simpler pre-defined working condition lines of the DPC engine. Consequently, the multi-variable nonlinear technical problem of simultaneously optimizing real driving environment (RDE) fuel consumption and pollutant emissions of the ACE heavy truck is simplified into two decoupled quasi-liner optimization problems, and ensures the reduction of on-vehicle computing resources for real-time AI inference computation and the improvement of the optimal performance, the convergent rate, and the robustness of the corresponding fuel-saving algorithm for the trained ML model or the learned RL model. Ultimately, the ACE truck achieves in the engineering sense the global minimum RDE fuel consumption and pollutant emissions meeting the standard consistently at high performance to cost ratio for any transport event and the RDE fuel consumption is decoupled from the vehicle configuration parameters and the human driver.

The invention provides a plant classification labeling method. The method comprises the following steps: S1, acquiring an orthoimage of a target area through an unmanned aerial vehicle, and segmenting to generate plant pattern spots; s2, superposing the orthoimage and the base map of the electronic map, and establishing a composite coordinate system; s3, displaying the superposed map on the mobile terminal, and receiving a marking instruction of a user on the pattern spots; when the user cannot identify the plant type, calling a plant identification API to classify the plant image uploaded by the user, and associating the result to the corresponding plant pattern spot; s4, storing the labeled plant data to a database, and supporting statistics and management of the vegetation types, number and distribution of the target area through a geofence function; s5, a visual interface is provided, a user is allowed to check detailed information of the plants by clicking map marks, the detailed information comprises names, photos and statistical results, through the plant classification marking method, the types, the number and the distribution of the vegetation in the statistical area can be systematically analyzed, data are accurate, and presentation is visual.

The invention discloses a method for constructing a three-dimensional geographic entity and a three-dimensional electronic map, which comprises the following steps of: firstly, classifying acquired basic surveying and mapping data based on a constructed multi-level classification framework, and determining an entity category to which each element in the basic surveying and mapping data belongs; then, according to entity category design mapping data corresponding to the elements, converting the mapping data into a geometric mapping relation and an attribute mapping relation of a two-dimensional geographic entity, and through the geometric mapping relation and the attribute mapping relation, converting the mapping data and the attribute information corresponding to the elements into geographic entity geometry and geographic entity attributes; semantized geographic two-dimensional entities are generated to effectively inherit and structurally reuse stock data, and massive waste and repeated construction of data resources are avoided. And then, selecting a corresponding three-dimensional conversion method according to the type of the two-dimensional geographic entity, and converting the two-dimensional geographic entity into a three-dimensional geographic entity. And finally, constructing a corresponding three-dimensional electronic map according to the three-dimensional geographic entities corresponding to all the elements.

The invention discloses a visual drawing method and device for an inland ship navigation trajectory and a medium, and the method comprises the steps: collecting GPS positioning data, AIS dynamic parameters and static attribute data of a ship through a ship terminal, carrying out the preprocessing of the GPS positioning data and the AIS dynamic parameters, and storing the processed data in a database according to a timestamp index; calling a geocoding service interface, mapping the processed longitude and latitude coordinates of the ship to an electronic navigation channel chart coordinate system, and periodically updating a ship position mark in an electronic map interface; in response to a time period query instruction input by a user, extracting ship track point data corresponding to the timestamp sequence from the database, and superposing the ship track point data to the electronic channel chart to generate a dynamic track line; a user operation instruction is received through the time axis control, the ship mark position and the course display state on the trajectory line are dynamically adjusted, and visualized backtracking of the historical trajectory of the ship is achieved.

The invention provides an intelligent robot path scheduling method and system for scenic spot tourists, and relates to the technical field of path scheduling, and the method comprises the steps: obtaining robot position and state information and tourist service request information, and building a scenic spot electronic map; constructing a robot service capability evaluation model; path planning and scoring are carried out, and an optimal service path is selected; selecting the most suitable target service robot; sending the optimal service path to the target robot and loading the optimal service path; the motion trail of the robot is monitored in real time, and the path is dynamically adjusted if necessary. According to the method, the scenic spot service efficiency and tourist experience are improved.

The invention discloses an under-mine environment accurate positioning system based on a UWB technology, and relates to the technical field of data processing and positioning, an underground area is divided into a safe area and a dangerous area by obtaining the structure risk value of each sub-area and combining the structure risk value and the position information of the corresponding sub-area, and the safe area and the dangerous area are accurately positioned. A plurality of rescue robots are arranged in the underground area; acquiring position information of the mobile tag, displaying the position information on an electronic map, generating an air quality coefficient, and dividing the plurality of sub-regions into risk regions and safety regions according to the air quality coefficient; and sending inquiry information to the miner, acquiring a corresponding safety coefficient, and if the acquired safety coefficient is lower than a safety threshold value, planning a support path to the miner for the rescue robot, so that the rescue robot rescues the miner along the support path. After the miner is found according to the position information of the miner, the miner is rescued through guidance of the rescue robot, and the miner is prevented from getting lost and being lost.

The invention relates to a construction method of a foundation pit support structure for replacing polluted soil, which comprises the following steps of: 1, carrying out refined investigation and three-dimensional modeling on a polluted site, and making a three-dimensional electronic map; secondly, pollution removal dynamic planning is conducted, soil layers with different pollution depths and underground water are partitioned through a three-dimensional electronic map, drainage wells are arranged according to the pollution depths of the different partitions, holes are formed through a casing pipe rotary drilling method, and the situation that in the drilling process, the upper layer soil body, the lower layer soil body and the underground water are subjected to layer mixing pollution is prevented; thirdly, earth excavation is accurately controlled; 4, constructing a retaining structure: constructing secant piles and a waterproof barrier outside the pit; 5, hierarchical control of a precipitation system: arranging a drainage well and an emergency precipitation well; and sixthly, staged excavation is conducted, specifically, layered excavation is conducted, and temporary bottom sealing plate construction is completed.

The invention discloses an environmental sanitation cleaning performance evaluation method and system based on work trajectory recognition, and relates to the technical field of intelligent environmental sanitation work management and performance evaluation, and the method comprises the steps: collecting the multi-source trajectory data of environmental sanitation vehicles and personnel, and generating a standardized trajectory data set through time synchronization, abnormality elimination and space registration; on the basis of the standardized trajectory data set, distinguishing an effective operation section and a non-operation section in combination with operation types, and labeling abnormal behaviors to output a recognition trajectory; carrying out overlay analysis on the recognition track and an electronic map, generating a regional operation completion degree, and outputting a space coverage and anomaly statistical result; and calculating a comprehensive performance score according to a regional operation completion degree result. According to the method, the effective operation section and the abnormal behavior are recognized in combination with the operation type, and the operation authenticity judgment precision is improved; and the identification track and an electronic map are superposed to calculate the work completion degree and generate a spatial statistical result, and finally a quantitative performance score is formed, so that automatic evaluation and refined management of the whole process of environmental sanitation work are realized.

The invention relates to a railway electronic map generation method, which comprises the following steps: firstly, determining an aerial survey area and finding out a no-fly range, and then selecting an unmanned aerial vehicle take-off and landing point through field investigation and verifying image quality. In the course planning stage, it is ensured that the image overlapping rate meets the high-precision requirement. Performing aerial survey by using the unmanned aerial vehicle, and acquiring detailed geographic information of the railway yard; the accurate selection and collection of the control points further improve the accuracy of the map. And finally, based on the aerial survey data and the control point data, generating a high-quality railway electronic map. The method has the advantages of high efficiency, high precision, high flexibility and the like.

The invention relates to the technical field of AGV scheduling, and particularly discloses a multi-AGV task scheduling system and method for solving an emergency order insertion problem, and the system comprises a task scheduling module, a path planning module, a real-time monitoring module and a map management module. The task scheduling module realizes multi-objective optimization task allocation based on an improved NSGA-II algorithm, optimizes an initialized population through an NNC (Neighbor Construction) strategy, enhances the global search capability in combination with a 2-opt mutation method, and designs an emergency order insertion strategy to dynamically respond to an emergency task; the real-time monitoring module integrates a MySQL database and a Visual Studio interactive interface, and supports electronic map construction (based on ArcMap10.4), AGV state real-time feedback and task dynamic adjustment; the map management module defines workshop layout and road traffic rules. According to the invention, by fusing the multi-objective optimization algorithm and the dynamic path planning technology, the problem of low efficiency of multi-AGV task allocation is solved, and the logistics efficiency and the system robustness of the track equipment assembly workshop are significantly improved.

The invention relates to the field of combat command and dispatch, in particular to a multistage linkage combat unit command and dispatch system. According to the invention, a basic-level minimum emergency unit element information base is constructed through a data acquisition module; generating an electronic map supporting 2D and 3D switching; an intelligent analysis early warning module identifies abnormal conditions and generates early warning information; a plurality of multi-level linkage combat unit topology networks are generated through the multi-level linkage command architecture module; generating a command data large screen for dynamically aggregating public security indexes and a global situation visualization electronic map through a global situation visualization module; an early warning area is circled and selected through the intelligent scheduling module; and associating the corresponding multi-stage linkage combat unit to generate a deployment instruction. According to the multi-level linkage combat unit command and dispatch system provided by the invention, the multi-level linkage combat unit is effectively combined with a dynamic visual geographical environment from data acquisition, analysis and early warning to command and dispatch through cooperation of multiple modules, so that the command and dispatch efficiency is remarkably improved.

The invention discloses an underground pipeline detection method and system based on multi-source data fusion and intelligent analysis, and belongs to the technical field of pipeline detection. The method comprises the steps of collecting multi-source data of a target area; wherein the multi-source data comprises electromagnetic signal data, electromagnetic wave reflection data and sound wave propagation data; performing filtering and normalization preprocessing on the multi-source data to obtain target data; constructing a multi-source data fusion model to perform feature level fusion on the target data to generate a fusion feature vector; an underground pipeline recognition model based on deep learning is constructed to intelligently analyze and recognize the fusion feature vector, and a recognition result of the underground pipeline is obtained; and marking and displaying the identification result on an electronic map in a visual mode. According to the invention, by fusing data collected by various detection technologies and applying an intelligent analysis algorithm, the accuracy, reliability and efficiency of underground pipeline detection are improved, and the limitation problem of the existing detection technology is solved.