1150 results about "Electric fence" patented technology

The invention provides an unmanned aerial vehicle low-altitude intelligent traffic dynamic airspace management and control method and system, and relates to the technical field of intelligent control, and the method comprises the steps: taking an electronic fence geographic coordinate set as a monitoring reference boundary, fusing ADS-B data, meteorological information and an unmanned aerial vehicle equipment state, generating a real-time risk thermodynamic diagram, and outputting a grading alarm instruction; receiving a real-time risk thermodynamic diagram and a grading alarm instruction, and combining wind speed prediction and dynamic airspace occupation data; when the grading alarm instruction is triggered, executing the following operations: constructing a route feasible solution space by taking a no-fly zone and a high-risk zone in the risk thermodynamic diagram as constraint conditions; and iterating an evolutionary path population through selection, intersection and mutation operations of a genetic algorithm by taking the lowest energy consumption as an optimization target, so as to output a global final obstacle avoidance bypassing path, and issuing a route updating instruction to an unmanned aerial vehicle flight control system. According to the invention, the utilization of airspace resources is maximized on the premise of ensuring safety.

The invention provides a positioning and tracking early-warning method and system for a Bluetooth signal, and relates to the technical field of positioning and tracking, and the method comprises the steps: receiving a Bluetooth signal of a target Bluetooth device through a Bluetooth receiver, correcting a signal feature parameter through a signal attenuation compensation model, and combining the position coordinate of the Bluetooth receiver, the real-time position of the target equipment is calculated through a positioning algorithm, and the real-time position and the corrected signal characteristic parameters are stored in a track database; based on historical trajectory data, a space-time diagram convolutional neural network model is constructed and trained to predict a target trajectory, and an electronic fence is dynamically generated in combination with target activity rule parameters; and generating fence early warning information by comparing the prediction track and the electronic fence boundary, extracting a target behavior feature vector, identifying an abnormal behavior by using a behavior identification model, and generating comprehensive early warning information in combination with the fence early warning information.

The invention provides an all-weather autonomous inspection method and system based on cluster task dynamic load balancing, and relates to the technical field of inspection monitoring, and the method comprises the steps: collecting the remaining electric quantity, the positioning position, the task queue length and the sensor health state of an unmanned aerial vehicle cluster in real time through an airborne terminal; fusing the meteorological data and the multi-source environment sensing data, and constructing a dynamic obstacle map and a meteorological influence model; dividing an inspection area into a plurality of sub-areas based on an electronic fence, dynamically adjusting the inspection priority of each sub-area, setting task weights of a water taking head and a raw water pipeline facility, and distributing inspection tasks according to the priorities; based on the remaining power of the unmanned aerial vehicle, the task priority, the current load and the meteorological data, a bipartite graph matching model of the unmanned aerial vehicle and the task is constructed, the matching weight is dynamically calculated, the optimal matching distribution of the unmanned aerial vehicle and the inspection task is completed, and the efficient inspection operation of the unmanned aerial vehicle cluster in the complex environment is realized.

The invention discloses an unmanned aerial vehicle aerial three-dimensional electronic fence construction method and system, and relates to the technical field of unmanned aerial vehicles, and the method comprises the following steps: dividing the region boundary of an electronic fence in a preset geographic range based on a geographic information system and a three-dimensional modeling technology, and calculating the range of the electronic fence; integrating the configured electronic fence to an unmanned aerial vehicle system, establishing a real-time communication and data exchange channel with the unmanned aerial vehicle, and receiving position information and flight state data fed back in the flight process of the unmanned aerial vehicle in real time; and monitoring the flight state of the unmanned aerial vehicle and the area boundary of the electronic fence in real time, and triggering an early warning mechanism when the unmanned aerial vehicle is found to have a boundary crossing behavior. According to the electronic fence system, the size, shape and position of the fence can be automatically adjusted according to the real-time flight state of the unmanned aerial vehicle and the environment change, the dynamic adjustment capability of the electronic fence is directly improved, and it is ensured that the unmanned aerial vehicle can always fly safely in the complex and changeable airspace environment.

The invention provides a safety early warning method and device for abnormal behavior trajectory analysis and a medium, and relates to the technical field of safety early warning, and the method comprises the steps: collecting behavior trajectory data of a target region through a multi-source sensing device, and carrying out the multi-dimensional feature extraction of a behavior trajectory data set; according to the stay frequency characteristics, carrying out abnormity determination on the track space-time distribution characteristics and the speed change characteristics, and constructing an abnormal behavior determination vector; performing wandering mode recognition based on the abnormal behavior judgment vector, determining an abnormal behavior level, and triggering a graded early warning mechanism according to the abnormal behavior level; and generating an abnormal behavior alarm signal according to the grading early warning mechanism, combining the abnormal behavior alarm signal with the electronic fence information of the target area to generate a safety early warning report, and pushing the report to a monitoring terminal. According to the invention, the technical problem of abnormal behavior recognition accuracy in the prior art can be solved, and the technical effect of improving the behavior judgment accuracy is achieved.

The invention discloses a standard video-in-channel monitoring early warning model method and terminal, and the method specifically comprises the steps: creating a universal video access platform, and configuring an early warning model, specifically, the configuration of the early warning model comprises the steps: analyzing a video stream frame by frame, judging whether an image is abnormal or not, and immediately giving out an early warning by a system once the abnormality is detected, real-time playback or storage of related frames is triggered; the video corresponds to a static wide angle, video analysis is carried out through static background comparison and sound analysis, whether a change occurs is judged, and a change result is recorded; a video middle station realizes deep understanding and alarm management of video contents through an intelligent analysis technology and in combination with multi-dimensional information, an algorithm model is trained and optimized by constructing a positive sample set and an error sample set, configuration is adjusted through a visual interface, and the alarm accuracy and efficiency are improved; dynamic video electronic fence early warning is established, and through real-time monitoring and intelligent analysis, abnormity identification is realized, so that an alarm mechanism is triggered.

The embodiment of the invention discloses a level-to-level management strategy generation method and system for an electronic fence based on a 5G base station iron tower, and the method comprises the steps: collecting a multi-source heterogeneous monitoring data set covering an electronic fence warning region through sensor arrays disposed at different monitoring point positions of the 5G base station iron tower; the data comprise environment sensing data and target motion data; performing space-time correlation fusion processing on the data set to generate a basic analysis data set, determining a space relative relationship between the target motion data and the electronic fence boundary and potential influence of environment perception data on the motion behavior of the target object based on the basic analysis data set, and generating risk assessment information; a hierarchical management strategy is made according to the risk assessment information, strategy execution parameters are adjusted by continuously tracking a behavior evolution process of a target object in an electronic fence warning area to realize optimization iteration, and the accuracy and adaptability of electronic fence management are improved.

The invention discloses an anti-drowning early warning system of a self-adaptive dynamic virtual electronic fence, and aims to solve the problems that an existing anti-drowning early warning system cannot adapt to water level changes and early warning lags behind. The virtual electronic fence setting module is used for setting static and dynamic virtual electronic fences, identifying and analyzing personnel behaviors and controlling alarms; the data acquisition module is used for acquiring environment data information and video monitoring information; and the data storage module is used for storing data, alarm information, virtual electronic fence setting information and water level change information of the virtual electronic fence according to the water level change adjustment range. The system is based on real-time detection of a YOLOv8 model and is combined with a virtual electronic fence technology, has the characteristics of high-precision identification, low-delay response, field environment adaptability and the like, can effectively reduce the occurrence rate of drowning accidents, and is a set of intelligent, efficient and convenient-to-maintain system.

The invention discloses a personnel trajectory drawing method and system based on an AI algorithm. The method comprises the following steps: acquiring a positioning equipment signal and monitoring video data; performing dynamic Kalman filtering denoising processing on the positioning equipment signal to obtain first track data, and performing adaptive illumination compensation enhancement processing on the monitoring video data to obtain first video data; performing trajectory prediction compensation on the signal interruption segment based on an LSTM neural network; personnel motion posture features and scene semantic features are extracted; constructing a space-time correlation graph by adopting a graph convolutional neural network to obtain enhanced trajectory data; performing multi-scale trajectory reconstruction based on an improved Transform architecture to generate final personnel trajectory information; and outputting a visual trajectory report including trajectory precision evaluation, abnormal behavior marking and an electronic fence trigger event. According to the method, deep fusion of multi-source heterogeneous data and accurate reconstruction of the trajectory are realized, and continuity and reliability of personnel trajectory drawing in a complex scene are remarkably improved.

The present disclosure an electric fence device, including a transmitter and at least one receiver. The transmitter includes a first integrated circuit board; wherein, the first integrated circuit board is arranged with a first radar module and a first wireless transceiver module. The at least one receiver is configured to be worn on a pet. The receiver comprises a second integrated circuit board; the second integrated circuit board is arranged with a second radar module and a second wireless transceiver module. The first radar module and the second radar module are communicatively connected to each other perform measurement signal transmission to determine a location of the pet; the first wireless transceiver module and the second wireless transceiver module are communicatively connected to each other to perform instruction signal transmission and data feedback.

The invention relates to the technical field of automobile Bluetooth control, in particular to an automobile Bluetooth control method and system based on a keyless entry mode. According to the method, the dynamic behavior time sequence of each Bluetooth device in the vehicle-mounted Bluetooth sensing area of the automobile is compared and analyzed, the candidate Bluetooth device with the control intention is screened out, and the recognition accuracy is improved; the real-time signal intensity, historical user operation behavior data and equipment trust level of the candidate Bluetooth equipment are comprehensively considered, and the control priority of each candidate Bluetooth equipment is fused and analyzed, so that flexible and accurate authority management is realized; selecting the candidate Bluetooth device with the highest control priority as an authorized Bluetooth device to establish a communication link and distribute the automobile Bluetooth control authority to ensure the reasonable distribution of the control authority; when the automobile runs, the real-time position of the authorized Bluetooth device is obtained, the Bluetooth device control authority corresponding to the automobile Bluetooth is dynamically adjusted by combining the corresponding electronic fence boundary of the automobile, and potential safety hazards are effectively reduced.

The invention discloses an intelligent security and protection management system based on 5G, AI and UWB positioning technologies. The intelligent security and protection management system comprises an image video acquisition device, an environmental factor acquisition device, a UWB positioning module, a 5G communication network module and an intelligent security and protection management platform, the intelligent security and protection management platform comprises an AI video identification subsystem, a cockpit subsystem, a virtual electronic fence subsystem, an operation risk security management and control subsystem, an operation ticket visa subsystem, a video linkage subsystem and a query statistics subsystem. The intelligent security and protection management system based on the 5G, AI and UWB positioning technologies has the advantages of high-precision positioning technology, intelligent video analysis, highly integrated system architecture, flexible expansibility and customizability, safe and reliable data transmission and storage and the like.

The invention relates to the technical field of intelligent traffic monitoring, in particular to a toll station pedestrian and non-motor vehicle intrusion intelligent early warning system and method, a terminal layer comprises a sensing terminal composed of a camera, a hard disk video recorder and the like, and an early warning terminal composed of a directional sound post and the like; an edge computing unit is deployed on the edge layer, targets are detected in real time, tracks are tracked and classified, and cloud rechecking is triggered by low-confidence targets; the cloud layer utilizes a visual language large model to recheck a target, pre-mark data, generate an electronic fence and store data; the system adopts a dynamic grading early warning module, three-level early warning is triggered according to a target track, a position and staying time, and automatic degradation is carried out along with the presence of a worker; in addition, through a closed-loop optimization mechanism, a positive / false alarm feedback iteration visual small model is collected. According to the invention, cloud side-end cooperation is realized, multiple models and algorithms are fused, high-precision detection, real-time response, dynamic self-adaption and self-optimization capabilities are realized, the intrusion risk can be effectively prevented, and the safety management level of the toll station is improved.

The invention provides a leasing equipment full life cycle monitoring method and system based on the Internet of Things, and belongs to the technical field of equipment operation and maintenance monitoring, and the method comprises the steps: obtaining real-time state data of leasing equipment in an operation process through a multi-source sensor; performing feature extraction on the real-time state data to obtain various feature vectors, and constructing a multi-dimensional feature vector set; inputting the multi-dimensional feature vector set into a random forest model, and judging whether the leasing equipment is in an abnormal state or not in combination with a space-time clustering algorithm; if yes, fault prediction is carried out on the leasing equipment in combination with an abnormal detection result, historical operation data and a baseline model, and a fault probability value of the leasing equipment is obtained; the future position of the leasing equipment is predicted based on the position data, an electronic fence boundary is set for the leasing equipment, if the future position exceeds the electronic fence boundary, an early warning notification of trajectory deviation is generated, and the system finally realizes trajectory and fault visual presentation in a thermodynamic diagram mode, so that the equipment operation and maintenance intelligence and management precision are improved.

The invention discloses a channel electronic fence calculation method and system based on an unmanned aerial vehicle. The method comprises the following steps: setting a channel basic fence according to geographic features of a channel; setting a lowest fence standard according to ship attributes; fusing the navigation channel basic fence and the lowest fence through a label priority mechanism to obtain a navigation electronic fence of the ship; acquiring channel monitoring data through an unmanned aerial vehicle group to obtain a real-time monitoring label; and dynamically adjusting the navigation electronic fence based on a preset rule engine and the real-time monitoring tag. According to the invention, dynamic adjustment of fence parameters is realized through linkage of the real-time monitoring label and the rule engine in cooperation with the unmanned aerial vehicle group; customizing a core protection area according to different types, loading states and maneuvering performance of cargo ships, passenger ships and the like; by constructing a multi-dimensional label system, multi-source data is converted into labels with unified semantics, and deep data fusion is achieved; and a machine learning model is introduced to dynamically calibrate the label, and a label system and a calibration rule are optimized.

The invention relates to a chemical plant dangerous area electronic fence generation method and system, and the method comprises the steps: obtaining the positioning data of a target person, the positioning data of production equipment, and the video monitoring data and environment sensing data of a target area, carrying out the recognition based on the video monitoring data, and obtaining the behavior data of the target person, the method comprises the steps of dividing a target area into virtual grids based on a dynamic grid algorithm, determining distribution of geographic features based on GIS geographic information of the target area, filtering impassable areas based on the distribution of the geographic features, aggregating and combining adjacent grids, generating a closed boundary, and establishing a risk level evaluation model to evaluate the risk level of each virtual grid. The boundary adjusting module is used for adjusting the minimum buffer area width of the closed boundary to obtain a final electronic fence boundary, and the electronic fence boundary is used for carrying out risk early warning. According to the invention, dynamic and accurate sensing and protection of the high-risk area in the chemical plant are realized.

The present invention relates to the field of electronic fence technology, specifically to an electronic fence monitoring method and system for unmanned aerial vehicles, comprising the following steps: based on the real-time positioning data of the unmanned aerial vehicle, by analyzing the positioning changes of the unmanned aerial vehicle within a period of time, calculating the flight speed of the unmanned aerial vehicle, and analyzing the change trend of the flight speed of the unmanned aerial vehicle according to the flight speed data of the unmanned aerial vehicle within a period of time, and obtaining the speed information of the unmanned aerial vehicle. The present invention can analyze the distance between the unmanned aerial vehicle and the electronic fence in real time and estimate the crossing time by continuously tracking the flight speed and flight direction, thereby providing scientific data support for preventing potential safety risks, and by adjusting the warning threshold and matching the reaction time of the operator, improving the adaptability and practicality of the early warning, making the warning more timely and effective, significantly reducing the possibility of false alarms and missed alarms, enhancing the response speed and accuracy of the unmanned aerial vehicle electronic fence system, and effectively preventing the illegal flight of the unmanned aerial vehicle and the occurrence of safety accidents.

The invention discloses an electronic fence positioning method and system applied to low-altitude flight control, and belongs to the technical field of data analysis. According to the embodiment of the invention, the low-altitude flight fence space is constructed and the flight early warning quantitative characteristics are set, so that the fine management basis of low-altitude flight is realized. The electronic fence monitoring route and the space-time cross sensing data thereof are acquired to determine the local management and control area, so that airspaces with different functions and risks can be accurately focused, and the management and control efficiency is improved. Alarm data of different monitoring routes are determined according to flight early warning quantitative characteristics, differences of tasks of different routes in the same area are considered, the method can adapt to complex and diversified flight scenes, and misjudgment is reduced. And after the trigger condition is responded, the monitoring risk decision feature is determined and the flight is controlled, so that the abnormal condition of the low-altitude aircraft can be handled in time in a targeted manner, the safety and orderliness of the low-altitude flight are effectively ensured, and potential threats to specific areas (such as airports and activity sites) are avoided.

The invention discloses a safety early warning method and system based on Beidou + UWB positioning, and relates to the technical field of personnel positioning and safety early warning, and the method comprises the steps: collecting positioning signal data in real time, and carrying out the preprocessing; based on real-time quality evaluation of a positioning signal source, adaptively adjusting a fusion weight, and generating a continuous high-precision positioning data sequence; predicting a future motion trail by using the trail prediction model, performing border crossing judgment in combination with electronic fence spatial data, and outputting a border crossing prediction mark; performing risk analysis by taking the track sequence and the border crossing mark as input and combining the spatial distance between the personnel and the electronic fence, the movement speed and the regional risk level, and outputting a risk score and a level mark thereof; and performing graded response according to the risk grades, and recording and feeding back safety early warning data. According to the invention, high-precision continuous positioning in a complex environment is realized, personnel border-crossing active early warning and risk grading response are supported, and the real-time performance, the accuracy and the intelligent level of safety supervision are remarkably improved.

The invention belongs to the technical field of network switching, and discloses a mine scene-oriented wireless network flexible switching method and system, and the method comprises the steps: analyzing signal information through employing a beam forming optimization algorithm, and obtaining an optimal beam forming scheme; determining the position of the current mobile terminal; establishing a final communication connection based on the network switching demand, and terminating the initial communication connection; and dynamically adjusting the beamforming scheme according to a preset algorithm and the priority list. According to the invention, adaptive network switching and user label definition are carried out based on the combination of the beamforming technology, the electronic fence information of the Internet of Things and the positioning data, so that network switching is smoother, and signal interruption and network quality reduction caused by frequent switching are avoided.

The invention discloses a muck truck behavior research and judgment method, device and equipment based on virtual electronic fences, and relates to the technical field of vehicle state monitoring, the method comprises the following steps: obtaining real-time coordinate data of different sites, and generating dynamic electronic fences of the different sites according to the real-time coordinate data of the different sites; processing the multi-source driving data of the muck truck, and analyzing and recording the real-time driving state of the muck truck in combination with the dynamic electronic fences of the different sites; and based on the real-time driving state of the muck truck and the dynamic electronic fences of the different sites, studying and judging whether the muck truck has illegal behaviors or not. By establishing the dynamic electronic fence, a supervision blind area caused by mismatching of a traditional fence and a dynamic scene is solved, multi-source driving data is fused, the composite violation problem that a single data source is difficult to find is solved, matching calculation is performed on the driving state, violation behaviors are found immediately, evidence is stored immediately after finding, and the driving safety is improved. And the response time from behavior occurrence to supervision intervention is remarkably shortened.

A wireless electronic fence is worn on a pet and includes: a positioning assembly, a signal detection assembly, a warning assembly, and a master control circuit. The positioning assembly receives a first signal sent by an external terminal, determines a position of the positioning assembly based on the first signal; and outputs a position detection signal. The signal detection assembly detects a signal strength of the first signal and outputs a signal strength detection signal. The master control circuit receives the signal strength detection signal; compares the signal strength of the first signal carried in the signal strength detection signal with a preset signal strength to produce a comparison result; and controls the warning assembly to operate or to stop operating according to the comparison result.

The invention discloses a human-hat matching method, system and equipment based on an intelligent safety helmet, and relates to the technical field of biological feature recognition, and the human-hat matching method based on the intelligent safety helmet comprises the steps: determining a matching strategy according to a working area where the intelligent safety helmet is located; receiving a human-hat matching instruction, and generating a voice prompt-data acquisition instruction according to the matching strategy and the human-hat matching instruction; the voice prompt-data acquisition instruction is sent to the intelligent safety helmet located in a working electronic fence coverage area, so that the intelligent safety helmet sends a preset voice prompt and feeds back acquired identity data, and the intelligent safety helmet is in a power-on state and a wearing in-place state; and carrying out human-hat matching according to the matching strategy and the identity data to obtain a human-hat matching result. According to the invention, people-hat matching can be accurately carried out in construction areas under various working conditions, and the construction safety management level is effectively improved.

The invention belongs to the technical field of intelligent traffic monitoring, and relates to a vehicle track intelligent GIS electronic fence visualization system based on a GPS, and the system comprises a track data collection module which is used for obtaining the historical driving track point data of a plurality of vehicles in a preset time period; the aggregation area identification module is used for identifying a high-frequency aggregation area of the historical driving track point data; the elastic fence generation module is used for expanding a dynamic buffer area outwards by taking the boundary of the high-frequency aggregation area as a reference; the border crossing state judgment module is used for calculating the spatial relationship between the real-time position of the vehicle and the elastic electronic fence; the behavior analysis module is used for identifying repeated border-crossing road sections and high-incidence time periods; and the multi-source visualization module is used for overlapping and displaying the elastic electronic fence layer, the real-time vehicle position marking layer and the border-crossing thermodynamic layer on the GIS map. The problem that a closed-loop optimization mechanism based on data feedback cannot be formed is solved.

The invention relates to the technical field of sensor measurement, in particular to an intelligent water area virtual electronic fence based on acousto-optic-electric fusion. The system specifically comprises a water area sensor fusion network, a water area interface fluctuation feature extraction unit, an intrusion probability prediction unit and a self-adaptive alarm response unit. The water area sensor fusion network is used for capturing a sound wave signal, an optical signal and an electromagnetic signal in a target water area, and performing dynamic attenuation correction according to physical characteristics of water to obtain a fusion sensing result; the water area interface fluctuation feature extraction unit is used for extracting fluctuation energy spectrum density related to water disturbance at each frequency; the intrusion probability prediction unit is used for calculating the current anomaly metric and predicting the intrusion probability of each position in the target water area; and the adaptive alarm response unit is used for calculating the current alarm intensity of each position and executing an early warning strategy. According to the invention, high-probability intrusion threats can be rapidly identified and amplified.

The invention discloses a vertical management system for concrete production, transportation and pouring, and the system is characterized in that a concrete production task management system judges production demands according to a project concrete production plan and field demand feedback, and automatically arranges the production tasks of all concrete mixing stations according to the number of the mixing stations, the production capacity, the field demand condition and the concrete mix proportion; the concrete transportation management system obtains the position information of the equipment, determines the position information of the equipment according to the electronic fence data of the delimited area, judges the operation state of the equipment according to the change of the position information of the equipment, determines the operation efficiency information according to the state change, and issues a scheduling instruction; according to the concrete pouring management system, concrete sign-in judgment and pouring point pouring strength calculation are achieved through a sign-in judgment algorithm according to the position relation between the mixing truck and the pump truck, cluster dispatching management of a large number of equipment and facilities in concrete production, transportation and pouring sites can be achieved, and the production efficiency of dispatching operation is improved.

The invention relates to the technical field of geological data acquisition, and particularly discloses a lossless field real-time acquisition method and system for field data of land quality, and the method comprises the steps: receiving control information inputted by a manager, and creating a dynamic form; determining a sampling point position based on the pattern spot pattern, and synchronously determining an electronic fence of the sampling point position; and sending the sampling point position to the handheld end, obtaining the position of the handheld end in real time, sending the dynamic form to the handheld end when the position is included in the electronic fence, and obtaining land sampling data containing the height based on the dynamic form. According to the method, a management personnel-oriented platform is established, a dynamic form establishment environment is provided, and the form established by the management personnel is received, so that front-line sampling personnel can carry out data filling according to the form and convert an original handwriting mode into a selection mode or a typing mode, and the interaction efficiency is greatly improved.

The invention provides an unmanned container truck intersection identification method based on map data, and the method comprises the steps: 1, adding the longitudes and latitudes of four vertexes of an electronic fence on an unmanned platform, and constructing an intersection electronic fence; step 2, performing one-to-one correspondence on the intersection electronic fences and intersection areas in the map data of the unmanned container truck operation area; 3, the unmanned container truck sends the vehicle message to the unmanned driving platform in real time; step 4, selecting lane lines associated with the intersection area in the vehicle path planning lane line set; step 5, judging whether the current lane line of the vehicle is a lane line associated with the intersection area or not, and if so, judging whether the distance between the unmanned container truck and the intersection electronic fence corresponding to the intersection area is smaller than a threshold value or not according to the real-time latitude and longitude information of the vehicle; and step 6, if yes, determining that the current driving vehicle arrives at the intersection. The technical problems that the prior art cannot be suitable for scene migration and the implementation cost is high are effectively solved.

The invention relates to an electronic fence detection method and device, computer equipment and a readable storage medium. The method comprises the following steps: constructing a spatial index of an electronic fence corresponding to a target area to be detected, performing positioning monitoring on each target object based on the target area, and constructing each point object for querying in the spatial index; according to the spatial index of the electronic fence, screening out a plurality of associated fence areas corresponding to each point object; obtaining a position judgment result of any point object by judging a position relationship between any point object and the corresponding multiple associated fence areas, and determining a buffer area detection result of any point object according to buffer area configuration information of the multiple associated fence areas corresponding to any point object; and in combination with the position judgment result of each point object and the buffer area detection result, obtaining the position state of each target object in the target area. By adopting the method, the calculation amount of position judgment can be reduced, and the accuracy and processing efficiency of electronic fence detection are improved.

The invention discloses a three-dimensional dynamic safety management and control method and system for power transmission and transformation hoisting operation, and relates to the technical field of construction safety, and the method comprises the steps: obtaining point cloud data of a target operation area through ground three-dimensional laser scanning; according to the point cloud data, a three-dimensional grid model is constructed through an oblique photography technology and a Beidou real-time dynamic carrier phase difference technology, and a semantic electronic fence is generated; according to a pure vision technology, through target detection, three-dimensional reconstruction and time sequence tracking, a hanging object 4D digital branch is constructed, and a hanging object prediction track is obtained; the shortest three-dimensional distance is calculated through an efficient collision detection algorithm according to the hanging object prediction track and the semantic electronic fence, multi-dimensional risk assessment is carried out, and graded early warning signals are generated; and carrying out comprehensive alarm prompting according to the graded early warning signal. According to the invention, a traditional passive protection mode depending on single threshold alarm is changed, and quantitative evaluation and predictive management and control of dynamic risks are realized.