Method, device and equipment for judging behavior of muck truck based on virtual electronic fence

Abstract

The application discloses a method, device and equipment for judging the behavior of a muck truck based on a virtual electronic fence, and relates to the technical field of vehicle state monitoring. The method comprises the following steps: acquiring real-time coordinate data of different sites, and generating dynamic electronic fences of the different sites according to the real-time coordinate data; processing 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 judging whether the muck truck has illegal behavior based on the real-time driving state of the muck truck and the dynamic electronic fences of the different sites. The application establishes dynamic electronic fences, solves the supervision blind spot caused by the mismatch between traditional fences and dynamic scenes, fuses multi-source driving data, solves the complex violation problem that cannot be found by a single data source, matches and calculates the driving state, realizes the discovery and evidence storage of illegal behavior as soon as the illegal behavior occurs, and significantly compresses the response time from the occurrence of the behavior to the intervention of supervision.

Description

Technical Field

[0001] This application relates to the field of vehicle status monitoring technology, and more specifically, to a method, device, and equipment for judging the behavior of dump trucks based on virtual electronic fences. Background Technology

[0002] With the rapid development of urban construction, the supervision of construction waste transportation has become a significant challenge for urban management. Traditional supervision methods mainly rely on manual inspections, vehicle registration, and post-event tracking, which are insufficient for real-time monitoring and accurate early warning of dumping activities by construction waste trucks. Especially in complex urban environments, illegal dumping often exhibits characteristics of concealment and imminent occurrence, necessitating the use of intelligent technologies to improve supervision efficiency.

[0003] Existing technologies primarily employ fixed electronic fence monitoring to prevent illegal dumping: Geographical fence boundaries are pre-set in fixed areas such as disposal sites and construction sites, and vehicle-mounted GPS devices determine whether vehicles have entered the designated area. If a vehicle exceeds the fence boundary, a violation warning is triggered. Trajectory deviation analysis: The transportation routes of dump trucks are pre-planned, and violations are determined by comparing the actual vehicle trajectory with the registered route (e.g., distance deviation exceeding a threshold). Manual video verification: Cameras are deployed at key road sections, and personnel visually inspect the vehicle loading status and dumping behavior in the video footage.

[0004] However, the above methods rely solely on GPS positioning or video clips, lacking the fusion analysis of multi-dimensional information such as load data and time rules, and are unable to identify concealed dumping behavior when the trajectory is compliant; the boundaries and rule parameters of the electronic fence are fixed and cannot dynamically adapt to changes in scenarios such as temporary construction sites and sudden control areas; the determination of violations relies on post-event trajectory playback or manual review, and there is a lag of several hours to several days from the occurrence of the behavior to the generation of the warning, which makes law enforcement and evidence collection difficult. Summary of the Invention

[0005] To address at least one deficiency or improvement need in existing technologies, this invention provides a method, device, and equipment for judging the behavior of dump trucks based on virtual electronic fences. This addresses the problems in existing technologies that rely solely on GPS positioning or video clips, lack fusion analysis of multi-dimensional information such as load data and time rules, cannot identify concealed dumping behavior when the trajectory is compliant, have fixed electronic fence boundaries and rule parameters that cannot dynamically adapt to changes in scenarios such as temporary construction sites and sudden control areas, and suffer from serious lag and difficulty in rounding during manual verification.

[0006] To achieve the above objectives, according to a first aspect of the present invention, a method for judging the behavior of construction waste trucks based on virtual electronic fences is provided, comprising:

[0007] Acquire real-time coordinate data of different sites, and generate dynamic electronic fences for different sites based on the real-time coordinate data of different sites.

[0008] The multi-source driving data of the dump trucks is processed, and the real-time driving status of the dump trucks is analyzed and recorded in combination with the dynamic electronic fences of different sites.

[0009] The system analyzes the real-time driving status of dump trucks and the dynamic electronic fences at different sites to determine whether dump trucks are engaging in illegal activities.

[0010] In one possible implementation, real-time coordinate data of different sites is acquired, and dynamic electronic fences for different sites are generated based on the real-time coordinate data of different sites. The implementation also includes:

[0011] The real-time coordinate data of different sites are determined based on the registered site coordinate boundaries, real-time positioning information, and real-time camera information.

[0012] Polygon vertices are extracted from real-time coordinate data of different sites using edge recognition and feature matching algorithms.

[0013] Dynamic electronic fences for different sites are generated based on real-time coordinate data and polygon vertices.

[0014] In one possible implementation, determining the real-time coordinate data of different sites based on the registered site coordinate boundaries, real-time positioning information, and real-time camera information also includes:

[0015] The registered site coordinate boundaries, real-time positioning information, and real-time camera information are preprocessed and coordinate transformation is performed to obtain multi-source coordinate data in the same coordinate system;

[0016] By fusing and dynamically updating multi-source coordinate data in the same coordinate system, real-time coordinate data for different sites can be obtained.

[0017] In one possible implementation, dynamic electronic fences for different sites are generated based on real-time coordinate data and polygon vertices, and the method further includes:

[0018] Connect the vertices of the polygon in a preset order to generate the initial polygonal electronic fences for different sites;

[0019] Calculate the overlap between the initial polygonal electronic fence and the real-time coordinate data of the corresponding site;

[0020] The initial polygonal electronic fence with a lower than preset overlap is dynamically adjusted based on real-time coordinate data.

[0021] In one possible implementation, the multi-source driving data includes the starting point coordinates and the ending point coordinates; processing the multi-source driving data of the dump trucks, and combining it with the analysis and recording of the real-time driving status of the dump trucks using dynamic electronic fences at different sites, also includes:

[0022] Determine the trajectory of the dump truck based on the starting and ending coordinates, and calculate the average speed of the dump truck.

[0023] The position of the dump trucks relative to the dynamic electronic fences at different sites was analyzed based on the driving trajectory of the dump trucks.

[0024] In one possible implementation, judging whether a dump truck is engaging in illegal activities based on its real-time driving status and dynamic electronic fences at different sites also includes:

[0025] Monitor the real-time load data of dump trucks, and calculate the load difference when the real-time load data changes;

[0026] The determination of whether the dump truck has engaged in illegal activities is based on the average speed of the dump truck, the position of the dump truck relative to the dynamic electronic fence, and the difference in load.

[0027] In one possible implementation, the dynamic electronic fence includes dynamic electronic fences at construction sites and dynamic electronic fences at disposal sites; judging whether a dump truck is engaging in illegal activities based on the average speed of the dump truck, the position of the dump truck relative to the dynamic electronic fence, and the difference in load capacity also includes:

[0028] If the real-time load data exceeds the preset maximum load, an overload alarm will be generated, and the dump truck will be prohibited from leaving the construction site's dynamic electronic fence.

[0029] If a dump truck fails to enter the corresponding dynamic electronic fence of the disposal site and the load difference exceeds the preset change threshold, the dump truck is illegally dumping and an illegal dumping warning record is generated.

[0030] If a dump truck fails to enter the corresponding dynamic electronic fence of the disposal site and the load difference does not exceed the preset change threshold, the dump truck is considered to have committed road spillage behavior, and a road spillage warning record will be generated.

[0031] If a dump truck fails to enter the corresponding dynamic electronic fence of the disposal site and the average speed of the dump truck exceeds the preset speed threshold, a dump truck speeding warning record will be generated.

[0032] According to a second aspect of the present invention, a device for analyzing the behavior of construction waste trucks based on virtual electronic fences is also provided, comprising:

[0033] The dynamic fence module is configured to acquire real-time coordinate data of different sites and generate dynamic electronic fences for different sites based on the real-time coordinate data of different sites.

[0034] The driving status module is configured to process multi-source driving data of dump trucks and analyze and record the real-time driving status of dump trucks in conjunction with dynamic electronic fences of different sites.

[0035] The behavior analysis module is configured to analyze whether the dump truck has engaged in illegal activities based on the real-time driving status of the dump truck and the dynamic electronic fences of different sites.

[0036] According to a third aspect of the present invention, a device for judging the behavior of construction waste trucks based on virtual electronic fences is also provided, which includes at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program, and when the computer program is executed by the processing unit, the processing unit performs the steps of any of the above-described methods for judging the behavior of construction waste trucks based on virtual electronic fences.

[0037] According to a fourth aspect of the present invention, a storage medium is also provided, which stores a computer program executable by a virtual electronic fence-based dump truck behavior analysis device. When the computer program is run on the virtual electronic fence-based dump truck behavior analysis device, the virtual electronic fence-based dump truck behavior analysis device performs the steps of any of the above-described virtual electronic fence-based dump truck behavior analysis methods.

[0038] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects:

[0039] This invention provides a method for judging the behavior of construction waste trucks based on virtual electronic fences. In terms of scenario adaptability, it breaks through the static limitations of traditional electronic fences by dynamically generating dynamic electronic fences through real-time acquisition of construction site coordinates. This allows the monitoring range to change instantly according to the needs of temporary construction site establishment and emergency control area adjustments, effectively solving the monitoring blind spots caused by the mismatch between traditional fences and dynamic scenarios. It is particularly suitable for the frequent temporary engineering scenarios in urban construction. In terms of data analysis depth, it integrates multi-source driving data to determine the spatiotemporal trajectory, load status, and dwell time of construction waste trucks. This not only identifies explicit violations such as driving beyond designated boundaries but also accurately captures concealed dumping behavior through coupled analysis of sudden load changes and unusual dwell times, solving the problem of complex violations that are difficult to detect with a single data source. Regarding the timeliness of supervision, a real-time streaming data processing architecture is established, upgrading the traditional post-event manual verification mode to an intelligent early warning system. It matches and calculates driving status to achieve immediate detection and evidence preservation of violations, significantly reducing the response time from the occurrence of the behavior to regulatory intervention and effectively preventing the loss of evidence and the expansion of the consequences of violations. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 A flowchart illustrating an embodiment of the method for judging the behavior of construction waste trucks based on virtual electronic fences provided by the present invention;

[0042] Figure 2 Provided by the present invention Figure 1 A schematic flowchart of an embodiment of step S101;

[0043] Figure 3 Provided by the present invention Figure 2 A flowchart illustrating an embodiment of step S203;

[0044] Figure 4 A schematic diagram of an embodiment of the device for judging the behavior of construction waste trucks based on virtual electronic fences provided by the present invention;

[0045] Figure 5 A schematic diagram of the structure of a dump truck behavior analysis device based on a virtual electronic fence provided in an embodiment of the present invention. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0047] The terms "first," "second," "third," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0048] This invention provides a method, device, and equipment for judging the behavior of construction waste trucks based on virtual electronic fences, which will be described in detail below.

[0049] Please see Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the method for judging the behavior of construction waste trucks based on virtual electronic fences provided by the present invention. In a specific embodiment of the present invention, a method for judging the behavior of construction waste trucks based on virtual electronic fences is disclosed, including:

[0050] S101. Obtain real-time coordinate data of different sites and generate dynamic electronic fences for different sites based on the real-time coordinate data of different sites.

[0051] S102. Process the multi-source driving data of the dump trucks, and analyze and record the real-time driving status of the dump trucks in combination with the dynamic electronic fences of different sites.

[0052] S103. Based on the real-time driving status of the dump truck and the dynamic electronic fences of different sites, determine whether the dump truck has committed any illegal acts.

[0053] In the above embodiments, by accessing diverse data sources such as municipal construction permit systems, traffic control platforms, and GPS, the boundary coordinate data of sites such as construction sites and waste disposal sites can be obtained in real time. This solves the problem that traditional electronic fences rely on fixed geographic fences and cannot adapt to temporary construction sites or areas requiring emergency control (such as road repair zones). The geometric model of the electronic fence (such as a polygonal fence) is dynamically generated based on the site coordinates, supporting automatic expansion or contraction of the fence area according to construction progress and control needs. For example, a fence is automatically generated when a temporary construction site is activated and automatically deactivated after the project ends, avoiding the lag of frequent manual configuration. Rule parameters such as effective time periods and permitted work types can be added to the electronic fence (e.g., only allowing specific vehicles to enter from 7:00 to 22:00), realizing multi-dimensional constraints of "space + time + business rules," and preventing overtime work and illegal intrusion from the source.

[0054] By integrating multi-source information such as GPS location data, load sensor data, and camera video streams from dump trucks, and using technologies such as data cleaning and spatiotemporal alignment, multi-dimensional vehicle operation data is constructed, breaking through the limitations of single GPS positioning.

[0055] The vehicle trajectory is matched with the spatiotemporal rules of the dynamic electronic fence to analyze key behavioral characteristics, which may include, but are not limited to: determining whether the vehicle enters / leaves the electronic fence area during the permitted time period; and identifying suspected illegal dumping by combining the duration of stay within the electronic fence with a sudden drop in load data (such as from fully loaded to empty). Finally, key indicators such as the vehicle's entry and exit time from the fence and load change curves are persistently stored to provide data support for subsequent violation tracing.

[0056] Cross-validation is performed for complex scenarios such as vehicles with compliant trajectories but abnormal loads, or vehicles with compliant time periods but abnormal locations. For example, a vehicle may be within a legal fence but fail to unload according to the permitted load standard. By comparing load sensor data with declaration records, behaviors such as falsely reporting loads and fraudulent dumping can be identified. The analysis results are correlated with the original data (timestamps, coordinates, sensor readings) to generate a credible evidence package containing complete spatiotemporal context. This supports one-click export of law enforcement reports, solving the problems of low efficiency and easy omissions in manual evidence collection.

[0057] Compared with existing technologies, the virtual electronic fence-based method for judging the behavior of construction waste trucks provided in this embodiment breaks through the static limitations of traditional electronic fences in terms of scene adaptability. By dynamically generating dynamic electronic fences through real-time acquisition of construction site coordinates, the monitoring scope can change instantly according to the needs of temporary construction site establishment and emergency control area adjustment. This effectively solves the monitoring blind spots caused by the mismatch between traditional fences and dynamic scenes, and is particularly suitable for the temporary engineering scenarios that frequently occur in urban construction. In terms of data analysis depth, it integrates multi-source driving data to determine the spatiotemporal trajectory, load status, and dwell time of construction waste trucks. It can not only identify obvious violations such as driving beyond the designated area, but also accurately capture hidden dumping behavior through coupled analysis of load changes and unusual dwellings, solving the problem of complex violations that are difficult to detect with a single data source. In terms of regulatory timeliness, a real-time streaming data processing architecture is established, upgrading the traditional post-event manual verification mode to an intelligent early warning system. It matches and calculates the driving status to achieve immediate detection and evidence preservation of violations, significantly reducing the response time from the occurrence of the behavior to regulatory intervention, and effectively avoiding the loss of evidence and the expansion of the consequences of violations.

[0058] Please see Figure 2 , Figure 2 Provided by the present invention Figure 1 A flowchart illustrating one embodiment of step S101. In some embodiments of the present invention, real-time coordinate data of different sites are acquired, and dynamic electronic fences for different sites are generated based on the real-time coordinate data of different sites. The method further includes:

[0059] S201. Determine the real-time coordinate data of different sites based on the registered site coordinate boundaries, real-time positioning information, and real-time camera information.

[0060] S202. Extract polygon vertices from real-time coordinate data of different sites using edge recognition and feature matching algorithms;

[0061] S203. Generate dynamic electronic fences for different sites based on real-time coordinate data and polygon vertices.

[0062] In the above embodiments, a multi-source data verification mechanism is constructed by integrating the registered site coordinate boundaries, real-time positioning information, and real-time video information to solve the problem that a single data source is susceptible to environmental interference. For temporary construction site boundary changes (such as expansion of the construction area) or sudden control zones (such as road collapse emergency zones), the registered coordinates are dynamically corrected using real-time positioning and video data to ensure the spatiotemporal consistency of the site boundaries and avoid fence deviations due to information lag.

[0063] Based on image frames from video streams, edge detection and semantic segmentation techniques are used to identify visual features such as construction site fencing and the distribution of construction machinery, extracting pixel-level contours of the actual physical boundaries of the site. This solves the problems of low efficiency and difficulty in adapting to dynamic scenes associated with traditional manual annotation. The contour coordinates of the visually recognized data are spatially matched with the registered coordinates and real-time positioning data. By calculating the geometric relationships of feature points (such as building corners and road signs), the precise geographic coordinates of the polygon vertices are determined, eliminating contour extraction errors caused by viewpoint distortion or occlusion and improving the reliability of vertex coordinates.

[0064] Based on the polygon vertices extracted by S202, a geofencing algorithm (such as the ray casting method) is used to generate the minimum closed polygon, dynamically covering the actual work area of ​​the site and supporting accurate description of complex terrain. Dynamic attributes (such as the effective time period of the fence and the types of vehicles allowed) can be added to the geofencing to achieve real-time synchronization between fence rules and business scenarios. Redundant vertices are eliminated through convex hull algorithms or vertex simplification strategies (such as the Douglas-Peucker algorithm), reducing the complexity of the fence model and improving the computational efficiency of subsequent trajectory matching and violation determination.

[0065] In some embodiments of the present invention, determining real-time coordinate data for different sites based on registered site coordinate boundaries, real-time positioning information, and real-time camera information further includes:

[0066] The registered site coordinate boundaries, real-time positioning information, and real-time camera information are preprocessed and coordinate transformation is performed to obtain multi-source coordinate data in the same coordinate system;

[0067] By fusing and dynamically updating multi-source coordinate data in the same coordinate system, real-time coordinate data for different sites can be obtained.

[0068] In the above embodiments, the registered site coordinate boundaries, real-time positioning information, and real-time camera information are preprocessed to solve the data noise problem. For example, abrupt changes in GPS positioning (such as coordinate abrupt changes caused by signal obstruction) are filtered out; and missing frames in the video stream caused by obstruction or changes in lighting are repaired.

[0069] The coordinate systems of different data sources are uniformly transformed to the same geographic reference system (such as the CGCS2000 National Geodetic Coordinate System) through affine transformation or deep learning pose estimation models, eliminating boundary deviations caused by coordinate system differences; perspective correction and geographic registration are performed on feature points in video images to achieve accurate mapping from pixel coordinates to geographic coordinates.

[0070] Weights are assigned to multi-source coordinate data based on data confidence levels (such as GPS positioning accuracy and video resolution), and Kalman filtering or Bayesian estimation algorithms are used for fusion. For example, registered coordinates serve as a baseline, but their confidence decays over time; real-time positioning data has high accuracy but is susceptible to interference, so dynamic weights are assigned; video data has increased confidence within the visible range and is used for local calibration. The fusion results are used to correct the coordinate points at site boundaries, overcoming the limitations of a single data source (such as outdated registered data and drifting positioning signals).

[0071] Based on the timestamps of real-time positioning and video data, the site boundary is adjusted incrementally at the millisecond level to adapt to sudden scenarios; significant changes in coordinate data are detected by edge computing nodes, and the fence model is automatically reconstructed to avoid invalid calculations.

[0072] Please see Figure 3 , Figure 3 Provided by the present invention Figure 2 A flowchart illustrating an embodiment of step S203. In some embodiments of the present invention, generating dynamic electronic fences for different sites based on real-time coordinate data and polygon vertices of different sites further includes:

[0073] S301. Connect the polygon vertices in a preset order to generate initial polygonal electronic fences for different sites.

[0074] S302. Calculate the overlap between the initial polygonal electronic fence and the real-time coordinate data of the corresponding site.

[0075] S303. Dynamically adjust the initial polygonal electronic fence that is below the preset overlap degree based on real-time coordinate data.

[0076] In the above embodiments, the extracted polygon vertices are connected in a preset order (e.g., clockwise / counterclockwise) to generate a closed initial polygonal electronic fence, ensuring geometric topological correctness (e.g., avoiding self-intersections and concave polygons) and providing a standardized geometric basis for subsequent analysis. A convex hull algorithm is used to wrap the vertex set, eliminating concave areas caused by feature extraction errors and ensuring the fence covers the complete operational area of ​​the actual site. For multi-plot scenarios (e.g., scattered waste disposal areas), multiple independent polygonal fences can be generated, avoiding overgeneralization of a single fence.

[0077] Based on real-time coordinate data, a spatial overlay analysis algorithm is used to quantify the coverage overlap between the initial polygonal fence and the actual site. For example, this involves calculating the percentage of dynamic monitoring points within the fence and assessing the average distance deviation between the fence boundary and the actual site boundary. A distance field algorithm is introduced to calculate the shortest distance distribution from the fence boundary to real-time coordinate points, identifying areas with insufficient coverage. Differentiated overlap thresholds are set according to site type (e.g., ≥95% for fixed sites, ≥85% for temporary construction sites) to avoid misjudgments due to scene differences. Areas with overlap below the threshold are automatically marked as areas requiring optimization, triggering a dynamic fence adjustment process.

[0078] For areas with insufficient coverage, a vertex interpolation optimization algorithm is used to adjust the coordinates of polygon vertices, causing the fence boundary to converge towards the real-time coordinate point set. For newly added real-time coordinate clusters, an incremental vertex insertion strategy is adopted to expand the fence range and maintain polygon closure. During the adjustment process, site business rules are combined to restrict the vertex movement range to ensure fence compliance. For large-scale deformation scenarios, polygon affine transformation is used to quickly reconstruct the fence, reducing computational overhead. After each adjustment, the coverage overlap is recalculated until a threshold is met or the maximum number of iterations is reached, forming a closed-loop iterative mechanism of "generation-evaluation-optimization". Historical adjustment data is recorded to train the fence optimization model and improve the efficiency of subsequent adjustments.

[0079] In some embodiments of the present invention, the multi-source driving data includes starting point coordinates and ending point coordinates; processing the multi-source driving data of the dump trucks, and combining it with dynamic electronic fences of different sites to analyze and record the real-time driving status of the dump trucks, further includes:

[0080] Determine the trajectory of the dump truck based on the starting and ending coordinates, and calculate the average speed of the dump truck.

[0081] The position of the dump trucks relative to the dynamic electronic fences at different sites was analyzed based on the driving trajectory of the dump trucks.

[0082] In the above embodiments, based on the coordinates of the start and end points, combined with discrete GPS points reported by the vehicle, missing trajectory points are supplemented using Bézier curve interpolation or map path planning APIs (such as Gaode / Baidu Maps) to solve the trajectory breakage problem caused by signal loss and restore the complete driving path. Based on the timestamp sequence of the trajectory points, instantaneous speed (distance / time difference between adjacent points) is calculated segment by segment, and outliers (such as rapid acceleration / deceleration noise) are filtered out. A sliding window averaging algorithm is used to output a smoothed real-time average speed to identify speeding, abnormal stops, and other behaviors. Logical verification is performed on anomalies in the start / end point coordinates, automatically correcting or marking them as suspicious data. For trajectory points with disordered or missing timestamps, time series repair is performed based on the vehicle motion model.

[0083] The trajectory points are spatially matched with the polygonal boundaries of the dynamic electronic fence at the millisecond level. The point-to-surface inclusion detection is accelerated by using the ray method or R-tree index to determine whether the vehicle has entered / left the fenced area. For areas with dense trajectory points, abnormal clustering points are identified by kernel density estimation or DBSCAN clustering algorithm.

[0084] In some embodiments of the present invention, the method of determining whether a dump truck has engaged in illegal activities based on its real-time driving status and dynamic electronic fences at different sites further includes:

[0085] Monitor the real-time load data of dump trucks, and calculate the load difference when the real-time load data changes;

[0086] The determination of whether the dump truck has engaged in illegal activities is based on the average speed of the dump truck, the position of the dump truck relative to the dynamic electronic fence, and the difference in load.

[0087] In the above embodiments, the weight data of the dump truck is collected in real time by the vehicle-mounted weighing sensor. A sliding window variance analysis or abrupt change detection algorithm is used to locate the timestamp of suspected dumping operations. The load difference (ΔW = W_before - W_after) is calculated and compared with a preset threshold (e.g., ΔW ≥ 8 tons) to filter out minor fluctuations caused by road bumps or sensor noise.

[0088] In some embodiments of the present invention, the dynamic electronic fence includes a construction site dynamic electronic fence and a disposal site dynamic electronic fence; judging whether the dump truck has committed illegal acts based on the average speed of the dump truck, the position of the dump truck relative to the dynamic electronic fence, and the load difference, further includes:

[0089] If the real-time load data exceeds the preset maximum load, an overload alarm will be generated, and the dump truck will be prohibited from leaving the construction site's dynamic electronic fence.

[0090] If a dump truck fails to enter the corresponding dynamic electronic fence of the disposal site and the load difference exceeds the preset change threshold, the dump truck is illegally dumping and an illegal dumping warning record is generated.

[0091] If a dump truck fails to enter the corresponding dynamic electronic fence of the disposal site and the load difference does not exceed the preset change threshold, the dump truck is considered to have committed road spillage behavior, and a road spillage warning record will be generated.

[0092] If a dump truck fails to enter the corresponding dynamic electronic fence of the disposal site and the average speed of the dump truck exceeds the preset speed threshold, a dump truck speeding warning record will be generated.

[0093] In the above embodiments, the load data of dump trucks within the dynamic electronic fence of the construction site is monitored in real time. If the load exceeds the preset maximum load (e.g., ≥30 tons), an overload alarm is triggered. The load data is synchronized with the fence status in milliseconds to prevent overloaded vehicles from leaving the site illegally. Overload records are uploaded to the monitoring platform in real time and used as a basis for deducting points in the enterprise's credit score.

[0094] If a dump truck fails to enter any dynamic electronic fence of a disposal site and the load difference ΔW exceeds a preset threshold (e.g., ΔW ≥ 8 tons), it is deemed to be illegally dumping. The location of the illegal dumping is determined by spatiotemporal matching of the load curve's abrupt change point with the GPS trajectory; video streams from cameras around the dumping point are automatically retrieved to generate a visual evidence chain of "zero load + failure to enter a disposal site."

[0095] If the dump truck does not enter the disposal site enclosure and ΔW does not exceed the threshold (e.g., 1 ton ≤ ΔW < 8 tons), a road spillage warning is triggered. Correlation analysis between minor changes in load and driving trajectory (e.g., load reduction on continuously bumpy road sections); linkage with the municipal sanitation system to initiate automatic cleaning or manual inspection of the warning section.

[0096] If a dump truck fails to enter the disposal site's perimeter and its average speed exceeds a preset threshold (e.g., ≥60km / h on urban roads), a speeding warning is triggered. Speed ​​limits are dynamically adjusted based on road type (e.g., school zones, elevated roads) (e.g., 30km / h in school zones). Real-time road speed limit information is obtained using a high-precision map API to avoid static rules becoming outdated. For vehicles that repeatedly exceed the speed limit (e.g., 3 times within 10 minutes), the warning level is upgraded, and law enforcement personnel are notified for on-site handling.

[0097] To better implement the virtual electronic fence-based method for judging the behavior of construction waste trucks in this invention, based on the virtual electronic fence-based method for judging the behavior of construction waste trucks, please refer to the corresponding documentation. Figure 4 , Figure 4 This is a schematic diagram of an embodiment of the dump truck behavior analysis device based on a virtual electronic fence provided by the present invention. The embodiment of the present invention provides a dump truck behavior analysis device 400 based on a virtual electronic fence, comprising:

[0098] The dynamic fence module 410 is configured to acquire real-time coordinate data of different sites and generate dynamic electronic fences for different sites based on the real-time coordinate data of different sites.

[0099] The driving status module 420 is configured to process multi-source driving data of the dump truck, and analyze and record the real-time driving status of the dump truck in combination with the dynamic electronic fences of different sites.

[0100] The behavior analysis module 430 is configured to analyze whether the dump truck has engaged in illegal activities based on the real-time driving status of the dump truck and the dynamic electronic fences of different sites.

[0101] It should be noted that the device 400 provided in the above embodiments can implement the technical solutions described in the above method embodiments. The specific implementation principles of the above modules or units can be found in the corresponding content in the above method embodiments, and will not be repeated here.

[0102] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of a construction waste truck behavior analysis device based on a virtual electronic fence, provided in an embodiment of the present invention. Based on the above-described method for analyzing construction waste truck behavior based on a virtual electronic fence, the present invention also provides a corresponding device for analyzing construction waste truck behavior based on a virtual electronic fence. This device can be a mobile terminal, desktop computer, laptop, handheld computer, or server, etc. The virtual electronic fence-based construction waste truck behavior analysis device 500 includes a processor 510, a memory 520, and a display 530. Figure 5 Only some components of the dump truck behavior analysis device based on virtual electronic fence are shown. However, it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead.

[0103] In some embodiments, the memory 520 can be an internal storage unit of the virtual electronic fence-based dump truck behavior analysis device 500, such as a hard disk or memory of the virtual electronic fence-based dump truck behavior analysis device 500. In other embodiments, the memory 520 can also be an external storage device of the virtual electronic fence-based dump truck behavior analysis device 500, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the virtual electronic fence-based dump truck behavior analysis device 500. Furthermore, the memory 520 can include both internal and external storage units of the virtual electronic fence-based dump truck behavior analysis device 500. The memory 520 is used to store application software and various types of data installed on the virtual electronic fence-based dump truck behavior analysis device 500, such as the program code installed on the virtual electronic fence-based dump truck behavior analysis device 500. The memory 520 can also be used to temporarily store data that has been output or will be output. In one embodiment, the memory 520 stores a dump truck behavior analysis program 540 based on a virtual electronic fence. The dump truck behavior analysis program 540 based on a virtual electronic fence can be executed by the processor 510 to realize the dump truck behavior analysis method based on a virtual electronic fence in the various embodiments of this application.

[0104] In some embodiments, processor 510 may be a central processing unit (CPU), a microprocessor, or other data processing chip, used to run program code stored in memory 520 or process data, such as executing a method for judging the behavior of dump trucks based on virtual electronic fences.

[0105] In some embodiments, display 530 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. Display 530 is used to display information from the virtual electronic fence-based dump truck behavior analysis device 500 and to display a user interface for visualization. Components 510-530 of the virtual electronic fence-based dump truck behavior analysis device 500 communicate with each other via a system bus.

[0106] In one embodiment, when the processor 510 executes the virtual electronic fence-based dump truck behavior analysis program 540 in the memory 520, it implements the steps in the virtual electronic fence-based dump truck behavior analysis method described above.

[0107] This embodiment also provides a computer-readable storage medium storing a dump truck behavior analysis program based on a virtual electronic fence. When the dump truck behavior analysis program based on the virtual electronic fence is executed by a processor, it performs the following steps:

[0108] Acquire real-time coordinate data of different sites, and generate dynamic electronic fences for different sites based on the real-time coordinate data of different sites.

[0109] The multi-source driving data of the dump trucks is processed, and the real-time driving status of the dump trucks is analyzed and recorded in combination with the dynamic electronic fences of different sites.

[0110] The system analyzes the real-time driving status of dump trucks and the dynamic electronic fences at different sites to determine whether dump trucks are engaging in illegal activities.

[0111] In summary, the method for judging the behavior of construction waste trucks based on virtual electronic fences provided by this invention overcomes the static limitations of traditional electronic fences in terms of scenario adaptability. By dynamically generating dynamic electronic fences through real-time acquisition of construction site coordinates, the regulatory scope can change instantly according to the needs of temporary construction site establishment and emergency control area adjustments. This effectively solves the regulatory blind spots caused by the mismatch between traditional fences and dynamic scenarios, and is particularly suitable for the frequent temporary engineering scenarios in urban construction. In terms of data analysis depth, it integrates multi-source driving data to determine the spatiotemporal trajectory, load status, and dwell time of construction waste trucks. It can not only identify obvious violations such as driving beyond the designated area, but also accurately capture hidden dumping behaviors through coupled analysis of load changes and unusual dwell times, solving the problem of complex violations that are difficult to detect with a single data source. In terms of regulatory timeliness, it establishes a real-time streaming data processing architecture, upgrading the traditional post-event manual verification mode to an intelligent early warning system. It matches and calculates driving status to achieve immediate detection and evidence preservation of violations, significantly reducing the response time from the occurrence of the behavior to regulatory intervention, and effectively avoiding the loss of evidence and the expansion of the consequences of violations.

[0112] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method. The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, as well as magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0113] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0114] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0115] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0116] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0117] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0118] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0119] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0120] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of embodiments of this disclosure upon considering the specification and practicing the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described herein. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

[0121] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0122] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for judging the behavior of construction waste trucks based on virtual electronic fences, characterized in that, include: Acquire real-time coordinate data of different sites, and generate dynamic electronic fences for different sites based on the real-time coordinate data of different sites. The multi-source driving data of the dump trucks is processed, and the real-time driving status of the dump trucks is analyzed and recorded in combination with the dynamic electronic fences of the different sites. The system analyzes whether the dump truck has engaged in illegal activities based on the real-time driving status of the dump truck and the dynamic electronic fences of different sites. The step of acquiring real-time coordinate data of different sites and generating dynamic electronic fences for different sites based on the real-time coordinate data of different sites also includes: The real-time coordinate data of different sites are determined based on the registered site coordinate boundaries, real-time positioning information, and real-time camera information. Polygon vertices are extracted from the real-time coordinate data of the different sites using edge recognition and feature matching algorithms; Dynamic electronic fences for different sites are generated based on real-time coordinate data of different sites and the vertices of the polygon. The process of generating dynamic electronic fences for different sites based on real-time coordinate data and polygon vertices further includes: The polygon vertices are connected in a preset order to generate initial polygonal electronic fences for different sites; Calculate the overlap between the initial polygonal electronic fence and the real-time coordinate data of the corresponding site; The initial polygonal electronic fence with a lower than preset overlap degree is dynamically adjusted based on the real-time coordinate data.

2. The method for judging the behavior of construction waste trucks based on virtual electronic fences as described in claim 1, characterized in that, The method of determining real-time coordinate data for different sites based on registered site coordinate boundaries, real-time positioning information, and real-time camera information also includes: The registered site coordinate boundaries, real-time positioning information, and real-time camera information are preprocessed and coordinate transformation is performed to obtain multi-source coordinate data in the same coordinate system; By fusing and dynamically updating multi-source coordinate data in the same coordinate system, real-time coordinate data for different sites can be obtained.

3. The method for judging the behavior of construction waste trucks based on virtual electronic fences as described in claim 1, characterized in that, The multi-source driving data includes the starting point coordinates and the ending point coordinates; the processing of the multi-source driving data of the dump trucks, combined with the analysis and recording of the real-time driving status of the dump trucks in conjunction with the dynamic electronic fences of different sites, also includes: The trajectory of the dump truck is determined based on the starting point coordinates and the ending point coordinates, and the average speed of the dump truck is calculated. The position of the dump truck relative to the dynamic electronic fence is analyzed based on the driving trajectory of the dump truck and the dynamic electronic fence of the different sites.

4. The method for judging the behavior of construction waste trucks based on virtual electronic fences as described in claim 3, characterized in that, The method of judging whether a dump truck has committed illegal acts based on the real-time driving status of the dump truck and the dynamic electronic fences of different sites also includes: Monitor the real-time load data of dump trucks, and calculate the load difference when the real-time load data changes; The determination of whether the dump truck has engaged in illegal activities is based on the average speed of the dump truck, the position of the dump truck relative to the dynamic electronic fence, and the difference in load.

5. The method for judging the behavior of construction waste trucks based on virtual electronic fences as described in claim 4, characterized in that, The dynamic electronic fences include dynamic electronic fences at construction sites and dynamic electronic fences at disposal sites. The method of determining whether a dump truck has committed illegal acts based on the average speed of the dump truck, the position of the dump truck relative to the dynamic electronic fence, and the load difference also includes: If the real-time load data exceeds the preset maximum load, an overload alarm record will be generated, prohibiting the dump truck from leaving the construction site's dynamic electronic fence. If a dump truck fails to enter the corresponding dynamic electronic fence of the disposal site, and the load difference exceeds the preset change threshold, then the dump truck is illegally dumping, and an illegal dumping warning record is generated. If a dump truck fails to enter the corresponding dynamic electronic fence of the disposal site, and the load difference does not exceed the preset change threshold, then the dump truck has a road spillage behavior, and a road spillage warning record is generated. If a dump truck fails to enter the corresponding dynamic electronic fence of the disposal site, and the average speed of the dump truck exceeds a preset speed threshold, a dump truck speeding warning record will be generated.

6. A device for analyzing the behavior of construction waste trucks based on virtual electronic fences, characterized in that, include: The dynamic fence module is configured to acquire real-time coordinate data of different sites and generate dynamic electronic fences for different sites based on the real-time coordinate data of different sites. The driving status module is configured to process multi-source driving data of the dump truck, and analyze and record the real-time driving status of the dump truck in conjunction with the dynamic electronic fences of the different sites. The behavior analysis module is configured to analyze whether the dump truck has engaged in illegal behavior based on the real-time driving status of the dump truck and the dynamic electronic fences of different sites. The step of acquiring real-time coordinate data of different sites and generating dynamic electronic fences for different sites based on the real-time coordinate data of different sites also includes: The real-time coordinate data of different sites are determined based on the registered site coordinate boundaries, real-time positioning information, and real-time camera information. Polygon vertices are extracted from the real-time coordinate data of the different sites using edge recognition and feature matching algorithms; Dynamic electronic fences for different sites are generated based on real-time coordinate data of different sites and the vertices of the polygon. The process of generating dynamic electronic fences for different sites based on real-time coordinate data and polygon vertices further includes: The polygon vertices are connected in a preset order to generate initial polygonal electronic fences for different sites; Calculate the overlap between the initial polygonal electronic fence and the real-time coordinate data of the corresponding site; The initial polygonal electronic fence with a lower than preset overlap degree is dynamically adjusted based on the real-time coordinate data.

7. A device for analyzing the behavior of construction waste trucks based on virtual electronic fences, characterized in that, It includes at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program, and when the computer program is executed by the processing unit, the processing unit performs the steps of the method for judging the behavior of dump trucks based on virtual electronic fences as described in any one of claims 1 to 5.

8. A storage medium, characterized in that, It stores a computer program that can be executed by a virtual electronic fence-based dump truck behavior analysis device. When the computer program is run on the virtual electronic fence-based dump truck behavior analysis device, the virtual electronic fence-based dump truck behavior analysis device performs the steps of the virtual electronic fence-based dump truck behavior analysis method according to any one of claims 1 to 5.

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