366 results about "Gps data" patented technology

The invention discloses an unmanned aerial vehicle trajectory tracking system based on multi-sensor fusion, which relates to the technical field of unmanned system autonomous navigation and control, and comprises an unmanned aerial vehicle data acquisition module, an unmanned aerial vehicle feature extraction module, a trajectory prediction deviation scoring module, a trajectory dynamic correction module and a trajectory monitoring module. The unmanned aerial vehicle data acquisition module acquires and preprocesses unmanned aerial vehicle and GPS data, the unmanned aerial vehicle feature extraction module constructs a trajectory tracking feature sequence table, the trajectory prediction deviation scoring module outputs three-dimensional trajectory prediction coordinates and deviation scores, and the trajectory dynamic correction module generates correction parameters. Based on the judgment logic, the judgment logic is converted into an unmanned aerial vehicle correction instruction and attitude feedback quantity, and the track monitoring module constructs a visual interface. According to the method, the trajectory tracking precision of the unmanned aerial vehicle in a complex environment is remarkably improved, real-time detection and dynamic correction of abnormal deviation are realized, the state monitoring capability is enhanced by a three-dimensional visual interface, the trajectory tracking error is reduced, the misjudgment rate is reduced, and the flight safety and the control efficiency are guaranteed.

The invention relates to the technical field of aviation communication, and discloses a true north calibration system and method for an aviation airborne laser communication equipment alignment system, and the method comprises the steps: synchronously collecting flight data through an IMU sensor and a double-antenna GPS at a preset sampling frequency, and outputting the real-time attitude angle information of an aircraft through an IMU; filtering and de-noising the synchronously acquired IMU and double-antenna GPS data, and carrying out noise suppression and deviation compensation on accelerometer and gyroscope data output by the IMU by adopting a Kalman filtering algorithm; based on the preprocessed sensor data, calculating an initial course angle by measuring relative position change and phase difference between antennas by using a double-antenna GPS (Global Positioning System); the calibration controller transmits the calculated true north direction information to an alignment system of the laser communication equipment in real time through a communication interface; and the attitude change and external environment disturbance of the aircraft are continuously monitored in the whole flight process. The method has the advantage that the alignment performance and the communication stability of the laser communication equipment are improved.

A self-adaptive multi-sensor fusion method using radar, laser radar, IMU and GPS in a complex environment comprises the following steps: receiving radar point clouds, and preliminarily distinguishing dynamic point clouds and static point clouds in a single frame; the dynamic point cloud and the static point cloud are processed respectively, and the absolute speed of the robot is obtained; receiving point cloud data through the laser radar, and performing time synchronization and space calibration on each frame of data of the millimeter wave radar and the laser radar; dynamic points in each frame are removed in real time, and laser radar point cloud data only containing static points and static millimeter wave radar point cloud data are obtained; geometric feature extraction is carried out on the static laser radar point cloud data, and whether the robot enters a degradation area or not is judged; laser radar or millimeter-wave radar point cloud data are selected according to the number of feature points of the laser radar point cloud for matching of scanned sub-maps; the pose and the speed of the robot are obtained through a GPS, the reliability of GPS data is judged through the speed estimated by the millimeter wave radar and the pose obtained by the front-end odometer, the weight of the GPS data in rear-end optimization is determined by calculating the residual error of the speed estimated by the millimeter wave radar and the pose obtained by the front-end odometer, and the weight is added into a factor graph to be jointly optimized with the front-end odometer.

The invention relates to the technical field of image processing, in particular to an irrigation prescription map inversion method based on unmanned aerial vehicle spectrum data. The method comprises the following steps: carrying out unmanned aerial vehicle data acquisition on a farmland area to obtain a multispectral image, DEM data and meteorological interpolation data; performing micro-landform parameter calculation according to the multispectral image, DEM data and unmanned aerial vehicle GPS data, and constructing a terrain-spectrum coupling model to obtain a terrain relief degree map and the terrain-spectrum coupling model; performing vegetation multi-dimensional state analysis by using a terrain-spectrum coupling model to obtain a vegetation index map, a canopy temperature map and a water stress preliminary judgment map; performing net radiation calculation by using the meteorological interpolation data to obtain a net radiation diagram; according to the net radiation diagram, the vegetation index diagram and the topographic relief degree diagram, soil heat flux estimation is conducted, and a soil heat flux diagram is obtained. According to the method, collaborative inversion is carried out by eliminating the terrain effect, and the precision and reliability of irrigation prescription map inversion are improved.

The disclosed invention provides a system and method for processing air traffic control (ATC) communications to ensure real-time validation of aircraft operations and improve pilot logbook accuracy. The system receives ATC voice communications through a digital radio system, converts them to text using a natural language processing model trained on aviation terminology, and extracts key operational data, including aircraft identifiers, instructions, and corrections. This data is correlated with Automatic Dependent Surveillance-Broadcast (ADS-B) and GPS data to verify compliance with ATC instructions. The system creates a continuous transcript of ATC-pilot communications, stitching together conversations across multiple frequencies. Deviations from ATC instructions are detected, generating alerts and logging the events. The method further provides automated reporting, archiving of communications, and enhanced safety metrics in immutable pilot logbooks, using blockchain technology for secure storage. This invention improves operational safety, transparency, and flight data integrity.

Disclosed herein is a method of transmitting a BSM message of V2X communication device provided in a vehicle in an autonomous driving system. The method of transmitting a BSM message of a V2X communication device according to an embodiment of the present invention may multiplex sensor data and GPS data received from in-vehicle sensors, respectively, and use the multiplexed sensor data to generate BSM data. As a result, it is possible to enhance stability of the V2X system and more efficiently correct errors or the like occurring between sensors.An autonomous vehicle according to the present invention may be linked with an artificial intelligence module, a drone (unmanned aerial vehicle (UAV)), a robot, an augmented reality (AR) device, a virtual reality (VR) device, devices related to 5G services and the like.

The invention relates to a positioning method and system based on adaptive multi-sensor fusion, belongs to the technical field of positioning, and aims to solve the problems of low positioning precision and poor stability in a complex environment in the existing positioning technology. According to the method, a VIW system and a GPS are deeply fused, and the advantages of all sensors are effectively integrated. The method comprises the following steps: firstly, evaluating, correcting and screening GPS data through an improved GPS precision factor model and an anomaly detection model based on fuzzy logic and statistical learning; and secondly, acquiring a local pose estimation result by using the VIW system, and realizing time synchronization of the GPS and the VIW system through a time difference compensation strategy. And finally, constructing an optimization objective function containing a VIW system residual term and a GPS residual term, and updating the transformation matrix of the VIW system and the GPS coordinate system. The method is suitable for the positioning requirements of intelligent robots, pilotless automobiles and other equipment in urban canyons, tunnels, indoor and long-distance and high-dynamic scenes.

The invention provides a traffic state data interpolation method and device, electronic equipment and a readable storage medium, and the method comprises the steps: obtaining original GPS data, carrying out the preprocessing of the original GPS data to obtain a preprocessed vehicle track data set, and generating a traffic speed tensor based on the preprocessed vehicle track data set; based on the traffic speed tensor, constructing a heterogeneous graph attention network model considering space and time factors in space and time perspectives; utilizing the heterogeneous graph attention network model to extract potential features of a space view angle and a time view angle, and performing feature fusion on the potential features to perform interpolation of missing traffic state data; and outputting an interpolation result of the traffic state data so as to realize accurate estimation of missing data. According to the invention, through fusion of space and time heterogeneous features, robust interpolation can be provided for the traffic state under different missing proportions, so that the traffic state can be predicted more accurately.

A battery control component of an electric vehicle may limit charging of a battery on the electric vehicle to a target state of charge (SOC), such as to reserve battery capacity for regenerative braking during downgrades. A computing device associated with the vehicle may calculate an estimated gradient profile and / or an estimated total energy consumption of a predicted upcoming route of the vehicle based on one or more data items, such as GPS data, altitude data, and / or map data. The computing device may determine a target SOC based on the estimated gradient profile. The computing device may determine a confidence factor associated with the estimated gradient profile, where the confidence factor depends on the quantity of data items used to calculate the estimated gradient profile. The computing device may adjust the target SOC based on the confidence factor.

The invention discloses an unmanned aerial vehicle delivery bidirectional authentication method and device based on implicit gait behaviors. A user places an order through a mobile phone delivery application program. After arriving at a designated place, the unmanned aerial vehicle hovers in the air, notifies a user of arrival of the unmanned aerial vehicle, and then establishes a key-protected communication channel with a mobile phone of the user. And the user holds the mobile phone and walks towards a specified position. And the unmanned aerial vehicle confirms the real-time position of the user through the shared GPS data, and searches the user by using a camera. Meanwhile, the unmanned aerial vehicle captures a user video and processes the user video in real time, and extracts a time sequence of user body key points; meanwhile, the mobile phone of the user continuously collects time series data from the IMU sensor. The two data are then exchanged between the drone and the user's mobile phone, thereby initiating a mutual authentication process. According to the invention, mutual identity verification is realized by using the hand movement mode when the user moves to the unmanned aerial vehicle, additional hardware or specific identity verification operation is not needed, and strong resistance to various spoofing attacks is shown.

The invention discloses a shared bicycle dangerous behavior identification method based on GPS trajectory data tracking, and belongs to the technical field of traffic safety. Comprising the steps of abnormal point elimination, point supplementation, coordinate system unification and normalization so as to improve data accuracy, and clustering division is carried out on data according to data features; in combination with a road network and POI data, hotspot and non-hotspot areas are determined through track intensity analysis; six dangerous behaviors are defined, historical data are analyzed, a threshold value is set, a predefined method is used for recognizing dangerous driving behaviors, and finally a recognition model is established to achieve accurate recognition of the six dangerous behaviors. Through mathematical statistics, the riding characteristics and dangerous behavior characteristics of the shared bicycle under different conditions are compared and researched; according to the dangerous behavior identification method based on the shared bicycle GPS track data, the utilization rate of the shared bicycle GPS data can be effectively improved, dangerous behaviors can be accurately identified, and the safety of riders and other traffic participants is guaranteed.

Methods, apparatuses, and computer-readable media for providing a pedestrian-oriented navigation app for a mobile device. Destination information is received from a pedestrian using a mobile device. The mobile device retrieves pedestrian-oriented mapping data and routing for the navigation of the pedestrian to the destination, determines a current location and direction of the pedestrian based upon GPS data and compass data retrieved from the device, and displays the current location and direction of the pedestrian along with a route for the pedestrian to the destination on the user interface of the mobile device based on the pedestrian-oriented mapping data and routing. If the mobile device detects that the pedestrian has deviated from the route, the mobile device alters the display on the user interface to alert the pedestrian to the deviation.

Techniques are described for using data capture devices at a building to automatically generate a building floor plan and to determine associated absolute location data for the generated floor plan, such as by associating separately captured GPS data or other absolute location data with the floor plan. In some situations, a building floor plan is automatically generated by analyzing visual data of images captured at multiple image acquisition locations by a camera device to determine room shapes of surrounding rooms, and GPS absolute location data is associated with the generated floor plan using additional data captured at other data capture locations at the building by a separate mobile device that moves independently from the camera device, such as by extending the absolute location data from the mobile device to the camera device's image acquisition location and its surrounding room shape.

The invention relates to the technical field of geo-fence triggering, in particular to a multi-mode positioning data fused GEO fence triggering method and triggering system. The method comprises the following steps that according to the distance between equipment and the fence boundary, a layered positioning strategy is adopted to demarcate a safe area, a transition area and a critical area; when the device is located in the safe area, outputting a coarse position coordinate of the device and a corresponding coarse positioning confidence coefficient by adopting a low-power-consumption coarse positioning algorithm; when the equipment is located in the transition area, fusing the GPS data and the IMU data by adopting an adaptive fusion algorithm to obtain an intermediate fusion position, an intermediate fusion speed and an intermediate positioning confidence coefficient; fusing the multi-modal data when the equipment is located in the critical zone, and predicting the probability that the equipment invades the fence by combining a trajectory risk assessment algorithm based on the equipment acceleration and the distance between the equipment and the fence boundary. Through hierarchical positioning strategy and multi-modal data fusion, the problems of insufficient precision and high power consumption of a single positioning mode in a complex scene are solved.

A system receives, from a plurality of connected vehicles, respective GPS data indicating an absolute location of a respective connected vehicle and on-board sensor data indicating locations of nearby vehicles and objects relative to the respective connected vehicle. The system processes the data to create a shared-world model that includes at least the locations of the plurality of connected vehicles and the nearby vehicles and objects. Some implementations of the shared-world model further include the speeds and trajectories of each of the plurality of connected vehicles and the nearby vehicles and objects. The system transmits a representation of the shared-world model to one or more of the plurality of connected vehicles, which may utilize the shared-world model to provide advanced warnings for drivers or to provide improved path planning for autonomous vehicles. Some representations of the shared-world model include lane-level traffic functions such as traffic density, traffic speed, and traffic throughput.

Methods, apparatuses, and computer-readable media for providing a pedestrian-oriented navigation app for a mobile device. Destination information is received from a pedestrian using a mobile device. The mobile device retrieves pedestrian-oriented mapping data and routing for the navigation of the pedestrian to the destination, determines a current location and direction of the pedestrian based upon GPS data and compass data retrieved from the device, and displays the current location and direction of the pedestrian along with a route for the pedestrian to the destination on the user interface of the mobile device based on the pedestrian-oriented mapping data and routing. If the mobile device detects that the pedestrian has deviated from the route, the mobile device alters the display on the user interface to alert the pedestrian to the deviation.

The invention relates to the technical field of online water quality intelligent monitoring scheme design, in particular to an online water quality intelligent monitoring method and system and electronic equipment. The method comprises the following steps: acquiring GPS data, water temperature data, PH data, dissolved oxygen content data and conductivity data of a target point location of a target water area within a preset duration according to a preset time interval through a GPS sensor, a water temperature sensor, a PH sensor, a dissolved oxygen sensor and a conductivity sensor which are arranged at the target point location of the target water area, and acquiring timestamp data; the online water quality intelligent monitoring model is trained, whether the water quality data of the target water area is abnormal or not is judged, overall online evaluation and judgment on the overall water quality data of the target water area are achieved, whether the overall water quality data of the target water area is abnormal or not is accurately judged, and the safety, reliability and intelligent degree of water quality detection are improved to a great extent. The intelligent degree and usability of the system are improved to a great extent, and the application scenarios of the system are greatly expanded.

A system and method attest the veracity of audiovisual depictions by inferring motion of the device recording those depictions from the audiovisual data, and comparing this inferred motion with contemporaneously sampled sensor data from that device, such as accelerometer or GPS data. If the inferred motion sensibly corresponds to changes in the other sensor data, then the video is determined to be authentic. Otherwise, an anomalous condition is signaled, altering the viewer that the video may have been digitally altered.

The embodiment of the invention provides a geographic information system (GIS) modeling method and device, electronic equipment and a medium, and the method comprises the steps: collecting video image data of a target area, recording the latitude and longitude coordinates of a collection position, carrying out the extraction of a key frame, carrying out the denoising processing, extracting the image feature points of the key frame, and carrying out the feature matching, determining a relative position between the key frames; the method comprises the following steps of: calculating a space coordinate of each image feature point by utilizing matched image feature points and GPS data of acquisition equipment, generating point cloud data, performing 3D Gaussian Splitting operation on each point in the point cloud data by applying a Gaussian weighting function to obtain an integral Splitting operation result, and reconstructing a three-dimensional model through the integral Splitting operation result to obtain a three-dimensional model. Smooth processing is carried out to optimize the surface quality of the three-dimensional model; and importing the reconstructed three-dimensional model into a GIS (Geographic Information System), managing model data by using a spatial database, and placing the three-dimensional model at a corresponding position in the GIS by using latitude and longitude coordinates.

The invention relates to the field of rocket recovery pose estimation design, and particularly discloses a multi-mode cooperative perception driven rocket recovery high-precision pose estimation system, which comprises a multi-scale Marker layout module, a multi-scale cooperative perception driven rocket recovery high-precision pose estimation module and a multi-scale cooperative perception driven rocket recovery high-precision pose estimation module, and is characterized in that the multi-scale Marker layout module is used for arranging three-level height detection bands around a recoverer device, and each band is configured with Marker type layout modes of different sizes; the multi-view cooperative detection module is used for collecting images through a plurality of high-resolution cameras installed on the side face of the rocket and outputting visual poses in combination with scale adaptive detection process optimization and a space consistency constraint strategy; the multi-sensor fusion module is used for performing fusion optimization on the visual pose, the IMU and the GPS data through a factor graph to construct a factor graph joint optimization framework; accuracy and stability of a rocket recovery pose estimation system are realized, and real-time performance, accuracy and anti-interference capability of a rocket recovery pose estimation scheme are improved.

In some implementations, a controller may obtain global positioning system (GPS) data from a GPS unit of an enrichment device. The controller may determine habitat information identifying a habitat for animals, of a plurality of habitats of animals, using the GPS data. The controller may determine a geofence of the habitat for animals based on the habitat information. The controller may determine a movement profile associated with the habitat for animals using the habitat information. The movement profile identifies one or more motions of the enrichment device. The controller may cause the enrichment device to move, within a boundary of the geofence, in accordance with the one or more motions of the movement profile. The enrichment device may move in accordance with the one or more motions to stimulate movement of one or more animals of the habitat for animals. The controller may monitor the movement and / or animal interaction.

The invention is suitable for the technical field of electric vehicle energy consumption management, and provides an electric vehicle energy consumption prediction method and system using GPS data, and the method comprises the steps: obtaining a GPS original data stream in real time, carrying out the preprocessing, and fusing a digital elevation model to generate an altitude sequence; calculating an instantaneous slope value and a slope change rate based on the altitude sequence, and quantifying the topographic relief intensity; calculating additional acceleration and additional energy consumption by combining the gradient change rate; based on the altitude sequence, the speed data and the real-time state of the kinetic energy recovery system, recoverable electric energy is predicted; and combining the reference energy consumption, the additional energy consumption and the recyclable electric energy to calculate and predict net energy consumption, and triggering model dynamic calibration through a continuous error. According to the invention, the energy consumption prediction precision is improved, and reliable support is provided for electric vehicle energy management.

The invention discloses a traffic jam detection and early warning method based on an unmanned aerial vehicle video stream, and belongs to the technical field of intelligent traffic. The system is combined with a floating vehicle triggering model, collects road videos in real time through an unmanned aerial vehicle, and realizes high-precision vehicle detection and tracking in combination with improved YOLOv8 and DeepSort algorithms; unmanned aerial vehicle data and floating vehicle GPS data are fused, three elements of traffic flow are quantified, and a dual-mechanism congestion detection model is constructed; respectively utilizing a GRU cooperative traffic wave theory to predict the congestion dissipation duration and utilizing an improved GRU + GCN model to predict the traffic situation; the signal lamps are dynamically regulated and controlled through multi-agent reinforcement learning, and active congestion relieving is achieved. The method has the advantages of wide-area coverage, high-precision perception and intelligent response, and the urban traffic control efficiency is remarkably improved.

The invention relates to a manual driving vehicle overspeed behavior identification and intervention method based on a detection carrier, and the method comprises the steps: building a detection carrier system, collecting adjacent HV point cloud data through a laser radar, carrying out the median average filtering, K-Means and DBSCAN combined clustering preprocessing, and achieving the multi-target dynamic tracking through a Point Pill + DeepSORT model; and calculating the real average speed of the HV by using a 1-3s self-adaptive speed measurement window, and comparing the road speed limit to complete the overspeed identification. And when overspeed is judged, dynamically triggering a corresponding high-speed camera to capture, extracting license plate information, fusing speed and GPS data to generate illegal evidence. The method comprises the following steps: quantifying the influence of a detection carrier on an HV individual overspeed behavior, training an HV swarm agent based on VAE-WGAN data enhancement and a double-branch deep Q network, simulating multiple traffic scenes in SUMO, and determining an optimal deployment scheme of the detection carrier by using a dynamic Gaussian mixture Bayesian network and a double-layer double-target optimization model. The method breaks through the limitation of traditional speed measurement, improves the recognition precision and deterrence effect, and balances the traffic safety and efficiency.

The invention belongs to the technical field of intelligent hidden danger detection, and more specifically relates to a hidden danger target geographic coordinate accurate calculation method and system based on an unmanned aerial vehicle and artificial intelligence detection, and a computer readable storage medium. The method comprises the following steps: the unmanned aerial vehicle identifies a target in a video image in real time and analyzes a video frame; when analyzing that the current frame image contains the hidden danger target, the control interface notifies the unmanned aerial vehicle to hover; according to the pixel coordinates of the hidden danger target in the video image and the camera focal length, the camera negative film width and height and the imaging size of the unmanned aerial vehicle cradle head, calculating a cradle head relative adjustment angle which enables the hidden danger target to be centered; according to the obtained relative adjustment angle of the holder, adjusting the holder to enable the hidden danger target to be in the center of a holder picture; and after the adjustment is completed, calculating the GPS data of the hidden danger target. The problems that in the prior art, data processing lags behind, hidden dangers cannot achieve closed-loop management, system fragmentation lacks end-to-end collaborative optimization, and consequently the overall efficiency is limited are solved.

The invention discloses a traffic flow prediction method, system and device, a medium and a computer program product, and the method comprises the steps: inputting a training set into a traffic flow prediction model, training the model, and obtaining a trained traffic flow prediction model; the trained traffic flow prediction model comprises a pre-trained spatial-temporal feature information extraction network used for performing feature extraction on historical GPS data to obtain spatial-temporal features of a known region; the multi-source information fusion flow prediction module is used for carrying out feature extraction on the historical traffic flow data to obtain traffic flow features of a known region, and is also used for carrying out feature extraction on the meteorological data to obtain meteorological data features of the known region; and the fusion prediction module is used for performing feature fusion on the spatial-temporal features, the traffic flow features and the meteorological data features of the known region, and predicting the fused features to obtain a traffic flow prediction value of the known region.

The invention provides an aviation obstruction beacon synchronous flickering system, method and device and a storage medium, the system comprises a main control module and a plurality of control panels, the main control module is sequentially connected with the plurality of levels of control panels in series through a data bus, and each control panel is respectively connected with a plurality of aviation obstruction beacons in parallel; the main control module comprises a GPS module and a light sensation module, the GPS module generates a GPS data packet at least comprising a pulse signal, the light sensation module generates a light sensation intensity value, and the main control module establishes a synchronous data packet according to the GPS data packet and the light sensation intensity value corresponding to the time sequence of the GPS data packet and transmits the synchronous data packet to the control panel step by step; and the control panel of each stage compensates the transmission time based on the serial sequence to obtain the synchronization time of the stage, and synchronously lightens the corresponding aviation obstruction lights at least based on the synchronization time and the light sensation intensity value. According to the invention, synchronous lighting of the aviation obstruction lights in multi-stage connection can be realized, and after the PPS pulse signal is lost, the aviation obstruction light system can still keep the synchronization characteristic for a period of time.

The invention, which relates to the technical field of mechanism material distribution, discloses a mechanism material distribution real-time collaboration and traceability system based on a unified data platform, comprising a data specification module, a dynamic routing module, a traceability code generation module, a storage verification module, a nutrition calculation module, a report generation module and an abnormal response module. The data specification module adopts a unified JSON Schema to define data specifications of a supplier end production batch number and a quality inspection report, a distribution end warehouse temperature and humidity and a vehicle GPS, and a school end acceptance image and student feedback; the dynamic routing module is used for realizing state change and pushing to the three-party system in real time through a dynamic routing engine based on the output of the data specification module; the traceability code generation module is used for generating a four-segment traceability code according to the structured data of the data specification module and storing a key data hash value of each link; and the evidence storage verification module is based on the output of the traceability code generation module.

A method and system for adjusting a digital elevation model (DEM). A satellite image with one or more roads and the DEM are received. The DEM includes an elevation of each pixel of the satellite image. Recorded GPS data corresponding to the one or more roads is received. A pixel in the satellite image corresponding to the one or more roads is determined. A determination is made as to whether the location of the pixel corresponds to the GPS data. After determining that the location of the pixel does not correspond to the GPS data, a set of pixels is determined in the DEM that surround the pixel. The elevation of each pixel of the set of pixels of the DEM is adjusted so that the location of the pixel in the satellite image corresponds to the one or more roads.

The present invention relates to the field of geographic fence determination technology, and in particular to a geographic fence determination method based on GPS data, comprising the following steps: step one: uploading vehicle location information to a message service Kafka through a vehicle GPS; step two: in the fence determination service, monitoring Kafka messages; step three: for each group of vehicle location information, using a fence determination algorithm to make a determination through GPS data; step four: after a vehicle triggers a fence, continuing to trigger corresponding fence rules, and making an early warning or log record. In the present invention, a ray method is used to make a high-precision determination of a static polygonal fence, which is suitable for operation monitoring in a fixed area. At the same time, a dynamic path determination technology is introduced to calculate the shortest distance from a target point to a path in real time, thereby ensuring that the frequently changing operation trajectory of a muck truck is also within the monitoring range. Through a floating-point error correction and tolerance mechanism, the possibility of boundary misjudgment is effectively reduced, and the accuracy and real-time performance of muck truck operation monitoring are significantly improved.