GIS-BIM-based in-service road diseased section marking cooperation platform and method

Abstract

The invention discloses a GIS-BIM-based in-service road disease section marking cooperation platform and method, and the method comprises the steps: constructing an EBS structure tree model, importing the EBS structure tree model into a GIS system to form a GIS-BIM platform, and transmitting a to-be-inspected line and a stake number coordinate table to an unmanned plane; the unmanned aerial vehicle inspects and shoots a long picture and matches a stake number label, and the server cuts the picture and identifies disease features; and the GIS-BIM platform maps the disease pictures to the corresponding BIM model segments, and deletes the maps if no disease pictures are inspected again. The stake mark coordinate table is generated according to stake mark progressive increase, disease recognition adopts a convolutional neural network model, and color gradient distinguishing is performed according to severity. The platform integrates EBS and WBS dual-core structure trees, realizes full-period collaboration through stake mark interval dynamic mapping, improves the disease marking efficiency and precision, and realizes full-process digital operation and full-period automatic collaboration.

Description

Technical Field

[0001] The present invention relates to the technical field of highway digitization, and particularly relates to a collaborative platform and method for marking disease sections of in-service highways based on GIS-BIM. Background Art

[0002] In the technical field of highway digitization, traditional methods for marking disease sections of in-service highways mainly rely on manual inspections. This approach has significant drawbacks. Manual inspections are inefficient, difficult to quickly cover a large range of highway lines, and prone to missed inspections. At the same time, when manually locating disease sections, the accuracy is often insufficient, resulting in large deviations and inaccurate disease markings, which affect subsequent maintenance and repair work.

[0003] In addition, in the traditional highway maintenance management model, there are data island problems among links such as design, construction, and maintenance. The data of each link cannot be effectively interconnected and coordinated, making it difficult to efficiently connect processes such as disease location, task assignment, repair progress tracking, and completion data archiving, resulting in unreasonable scheduling of maintenance resources and low maintenance efficiency.

[0004] In terms of the management and display of disease information, traditional methods lack intuitive visualization means, making it difficult to clearly and quickly display the severity and distribution of diseases, and inconvenient for managers to make decisions and manage. Moreover, for the full-cycle data of disease treatment, there is a lack of a complete traceability system, which is not conducive to the long-term assessment and management of the health status of highway facilities.

[0005] In summary, the existing technologies have many deficiencies in the marking, location, management, and full-cycle coordination of disease sections of in-service highways, and there is an urgent need for a more efficient, accurate, and collaborative method and platform to solve these problems. Summary of the Invention

[0006] To solve the above technical problems, the present invention adopts the following solutions: A method for marking disease sections of in-service highways based on GIS-BIM, including a GIS-BIM platform. An EBS structure tree model is preset in the GIS-BIM platform. The EBS structure tree model divides the route into various facility sections. Each facility section includes a mileage interval of the starting mileage and the ending mileage, and the corresponding BIM model. The BIM model includes a road surface model, and the road surface model is segmented according to the mileage. The specific steps are as follows: S1. The GIS-BIM platform constructs a mileage coordinate table from the inspection route and the mileage and corresponding longitude and latitude coordinates of each facility section in the inspection route and sends it to the inspection UAV; S2. The inspection UAV conducts inspections according to the received inspection route and continuously takes pictures to obtain a long inspection road map of the entire route. While taking the long inspection road map, the UAV's longitude and latitude coordinates located by GPS on the inspection UAV are matched with the longitude and latitude of the stake numbers in the stake number coordinate table. If the match is successful, stake number labels are marked on the long inspection road map; S3. After the inspection UAV finishes inspecting the required inspection route, it sends the long inspection road map of the entire route to the server, and the server cuts the long inspection road map into stake number segmented pictures according to the stake number labels; S4. The server identifies the disease characteristics in the segmented pictures and marks the disease marks to obtain disease pictures, and sends the disease pictures with stake number labels to the GIS-BIM platform; S5. The GIS-BIM platform saves the disease pictures with stake number labels and traverses the stake number intervals of the BIM model according to the stake number labels of the disease pictures to achieve the matching of stake number intervals to obtain the matching facility sections. Then, it searches for the corresponding stake numbers and the corresponding road surface models in the matching facility sections through the stake number labels on the disease pictures, and loads the disease pictures onto the road surface models in the corresponding BIM models in the form of textures; S6. When the GIS-BIM platform does not receive the disease pictures of the corresponding BIM model after the inspection route passes through the UAV inspection again, it deletes the textures on the corresponding BIM model to display the road surface model in the corresponding BIM model, and deletes the corresponding disease pictures.

[0007] Each of the above-mentioned facility sections includes tunnels, bridges, and ordinary roads, all of which include road surfaces, and their corresponding BIM models also include road surface models.

[0008] Furthermore, In S1, the construction of the stake number coordinate table includes: Based on the road surface models of each facility section in the inspection route, extract the stake number intervals of each facility section, all stake numbers, and the longitude and latitude coordinates corresponding to all stake numbers, and generate a structured table in ascending order of stake numbers. The table fields include stake number, longitude, and latitude.

[0009] Furthermore, In S2, the matching method of the longitude and latitude coordinates located by the UAV GPS and the longitude and latitude of the stake numbers is: Calculate the Euclidean distance between the longitude and latitude of the surveying and mapping UAV and the longitude and latitude of each stake number in the stake number coordinate table in real time. If the Euclidean distance is less than or equal to the preset matching threshold, the match is successful, and the corresponding stake number label is marked on the long inspection map.

[0010] Furthermore, In S4, the recognition of disease characteristics uses a convolutional neural network model. The model supports multi-label classification, and the recognition types include at least one of cracks, potholes, settlement, and spalling.

[0011] Furthermore, The EBS and WBS are associated to form a dual-core structure tree. The EBS structure tree constructs a BIM model based on each facility section and the pile number, associating design parameters with disease information; the WBS structure tree is based on the decomposition of construction tasks, associating repair progress with maintenance resources; the two are dynamically mapped through the pile number interval to achieve full-cycle collaboration of disease location, task assignment, and completion data archiving.

[0012] Furthermore, The dynamic mapping includes: When the disease picture is loaded into the BIM model section, a corresponding construction task node is automatically generated in the WBS structure tree, and fields such as the responsible unit, estimated construction period, and repair status are bound; after the repair is completed, the completion attributes of the corresponding facility in the EBS structure tree and the status of the WBS task node are synchronously updated.

[0013] Furthermore, In S6, the corresponding disease picture is deleted, and the following operations are synchronously performed: The repaired BIM model is marked as "accepted", and the original disease picture, repair record, and acceptance report are archived to the completion database of the EBS structure tree and associated with the corresponding pile number interval.

[0014] Furthermore, A collaborative platform for marking disease sections of in-service highways based on GIS-BIM. The GIS-BIM platform pushes disease pictures, associated construction task information, and locations to repair personnel. After the inspection personnel fill in the repair progress, the task status change in the WBS structure tree is automatically updated, and a real-time notification is sent to the GIS-BIM platform simultaneously.

[0015] Furthermore, The collaborative platform includes a readable storage medium and a processor. The computer program in the readable storage medium is executed by the processor to implement the above method for marking disease sections of in-service highways based on GIS-BIM.

[0016] Compared with the prior art, the beneficial effects of the present invention are: 1. The present invention uses GIS-BIM platform integration and UAV intelligent inspection technology to achieve accurate positioning and visual marking of diseased road sections. By constructing an EBS structure tree model and importing it into the GIS system to form an integrated platform, the stake coordinates of the BIM model are deeply integrated with the GIS spatial positioning. In the application scenario, when the UAV conducts line inspection based on the stake coordinate table, the corresponding stake label is automatically marked in the inspection long map through the Euclidean distance matching of the GPS coordinates and the stake longitude and latitude (threshold 50m). The server then cuts the picture according to the stake number and identifies the disease, and finally accurately loads the disease picture to the surface of the BIM model segment in the form of a map. This process upgrades the traditional disease positioning method that relies on manual inspection to a full-process digital operation of "UAV shooting-automatic matching-intelligent identification-model positioning", avoiding manual missed inspections and positioning deviations, improving the efficiency and accuracy of disease marking, and distinguishing the severity of the disease (red / yellow / green) through color gradients, realizing intuitive and hierarchical management of highway diseases.

[0017] 2. Based on the full-cycle coordination mechanism of the dual-core structure tree (EBS and WBS), the full-process data link of disease management from discovery to repair is opened up. The platform integrates EBS (facility breakdown structure) and WBS (work breakdown structure), and realizes the seamless association of design parameters, disease information and construction tasks through dynamic mapping of pile number intervals. In the application scenario, when the disease image is loaded into the BIM model segment, the system automatically generates a construction task node in the WBS, binds the responsible unit, construction period and repair status; after the repair is completed, the completion attributes and WBS task status of the facility in the EBS are updated synchronously, and the original disease image and repair record are archived to the completion database. This mechanism breaks the data silos of design, construction and maintenance in traditional maintenance, realizes the full-cycle automated coordination of "disease location-task dispatch-progress tracking-acceptance archiving", reduces manual operation errors, improves the efficiency of maintenance resource scheduling, and provides a complete data traceability system for the full life cycle management of highways. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic diagram of a flow chart of the present invention; Figure 2 This is a schematic diagram of the EBS structure tree; Figure 3 It is a schematic diagram of line information; Figure 4 It is the intention of pile number coordinates; Figure 5 This is a schematic diagram of the matching range of the stake number longitude and latitude coordinates; Figure 6 Modeling sections for BIM.

[0019] Reference numerals: 1 - unmanned aerial vehicle, 2 - stake number, 3 - pavement model, 4 - facility section, 5 - stake number interval, 6 - guardrail model, 7 - middle layer model of foundation, 8 - foundation model, 9 - road center line, 10 - stake number longitude and latitude coordinate points, 11 - matching threshold. Detailed implementation manners

[0020] The following combines the embodiments and the accompanying drawings to further elaborate on the present invention in detail, but the implementation manners of the present invention are not limited thereto.

[0021] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "longitudinal", "lateral", "horizontal", "inner", "outer", "front", "rear", "top", "bottom", etc. is based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the product of the present invention is usually placed during use. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention.

[0022] In the description of the present invention, it should also be noted that unless otherwise clearly specified and defined, the terms "set", "provided with", "installed", "connected", "connected to" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations. Embodiment

[0023] A method for marking disease sections of in-service highways based on GIS - BIM includes a GIS - BIM platform. An EBS structure tree model is preset in the GIS - BIM platform. The EBS structure tree model divides the route into each facility section. Each facility section includes a stake number interval with a starting stake number and an ending stake number, and a corresponding BIM model. The BIM model includes a pavement model, and the pavement model is segmented according to the stake number. The specific steps are as follows: S1. The GIS - BIM platform constructs a stake number coordinate table from the inspection route, the stake numbers of each facility section in the inspection route, and the longitude and latitude coordinates corresponding to the stake numbers, and sends it to the inspection unmanned aerial vehicle. S2. The inspection unmanned aerial vehicle conducts inspections according to the received route to be inspected and continuously takes pictures to obtain a long inspection road map of the entire route. While taking the long inspection road map, the longitude and latitude coordinates of the unmanned aerial vehicle located by GPS on the inspection unmanned aerial vehicle are matched with the stake number longitude and latitude in the stake number coordinate table. If the match is successful, a stake number label is marked on the long inspection road map. S3. After the inspection UAV has completed the inspection of the line to be inspected, it sends the long inspection road map of the entire line to the server, and the server cuts the long inspection road map into stake-number segmented pictures according to the stake-number tags; S4. The server identifies the disease characteristics in the segmented pictures and marks the disease marks to obtain disease pictures, and sends the disease pictures with stake-number tags to the GIS-BIM platform; S5. The GIS-BIM platform saves the disease pictures with stake-number tags and traverses the stake-number intervals of the BIM model according to the stake-number tags of the disease pictures to achieve the matching of the stake-number intervals to obtain the matching facility sections. Then, it searches for the corresponding stake numbers and the corresponding road surface models in the matching facility sections through the stake-number tags on the disease pictures, and loads the disease pictures onto the road surface models in the corresponding BIM models in the form of textures; S6. After the inspection line passes through the UAV inspection again, when the GIS-BIM platform does not receive the disease pictures of the corresponding BIM model, it deletes the textures on the corresponding BIM model to display the road surface model in the corresponding BIM model, and deletes the corresponding disease pictures.

[0024] By importing different BIM models into the GIS system according to the hierarchical relationship of the EBS structure tree to form the GIS-BIM platform, the integration of hierarchical management and spatial positioning of highway facilities is realized. The EBS structure tree is constructed based on the BIM models of facility types, and can clearly express the hierarchical relationships of facilities (such as road surfaces, bridges, tunnels), sub-facilities (such as roadbeds, beam bodies, tunnel surfaces) and components (such as guardrails, lighting structures), which is convenient for refined management; combined with the spatial analysis ability of the GIS system, it can quickly locate the BIM model segments corresponding to diseases and improve the data collaboration efficiency.

[0025] When constructing the GIS-BIM platform of a certain expressway, first import the BIM models of facilities such as road surfaces, bridges, and tunnels into the GIS system layer by layer according to the EBS structure tree. For example, under the bridge facility, sub-facilities "beam body", "pile cap", and "pier column" are divided, and under the beam body sub-facility, components such as "T beam" and "diaphragm plate" are further divided. Each BIM model contains the stake number and the corresponding longitude and latitude coordinates. For example, the stake-number interval of the bridge beam body component is from K00+200 to K10+500, and the longitude and latitude coordinates are accurately matched to the position.

[0026] The structure of the EBS structure tree is as Figure 2 shown, where the design drawings in the relevant information of the EBS structure tree represent the BIM models selected and set in the EBS structure tree.

[0027] In one embodiment, each of the facility sections includes tunnels, bridges, and ordinary roads, and the cross-sectional structures of their BIM models are as Figure 6As shown, the BIM models corresponding to tunnels, bridges, and ordinary roads all include pavement models, and the segmentation of each facility section and the line information in the inspection route are as Figure 3 shown.

[0028] Furthermore, in the above S1, the construction of the stake number coordinate table includes: Based on the pavement models of each facility section in the inspection route, extract the stake number intervals of each facility section, all stake numbers, and the longitude and latitude coordinates corresponding to all stake numbers, and generate a structured table in ascending order of stake numbers. The table fields include stake number, longitude, and latitude.

[0029] Extract the stake numbers and longitude and latitude coordinates of the BIM model of the facility type in the line to be inspected, and generate a structured table containing the fields of "stake number, longitude, and latitude" in ascending order of stake numbers, providing an accurate coordinate matching benchmark for UAV inspection. Structured data avoids the confusion of coordinate information, and sorting by stake number facilitates the UAV to quickly retrieve and match in order during flight, improving the inspection efficiency and positioning accuracy.

[0030] In the embodiment, the stake number coordinate table is as Figure 4 shown. Extract all stake numbers (such as K0+000, K00+100…K21+000) and the corresponding longitude and latitude coordinates from its BIM model, and generate a stake number coordinate table in ascending order of stake numbers. When the UAV inspects this tunnel line, the carried stake number coordinate table can be matched with the UAV GPS coordinates in real time to ensure that the pictures taken at different stake number positions are accurately associated with the corresponding BIM model.

[0031] Furthermore, in the above S2, the matching method between the longitude and latitude coordinates of the UAV GPS positioning and the longitude and latitude of the stake number is: Calculate the Euclidean distance between the longitude and latitude of the surveying and mapping UAV and the longitude and latitude of each stake number in the stake number coordinate table in real time. If the Euclidean distance is less than or equal to the preset matching threshold, it is considered a successful match, and the corresponding stake number label is marked on the inspection long map.

[0032] In the embodiment, the stake number generally refers to the longitude and latitude coordinates referring to the longitude and latitude coordinates at the center line of the road corresponding to the stake number. The matching of the UAV longitude and latitude coordinates with the stake number longitude and latitude is as Figure 5 shown. The UAV flies along the center line of the inspection road, calculates the Euclidean distance between the longitude and latitude of the inspection UAV and the longitude and latitude of the stake number in real time, and compares it with the matching threshold to determine the trigger range of the inspection UAV, ensuring that the inspection UAV dynamically and accurately marks the stake number label during flight. It avoids the computational redundancy of global coordinate matching, only calculates the distance for adjacent stake numbers, and improves the matching efficiency; the threshold setting balances the positioning accuracy and the UAV flight error to ensure the reliability of the stake number label marking.

[0033] If in this inspection route, if the station number refers to the side line or isolation center line of the inspection route, then convert the longitude and latitude coordinates of the station number into longitude and latitude according to the distance from the station number to the road center line, calculate the longitude and latitude of the corresponding road center line based on the longitude and latitude of the station number itself, and then compare it with the matching threshold.

[0034] For example, when a drone inspects a bridge route, it obtains its own GPS coordinates in real time (such as longitude 118.001 and latitude 30.002), and calculates the Euclidean distance with the adjacent station numbers in the station number coordinate table (such as the longitude and latitude of K15+000 being 118.000 and 30.003). If the distance is 0.5m (< matching threshold of 1m), it is determined that the matching is successful, and the label of the K15+000 station number is marked on the inspection long map, providing an accurate basis for subsequent cutting of pictures according to the station number.

[0035] Furthermore, In S4, the recognition of disease characteristics uses a convolutional neural network model, and the model supports multi-label classification. The recognition types include at least one of cracks, potholes, settlement, and spalling.

[0036] Utilizing the characteristics of the convolutional neural network model that supports multi-label classification, it can simultaneously identify multiple disease types such as cracks, potholes, settlement, and spalling, and automatically associate severity levels, such as high risk, medium risk, and low risk, avoiding the subjectivity and missed inspections of manual recognition and improving the recognition efficiency.

[0037] After the server receives a segmented picture of a certain road surface, the convolutional neural network model automatically identifies two diseases, "crack (high risk)" and "spalling (low risk)". The system automatically generates a disease list according to the recognition results. The high-risk cracks trigger the maintenance process first, and the low-risk spalling is included in the daily inspection plan, realizing the differential management of diseases.

[0038] Furthermore, The EBS is associated with the WBS to form a dual-core structure tree. The EBS structure tree constructs a BIM model based on each facility section and station number, associating design parameters and disease information; the WBS structure tree is based on the decomposition of construction tasks, associating repair progress and maintenance resources; the two are dynamically mapped through the station number interval to achieve full-cycle collaboration of disease location, task assignment, and completion data archiving.

[0039] The EBS structure tree focuses on facility entities (such as road surfaces and bridges) and their disease information, and the WBS structure tree focuses on construction tasks) and their resource scheduling. The two are dynamically mapped through the station number interval to achieve full-cycle collaboration of "disease location - task assignment - repair progress - completion archiving". The dual-core architecture breaks the data islands in the design, construction, and maintenance links, ensures the consistency of data in each business link, and improves the collaboration efficiency and management accuracy of highway maintenance.

[0040] When the EBS structure tree locates a pavement disease section (pile number K00+000 - K00+500), the system automatically generates a task node of "pavement repair project" in the WBS structure tree and binds fields such as the responsible unit and the estimated construction period. During the repair process, the WBS updates the task status in real time (such as "under construction", "already accepted"), synchronously triggers the update of the completion attributes of the corresponding facilities in the EBS structure tree (such as "repair completed"), and archives the repair records to the EBS completion database to achieve full-process data linkage.

[0041] Furthermore, The dynamic mapping includes: When the disease picture is loaded into the BIM model section, a corresponding construction task node is automatically generated in the WBS structure tree, and fields such as the responsible unit, the estimated construction period, and the repair status are bound; after the repair is completed, the completion attributes of the corresponding facilities in the EBS structure tree and the status of the WBS task node are synchronously updated.

[0042] When the disease picture is loaded onto the surface of the pavement model in the BIM model section, a construction task node is automatically generated in the WBS structure tree, reducing manual operation errors and improving the task assignment efficiency; after the repair is completed, the EBS and WBS statuses are synchronously updated to ensure real-time data consistency and avoid information lag. This mechanism realizes the automatic connection between disease discovery and repair tasks, ensuring the timeliness and standardization of the maintenance process.

[0043] Furthermore, In S6, after deleting the corresponding disease picture, the following operations are synchronously executed: Mark the repaired BIM model as "already accepted", and archive the original disease picture, repair records, and acceptance report to the completion database of the EBS structure tree and associate them with the corresponding pile number range.

[0044] When deleting the disease picture texture, mark the BIM model section as "already accepted" synchronously, and archive the original disease picture, repair records, and acceptance report to the EBS completion database to ensure the traceability of the disease treatment process. This operation forms a complete maintenance management closed-loop, providing data support for subsequent facility health assessment and historical problem tracing.

[0045] After confirming that a bridge disease has been repaired during the next inspection, the GIS-BIM platform automatically deletes the disease texture of the bridge BIM model section, marks it as "already accepted", and archives the original disease picture, construction logs during the repair process, material inspection reports, acceptance forms, etc. to the completion database of the EBS structure tree and associates them with the corresponding pile number range.

[0046] Furthermore, A collaborative platform for marking disease sections of in-service highways based on GIS-BIM. The GIS-BIM platform pushes disease pictures, associated construction task information, and locations to repair personnel. After the inspection personnel fill in the repair progress, the task status change in the WBS structure tree is automatically updated, and a real-time notification is sent to the GIS-BIM platform.

[0047] Furthermore, The collaborative platform includes a readable storage medium and a processor. The computer program in the readable storage medium is executed by the processor to implement the above method for marking disease sections of in-service highways based on GIS-BIM.

[0048] The above is only a preferred embodiment of the present invention, and does not impose any form of limitation on the present invention. Based on the technical essence of the present invention, any simple modification, equivalent replacement, and improvement made to the above embodiments within the spirit and principle of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A method for marking disease sections of in-service highways based on GIS-BIM, characterized in that, It includes a GIS-BIM platform. An EBS structure tree model is preset in the GIS-BIM platform. The EBS structure tree model divides the route into various facility sections. Each facility section includes a mileage interval of a starting mileage and an ending mileage, and a corresponding BIM model. The BIM model includes a road surface model, and the road surface model is segmented by mileage. The specific steps are as follows: S1. The GIS-BIM platform constructs a mileage coordinate table from the inspection route, the mileages of each facility section in the inspection route, and the longitude and latitude coordinates corresponding to the mileages, and sends it to the inspection UAV. S2. The inspection UAV conducts inspections according to the received route to be inspected and continuously takes pictures to obtain a long inspection road map of the entire route. While taking the long inspection road map, the longitude and latitude coordinates of the UAV located by GPS on the inspection UAV are matched with the mileage longitude and latitude in the mileage coordinate table. If the match is successful, mileage labels are marked on the long inspection road map. S3. After the inspection UAV finishes inspecting the route to be inspected, it sends the long inspection road map of the entire route to the server. The server cuts the long inspection road map into mileage-segmented pictures according to the mileage labels. S4. The server identifies the disease characteristics in the segmented pictures and marks disease marks to obtain disease pictures, and sends the disease pictures with mileage labels to the GIS-BIM platform. S5. The GIS-BIM platform saves the disease pictures with mileage labels and traverses the mileage intervals of the BIM model according to the mileage labels of the disease pictures to achieve mileage interval matching to obtain the matching facility sections. Then, it searches for the corresponding mileages and the corresponding road surface models in the matching facility sections through the mileage labels on the disease pictures, and loads the disease pictures onto the road surface models in the corresponding BIM models in the form of textures. S6. After the inspection route passes through the UAV inspection again, when the GIS-BIM platform does not receive the disease pictures of the corresponding BIM model, it deletes the textures on the corresponding BIM model and displays the road surface model in the corresponding BIM model, and deletes the corresponding disease pictures.

2. A method for marking disease sections of in-service highways based on GIS-BIM according to claim 1, characterized in that, In the above S1, the construction of the mileage coordinate table includes: Based on the road surface models of each facility section in the inspection route, the mileage intervals of each facility section, all mileages, and the longitude and latitude coordinates corresponding to all mileages are extracted, and a structured table is generated in ascending order of mileage. The table fields include mileage, longitude, and latitude.

3. A method for marking disease sections of in-service highways based on GIS-BIM according to claim 1, characterized in that, In the above S2, the matching method of the longitude and latitude coordinates located by the UAV GPS and the mileage longitude and latitude is: The Euclidean distance between the longitude and latitude of the surveying and mapping UAV and the longitude and latitude of each mileage in the mileage coordinate table is calculated in real time. If the Euclidean distance is less than or equal to the preset matching threshold, the match is successful, and the corresponding mileage label is marked on the long inspection map.

4. A method for marking disease sections of in-service highways based on GIS-BIM according to claim 1, characterized in that, In the above S4, a convolutional neural network model is used to identify the disease characteristics. The model supports multi-label classification, and the identification types include at least one of cracks, potholes, subsidence, and spalling.

5. A method for marking disease sections of in-service highways based on GIS-BIM according to claim 1, characterized in that The EBS is associated with the WBS to form a dual-core structure tree. The EBS structure tree constructs a BIM model based on each facility section and the stake number, associating design parameters with disease information; the WBS structure tree is based on the decomposition of construction tasks, associating repair progress with maintenance resources; the two are dynamically mapped through the stake number interval to achieve full-cycle collaboration of disease location, task assignment, and completion data archiving.

6. The method for marking disease sections of in-service highways based on GIS-BIM according to claim 5, characterized in that, The dynamic mapping includes: When the disease picture is loaded into the BIM model section, a corresponding construction task node is automatically generated in the WBS structure tree, and the responsible unit, estimated construction period, and repair status fields are bound; after the repair is completed, the completion attributes of the corresponding facility in the EBS structure tree and the status of the WBS task node are synchronously updated.

7. A method for marking disease sections of in-service highways based on GIS-BIM according to claim 1, wherein In S6, the corresponding disease picture is deleted, and the following operations are synchronously performed: Mark the repaired BIM model as "accepted", and archive the original disease picture, repair record, and acceptance report to the completion database of the EBS structure tree, associating them with the corresponding stake number interval.

8. A collaborative platform for marking disease sections of in-service highways based on GIS-BIM, characterized in that, The GIS-BIM platform pushes the disease picture, associated construction task information, and location to the repair personnel. After the inspection personnel fill in the repair progress, the task status change in the WBS structure tree is automatically updated, and a real-time notification is sent to the GIS-BIM platform at the same time.

9. A collaborative platform for marking disease sections of in-service highways based on GIS-BIM according to claim 8, comprising a readable storage medium and a processor, characterized in that, The computer program in the readable storage medium is executed by the processor to implement a method for marking disease sections of in-service highways based on GIS-BIM according to any one of claims 1-7.

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