Intelligent identification and detection method and system for vehicles entering and exiting from construction site

Abstract

The invention discloses an intelligent recognition and detection method and system for vehicles entering and exiting from a construction site, and the method comprises the steps: collecting a plurality of vehicle images of a target vehicle entering and exiting from the construction site at different angles, and monitoring the driving information of the target vehicle; identifying the type and identity of the target vehicle according to the plurality of vehicle images at different angles; if the target vehicle is an unknown vehicle, triggering and sending an alarm to a security terminal for manual re-checking; if the target vehicle is the known vehicle, specific part information of the vehicle in the vehicle image is extracted; and comparing the driving information and the specific part information with a preset construction site vehicle safety specification, and calculating a behavior score of the target vehicle so as to perform intelligent detection management on the target vehicle based on the behavior score. According to the embodiment of the invention, the method can achieve the accurate judgment of the identity, type and safety state of the vehicle through the comprehensive scanning and information extraction of the target vehicle entering and exiting the construction site, and provides an effective technical support for the safety management of the construction site.

Description

Technical Field

[0001] The present invention belongs to the technical field of image recognition, and in particular to a method and system for intelligently identifying and detecting vehicles entering and leaving a construction site. Background Art

[0002] With the acceleration of urbanization, construction activities on construction sites are becoming more frequent, and the pressure on construction site safety management is increasing. The management of vehicles entering and leaving the construction site is not only related to construction site safety, but also involves construction efficiency, resource allocation and the safety of the public. Therefore, how to efficiently and accurately identify and manage vehicles entering and leaving the construction site has become an important issue in current construction site safety management.

[0003] Traditional methods of site vehicle management rely on manual inspection and paper records, which are slow to process information, prone to omissions and errors, and unable to respond to potential safety hazards in a timely manner. At the same time, the site environment is complex and changeable, with a wide variety of vehicle types, which limits the accuracy and efficiency of manual identification. In addition, at high-traffic site entrances and exits, vehicles queuing for inspection may also cause delays in construction progress and affect the overall progress of the project. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for intelligent identification and detection of vehicles entering and leaving a construction site, so as to address the deficiencies in the prior art. By comprehensively scanning and extracting information from target vehicles entering and leaving the construction site, accurate judgment of the vehicle's identity, type and safety status can be achieved, thereby providing effective technical support for construction site safety management.

[0005] An embodiment of the present application provides a method for intelligently identifying and detecting vehicles entering and leaving a construction site, the method comprising: Collect multiple vehicle images of target vehicles entering and leaving the construction site from different angles, and monitor the driving information of the target vehicles; Identify the type and identity of the target vehicle based on multiple vehicle images taken at different angles; If the target vehicle is identified as an unknown vehicle, an alarm is triggered and sent to the security terminal for manual review; If the target vehicle is identified as a known vehicle, extracting specific part information of the vehicle in the vehicle image, wherein the specific part information is information to be detected to determine whether it complies with the safety regulations for construction site vehicles; The driving information and the specific part information are compared with preset construction site vehicle safety specifications, and a behavior score of the target vehicle is calculated, so as to perform intelligent detection and management of the target vehicle based on the behavior score.

[0006] Optionally, identifying the type and identity of the target vehicle based on a plurality of vehicle images taken at different angles includes: Input the plurality of vehicle images at different angles into a pre-trained vehicle recognition model, and output the vehicle type of the target vehicle; Extracting a plurality of specific identification features from the plurality of vehicle images at different angles, wherein the specific identification features at least include: a license plate information feature; Compare the vehicle type and the specific identification features with the vehicle types and specific identification features in the collected and stored historical vehicle images one by one; According to the comparison result, the identity of the target vehicle is identified, wherein the identity includes: a known vehicle and an unknown vehicle.

[0007] Optionally, the driving information includes at least: driving speed; The comparing the driving information and the specific part information with the preset construction site vehicle safety specification and calculating the behavior score of the target vehicle includes: Determine whether each driving information and each specific part information complies with the preset construction site vehicle safety regulations; For driving information or specific part of information that fully complies with the preset construction site vehicle safety regulations, the driving information or specific part of information that fully complies with the regulations is scored as a first score; For the driving information or specific part of the information that partially complies with the preset construction site vehicle safety regulations, scoring the partially compliant driving information or specific part of the information into a second score according to the degree of partial compliance; For driving information or specific part of information that does not conform to the preset construction site vehicle safety regulations at all, the driving information or specific part of information that does not conform at all is scored as a third score; Determine a weight score of the importance of each driving information and each specific part of information to the safety of the construction site vehicle, and calculate a behavior score of the target vehicle based on the first score, the second score, the third score and the weight score.

[0008] Optionally, the performing intelligent detection management on the target vehicle based on the behavior score includes: If the behavior score is greater than the first preset safety score, sending a release instruction to the security terminal; If the behavior score is less than or equal to the first preset security score and greater than the second preset security score, and the average of the historical behavior scores is higher than the preset security threshold, a release instruction is sent to the security terminal; If the behavior score is less than or equal to the first preset security score and greater than the second preset security score, and the average of the historical behavior scores is not higher than the preset security threshold, a manual inspection instruction is sent to the security terminal; If the behavior score is less than or equal to the second preset security score, a manual inspection instruction is sent to the security terminal.

[0009] Another embodiment of the present application provides a system for intelligent identification and detection of vehicles entering and leaving a construction site, the system comprising: A collection module is used to collect multiple vehicle images of target vehicles entering and leaving the construction site from different angles, and monitor the driving information of the target vehicles; An identification module, used to identify the type and identity of the target vehicle based on multiple vehicle images taken at different angles; A trigger module, for triggering and sending an alarm to a security terminal for manual review if the target vehicle is identified as an unknown vehicle; An extraction module, for extracting specific part information of the vehicle in the vehicle image if the target vehicle is identified as a known vehicle, wherein the specific part information is information to be detected to determine whether it complies with the safety regulations for construction site vehicles; The detection module is used to compare the driving information and the specific part information with the preset construction site vehicle safety specifications, and calculate the behavior score of the target vehicle, so as to perform intelligent detection and management of the target vehicle based on the behavior score.

[0010] Yet another embodiment of the present application provides a storage medium, wherein the storage medium stores a computer program, wherein the computer program is configured to execute any of the above methods when running.

[0011] Yet another embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute any of the methods described above.

[0012] Compared with the prior art, the present invention provides an intelligent identification and detection method for vehicles entering and leaving a construction site, which collects multiple vehicle images of target vehicles entering and leaving the construction site at different angles, and monitors the driving information of the target vehicles; identifies the type and identity of the target vehicle based on the multiple vehicle images at different angles; if the target vehicle is an unknown vehicle, triggers and sends an alarm to a security terminal for manual review; if the target vehicle is a known vehicle, extracts specific part information of the vehicle in the vehicle image; compares the driving information and specific part information with preset construction site vehicle safety specifications, and calculates the behavior score of the target vehicle, so as to perform intelligent detection and management of the target vehicle based on the behavior score, thereby being able to accurately judge the identity, type and safety status of the vehicle by comprehensively scanning and extracting information from the target vehicles entering and leaving the construction site, thereby providing effective technical support for construction site safety management. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A hardware structure block diagram of a computer terminal for a method for intelligently identifying and detecting vehicles entering and leaving a construction site provided by an embodiment of the present invention; Figure 2 A schematic diagram of a flow chart of a method for intelligently identifying and detecting vehicles entering and leaving a construction site provided by an embodiment of the present invention; Figure 3 A schematic structural diagram of a system for intelligently identifying and detecting vehicles entering and leaving a construction site provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0014] The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, but should not be construed as limiting the present invention.

[0015] The embodiment of the present invention firstly provides a method for intelligently identifying and detecting vehicles entering and leaving a construction site. The method can be applied to electronic devices, such as computer terminals, specifically ordinary computers, etc.

[0016] The following describes it in detail by taking running on a computer terminal as an example. Figure 1 The hardware structure block diagram of a computer terminal for a method for intelligently identifying and detecting vehicles entering and leaving a construction site provided by an embodiment of the present invention. Figure 1 As shown, the computer terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Optionally, the computer terminal may also include a transmission device 106 for communication functions and an input and output device 108. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above-mentioned computer terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0017] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / modules corresponding to the intelligent identification and detection method for vehicles entering and leaving the construction site in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0018] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of a computer terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0019] See also Figure 2 The embodiment of the present invention provides a method for intelligently identifying and detecting vehicles entering and leaving a construction site, which may include the following steps: S201, collecting multiple vehicle images of target vehicles entering and leaving the construction site at different angles, and monitoring the driving information of the target vehicles; In practical applications, the construction site environment is complex and there are many types of vehicles, so a monitoring method that can fully perceive the characteristics and dynamic behavior of vehicles is needed. By acquiring high-quality vehicle images from multiple angles, the system can more comprehensively capture the appearance characteristics of the vehicle, including the vehicle model, color, special signs (such as damage, pollution, etc.) and body accessories (such as roof license plates, etc.). This information is crucial for identifying the identity of the vehicle, especially in low light or partial occlusion conditions, where a single perspective is often insufficient to provide comprehensive information.

[0020] In addition, monitoring the vehicle's driving information (such as speed, acceleration, dwell time, etc.) lays the foundation for vehicle behavior analysis and safety scoring. These dynamic data help determine whether the vehicle complies with construction site safety regulations, such as whether the speed exceeds the standard, whether abnormal acceleration occurs, etc. This step not only provides the necessary data basis for the subsequent identification and management process, but also improves the accuracy and safety of identification by capturing multi-angle images and driving information. One implementation method may include: 1. Multi-angle camera module design: Multiple high-resolution cameras are placed at the entrance of the construction site. These cameras are arranged at different angles (for example, front view, side view, and top view) to cover all directions of the vehicle entry and exit path.

[0021] Configure the camera's autofocus and optical zoom functions to meet image acquisition needs at different distances and lighting conditions.

[0022] 2. Dynamic perspective adjustment and synchronization mechanism: Design a dynamic perspective adjustment algorithm based on computer vision. The algorithm analyzes the preliminary image of the camera in real time, identifies the vehicle's entry direction and expected driving trajectory, and automatically adjusts the camera's shooting angle and focal length.

[0023] Use a time synchronization protocol (e.g. PTP - Precision Time Protocol) to unify the capture time between cameras to ensure timing consistency between images.

[0024] 3. Multimodal sensor fusion: Based on the camera, LiDAR and radar sensors are integrated to capture the precise position information and velocity vector of the vehicle. A data fusion algorithm is introduced to combine visual data with LiDAR point cloud data to generate a high-precision 3D vehicle model.

[0025] 4. Edge computing and real-time processing: Introduce edge computing devices to achieve real-time processing of image and sensor data. By running pre-processing algorithms (e.g., edge detection, license plate recognition, etc.) on edge devices, the processed data is transmitted to the central server to reduce bandwidth consumption and latency. Design low-latency data communication protocols to ensure fast and reliable data exchange between sensors and edge devices, and between edge devices and central servers.

[0026] 5. Intelligent driving information monitoring and analysis: Deploy intelligent traffic sensors to capture vehicle speed, acceleration and path change information in real time. Use intelligent algorithms to analyze vehicle speed change patterns and trajectory deviations to identify potential abnormal behaviors (such as speeding, sudden braking, and illegal U-turns).

[0027] Through the above steps, multi-angle and all-round monitoring and identification of vehicles can be achieved in the construction site environment, ensuring that the system outputs high-precision recognition results under different lighting and complex backgrounds, providing solid data support for subsequent identification and safety management.

[0028] S202, identifying the type and identity of the target vehicle based on a plurality of vehicle images taken at different angles; In a construction site environment, vehicle type and identity recognition is crucial to ensuring site safety and management efficiency. By acquiring vehicle images from multiple angles, the system can more comprehensively analyze vehicle features and provide accurate recognition results.

[0029] At the entrance of a construction site, vehicles may enter at different angles and speeds. Therefore, images from a single perspective are often insufficient to effectively extract all necessary vehicle features. Through multi-angle image acquisition, the system is able to capture the full view of the vehicle, thereby more accurately identifying the vehicle's brand, model, color and other information. This integrated analysis of multi-angle views helps improve the robustness and accuracy of recognition, especially when the vehicle has a complex shape or is obstructed. In addition, by comparing the type of vehicle and the identity information in the historical data, the system can quickly determine whether the vehicle is an authorized vehicle, thereby triggering a security alarm when necessary.

[0030] Specifically, the plurality of vehicle images at different angles may be input into a pre-trained vehicle recognition model to output the vehicle type of the target vehicle; Inputting multi-angle images into the deep learning model is a key step in identifying vehicle types. The pre-trained vehicle recognition model can automatically analyze the features in the image and identify the vehicle's brand, model, and other information. Multi-angle input increases the completeness and accuracy of the information.

[0031] A deep convolutional neural network (CNN) with a multi-branch structure can be designed, where each branch is used to process images from different angles. In the second-layer fusion branch structure, the features extracted by each branch are merged through the feature fusion module, and the importance of different angles is dynamically weighted using the attention mechanism. Finally, the fully connected layer and Softmax classifier are used to output the type of vehicle.

[0032] Extracting a plurality of specific identification features from the plurality of vehicle images at different angles, wherein the specific identification features at least include: a license plate information feature; Extracting specific identification features of a vehicle, such as a license plate, is a necessary step in identifying the vehicle. License plate information is the most direct vehicle identification mark and can be used for accurate identity verification.

[0033] Recurrent neural networks (RNNs) combined with long short-term memory (LSTM) networks can be used to perform sequence processing on multi-angle images to identify license plate information in the images. Multi-scale feature pyramids are constructed to capture license plate features of different sizes and angles. Regularized convolutional layers are applied to reduce the impact of angle changes and improve the robustness of license plate recognition.

[0034] Compare the vehicle type and the specific identification features with the vehicle types and specific identification features in the collected and stored historical vehicle images one by one; By comparing with historical vehicle data, the system can verify the identity of the vehicle and determine whether it is a known or unknown vehicle. This process is a key step in ensuring vehicle access rights management.

[0035] A hash index database can be built to store the hash codes of all historical vehicle types and specific identification features, and feature indexing can be achieved through hash codes. When comparing features, the local sensitive hashing (LSH) algorithm is used to accelerate the feature comparison process, and the similarity is measured by hash distance. If the similarity exceeds a certain threshold, the comparison is considered consistent. Furthermore, fuzzy matching technology can be combined in the comparison process to tolerate subtle differences in features caused by changes in lighting or angle.

[0036] According to the comparison result, the identity of the target vehicle is identified, wherein the identity includes: a known vehicle and an unknown vehicle.

[0037] The vehicle identity is identified based on the comparison results to ensure that only known vehicles can enter the construction site directly, and unknown vehicles need to be manually checked first. This process not only improves safety, but also facilitates dynamic management and recording of vehicle flow.

[0038] S203, if the target vehicle is identified as an unknown vehicle, triggering and sending an alarm to a security terminal for manual review; When the system identifies an unknown vehicle through the vehicle identification program, it means that the vehicle has not appeared in the historical data and may pose a potential safety risk. Therefore, the system automatically triggers an alarm and sends the information to the security terminal immediately for manual review. The manual review process includes further image analysis, data comparison and on-site verification of the unknown vehicle to ensure that the safety of the construction site is not threatened. One implementation method may include: 1. Set alarm trigger conditions: During the recognition process, the system uses pre-set threshold judgment conditions to clearly define under what circumstances the identified vehicle will be marked as an "unknown vehicle". For example, when the confidence of the recognition model is lower than a certain value (such as 0.7), the system automatically marks the vehicle as unknown.

[0039] 2. Generate alarm information: Once marked as an "unknown vehicle", the system will immediately generate an alarm message containing key information. The alarm information should include: vehicle image, recognition time, recognition confidence, vehicle entry and exit time, location, and comparison results with historical data (if no record).

[0040] 3. Realize real-time data transmission: The system quickly transmits alarm information to the security terminal through the Internet or a dedicated network. Use reliable data transmission protocols (such as MQTT or WebSocket) to ensure the timeliness and integrity of information, and encrypt the data to ensure transmission security.

[0041] 4. Security terminal receiving and processing process: After the security terminal receives the alarm, it immediately triggers the preset manual review workflow, which includes: automatically pushing the alarm information to the security personnel's mobile device or terminal to ensure timely information transmission; providing real-time monitoring video stream for security personnel to further analyze the vehicle status and surrounding environment and assess potential threats; generating manual review task records, including review time, processing personnel, review results and other information for subsequent review and archiving.

[0042] 5. Further analysis and feedback mechanism: If the security personnel confirm that the vehicle is indeed an unknown vehicle during the review process, the system will record the information and update the database; if the vehicle information is confirmed and registered, the information will be fed back to the recognition model to optimize future recognition capabilities; at the same time, a regular review mechanism is set up to regularly analyze the results of unknown vehicle processing, identify potential false alarms and missed alarms, and further optimize system performance.

[0043] Through this series of steps, the system has a flexible, efficient and reliable alarm mechanism, which ensures the sustainability and effectiveness of construction site safety management and improves the comprehensive capabilities of intelligent detection.

[0044] S204, if the target vehicle is identified as a known vehicle, extracting specific part information of the vehicle in the vehicle image, wherein the specific part information is information to be detected to determine whether it complies with the safety regulations for construction site vehicles; This step aims to conduct a more in-depth monitoring and evaluation of known vehicles, and to determine whether they meet the safety regulations of the construction site by extracting specific parts of information. These specific parts may include key safety components such as the vehicle's safety logo, tire condition, headlights, and reflectors. The extraction of this information is not only to ensure the safety of the vehicle, but also to provide a basis for the overall safety management of the construction site. One implementation method may include: 1. Image preprocessing and segmentation: After obtaining the vehicle image, image preprocessing is performed first, including denoising, contrast enhancement and other operations. Then, image segmentation technology is used to extract specific parts of the vehicle image (such as lights, tires, license plates, etc.). Semantic segmentation or instance segmentation algorithms such as U-Net or Mask R-CNN are used to classify the vehicle image pixel by pixel and separate the key components.

[0045] 2. Feature extraction and description: Extract features from the segmented specific parts, and use feature descriptor algorithms (such as SIFT, SURF or HOG) to extract feature information such as shape, color and texture. These features will be used for subsequent matching. Taking tires as an example, the tread depth, crack conditions, etc. of the tire can be analyzed to determine whether it meets safety standards.

[0046] 3. Compliance detection: Based on the preset safety regulations of the construction site, a compliance detection model is established. The model can be a rule-based system that judges specific parts of the extracted information: such as whether the tire tread depth meets the national standards, whether the headlights are on, etc. The extracted features are compared with the set safety standards, and the system will generate a corresponding compliance score.

[0047] 4. Risk scoring and feedback generation: For each specific part, if there is a non-conformity, the system will automatically generate a risk score and record the specific information of the non-compliance. For example, if insufficient tire depth is detected, a risk alert will be generated, and the defect, tire location, and image evidence will be recorded to form a complete inspection report.

[0048] 5. Information integration and report generation: After all test results are summarized, a vehicle safety compliance report is generated, which includes vehicle identification information, test results of specific parts, compliance judgment and recommended measures. The report can also be pushed to the security integrated management platform in real time through a dynamic interface, so that managers can quickly obtain information.

[0049] Through the above steps, this method not only effectively extracts and evaluates specific part information of the vehicle, ensuring the safety compliance of known vehicles on the construction site, but also improves the overall efficiency and accuracy of intelligent detection, laying a solid foundation for construction site safety management.

[0050] S205, comparing the driving information and the specific part information with preset construction site vehicle safety specifications, and calculating a behavior score of the target vehicle, so as to perform intelligent detection and management of the target vehicle based on the behavior score.

[0051] The core of this step is to conduct detailed analysis and scoring by comparing the collected driving information (such as speed, driving trajectory) and the extracted specific information (such as the status of vehicle safety components) with the pre-set construction site vehicle safety regulations. This process aims to quantify the safety compliance of the vehicle, identify possible risks, and provide decision-making basis for intelligent inspection management through the behavior scoring system.

[0052] Specifically, the driving information includes at least: driving speed; it can be determined whether each driving information and each specific part of information conforms to the preset construction site vehicle safety specification; First, a standardized data set is established based on the driving information obtained from the vehicle identification module and the specific part of the information extracted. Each driving information and specific part of the information (such as speed, light status, tire condition, etc.) is checked item by item with the preset construction site vehicle safety regulations, and a logistic regression model is used to form the pass and fail judgment criteria.

[0053] For driving information or specific part of information that fully complies with the preset construction site vehicle safety regulations, the driving information or specific part of information that fully complies with the regulations is scored as a first score; For driving information and specific partial information that are judged to be fully compliant, by setting a full score standard (for example, a full score of 1), the compliant item is directly scored as a first score, for example, 1. A unified scoring standard can be used, and the score is stored in a database for subsequent analysis and reference.

[0054] For the driving information or specific part of the information that partially complies with the preset construction site vehicle safety regulations, scoring the partially compliant driving information or specific part of the information into a second score according to the degree of partial compliance; For partially compliant parameters, corresponding second scores are set according to different compliance levels, such as 0.8 points and 0.6 points. Fuzzy logic algorithms can also be used to calculate the compliance, combining fuzzy logic and membership functions to form an effective scoring mechanism.

[0055] For driving information or specific part of information that does not conform to the preset construction site vehicle safety regulations at all, the driving information or specific part of information that does not conform at all is scored as a third score; For items that are completely non-compliant, the system will mark this information as serious non-compliance and give the lowest third score, such as 0. These non-compliant items not only affect the overall score, but will also be marked when the system generates a risk report, and send warning messages to the corresponding managers.

[0056] For example, assume that the driving information and specific part information of a construction site vehicle are monitored, including the following parameters: 1. Driving speed (standard range: 30-60 km / h) 2. Headlight status (should be on) 3. Rearview mirror condition (should be intact) During the monitoring process, the following test results were obtained: - Driving speed: 55 km / h (compliant) - Headlight status: Off (non-compliant) - Rearview mirror condition: slight scratches (partially compliant) Scoring mechanism: 1. Driving speed - Compliance: The driving speed of 55 km / h is within the specification, so a full score of 1 point is awarded.

[0057] 2. Headlight status - Compliance: The headlights were not illuminated, so it was considered a total non-compliance and was scored 0 points.

[0058] 3. Rearview mirror status - Eligible condition: The rearview mirror has slight scratches, and the score can be set as follows: - Completely compliant (no scratches): 1 point - Partially compliant (minor scratches): 0.6 points - Not at all (severely damaged): 0 points In this case, the mirror had a minor scratch, so I scored it 0.6 points.

[0059] Determine a weight score of the importance of each driving information and each specific part of information to the safety of the construction site vehicle, and calculate a behavior score of the target vehicle based on the first score, the second score, the third score and the weight score.

[0060] According to the importance of each piece of information in the safety specification, a weighted score is set. For example, the speed may have a higher weight, while the light status may have a relatively lower weight. The score of each item is multiplied by the weight through a weighted formula and then accumulated to finally calculate the behavior score of the target vehicle. The score can be weighted averaged to ensure that more important safety factors have a greater impact on the total score, and a comprehensive report can be generated for management decision-making.

[0061] Specifically, the target vehicle is intelligently detected and managed based on the behavior score, and if the behavior score is greater than a first preset safety score, a release instruction is sent to a security terminal; When the behavior score of the target vehicle is higher than the first preset safety score, it means that the safety and compliance of the vehicle meet high standards, so it can be released directly without manual intervention. This step can improve the efficiency of vehicles passing through the construction site, reduce unnecessary waiting time, thereby improving logistics efficiency and enhancing the overall operation smoothness of the construction site.

[0062] If the behavior score is less than or equal to the first preset security score and greater than the second preset security score, and the average of the historical behavior scores is higher than the preset security threshold, a release instruction is sent to the security terminal; Under this condition, if the vehicle's behavior score does not meet the highest safety standards, but its historical score is good, the system will automatically consider the vehicle to have a high probability of compliance and release it. This step can achieve a "trust but verify" management concept by referring to historical data, which ensures safety without affecting normal logistics operations.

[0063] If the behavior score is less than or equal to the first preset security score and greater than the second preset security score, and the average of the historical behavior scores is not higher than the preset security threshold, a manual inspection instruction is sent to the security terminal; When the vehicle's behavior score is in the middle range and the historical score does not meet the preset standard, the system will automatically request a manual inspection to ensure safety. This mechanism is designed to detect and handle risks in a timely manner, ensuring that there are sufficient inspection guarantees even in normal operating procedures to improve overall safety.

[0064] If the behavior score is less than or equal to the second preset security score, a manual inspection instruction is sent to the security terminal.

[0065] When the vehicle's behavior score is lower than the specified minimum safety standard, the system will automatically prevent the vehicle from entering the construction site and require security personnel to conduct a manual inspection to assess the vehicle's safety hazards. This step can effectively avoid safety accidents and ensure the safety of construction site operations.

[0066] Through this implementation method, the system not only focuses on the current behavior score, but also fully considers the changes in historical data and dynamic environment, making intelligent detection management more accurate, flexible and safe.

[0067] It can be seen that multiple vehicle images of target vehicles entering and leaving the construction site are collected from different angles, and the driving information of the target vehicles is monitored; the type and identity of the target vehicle are identified based on the multiple vehicle images from different angles; if the target vehicle is an unknown vehicle, an alarm is triggered and sent to the security terminal for manual review; if the target vehicle is a known vehicle, specific part information of the vehicle in the vehicle image is extracted; the driving information and specific part information are compared with the preset construction site vehicle safety specifications, and the behavior score of the target vehicle is calculated, so as to perform intelligent detection and management of the target vehicle based on the behavior score, so as to achieve accurate judgment of the identity, type and safety status of the vehicle by comprehensively scanning and extracting information of the target vehicles entering and leaving the construction site, thereby providing effective technical support for construction site safety management.

[0068] Another embodiment of the present invention provides an intelligent identification and detection system for vehicles entering and leaving a construction site, see Figure 3 , the system may include: The acquisition module 301 is used to acquire multiple vehicle images of target vehicles entering and leaving the construction site at different angles, and monitor the driving information of the target vehicles; The identification module 302 is used to identify the type and identity of the target vehicle based on multiple vehicle images at different angles; A trigger module 303 is used to trigger and send an alarm to a security terminal for manual review if the target vehicle is identified as an unknown vehicle; An extraction module 304 is used to extract specific part information of the vehicle in the vehicle image if the target vehicle is identified as a known vehicle, wherein the specific part information is information to be detected to determine whether it complies with the safety regulations for construction site vehicles; The detection module 305 is used to compare the driving information and the specific part information with the preset construction site vehicle safety specifications, and calculate the behavior score of the target vehicle, so as to perform intelligent detection and management of the target vehicle based on the behavior score.

[0069] It can be seen that multiple vehicle images of target vehicles entering and leaving the construction site are collected from different angles, and the driving information of the target vehicles is monitored; the type and identity of the target vehicle are identified based on the multiple vehicle images from different angles; if the target vehicle is an unknown vehicle, an alarm is triggered and sent to the security terminal for manual review; if the target vehicle is a known vehicle, specific part information of the vehicle in the vehicle image is extracted; the driving information and specific part information are compared with the preset construction site vehicle safety specifications, and the behavior score of the target vehicle is calculated, so as to perform intelligent detection and management of the target vehicle based on the behavior score, so as to achieve accurate judgment of the identity, type and safety status of the vehicle by comprehensively scanning and extracting information of the target vehicles entering and leaving the construction site, thereby providing effective technical support for construction site safety management.

[0070] An embodiment of the present invention further provides a storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when running.

[0071] Specifically, in this embodiment, the above storage medium may be configured to store a computer program for performing the following steps: S201, collecting multiple vehicle images of target vehicles entering and leaving the construction site at different angles, and monitoring the driving information of the target vehicles; S202, identifying the type and identity of the target vehicle based on a plurality of vehicle images taken at different angles; S203, if the target vehicle is identified as an unknown vehicle, triggering and sending an alarm to a security terminal for manual review; S204, if the target vehicle is identified as a known vehicle, extracting specific part information of the vehicle in the vehicle image, wherein the specific part information is information to be detected to determine whether it complies with the safety regulations for construction site vehicles; S205, comparing the driving information and the specific part information with preset construction site vehicle safety specifications, and calculating a behavior score of the target vehicle, so as to perform intelligent detection and management of the target vehicle based on the behavior score.

[0072] It can be seen that multiple vehicle images of target vehicles entering and leaving the construction site are collected from different angles, and the driving information of the target vehicles is monitored; the type and identity of the target vehicle are identified based on the multiple vehicle images from different angles; if the target vehicle is an unknown vehicle, an alarm is triggered and sent to the security terminal for manual review; if the target vehicle is a known vehicle, specific part information of the vehicle in the vehicle image is extracted; the driving information and specific part information are compared with the preset construction site vehicle safety specifications, and the behavior score of the target vehicle is calculated, so as to perform intelligent detection and management of the target vehicle based on the behavior score, so as to achieve accurate judgment of the identity, type and safety status of the vehicle by comprehensively scanning and extracting information of the target vehicles entering and leaving the construction site, thereby providing effective technical support for construction site safety management.

[0073] An embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0074] Specifically, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0075] Specifically, in this embodiment, the processor may be configured to perform the following steps through a computer program: S201, collecting multiple vehicle images of target vehicles entering and leaving the construction site at different angles, and monitoring the driving information of the target vehicles; S202, identifying the type and identity of the target vehicle based on a plurality of vehicle images taken at different angles; S203, if the target vehicle is identified as an unknown vehicle, triggering and sending an alarm to a security terminal for manual review; S204, if the target vehicle is identified as a known vehicle, extracting specific part information of the vehicle in the vehicle image, wherein the specific part information is information to be detected to determine whether it complies with the safety regulations for construction site vehicles; S205, comparing the driving information and the specific part information with preset construction site vehicle safety specifications, and calculating a behavior score of the target vehicle, so as to perform intelligent detection and management of the target vehicle based on the behavior score.

[0076] It can be seen that multiple vehicle images of target vehicles entering and leaving the construction site are collected from different angles, and the driving information of the target vehicles is monitored; the type and identity of the target vehicle are identified based on the multiple vehicle images from different angles; if the target vehicle is an unknown vehicle, an alarm is triggered and sent to the security terminal for manual review; if the target vehicle is a known vehicle, specific part information of the vehicle in the vehicle image is extracted; the driving information and specific part information are compared with the preset construction site vehicle safety specifications, and the behavior score of the target vehicle is calculated, so as to perform intelligent detection and management of the target vehicle based on the behavior score, so as to achieve accurate judgment of the identity, type and safety status of the vehicle by comprehensively scanning and extracting information of the target vehicles entering and leaving the construction site, thereby providing effective technical support for construction site safety management.

[0077] The above describes in detail the structure, features and effects of the present invention based on the embodiments shown in the drawings. The above is only a preferred embodiment of the present invention, but the present invention is not limited to the scope of implementation shown in the drawings. Any changes made according to the concept of the present invention, or modifications to equivalent embodiments with equivalent changes, which still do not exceed the spirit covered by the description and drawings, should be within the protection scope of the present invention.

Claims

1. A method for intelligent identification and detection of vehicles entering and leaving a construction site, characterized in that: The method comprises: Collect multiple vehicle images of target vehicles entering and leaving the construction site from different angles, and monitor the driving information of the target vehicles; Identify the type and identity of the target vehicle based on multiple vehicle images taken at different angles; If the target vehicle is identified as an unknown vehicle, an alarm is triggered and sent to the security terminal for manual review; If the target vehicle is identified as a known vehicle, extracting specific part information of the vehicle in the vehicle image, wherein the specific part information is information to be detected to determine whether it complies with the safety regulations for construction site vehicles; The driving information and the specific part information are compared with preset construction site vehicle safety specifications, and a behavior score of the target vehicle is calculated, so as to perform intelligent detection and management of the target vehicle based on the behavior score.

2. The method according to claim 1, characterized in that The method of identifying the type and identity of the target vehicle based on multiple vehicle images from different angles includes: Input the plurality of vehicle images at different angles into a pre-trained vehicle recognition model, and output the vehicle type of the target vehicle; Extracting a plurality of specific identification features from the plurality of vehicle images at different angles, wherein the specific identification features at least include: a license plate information feature; Compare the vehicle type and the specific identification features with the vehicle types and specific identification features in the collected and stored historical vehicle images one by one; According to the comparison result, the identity of the target vehicle is identified, wherein the identity includes: a known vehicle and an unknown vehicle.

3. The method according to claim 2, characterized in that The driving information at least includes: driving speed; The comparing the driving information and the specific part information with the preset construction site vehicle safety specification and calculating the behavior score of the target vehicle includes: Determine whether each driving information and each specific part information complies with the preset construction site vehicle safety regulations; For driving information or specific part of information that fully complies with the preset construction site vehicle safety regulations, the driving information or specific part of information that fully complies with the regulations is scored as a first score; For the driving information or specific part of the information that partially complies with the preset construction site vehicle safety regulations, scoring the partially compliant driving information or specific part of the information into a second score according to the degree of partial compliance; For driving information or specific part of information that does not conform to the preset construction site vehicle safety regulations at all, the driving information or specific part of information that does not conform at all is scored as a third score; Determine a weight score of the importance of each driving information and each specific part of information to the safety of the construction site vehicle, and calculate a behavior score of the target vehicle based on the first score, the second score, the third score and the weight score.

4. The method according to claim 3, characterized in that The intelligent detection and management of the target vehicle based on the behavior score includes: If the behavior score is greater than the first preset safety score, sending a release instruction to the security terminal; If the behavior score is less than or equal to the first preset security score and greater than the second preset security score, and the average of the historical behavior scores is higher than the preset security threshold, a release instruction is sent to the security terminal; If the behavior score is less than or equal to the first preset security score and greater than the second preset security score, and the average of the historical behavior scores is not higher than the preset security threshold, a manual inspection instruction is sent to the security terminal; If the behavior score is less than or equal to the second preset security score, a manual inspection instruction is sent to the security terminal.

5. An intelligent identification and detection system for vehicles entering and leaving a construction site, characterized in that: The system comprises: A collection module is used to collect multiple vehicle images of target vehicles entering and leaving the construction site from different angles, and monitor the driving information of the target vehicles; An identification module, used to identify the type and identity of the target vehicle based on multiple vehicle images taken at different angles; A trigger module, for triggering and sending an alarm to a security terminal for manual review if the target vehicle is identified as an unknown vehicle; An extraction module, for extracting specific part information of the vehicle in the vehicle image if the target vehicle is identified as a known vehicle, wherein the specific part information is information to be detected to determine whether it complies with the safety regulations for construction site vehicles; The detection module is used to compare the driving information and the specific part information with the preset construction site vehicle safety specifications, and calculate the behavior score of the target vehicle, so as to perform intelligent detection and management of the target vehicle based on the behavior score.

6. The system according to claim 5, characterized in that The identification module is specifically used for: Input the plurality of vehicle images at different angles into a pre-trained vehicle recognition model, and output the vehicle type of the target vehicle; Extracting a plurality of specific identification features from the plurality of vehicle images at different angles, wherein the specific identification features at least include: a license plate information feature; Compare the vehicle type and the specific identification features with the vehicle types and specific identification features in the collected and stored historical vehicle images one by one; According to the comparison result, the identity of the target vehicle is identified, wherein the identity includes: a known vehicle and an unknown vehicle.

7. The system according to claim 6, characterized in that The driving information at least includes: driving speed; the detection module is specifically used to: Determine whether each driving information and each specific part information complies with the preset construction site vehicle safety regulations; For driving information or specific part of information that fully complies with the preset construction site vehicle safety regulations, the driving information or specific part of information that fully complies with the regulations is scored as a first score; For the driving information or specific part of the information that partially complies with the preset construction site vehicle safety regulations, scoring the partially compliant driving information or specific part of the information into a second score according to the degree of partial compliance; For driving information or specific part of information that does not conform to the preset construction site vehicle safety regulations at all, the driving information or specific part of information that does not conform at all is scored as a third score; Determine a weight score of the importance of each driving information and each specific part of information to the safety of the construction site vehicle, and calculate a behavior score of the target vehicle based on the first score, the second score, the third score and the weight score.

8. The system according to claim 7, characterized in that The detection module is specifically used for: If the behavior score is greater than the first preset safety score, sending a release instruction to the security terminal; If the behavior score is less than or equal to the first preset security score and greater than the second preset security score, and the average of the historical behavior scores is higher than the preset security threshold, a release instruction is sent to the security terminal; If the behavior score is less than or equal to the first preset security score and greater than the second preset security score, and the average of the historical behavior scores is not higher than the preset security threshold, a manual inspection instruction is sent to the security terminal; If the behavior score is less than or equal to the second preset security score, a manual inspection instruction is sent to the security terminal.

9. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the method according to any one of claims 1 to 4 when executed.

10. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to perform the method according to any one of claims 1 to 4.

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