A method, system, device and medium for departure management with trusted trajectory and visual detection

Abstract

The present application relates to the technical field of construction off-site closed-loop management, and particularly relates to a reliable trajectory and visual detection off-site management method, system, device and medium. It comprises the following steps: calling trajectory data of construction personnel corresponding to construction work order, automatically comparing trajectory data with construction work order rules, and outputting trajectory compliance verification results; triggering visual scanning of the construction area, collecting construction area images and performing intelligent detection of residual objects, and outputting residual object detection and risk classification results; confirming the exit state of the construction personnel, cross-verifying the positioning terminal data and the entrance and exit personnel count data, and outputting personnel exit confirmation results; performing multi-condition joint accountability according to the trajectory compliance verification results, the residual object detection and risk classification results, and the personnel exit confirmation results, allowing off-site when all conditions are met, and generating a signature record; when any condition is not met, the off-site application is rejected and the rejection reason is output.

Description

Technical Field

[0001] This invention relates to the field of closed-loop management technology for construction site departure, and in particular to a method, system, equipment, and medium for departure management based on reliable trajectory and visual detection. Background Technology

[0002] In scenarios with extremely high requirements for security, confidentiality, and environmental stability, such as computer rooms, data centers, substations, and communication base stations, the full-process management of construction activities (such as equipment installation, line modification, maintenance, and repair) is a crucial link in ensuring the safety of core facilities. Among these, the site departure phase, as the final stage of the entire construction lifecycle, directly relates to the safety of on-site assets, environmental cleanliness, subsequent operational safety, and the completeness of accountability. Loopholes in site departure management can lead to a series of serious problems, including tools or cables left behind causing equipment short circuits, personnel remaining in restricted areas creating safety hazards, undetected construction beyond designated boundaries leading to data leaks or facility damage, and the lack of complete traceability evidence afterward, resulting in the inability to determine responsibility.

[0003] Currently, the management methods for construction site departure in the industry are mainly divided into the following three categories: Manual verification mode: After the construction is completed, the site manager or the client's supervisor will conduct a manual inspection of the construction area to confirm whether there are any leftovers and whether all personnel have been evacuated. At the same time, they will check the paper or electronic documents such as the construction personnel sign-in sheets and construction work orders to determine whether there are any violations such as exceeding the time limit or going beyond the boundaries.

[0004] Single technology-assisted mode: In some scenarios, positioning technology (such as GPS, Bluetooth beacon) or video surveillance technology is introduced to record only the trajectory of construction personnel, or to check the construction area only by monitoring. The departure verification still needs to be done manually, and the technical means are not strongly bound to the departure signature.

[0005] Simple process mode: The work order system records the start and end time of construction and the permitted construction area, but it lacks real-time verification of the trajectory and intelligent detection of leftovers, and only uses "personnel application to leave the site + verbal confirmation from the administrator" as the basis for release.

[0006] However, the above-mentioned existing technical solutions have the following drawbacks in practical applications: First, the verification process is inefficient, reliant on manual labor, and prone to errors. Manual verification requires a significant amount of time to check each construction area one by one, especially in complex scenarios such as large computer rooms and multi-level base stations, where the probability of missing checks is extremely high. At the same time, when manually verifying tracks and work order information, fatigue and negligence can easily lead to violations going undetected (such as hidden abandoned tools or unregistered personnel).

[0007] Secondly, trajectory data is unreliable and lacks proactive compliance verification. Existing positioning technology can only record trajectories and cannot automatically compare them with the permitted range, path, and time of the work order, resulting in a disconnect between trajectory records and rules. Furthermore, it is difficult to detect pseudo-compliance behavior (such as appearing to be within the permitted range but actually briefly crossing the boundary before returning) during manual verification. Trajectory data cannot serve as the core basis for compliance determination.

[0008] Secondly, the detection of abandoned items is lagging behind, posing significant safety hazards. Manual inspection has limited ability to identify small abandoned items (such as thin wires, screwdrivers, and washers), which may cause serious equipment malfunctions. Some scenarios rely on surveillance playback for inspection, but playback is inefficient, prone to omissions, and cannot intercept the risk of abandoned items in real time before leaving the site.

[0009] Furthermore, the departure conditions are loose and lack mandatory closed-loop constraints. In the existing scheme, conditions such as personnel evacuation, compliance with trajectory, and absence of abandoned items are mostly determined independently, lacking a mandatory binding logic that requires all conditions to be met before departure is permitted. This leaves room for irregular operations such as personnel not being completely evacuated but signing off, or leaving behind items but allowing departure, indicating significant loopholes in the management process.

[0010] Finally, data traceability is weak, and liability determination is difficult. Trajectory data and verification records are mostly stored in a scattered manner, without forming an encrypted and tamper-proof evidence storage system; moreover, there is a lack of standardized audit reports, making it impossible to quickly trace violations during construction in the event of a safety incident, resulting in unclear liability determination. In addition, the manual verification model is subject to the risk of human intervention such as favoritism and unauthorized signatures, and requires a large amount of manpower for on-site monitoring, resulting in high management costs and poor stability. Summary of the Invention

[0011] The technical problem to be solved by the present invention is to provide a reliable trajectory and visual detection departure management method, system, equipment and medium to solve the technical problems of existing construction departure management, such as strong reliance on manual labor, lack of proactive compliance verification of trajectory, lag in detection of abandoned objects and lack of mandatory closed-loop constraints on departure conditions.

[0012] The technical solution of the present invention to solve the above-mentioned technical problems is as follows: In a first aspect, the present invention provides an exit management method based on reliable trajectory and visual detection, comprising: Obtain the construction departure request and lock the corresponding construction work order rules; Retrieve the trajectory data of the construction personnel corresponding to the construction work order, automatically compare the trajectory data with the construction work order rules, and output the trajectory compliance verification results; Trigger a visual scan of the construction area, collect images of the construction area and perform intelligent detection of debris, and output the results of debris detection and risk classification; Confirm the exit status of construction personnel, perform cross-validation by combining positioning terminal data and entrance / exit personnel count data, and output the personnel exit confirmation result; Based on the compliance verification results of the trajectory, the results of the detection and risk classification of abandoned items, and the results of the personnel exit confirmation, a multi-condition joint judgment is made. When all conditions are met, departure is allowed and a signature record is generated; when any condition is not met, the departure application is rejected and the reason for rejection is output. The data generated during the verification process is encrypted and stored as evidence, and a standardized audit report is generated based on the stored data.

[0013] Based on the above technical solution, the present invention can be further improved as follows.

[0014] Furthermore, the automatic comparison includes range comparison, path comparison, and time comparison; The range comparison includes: performing collision detection between the coordinate points of the trajectory data and the polygonal area of ​​the allowed construction range in the construction work order rules; if there are coordinate points outside the allowed range, it is determined to be an out-of-bounds violation. The path comparison includes: using a dynamic time warping algorithm to calculate the temporal similarity between the actual trajectory point sequence and the preset legal path sequence; if the similarity is lower than the preset similarity threshold, it is determined to be a path violation. The time comparison includes: calculating the actual construction time based on trajectory data; if the actual construction time exceeds the allowed construction time by a preset time threshold, it is determined to be an overtime violation. Based on the judgment results of boundary violation, path violation, and timeout violation, a trajectory compliance verification result is generated.

[0015] Furthermore, the process of acquiring images of the construction area and performing intelligent detection of debris, outputting debris detection and risk classification results, includes: The target detection model is used to detect targets in the collected construction area images and identify information about leftover objects. Based on the information about the abandoned items, the risks associated with the abandoned items are classified into high risk, medium risk, and low risk. If high-risk or medium-risk abandoned items are detected, an alarm is triggered and it is determined that the departure conditions are not met; if low-risk abandoned items are detected and the quantity is within the preset quantity threshold, they are marked and the departure conditions are determined to be met.

[0016] Furthermore, the confirmation of the construction personnel's exit status involves cross-validation of positioning terminal data and entrance / exit personnel count data, outputting a personnel exit confirmation result, including: Acquire the positioning terminal data of the construction personnel and determine whether the positioning coordinates fall outside the allowed construction range for a preset time. Simultaneously acquire cumulative data from entrance and exit personnel counting devices, and calculate the difference between the number of people entering and leaving; When the positioning coordinates of all construction personnel fall outside the allowed construction range for a preset time and the difference is zero, it is determined that all personnel will withdraw.

[0017] Furthermore, the multi-condition joint liability determination based on the trajectory compliance verification results, the results of abandoned object detection and risk classification, and the personnel exit confirmation results includes: Using the logical AND judgment rule, departure is permitted if and only if the trajectory compliance verification result is no violation, the result of the abandoned object detection and risk classification is no high-risk or medium-risk abandoned object and the number of low-risk abandoned objects meets the threshold, the personnel exit confirmation result is all exit and the verification process data is complete.

[0018] Furthermore, the process of encrypting and storing the data generated during the verification process, and generating a standardized audit report based on the stored data, includes: Encryption algorithms are used to encrypt and store trajectory data, image data, verification reports, and signature records, and the data hash values ​​are uploaded to the blockchain evidence storage platform. Extract the encrypted and stored data, and generate a standardized audit report according to a preset template, which includes work order information, trajectory compliance details, abandoned object detection results, personnel exit records, signature information, and storage hash value.

[0019] Secondly, the present invention provides an exit management system based on reliable trajectory and visual detection, comprising: The application receiving module is used to receive construction departure applications and lock the corresponding construction work order rules; The trajectory verification module is used to retrieve the trajectory data of construction personnel, automatically compare the trajectory data with the construction work order rules, and output the trajectory compliance verification result; the automatic comparison includes range comparison, path comparison and time comparison; The visual inspection module is used to trigger a visual scan of the construction area, acquire images of the construction area, perform intelligent detection of debris, and output the results of debris detection and risk classification. The personnel confirmation module is used to confirm the exit status of construction personnel. It performs cross-validation by combining positioning terminal data and personnel count data at entrances and exits, and outputs the personnel exit confirmation result. The joint accountability module is used to conduct multi-condition joint accountability based on the trajectory compliance verification results, the results of abandoned object detection and risk classification, and the personnel exit confirmation results. When all conditions are met, departure is allowed and a signature record is generated; when any condition is not met, the departure application is rejected and the reason for rejection is output. The evidence storage and auditing module is used to encrypt and store the data generated during the verification process, and to generate standardized audit reports based on the stored data.

[0020] Furthermore, the system adopts a collaborative architecture of hardware layer, data layer, algorithm layer and application layer; The hardware layer includes a Beidou and Bluetooth dual-mode positioning terminal, a high-definition AI vision acquisition unit, a personnel counting device, a communication module, and a server cluster; wherein, the personnel confirmation module performs cross-verification based on data from the Beidou and Bluetooth dual-mode positioning terminal and data from the personnel counting device; the visual detection module performs detection based on images acquired by the high-definition AI vision acquisition unit; The data layer includes a trajectory database, a work order rule database, an image database, and a verification result database, which are used to standardize and encrypt various types of data and provide data support for the trajectory verification module and the joint liability judgment module. The algorithm layer includes a spatiotemporal rule engine, an intelligent detection algorithm for abandoned objects, a multi-condition joint accountability algorithm, and an audit report generation algorithm, which are used to implement the core algorithm logic of the trajectory verification module, the visual detection module, the joint accountability module, and the evidence storage and auditing module, respectively. The application layer includes a work order management module, a real-time monitoring module, an exit application and signature module, a data traceability and audit module, and a system configuration module. The application receiving module realizes human-computer interaction through the exit application and signature module.

[0021] Thirdly, the present invention provides a computer device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of an exit management method based on a reliable trajectory and visual detection.

[0022] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the aforementioned reliable trajectory and visual detection departure management method. Attached Figure Description

[0023] Figure 1 A flowchart illustrating an exit management method based on reliable trajectory and visual detection; Figure 2 This is a schematic diagram of the structure of an exit management system based on reliable trajectory and visual detection. Figure 3 This is a schematic diagram of the electronic device of the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be described below with reference to the accompanying drawings. In the description of the present invention, unless otherwise stated, " / " indicates that the objects before and after are in an "or" relationship. For example, A / B can represent A or B. The "or" in the present invention is merely a description of the relationship between the related objects, indicating that three relationships can exist. For example, A or B can represent: A alone, A and B simultaneously, and B alone. A and B can be singular or plural. Furthermore, in the description of the present invention, unless otherwise stated, "multiple" refers to two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items.

[0025] Furthermore, to facilitate a clear description of the technical solutions of the embodiments of the present invention, the terms "first" and "second" are used in the embodiments of the present invention to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that the terms "first" and "second" are not necessarily different.

[0026] In this embodiment of the invention, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" or "for example" in this embodiment of the invention should not be construed as superior or more advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner for ease of understanding.

[0027] Example 1, such as Figure 1 As shown, this is the first embodiment of the present invention, which provides a method for construction site departure management based on reliable trajectory and visual detection. The construction site departure management process of this embodiment follows a closed-loop logic of application, verification, judgment, signature, and evidence storage. The specific steps are as follows: In this embodiment of the application, step S1, obtaining the construction departure application and locking the corresponding construction work order rule, is specifically implemented as follows: Once the construction task is completed, the construction manager submits a departure application through the application layer's departure application and signature module. The application information includes the work order ID, application time, and the construction manager's signature. After receiving the application, the system automatically locks the construction rules for that work order, prohibits modification, and triggers the subsequent verification process.

[0028] In this embodiment of the application, step S2 retrieves the trajectory data of the construction personnel corresponding to the construction work order, automatically compares the trajectory data with the construction work order rules, and outputs the trajectory compliance verification result. The specific implementation method is as follows: the system automatically retrieves the complete trajectory data of all construction personnel corresponding to the work order (the complete trajectory from the start of construction to the application for departure) from the trajectory database; the spatiotemporal rule engine compares the retrieved trajectory data with the construction scope, path, duration, and restricted areas in the work order rule database one by one.

[0029] S2.1: The range comparison includes: performing collision detection between the coordinate points of the trajectory data and the polygonal area of ​​the allowed construction range in the construction work order rules. If there are coordinate points that fall outside the allowed range, it is determined to be an out-of-bounds violation.

[0030] Range comparison: Collision detection is performed between the trajectory coordinates and the polygonal area of ​​the allowed construction range. If any coordinate point falls outside the allowed range, it is marked as an out-of-bounds violation, and the violation time, location, and duration are recorded.

[0031] S2.2: The path comparison includes: using a dynamic time warping algorithm to calculate the temporal similarity between the actual trajectory point sequence and the preset legal path sequence; if the similarity is lower than the preset similarity threshold, it is determined to be a path violation.

[0032] It should be noted that, in the embodiments of this application, the dynamic time warping algorithm is the DTW algorithm.

[0033] Path comparison: The DTW algorithm is used to calculate the similarity between the actual trajectory and the preset legal path. If the similarity is less than 85%, it is marked as a path violation and a trajectory comparison map is generated (the legal path and the actual path are displayed overlaid).

[0034] S2.3: The time comparison includes: calculating the actual construction time based on trajectory data; if the actual construction time exceeds the allowed construction time by a preset time threshold, it is determined to be an overtime violation.

[0035] Time comparison: Calculate the actual construction time (from the start time of the trajectory to the time of application for departure). If it exceeds the allowable time by ±10 minutes, it is marked as an overtime violation and the overtime duration is recorded.

[0036] S2.4: Based on the judgment results of boundary violation, path violation, and timeout violation, generate trajectory compliance verification results. Specifically, the spatiotemporal rule engine generates a trajectory compliance verification report, clearly indicating whether compliance is achieved and details of any violations (including screenshots and timelines).

[0037] In this embodiment of the application, step S3 triggers a visual scan of the construction area, collects images of the construction area and performs intelligent detection of debris, and outputs the results of debris detection and risk classification. The specific implementation method is as follows: the system sends a full-area scan command to all visual acquisition units in the construction area. The visual units perform full image acquisition of the construction area in a preset order (from the core equipment area to the passage area, from high to low). The acquisition interval is 1 second, and the cumulative number of acquired images is ≥10 (ensuring no dead angle coverage).

[0038] S3.1: Based on the target detection model, target detection is performed on the collected construction area images to identify information about leftover objects; In this embodiment, the target detection model is a deep learning-based target detection model (improved YOLOv8).

[0039] Construct a labeled sample library (≥100,000 samples) containing tools (screwdrivers, wrenches, electric drills, etc.), wires (network cables, power cords, optical fibers, etc.), and miscellaneous items (packaging bags, beverage bottles, gaskets, etc.). Train the model to ensure a detection accuracy of ≥99% and a false detection rate of ≤0.5%.

[0040] The images acquired by the vision unit are denoised, enhanced, and distortion corrected to ensure that the image quality meets the detection requirements. The deep learning-based object detection model (improved YOLOv8) scans the preprocessed image pixel by pixel to identify the category, location (marked with a coordinate box), and size of the remnant, and calculates the distance between the remnant and the core device.

[0041] S3.2: Based on the information about the abandoned items, classify the risks of the abandoned items into high risk, medium risk and low risk.

[0042] Based on the type and location of the abandoned items, the risks are divided into three levels (Level 1: High risk, such as conductive tools near equipment; Level 2: Medium risk, such as wires scattered in the passageway; Level 3: Low risk, such as debris far from equipment), and different handling strategies are corresponding to different risk levels.

[0043] S3.3: If high-risk or medium-risk abandoned items are detected, an alarm is triggered and it is determined that the departure conditions are not met; if low-risk abandoned items are detected and the quantity is within the preset quantity threshold, they are marked and the departure conditions are determined to be met.

[0044] If Level 1 or Level 2 debris is detected, the system immediately triggers an alarm, displays the location and image of the debris in a pop-up window on the real-time monitoring module, and notifies the construction supervisor to clean it up. If Level 3 debris is detected, the system automatically marks its location for easy cleanup later. The intelligent debris detection algorithm generates a debris detection report, clearly indicating the debris category, location, risk level, and processing status.

[0045] In this embodiment of the application, step S4 confirms the exit status of the construction personnel, performs cross-validation by combining the positioning terminal data and the personnel count data at the entrance and exit, and outputs the personnel exit confirmation result. The specific implementation method is as follows: S4.1: Obtain the positioning terminal data of the construction personnel and determine whether the positioning coordinates fall outside the allowed construction range for a preset time.

[0046] The system retrieves location terminal data from all construction personnel and checks whether the terminals are outside the construction area (location coordinates fall outside the allowable range for ≥5 minutes). If any personnel are still in the area, they are marked as not having logged out, and a reminder message is sent to their terminals.

[0047] S4.2: Synchronously acquire the cumulative data from the personnel counting devices at entrances and exits, and calculate the difference between the number of people entering and leaving.

[0048] The system synchronously retrieves the cumulative data of the personnel counting device at the entrance and exit, calculates the difference between the number of people entering and the number of people leaving, and if the difference is not equal to 0, it is marked as not all personnel have been evacuated, and the administrator is prompted to check the entrance and exit monitoring.

[0049] S4.3: When the positioning coordinates of all construction personnel fall outside the allowed construction range for a preset time and the difference is zero, it is determined that all personnel should exit.

[0050] Only when the positioning terminal data shows that all personnel have left and the difference in the counting device is 0, is it determined that all personnel have exited.

[0051] In this embodiment, step S5 performs a multi-condition joint judgment based on the trajectory compliance verification result, the abandoned object detection and risk classification result, and the personnel exit confirmation result. When all conditions are met, departure is allowed and a signature record is generated; when any condition is not met, the departure application is rejected and the reason for rejection is output. The specific implementation method is as follows: using the logical AND judgment rule, departure is allowed if and only if the trajectory compliance verification result is no violation, the abandoned object detection and risk classification result is no high-risk and medium-risk abandoned objects and the number of low-risk abandoned objects meets the threshold, the personnel exit confirmation result is all exited, and the verification process data is complete.

[0052] When the multi-condition joint accountability algorithm receives the trajectory compliance verification report, the abandoned object detection report, and the personnel exit confirmation result, it makes a judgment based on logic and rules: If all conditions are met, the system will automatically generate a permission to leave the site instruction, update the work order status to "left the site", send a signature success notification to the construction personnel and the administrator, and record the signature time and the operator. If any condition is not met, the system will generate a "Do Not Leave" instruction, clearly stating the reason for rejection (e.g., there is a Level 1 remnant, location: next to server 2 in area B of the computer room, personnel XXX has not left the construction area), and send it to the construction manager's terminal. After the rectification is completed, the leave application can be submitted again, and the system will repeat the verification process of steps S2-S4. All verification data and signature results are first encrypted and stored in the database, then uploaded to the blockchain for evidence storage. The storage order is strictly consistent with the verification process to ensure traceability and tamper-proof nature. Signature results are synchronized to the verification result database in real time, generating tamper-proof signature records.

[0053] It should be noted that the multi-condition joint judgment algorithm is the core logic of the departure verification. It adopts a logical AND judgment rule, and only when all of the following conditions are met simultaneously will departure be deemed permitted: The spacetime rule engine determines that there are no out-of-bounds, no timeouts, and no lingering in restricted areas. The intelligent algorithm for detecting abandoned objects determines that there are no Level 1 or Level 2 abandoned objects in the construction area, and the number of Level 3 abandoned objects is ≤3 (the threshold can be customized) and they have been marked. The positioning terminal shows that all construction workers have left the construction area, and the cumulative count difference at the entrance and exit of the personnel counting device is 0 (number of people entering = number of people leaving). The trajectory data, image data, and work order data are complete and without any abnormalities (such as the positioning terminal not being offline and the vision unit not being faulty).

[0054] In this embodiment of the application, step S6 encrypts and stores the data generated during the verification process, and generates a standardized audit report based on the stored data. The specific implementation method is as follows: S6.1: Use encryption algorithms to encrypt and store trajectory data, image data, verification reports and signature records, and upload the data hash value to the blockchain evidence storage platform; It should be noted that, in the embodiments of this application, the encryption algorithm used is the AES-256 encryption algorithm.

[0055] The system will encrypt all data from this departure verification (trajectory data, image data, verification report, and signature record) using AES-256, store it in the corresponding database, and upload the data hash value to the blockchain evidence storage platform to ensure that the data is tamper-proof and traceable.

[0056] S6.2: Extract the encrypted and stored data, and generate a standardized audit report according to the preset template, which includes work order information, trajectory compliance details, abandoned object detection results, personnel exit records, signature information and storage hash value.

[0057] The audit report generation algorithm automatically extracts the above data and generates a standardized audit report according to a preset template. The report includes the following core content: Basic information of a work order: Work order ID, name of the construction project, construction time, and list of construction personnel; Track compliance details: track timeline, compliance judgment result, violation screenshots (if any), track evidence hash value; Results of artifact detection: detection time, type and location of artifact, risk level, processing status, and image evidence hash value; Personnel Exit Records: Personnel list, exit time, screenshot of location terminal data, personnel counting device data; Signature information: Signature time, signature status, operator; After the audit report is generated, the system sends a notification to the administrator, who can then view and export the report in the data traceability and audit module.

[0058] It should be noted that the beneficial effects of the embodiments of this application compared to the prior art are as follows: This system automates the entire departure verification process, addressing the issues of heavy reliance on manual labor and low efficiency. By automatically comparing travel routes and using AI-powered visual detection to replace manual checks, it significantly improves verification efficiency and reduces the risk of human error and unauthorized intervention.

[0059] A reliable trajectory proactive compliance verification mechanism is established to address the issue of unreliable trajectory data. The trajectory is automatically and accurately compared with work order rules (range, path, time) to eliminate false compliance behavior and ensure the reliability of trajectory data as the core basis for compliance judgment.

[0060] By introducing visual AI-based risk classification and detection, the problem of delayed object detection is addressed. High / medium risk objects are intercepted in real time before the object leaves the site, eliminating the safety hazard of serious equipment malfunctions caused by small objects.

[0061] Establish a multi-condition mandatory closed-loop constraint logic to solve the problem of loose departure conditions. Set the compliance of the trajectory, the absence of high-risk abandoned items, and the complete evacuation of personnel as necessary and sufficient conditions for the logical AND operation, and eliminate the loopholes of allowing the release of personnel even if they have signed off on the departure before all personnel have been evacuated or if there are abandoned items.

[0062] To address the issue of weak traceability, we have established an encrypted evidence storage and automated auditing system. Utilizing AES-256 encryption and blockchain evidence storage, we ensure the immutability of verified data and automatically generate standardized audit reports, providing a legally binding basis for post-event traceability and liability determination.

[0063] Example 2, as Figure 2 As shown, this embodiment provides a reliable trajectory and visual detection departure management system. The system architecture of this embodiment includes four layers: hardware layer, data layer, algorithm layer, and application layer. Each layer works together to form a complete technology chain. The application receiving module is used to receive construction departure applications and lock the corresponding construction work order rules; The trajectory verification module is used to retrieve the trajectory data of construction personnel, automatically compare the trajectory data with the construction work order rules, and output the trajectory compliance verification result; the automatic comparison includes range comparison, path comparison and time comparison; The visual inspection module is used to trigger a visual scan of the construction area, acquire images of the construction area, perform intelligent detection of debris, and output the results of debris detection and risk classification. The personnel confirmation module is used to confirm the exit status of construction personnel. It performs cross-validation by combining positioning terminal data and personnel count data at entrances and exits, and outputs the personnel exit confirmation result. The joint accountability module is used to conduct multi-condition joint accountability based on the trajectory compliance verification results, the results of abandoned object detection and risk classification, and the personnel exit confirmation results. When all conditions are met, departure is allowed and a signature record is generated; when any condition is not met, the departure application is rejected and the reason for rejection is output. The evidence storage and auditing module is used to encrypt and store the data generated during the verification process, and to generate standardized audit reports based on the stored data.

[0064] Hardware Layer (Data Acquisition Terminal): The hardware layer provides the system with basic data acquisition capabilities, including the following core devices: Positioning terminals: Each construction worker is equipped with a smart terminal (such as a smart work badge or positioning wristband) with dual-mode positioning functions of Beidou and Bluetooth. The positioning accuracy is ≤1 meter, and it supports trajectory sampling once per second to ensure the continuity and accuracy of trajectory data. The terminal has a built-in encryption chip, and the collected trajectory data is transmitted in real time with encryption to prevent data from being tampered with or forged.

[0065] The visual acquisition unit deploys high-definition AI cameras (resolution ≥ 4K, frame rate ≥ 30fps) at key locations in the construction area (such as entrances and exits, areas with dense equipment, and corners of passageways). The cameras support shooting in low-light environments (night vision distance ≥ 10 meters), have real-time image transmission and edge computing capabilities, and can provide 360° coverage of the construction area without blind spots.

[0066] Personnel counting equipment: Infrared counters or millimeter-wave radar counters are deployed at the entrances and exits of the construction area to complement the data from the positioning terminal and to confirm whether all personnel have exited.

[0067] Communication module: Adopts 5G and industrial Ethernet dual-mode communication to ensure real-time transmission of positioning data and image data with a latency of ≤100ms, avoiding data loss due to communication interruption.

[0068] Server cluster: Includes edge servers (deployed locally in the construction site for real-time data processing) and cloud servers (for data storage and audit report generation), supporting distributed computing and disaster recovery backup.

[0069] System deployment requirements: Visual acquisition units should be deployed at a density of one unit every 5–10 meters to cover the construction area, ensuring no blind spots in monitoring; positioning terminals should be bound one-to-one with construction personnel, and personnel counting devices at entrances and exits should be deployed in alignment with access control / channels to achieve accurate statistics on personnel entering and exiting.

[0070] Data Layer (Data Storage and Management): The data layer is responsible for standardizing, encrypting, storing, and efficiently managing various types of collected data, including: Track Database: Stores reliable track data of construction personnel throughout the entire process. Each track record includes fields such as personnel ID, timestamp (accurate to milliseconds), latitude and longitude coordinates, altitude, and positioning accuracy. The track data is encrypted and stored using the AES-256 encryption algorithm, and data notarization is achieved through blockchain technology to ensure that the generation time and content of each track cannot be tampered with.

[0071] Work Order Rules Database: Stores core rule information for construction work orders, including: work order ID, list of construction personnel, permitted construction area (polygonal area defined by latitude and longitude coordinates), permitted construction path (preset sequence of legal passage coordinates), permitted construction duration (start and end timestamps), restricted area (coordinate range of core facilities that are prohibited from entering), etc. The rule data supports dynamic updates and batch import.

[0072] Image Database: Stores image / video data of the construction area captured by the vision acquisition unit, indexed by timestamp and area ID, supporting quick retrieval and backtracking; the image data is compressed and stored using H.265 encoding, saving storage space while ensuring image clarity.

[0073] Verification Result Database: Stores the results of each departure verification, including the application departure time, trajectory comparison results, abandoned object detection results, personnel exit confirmation results, signature status, reasons for rejection, etc., to provide data support for the audit report.

[0074] The algorithm layer is the core of the system, responsible for intelligent analysis and judgment of the collected data, and includes the following core algorithm modules: Spatiotemporal rule engine: Developed based on Geographic Information System (GIS), it has three core functions: range comparison, path comparison, and time comparison. The range comparison involves performing polygon collision detection between the continuous trajectory coordinates of construction workers and the permitted construction area and restricted area of ​​the work order, determining the inclusion relationship between each point and the polygon. Judgment rule: If any trajectory point falls into the restricted area, it is directly judged as a violation of the restricted area rule. If the trajectory point exceeds the permitted construction area, it is judged as a violation of boundary; if the duration of a brief boundary violation is greater than 1 second, it is recorded to form a sequence of boundary violation time, location, and duration.

[0075] Path comparison compares the actual trajectory point sequence of construction workers with the preset legal path sequence of the work order, and uses the Dynamic Time Warping (DTW) algorithm to calculate temporal similarity. Algorithm steps: Sample the actual trajectory and standard path into equal-length coordinate sequences; construct a distance matrix and calculate the Euclidean distance between each point; use dynamic programming to find the warped path with the minimum cumulative distance; output a normalized similarity score. Judgment rules: If the similarity is <85%, the path is judged as illegal; differences in travel speed are ignored, and only the path shape is matched.

[0076] The time comparison uses the first appearance time of the trajectory as the construction start time and the departure application time as the end time to calculate the actual construction duration. Judgment rules: If the actual duration is greater than the allowed duration + 10 minutes, it is judged as an overtime violation; if the actual duration is less than the allowed duration - 10 minutes, it is considered an early departure abnormal time threshold. The threshold can be customized in the backend.

[0077] The final output of the spatiotemporal rules engine includes: trajectory compliance determination results, violation type, violation location, and timeline.

[0078] Intelligent Residue Detection Algorithm: Based on a deep learning-based object detection model (improved YOLOv8), the algorithm achieves residue detection through the following steps: Sample training: Construct a labeled sample library (≥100,000 samples) containing tools (over 30 common construction tools such as screwdrivers, wrenches, and electric drills), wires (network cables, power cords, optical fibers, etc.), and miscellaneous items (packaging bags, beverage bottles, gaskets, etc.) to train the model and ensure a detection accuracy of ≥99% and a false detection rate of ≤0.5%. Image preprocessing: The images acquired by the vision unit are denoised, enhanced, and distortion corrected to ensure that the image quality meets the detection requirements; Target recognition and localization: The model scans the preprocessed image pixel by pixel to identify the type, location (marked with a coordinate box), and size of the debris, and calculates the distance between the debris and the core equipment; Risk classification: Based on the type and location of the leftover items, the risk is divided into three levels (Level 1: High risk, such as conductive tools near equipment; Level 2: Medium risk, such as wires scattered in the channel; Level 3: Low risk, such as debris far from equipment). Different risk levels correspond to different handling strategies.

[0079] Algorithm output: list of abandoned items, location, risk level, marked image, and whether the departure conditions are met.

[0080] The multi-condition joint accountability algorithm, which is the core logic of the departure verification, adopts a logical AND judgment rule. Only when all of the following conditions are met simultaneously will departure be deemed permitted: The spacetime rule engine determines that there are no out-of-bounds, no timeouts, and no lingering in restricted areas. The intelligent algorithm for detecting abandoned items determines that there are no Level 1 or Level 2 abandoned items in the construction area, and the number of Level 3 abandoned items is ≤3 (the threshold can be customized) and they have been marked. The positioning terminal shows that all construction workers have left the construction area, and the cumulative count difference at the entrance and exit of the personnel counting device is 0 (number of people entering = number of people leaving). The trajectory data, image data, and work order data are complete and without any abnormalities (such as the positioning terminal not being offline and the vision unit not being faulty).

[0081] It automatically extracts key data from the trajectory database and verification result database, and generates a standardized audit report according to a preset template. The report includes basic work order information, compliance details of construction personnel's trajectory (including screenshots of violations and timelines), detection results of abandoned objects (including image markers of abandoned objects), personnel exit confirmation records, data storage hash values, etc. It supports PDF export and online viewing.

[0082] Application Layer (User Interaction and Functional Modules): The application layer provides users with a visual user interface and core functions, including the following modules: Work order management module: Supports work order creation, editing, approval, and issuance. Users can set rules such as construction scope, path, duration, and restricted areas in the module, and upload the list of construction personnel and the binding information of the positioning terminal.

[0083] Real-time monitoring module: Visually displays the real-time trajectory of construction workers (marked with dynamic icons on the GIS map), real-time images of the construction area (supports switching between multiple cameras, zooming in and out), and the current verification status (such as "trajectory verification in progress" or "debris detection in progress"). Abnormal situations (such as boundary crossing or discovery of high-risk debris) will trigger a real-time pop-up alarm and send SMS / APP notifications to the administrator.

[0084] Departure Application and Sign-off Module: Construction personnel can submit departure applications through positioning terminals or mobile APPs, and the system will automatically trigger the verification process; administrators can view the verification progress and detailed results in the module, and for applications that are "not allowed to leave", they can view the reasons for rejection (such as "there is a boundary violation, time: 14:35, location: next to equipment No. 3 in area A of the computer room"), and issue rectification instructions.

[0085] Data traceability and auditing module: Users can query historical verification records and audit reports by work order ID, time range, construction personnel ID, etc., and view encrypted track data and image data; it supports track playback function (restoring the movement path of construction personnel according to the timeline) to facilitate post-event traceability.

[0086] System configuration module: supports user-defined verification rules (such as the risk threshold for abandoned objects, the similarity threshold for trajectory comparison, and the timeout threshold), equipment management (such as the status monitoring and fault alarm of vision units and positioning terminals), and user permission management (different operation permissions are assigned to different roles, such as administrators, supervisors, and construction personnel).

[0087] In some embodiments, the reliable trajectory and visual detection departure management system of the present invention can be implemented in a combination of hardware and software. As an example, the reliable trajectory and visual detection departure management system of the present invention can be a processor in the form of a hardware decoding processor, which is programmed to execute the reliable trajectory and visual detection departure management method of the present invention. For example, the processor in the form of a hardware decoding processor can be one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components.

[0088] The modules described in the embodiments of this invention can be implemented in software or hardware. The names of the modules are not, in some cases, limiting the scope of the module itself.

[0089] An electronic device according to an embodiment of the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any of the above-mentioned reliable trajectory and visual detection departure management methods. That is, an electronic device according to an embodiment of the present invention may include, but is not limited to: a processor and a memory; the memory is used to store the computer program; the processor is used to execute the reliable trajectory and visual detection departure management method shown in any embodiment of the present invention by calling the computer program.

[0090] In one alternative embodiment, an electronic device is provided, such as Figure 3 As shown, Figure 3The illustrated electronic device 4000 includes a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, for example, via a bus 4002. Optionally, the electronic device 4000 may further include a transceiver 4004, which can be used for data interaction between the electronic device and other electronic devices, such as sending and / or receiving data. It should be noted that in practical applications, the transceiver 4004 is not limited to one type, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present invention.

[0091] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this invention. Processor 4001 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0092] Bus 4002 may include a path for transmitting information between the aforementioned components. Bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 4002 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The bus 4002 is represented by only one thick line, but this does not mean that there is only one bus or one type of bus.

[0093] The memory 4003 may be ROM (Read Only Memory) or other types of static storage devices capable of storing static information and instructions, RAM (Random Access Memory) or other types of dynamic storage devices capable of storing information and instructions, or EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0094] The memory 4003 stores application code (computer program) for executing the present invention, and its execution is controlled by the processor 4001. The processor 4001 executes the application code stored in the memory 4003 to implement the content shown in the foregoing method embodiments.

[0095] Among them, electronic devices can also be terminal devices, which can be any device that can install applications, including at least one of smartphones, tablets, laptops, desktop computers, smart speakers, smartwatches, smart TVs, and smart in-vehicle devices.

[0096] It should be noted that, Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0097] An embodiment of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements any of the above-mentioned reliable trajectory and visual detection departure management methods.

[0098] Alternatively, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, a floppy disk, and an optical data storage device, etc.

[0099] In an exemplary embodiment, a computer program product or computer program is also provided, which includes computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the electronic device to perform the aforementioned reliable trajectory and visual detection departure management method.

[0100] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0101] It should be understood that the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0102] The computer-readable storage medium provided in this invention can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EEPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0103] The aforementioned computer-readable storage medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the method shown in the above embodiments.

[0104] The above description is merely a preferred embodiment of the present invention and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this invention is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-disclosed concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this invention.

[0105] It should be noted that the terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and represent a limitation on a specific order or sequence. Where appropriate, the order of use for similar objects can be interchanged so that the embodiments of this application described herein can be implemented in an order other than that shown or described.

[0106] Those skilled in the art will recognize that this invention can be implemented as a system, method, or computer program product. Therefore, this invention can be specifically implemented in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, this invention can also be implemented as a computer program product contained in one or more computer-readable media, which includes computer-readable program code.

[0107] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for departure management based on reliable trajectory and visual detection, characterized in that, include: Obtain the construction departure request and lock the corresponding construction work order rules; Retrieve the trajectory data of the construction personnel corresponding to the construction work order, automatically compare the trajectory data with the construction work order rules, and output the trajectory compliance verification results; Trigger a visual scan of the construction area, collect images of the construction area and perform intelligent detection of debris, and output the results of debris detection and risk classification; Confirm the exit status of construction personnel, perform cross-validation by combining positioning terminal data and entrance / exit personnel count data, and output the personnel exit confirmation result; Based on the compliance verification results of the trajectory, the results of the detection and risk classification of abandoned items, and the results of the personnel exit confirmation, a multi-condition joint judgment is made. When all conditions are met, departure is allowed and a signature record is generated; when any condition is not met, the departure application is rejected and the reason for rejection is output. The data generated during the verification process is encrypted and stored as evidence, and a standardized audit report is generated based on the stored data.

2. The departure management method based on reliable trajectory and visual detection according to claim 1, characterized in that, The automatic comparison includes range comparison, path comparison, and time comparison; The range comparison includes: performing collision detection between the coordinate points of the trajectory data and the polygonal area of ​​the allowed construction range in the construction work order rules; if there are coordinate points outside the allowed range, it is determined to be an out-of-bounds violation. The path comparison includes: using a dynamic time warping algorithm to calculate the temporal similarity between the actual trajectory point sequence and the preset legal path sequence; if the similarity is lower than the preset similarity threshold, it is determined to be a path violation. The time comparison includes: calculating the actual construction time based on trajectory data; if the actual construction time exceeds the allowed construction time by a preset time threshold, it is determined to be a violation of time limit. Based on the judgment results of boundary violation, path violation, and timeout violation, a trajectory compliance verification result is generated.

3. The departure management method based on reliable trajectory and visual detection according to claim 1, characterized in that, The process involves collecting images of the construction area and performing intelligent detection of debris, outputting debris detection and risk classification results, including: The target detection model is used to detect targets in the collected construction area images and identify information about leftover objects. Based on the information about the abandoned items, the risks associated with the abandoned items are classified into high risk, medium risk, and low risk. If high-risk or medium-risk items are detected, an alarm is triggered and the departure conditions are not met; if low-risk items are detected and the quantity is within a preset threshold, they are marked and the departure conditions are met.

4. The departure management method based on reliable trajectory and visual detection according to claim 1, characterized in that, The process of confirming the exit status of construction personnel involves cross-validation of location terminal data and entrance / exit personnel count data to output a personnel exit confirmation result, including: Acquire the positioning terminal data of the construction personnel and determine whether the positioning coordinates fall outside the allowed construction area for a preset time. Simultaneously acquire cumulative data from entrance and exit personnel counting devices, and calculate the difference between the number of people entering and leaving; When the positioning coordinates of all construction personnel fall outside the allowed construction range for a preset time and the difference is zero, it is determined that all personnel will withdraw.

5. The departure management method based on reliable trajectory and visual detection according to claim 1, characterized in that, The joint liability determination based on multiple conditions, including the results of the trajectory compliance verification, the results of the abandoned object detection and risk classification, and the results of the personnel exit confirmation, includes: The decision rule is based on logical AND. The departure is allowed if and only if the trajectory compliance verification result is no violation, the result of the abandoned object detection and risk classification is no high-risk or medium-risk abandoned object and the number of low-risk abandoned objects meets the threshold, and the personnel exit confirmation result is all exit.

6. The departure management method based on reliable trajectory and visual detection according to claim 1, characterized in that, The process of encrypting and storing the data generated during the verification process, and generating a standardized audit report based on the stored data, includes: Encryption algorithms are used to encrypt and store trajectory data, image data, verification reports, and signature records, and the data hash values ​​are uploaded to the blockchain evidence storage platform. Extract the encrypted and stored data, and generate a standardized audit report according to a preset template, which includes work order information, trajectory compliance details, abandoned object detection results, personnel exit records, signature information, and storage hash value.

7. A reliable trajectory and visual detection departure management system, applied to the method of any one of claims 1-6, characterized in that, include: The application receiving module is used to receive construction departure applications and lock the corresponding construction work order rules; The trajectory verification module is used to retrieve the trajectory data of construction personnel, automatically compare the trajectory data with the construction work order rules, and output the trajectory compliance verification result; the automatic comparison includes range comparison, path comparison and time comparison; The visual inspection module is used to trigger a visual scan of the construction area, acquire images of the construction area, perform intelligent detection of debris, and output the results of debris detection and risk classification. The personnel confirmation module is used to confirm the exit status of construction personnel. It performs cross-validation by combining positioning terminal data and personnel count data at entrances and exits, and outputs the personnel exit confirmation result. The joint accountability module is used to conduct multi-condition joint accountability based on the trajectory compliance verification results, the results of abandoned object detection and risk classification, and the personnel exit confirmation results. When all conditions are met, departure is allowed and a signature record is generated; when any condition is not met, the departure application is rejected and the reason for rejection is output. The evidence storage and auditing module is used to encrypt and store the data generated during the verification process, and to generate standardized audit reports based on the stored data.

8. The departure management system based on reliable trajectory and visual detection according to claim 7, characterized in that, The system adopts a collaborative architecture of hardware layer, data layer, algorithm layer and application layer; The hardware layer includes a Beidou and Bluetooth dual-mode positioning terminal, a high-definition AI vision acquisition unit, a personnel counting device, a communication module, and a server cluster; wherein, the personnel confirmation module performs cross-verification based on data from the Beidou and Bluetooth dual-mode positioning terminal and data from the personnel counting device; the visual detection module performs detection based on images acquired by the high-definition AI vision acquisition unit; The data layer includes a trajectory database, a work order rule database, an image database, and a verification result database, which are used to standardize and encrypt various types of data and provide data support for the trajectory verification module and the joint liability judgment module. The algorithm layer includes a spatiotemporal rule engine, an intelligent detection algorithm for abandoned objects, a multi-condition joint accountability algorithm, and an audit report generation algorithm, which are used to implement the core algorithm logic of the trajectory verification module, the visual detection module, the joint accountability module, and the evidence storage and auditing module, respectively. The application layer includes a work order management module, a real-time monitoring module, an exit application and signature module, a data traceability and audit module, and a system configuration module. The application receiving module realizes human-computer interaction through the exit application and signature module.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

Images