An automatic collection and trace management method and system for covert engineering image data

Abstract

The application discloses a kind of concealed engineering image data automatic acquisition and traceability management method and system, it is related to engineering management technical field, the whole process management data is constructed by obtaining concealed engineering image data;Extract the engineering element features in image data and management data, generate engineering entity image node;Based on engineering entity image node, time, space and process logic are consistent checking;According to the check result, construction process traceability diagram is constructed, the traceability path between process nodes is established, and image evidence chain is formed;Based on image evidence chain analysis construction process integrity and authenticity, calculate construction risk index and generate early warning information;Image evidence chain is summarized and calculated and trusted depositary processing, generate construction traceability record, and output traceability verification result, enhance the authenticity, integrity and traceability of construction process data.

Description

Technical Field

[0001] This invention relates to the field of engineering management technology, specifically to an automatic acquisition and traceability management method and system for hidden engineering image data. Background Technology

[0002] Concealed works are an important part of building construction, including steel reinforcement binding, waterproofing layer construction, and pipeline pre-embedding. After construction is completed, they are usually covered or sealed, and their quality is difficult to confirm through visual inspection of the finished product. Therefore, the video data of the construction stage becomes an important basis for acceptance, quality traceability and responsibility determination. Due to the complex on-site environment and close connection between processes, it is easy to miss or miss photos, or to be untimely in processing. The recorded images may deviate from the actual construction, making it difficult to fully reflect the construction process. Although the project management platform can store images, they are mostly simple archives and lack automatic association between images and construction units, parts and processes. It cannot form a continuous record covering the entire process. When problems occur, data needs to be compared manually, which is inefficient and makes it difficult to accurately locate responsibility. The lack of a mechanism for verifying the integrity of images and the sequence of construction based on the process flow makes it impossible to automatically identify missing key nodes or execution anomalies. Supervision relies on manual review, which has shortcomings such as high risk of omission and difficulty in traceability. Therefore, how to build a reliable traceability mechanism for the entire process based on construction image data to realize the automatic verification and traceability of the authenticity and integrity of the construction process is a technical problem that needs to be solved by those skilled in the art. Summary of the Invention

[0003] The purpose of this invention is to provide an automatic acquisition and traceability management method and system for concealed engineering image data, so as to solve the problems raised in the prior art.

[0004] To address the aforementioned technical problems, this invention provides the following technical solution: an automatic acquisition and traceability management method for concealed engineering image data, the method comprising: Step S100: Obtain hidden engineering image data, and construct corresponding full-process management data based on the image data to generate operation logs; Step S200: Acquire the image data and corresponding full-process management data, extract engineering element features, establish the association structure between engineering entities, construction procedures and image data, and generate engineering entity image nodes; Step S300: Based on the engineering entity image nodes, perform consistency verification on the time information, spatial location information and construction procedure logic of the image data, and generate the corresponding spatiotemporal consistency verification result. Step S400: Construct a construction process traceability diagram based on the spatiotemporal consistency verification results, establish traceability association paths between construction process nodes, and generate corresponding image evidence chains; Step S500: Analyze and evaluate the integrity and authenticity of the construction process based on the image evidence chain, calculate construction risk indicators, and generate early warning information based on the construction risk indicators; Step S600: Perform digest calculation and credible evidence storage processing on the image evidence chain to generate construction traceability records, and verify and output the construction process traceability results based on the construction traceability records.

[0005] Furthermore, step S100 includes: The engineering structure system is constructed according to the project, section, unit project, sub-project, item project, chainage and location, and a unique identifier is configured for each engineering location. The system receives image data uploaded by mobile terminals, including photos and videos collected after the completion of the construction of the engineering location. The image data is bound to the unique identifier of the corresponding engineering location, and the collection time information, location information, equipment information and personnel information corresponding to the image data are obtained. Based on the unique identifier and the acquired information, an identifiable image is generated, and credible evidence information is generated for the identifiable image. The identifiable image and credible evidence information are named, stored and archived according to preset rules, and their association with the corresponding engineering business records is established. Based on the aforementioned relationship, respond to query requests, retrieve corresponding image data according to at least one of the following query conditions: project location, time range, construction procedure, and photographer, and generate an image ledger. User role-based access control is implemented for the acquisition, storage, query, and retrieval of the image data, and corresponding operation logs are recorded. By constructing an engineering structure system, the problem of unclear correspondence between image data and actual construction objects is solved. By automatically binding image data collected by mobile terminals with unique identifiers of engineering parts to form image data elements, the authenticity and completeness of image data can be effectively improved, avoiding the problems existing in traditional manual recording methods, and providing a reliable data foundation for subsequent quality traceability. By generating tagged images and constructing credible evidence information, a continuous data chain can be formed throughout the entire construction process, realizing standardized management and traceable evidence of image data, significantly improving the efficiency and accuracy of problem tracing. By responding to query requests based on the aforementioned relationship and generating image ledgers, construction image data is transformed from passive archiving into an organized, searchable, and analyzable structured data resource, significantly improving the informatization level and utilization efficiency of engineering management.

[0006] Furthermore, step S200 includes: Acquire labeled image data, extract engineering element features from the labeled image data, the engineering element features include object name, process type, status information and acceptance information, integrate the extracted engineering element features with the corresponding acquisition time information and positioning information, and determine the corresponding target engineering entity part in the engineering structure system based on the positioning information; Obtain the unique identifier of the target engineering entity part, associate the engineering element features, acquisition time information and unique identifier, and generate the corresponding engineering entity image node; The engineering entity image nodes belonging to the same target engineering entity are sorted according to the acquisition time sequence, and the temporal association relationship between the nodes is established. The engineering entity image nodes are associated with the corresponding engineering parts in the engineering structure system, forming an association structure between engineering entities, construction procedures and construction image data. According to the association structure, a corresponding procedure image ledger is established, and the association relationship between engineering entity image nodes and construction procedures is recorded. By generating corresponding engineering entity image nodes, precise mapping and automatic linking of construction image data with specific engineering entities are achieved, improving the accuracy of the correspondence between image data and engineering entities. By establishing temporal relationships between nodes, the implementation process and evolution trajectory of construction procedures can be accurately reflected, forming a continuous image recording chain and improving the reliability of construction process traceability. By forming an association structure, unified management of engineering objects, construction activities, and image evidence is achieved, enabling rapid positioning and retrieval according to the engineering structure, improving the standardization and refinement of engineering data management. By recording the association between engineering entity image nodes and construction procedures, image archives reflecting the execution of procedures can be generated, providing complete and accurate evidence for project acceptance, quality inspection, process supervision, and responsibility determination, reducing manual processing workload and improving the efficiency of engineering data management.

[0007] Furthermore, step S300 includes: Acquire engineering entity image nodes belonging to the same target engineering entity part, arrange them in order of acquisition time, obtain the acquisition time information of adjacent engineering entity image nodes, calculate the difference between the acquisition time of the next engineering entity image node and the acquisition time of the previous engineering entity image node, and obtain the process time interval. Based on the construction process type, query the corresponding standard process time rule, compare the process time interval with the corresponding minimum construction time requirement, and generate a time anomaly mark when the process time interval is less than the minimum construction time requirement. Obtain the positioning information corresponding to the image nodes of the engineering entity; determine the corresponding target engineering entity part in the engineering structure system based on the unique identifier associated with the image nodes of the engineering entity; obtain the design coordinate information and construction area coordinate information corresponding to the target engineering entity part; and extract the boundary control points of the construction area based on the design coordinate information and construction area coordinate information. The control points of the construction area boundary are sequentially connected according to the preset boundary connection rules to generate a closed construction area boundary, and the target construction area boundary data is constructed based on the closed construction area boundary. The positioning information is analyzed to obtain the image acquisition coordinate points, and the image acquisition coordinate points are mapped to a unified coordinate reference system corresponding to the boundary data of the target construction area, thereby establishing a spatial positional relationship model between the boundary data of the target construction area and the image acquisition coordinate points. Based on the spatial location relationship model, the regional attribution relationship of the image acquisition coordinate point relative to the boundary of the target construction area is calculated. When the regional attribution relationship indicates that the image acquisition coordinate point is located within the closed area enclosed by the boundary of the target construction area, the location verification is confirmed to be successful. When the regional attribution relationship indicates that the image acquisition coordinate point is located outside the closed area enclosed by the boundary of the target construction area, a location anomaly marker is generated. Obtain the construction procedure type and construction status information corresponding to the current engineering entity image node, and obtain the previous procedure corresponding to the current construction procedure in the preset standard procedure flow. Determine whether the engineering entity image node corresponding to the previous procedure exists and whether its construction status meets the preset completion conditions. When there is no corresponding previous procedure node or the construction status does not meet the preset completion conditions, generate a procedure abnormality mark. Based on the generated time anomaly markers, location anomaly markers, and process anomaly markers, a spatiotemporal consistency verification result is formed for the corresponding engineering entity image nodes; By mapping the coordinates of image acquisition points to a unified coordinate reference system and performing regional attribution analysis based on the boundaries of closed construction areas, the system automatically determines the spatial legality of construction images, reducing manual review costs and improving the efficiency of on-site construction supervision. Automatic verification is achieved by judging the existence of preceding process nodes and whether the construction status meets preset completion conditions. When there are situations such as process reversal, missing or incomplete key preceding processes before proceeding to subsequent processes, the system can automatically generate process anomaly markers, thereby ensuring that the construction process complies with established construction specifications and process requirements, and improving the standardization and quality control level of construction management.

[0008] Furthermore, step S400 includes: Acquire multiple engineering entity image nodes that have passed the spatiotemporal consistency verification, and obtain the unique identifier, construction process type, acquisition time information and associated structural information corresponding to each engineering entity image node; Based on the construction process type corresponding to the engineering entity image node, the sequential process relationship is matched from the preset process dependency relationship library. When the construction process types corresponding to two engineering entity image nodes satisfy the sequential dependency relationship, a directed process association edge is established between the corresponding engineering entity image nodes. For multiple engineering entity image nodes belonging to the same target engineering entity part, they are initially sorted according to the acquisition time information to generate an initial construction process node sequence. Based on the directed process association edges between the engineering entity image nodes, the initial construction process node sequence is sorted by topological constraints so that the preceding engineering entity image node with the directed process association edge connection relationship is placed before the subsequent engineering entity image node, thus generating a construction process node sequence. According to the engineering structure system, the construction process node sequence corresponding to each target engineering entity is aggregated level by level to form construction process association data covering the project level, section level, unit project level and engineering part level; Each construction process node in the construction process node sequence is used as a node in the construction process traceability diagram. The construction process traceability diagram is constructed by combining directed process association edges. Based on the construction process traceability diagram, the traceability association path from the preceding construction process node to the subsequent construction process node is determined. The image data corresponding to the traceability association path is associated and organized to generate an image evidence chain of the entire construction process of the hidden works. When responding to a traceability request, based on the unique identifier corresponding to the target engineering entity, image data of the corresponding construction process node is extracted along the traceability path, and the corresponding construction process traceability result is output. By forming a chain of video evidence covering the entire construction process of concealed works, the continuous preservation and chain-like association of key evidence in the construction process are achieved. Compared with the traditional decentralized video archive management method, this invention can completely preserve video records of the entire process of concealed works from construction preparation, implementation of procedures to acceptance completion, thereby improving the integrity and credibility of construction process evidence.

[0009] Furthermore, step S500 includes: Obtain a list of standard procedures corresponding to the target engineering entity, the list of standard procedures including all standard procedures required to complete the construction of the engineering entity; Obtain the image evidence chain of the corresponding engineering entity, extract the process node set in the image evidence chain, and match the process node set with the standard process list item by item. Determine the standard process that does not match the corresponding process node in the standard process list as the missing process, and record the process position of the missing process in the standard process list. Obtain the preceding and subsequent processes corresponding to the missing process, and determine whether the process node corresponding to the preceding process and the process node corresponding to the subsequent process exist simultaneously in the image evidence chain. When the process node corresponding to the preceding process and the process node corresponding to the subsequent process exist simultaneously in the image evidence chain, the process segment between the preceding process and the subsequent process that contains the missing process is determined as the broken chain interval. Obtain the position of the missing process in the standard process list and the break interval, collect the planned execution number and actual completion number of the missing process in historical engineering data, calculate the missing process rate, and use the missing process rate as a process type risk indicator for the missing process; The degree of impact of the chain break interval is determined by the proportion of the number of missing processes in the chain break interval to the total number of processes in the chain break interval, and the degree of impact of the chain break interval is used as a chain break risk indicator. The process type risk index and the chain break risk index are normalized and calculated separately. The normalized process type risk index and the chain break risk index are then weighted and summed according to preset weights to calculate the integrity risk index of the missing process. When there are multiple missing processes, the integrity risk index of each missing process is weighted and summed according to preset process position weights to calculate the integrity risk index of the target project entity. Based on the spatiotemporal consistency verification results corresponding to each process node, the number of time anomalies, the number of location anomalies, and the number of process anomalies in the image evidence chain are counted. The number of time anomalies, the number of location anomalies, and the number of process anomalies are normalized and calculated respectively. The normalized number of time anomalies, the number of location anomalies, and the number of process anomalies are then weighted and summed according to preset weights to calculate the authenticity risk index of the target engineering entity. The integrity risk index and authenticity risk index of the target project entity are weighted according to the preset evaluation weight to obtain the construction risk index of the target project entity. When the construction risk index is higher than the risk index threshold or the integrity risk index of the missing process is higher than the integrity threshold, an early warning information is generated. The risk index threshold is obtained by acquiring a sample set of construction risk indicators from historical engineering data, calculating the mean and standard deviation of the sample set, multiplying the standard deviation by a preset threshold adjustment coefficient to obtain an adjustment value, and adding the adjustment value to the mean to obtain the risk index threshold; the integrity threshold is obtained by acquiring a sample set of integrity risk indicators from historical engineering data, calculating the mean and standard deviation of the sample set, multiplying the standard deviation by a preset integrity threshold adjustment coefficient to obtain an adjustment value, and adding the adjustment value to the mean to obtain the integrity threshold. By using process type risk indicators and chain break risk indicators, the risk of construction process can be quantitatively assessed. Through normalization and weighted aggregation, integrity risk indicators of the target project entity can be generated, providing data support and decision-making basis for project managers. By generating authenticity risk indicators, the credibility of construction process data can be comprehensively assessed, solving the problem that traditional construction records and video data are difficult to verify, and ensuring the reliability of construction risk assessment results.

[0010] Furthermore, step S600 includes: Obtain the image evidence chain corresponding to the target engineering entity, and extract the image nodes of each engineering entity, node associations, spatiotemporal consistency verification results, and construction credibility evaluation results from the image evidence chain. According to the tracing and association path order in the image evidence chain, the node identifier, image file summary value, acquisition time information and spatiotemporal consistency verification result corresponding to each engineering entity image node are combined according to the preset coding rules to form the node data of the corresponding engineering entity image node. Hash operations are performed on the data of each node to generate node summary values ​​for the corresponding engineering entity image nodes. The first node summary value is used as the initial chain summary value. Following the order of the traceability path, the previous chain summary value is concatenated with the current node summary value and then hashed to generate the current chain summary value. The current chain summary value is used as the previous chain summary value for the next node for iterative calculation until the cascading calculation of all node summary values ​​is completed to obtain the evidence chain summary value of the corresponding image evidence chain. The evidence chain summary value is sent to the traceability management platform, which obtains the corresponding trusted timestamp certificate based on the evidence chain summary value. Obtain the information of the responsible party corresponding to the image evidence chain, and associate and encapsulate the image evidence chain, evidence chain summary value, credible timestamp certificate, responsible party information and construction credibility evaluation results to generate construction traceability records; When responding to a traceability verification request, the image evidence chain in the construction traceability record is read and the evidence chain digest value is recalculated. The recalculated evidence chain digest value is compared with the evidence chain digest value in the construction traceability record. If the comparison is consistent, the corresponding trusted timestamp certificate is read, and the digital signature in the trusted timestamp certificate is verified using the verification public key of the trusted timestamp service agency. If the verification is successful, the evidence chain digest value recorded in the trusted timestamp certificate is extracted, and it is verified whether the evidence chain digest value is consistent with the recalculated evidence chain digest value. When the evidence chain digest values ​​match and the trusted timestamp certificate is verified, it is determined that the construction traceability record has not been tampered with, and a corresponding traceability trusted prompt message is generated. When the evidence chain digest values ​​do not match or the trusted timestamp certificate verification fails, a traceability abnormal prompt message is generated. When the evidence chain digest values ​​match and the trusted timestamp certificate is verified, it is determined that the construction traceability record has not been tampered with, and a corresponding traceability trusted prompt message is generated. When the evidence chain digest values ​​do not match or the trusted timestamp certificate verification fails, a traceability abnormal prompt message is generated. The trusted timestamp mechanism can prove that construction evidence existed at a specific time and has not been modified, effectively solving the problem of difficulty in proving the formation time of construction data and providing reliable time basis for project quality acceptance and other situations. When responding to traceability verification requests, it can quickly determine whether there is any tampering in construction traceability records, realize automatic identification and early warning of abnormal data, and improve the efficiency and accuracy of construction data review.

[0011] To better implement the above methods, an automatic acquisition and traceability management system for concealed engineering image data is also proposed. The system includes an operation log module, an engineering entity image node module, a spatiotemporal consistency verification module, an image evidence chain module, a construction risk indicator module, and a construction traceability module. Operation log module: acquires hidden engineering image data, constructs corresponding full-process management data based on the image data, and generates operation logs; Engineering entity image node module: acquires the image data and corresponding full-process management data, extracts engineering element features, establishes the association structure between engineering entities, construction procedures and image data, and generates engineering entity image nodes; Spatiotemporal consistency verification module: Based on the project entity image nodes, it performs consistency verification on the time information, spatial location information and construction procedure logic of the image data, and generates the corresponding spatiotemporal consistency verification results; Image Evidence Chain Module: Constructs a construction process traceability diagram based on the spatiotemporal consistency verification results, establishes traceability association paths between construction process nodes, and generates corresponding image evidence chains; Construction risk indicator module: Based on the image evidence chain, analyze and evaluate the integrity and authenticity of the construction process, calculate construction risk indicators, and generate early warning information based on the construction risk indicators; Construction traceability module: performs summary calculation and reliable evidence storage processing on the image evidence chain, generates construction traceability records, and verifies and outputs the construction process traceability results based on the construction traceability records.

[0012] Furthermore, the engineering entity image node module includes target engineering entity part units and engineering entity image generation node units: Target engineering entity unit: Acquire labeled image data, extract engineering element features from the labeled image data, the engineering element features include object name, process type, status information and acceptance information, integrate the extracted engineering element features with the corresponding acquisition time information and positioning information, and determine the corresponding target engineering entity unit in the engineering structure system based on the positioning information; The engineering entity image node generation unit obtains the unique identifier of the target engineering entity part, associates the engineering element features, acquisition time information and unique identifier to generate the corresponding engineering entity image node, sorts the engineering entity image nodes belonging to the same target engineering entity part according to the acquisition time order, establishes the temporal association relationship between the nodes, associates the engineering entity image node with the corresponding engineering part in the engineering structure system, forms the association structure between engineering entity, construction process and construction image data, establishes the corresponding process image ledger according to the association structure, and records the association relationship between engineering entity image nodes and construction process.

[0013] Furthermore, the image evidence chain module includes a directed process association edge unit and an image evidence chain generation unit: Directed process association edge unit: Obtain multiple engineering entity image nodes that have passed the spatiotemporal consistency verification, and obtain the unique identifier, construction process type, acquisition time information and association structure information corresponding to each engineering entity image node. Based on the construction process type corresponding to the engineering entity image node, match the preceding and following process relationships from the preset process dependency relationship library. When the construction process types corresponding to two engineering entity image nodes satisfy the preceding and following process dependency relationship, establish a directed process association edge between the corresponding engineering entity image nodes. The image evidence chain generation unit: For multiple engineering entity image nodes belonging to the same target engineering entity, they are initially sorted according to the acquisition time information to generate an initial construction process node sequence. Based on the directed process association edges between the engineering entity image nodes, the initial construction process node sequence is sorted by topological constraints, so that the preceding engineering entity image nodes with directed process association edge connections are placed before the following engineering entity image nodes, generating a construction process node sequence. The construction process node sequences corresponding to each target engineering entity are aggregated level by level according to the engineering structure system to form construction process association data covering the project level, section level, unit project level, and engineering part level. Each construction process node in the construction process node sequence is used as a node in the construction process traceability diagram, and the construction process traceability diagram is constructed in combination with the directed process association edges. Based on the construction process traceability diagram, the traceability association path from the preceding construction process node to the subsequent construction process node is determined, and the image data corresponding to the traceability association path is associated and organized to generate an image evidence chain for the entire construction process of the hidden works.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: by establishing an engineering structure system and a unique identification system, the standardized collection, unified management and engineering entity association of hidden engineering image data are realized, so that the image data can accurately correspond to specific engineering parts and construction stages, improve data management efficiency, organizational capacity and traceability, comprehensively utilize the collection time, positioning information and construction procedure logic relationship to perform spatiotemporal consistency verification of image data, automatically identify and mark reshoots, wrong shots, off-site shooting and process abnormalities, etc., and improve the authenticity and credibility of construction image data; By constructing a construction process traceability map and a continuous image evidence chain, the entire process of linking the project entity with the construction process can be traced, which facilitates quality inspection, responsibility determination, and subsequent maintenance. By analyzing indicators such as integrity risk and authenticity risk, missing construction data and abnormal situations can be identified, and early warning information can be automatically generated to improve the ability to supervise project quality and prevent risks. Combined with hash digest and trusted timestamp technology, evidence chain storage and anti-tampering verification can be achieved to ensure the integrity, authenticity, and judicial credibility of construction traceability data. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the structure of an automatic acquisition and traceability management system for concealed engineering image data according to the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Please see Figure 1 This invention provides a technical solution: an automatic acquisition and traceability management method for concealed engineering image data, the method comprising: Step S100: Obtain hidden engineering image data, and construct corresponding full-process management data based on the image data to generate operation logs; Step S100 includes: The engineering structure system is constructed according to the project, section, unit project, sub-project, item project, chainage and location, and a unique identifier is configured for each engineering location. The system receives image data uploaded by mobile terminals, including photos and videos collected after the completion of the construction of the engineering location. The image data is bound to the unique identifier of the corresponding engineering location, and the collection time information, location information, equipment information and personnel information corresponding to the image data are obtained. Based on the unique identifier and the acquired information, an identifiable image is generated, and credible evidence information is generated for the identifiable image. The identifiable image and credible evidence information are named, stored and archived according to preset rules, and their association with the corresponding engineering business records is established. Based on the aforementioned relationship, respond to query requests, retrieve corresponding image data according to at least one of the following query conditions: project location, time range, construction procedure, and photographer, and generate an image ledger. User role-based access control is implemented for the acquisition, storage, query, and retrieval of the image data, and corresponding operation logs are recorded. For example, in a new highway construction project, the roadbed and bridge / culvert works from K12+000 to K18+500 are taken as the implementation object. The engineering structure system is constructed according to the hierarchical structure of project—section—unit project—sub-project—item project—chainage—location. The project name is XX Expressway Project, the section is the third contract section, the unit project is the roadbed works, the sub-project is the drainage works, the item project is the culvert foundation construction, the construction chainage is K15+320, and the specific location is the foundation slab of box culvert No. 1. The system automatically generates a unique identifier SG3-LJ-PS-HD-K15+320-JCDB-0001 for this part of the project and writes the unique identifier into the corresponding database.

[0018] Step S200: Acquire the image data and corresponding full-process management data, extract engineering element features, establish the association structure between engineering entities, construction procedures and image data, and generate engineering entity image nodes; Step S200 includes: Acquire labeled image data, extract engineering element features from the labeled image data, the engineering element features include object name, process type, status information and acceptance information, integrate the extracted engineering element features with the corresponding acquisition time information and positioning information, and determine the corresponding target engineering entity part in the engineering structure system based on the positioning information; Obtain the unique identifier of the target engineering entity part, associate the engineering element features, acquisition time information and unique identifier, and generate the corresponding engineering entity image node; The engineering entity image nodes belonging to the same target engineering entity are sorted according to the acquisition time sequence, and the temporal association relationship between the nodes is established. The engineering entity image nodes are associated with the corresponding engineering parts in the engineering structure system, forming an association structure between engineering entities, construction procedures and construction image data. According to the association structure, a corresponding procedure image ledger is established, and the association relationship between engineering entity image nodes and construction procedures is recorded. For example, the system extracts engineering feature characteristics from the images. The object name is identified as the reinforcement of the foundation slab of the No. 1 box culvert. The process type is identified as the reinforcement binding. The status information is identified as reinforcement binding completed, protective layer pad block installation completed, and no concrete poured. The acceptance information is identified as the status before the concealed acceptance. The system retrieves the corresponding collection time 2026-03-18 14:26:35, location information 112.568921° East longitude and 28.214587° North latitude from the full-process management data. The object name (No. 1 box culvert foundation slab reinforcement), process type (foundation reinforcement binding), status information (binding completed), acquisition time (2026-03-18 14:26:35), and unique identifier (SG3-LJ-PS-HD-K15+320-JCDB-0001) are associated to generate the corresponding engineering entity image node NODE-20260318-0001. The node record includes the node number NODE-20260318-0001, engineering entity number SG3-LJ-PS-HD-K15+320-JCDB-0001, process type (foundation reinforcement binding), acquisition time (2026-03-18 14:26:35), and number of images (8). Construction workers continued to collect images of the same engineering entities. For example, after the supervisor's acceptance was completed at 09:12:18 on March 19, 2026, the system collected acceptance images, extracted the object name as "No. 1 Box Culvert Foundation Slab Reinforcement", the process type as "Reinforcement Acceptance", and the status information as "Acceptance Qualified", generating the engineering entity image node NODE-20260319-0005; after the foundation concrete pouring was completed at 16:35:42 on March 20, 2026, the system collected construction images, and extracted the object... Name: No. 1 Box Culvert Foundation Slab; Process Type: Foundation Concrete Pouring; Status Information: Pouring Completed; Generated Engineering Entity Image Node: NODE-20260320-0012; Sequence Association Results: Foundation Reinforcement Binding NODE-20260318-0001 → Reinforcement Acceptance NODE-20260319-0005 → Foundation Concrete Pouring NODE-20260320-0012 → Concrete Curing NODE-20260322-0008.

[0019] Step S300: Based on the engineering entity image nodes, perform consistency verification on the time information, spatial location information and construction procedure logic of the image data, and generate the corresponding spatiotemporal consistency verification result. Step S300 includes: Acquire engineering entity image nodes belonging to the same target engineering entity part, arrange them in order of acquisition time, obtain the acquisition time information of adjacent engineering entity image nodes, calculate the difference between the acquisition time of the next engineering entity image node and the acquisition time of the previous engineering entity image node, and obtain the process time interval. Based on the construction process type, query the corresponding standard process time rule, compare the process time interval with the corresponding minimum construction time requirement, and generate a time anomaly mark when the process time interval is less than the minimum construction time requirement. Obtain the positioning information corresponding to the image nodes of the engineering entity; determine the corresponding target engineering entity part in the engineering structure system based on the unique identifier associated with the image nodes of the engineering entity; obtain the design coordinate information and construction area coordinate information corresponding to the target engineering entity part; and extract the boundary control points of the construction area based on the design coordinate information and construction area coordinate information. The control points of the construction area boundary are sequentially connected according to the preset boundary connection rules to generate a closed construction area boundary, and the target construction area boundary data is constructed based on the closed construction area boundary. The positioning information is analyzed to obtain the image acquisition coordinate points, and the image acquisition coordinate points are mapped to a unified coordinate reference system corresponding to the boundary data of the target construction area, thereby establishing a spatial positional relationship model between the boundary data of the target construction area and the image acquisition coordinate points. Based on the spatial location relationship model, the regional attribution relationship of the image acquisition coordinate point relative to the boundary of the target construction area is calculated. When the regional attribution relationship indicates that the image acquisition coordinate point is located within the closed area enclosed by the boundary of the target construction area, the location verification is confirmed to be successful. When the regional attribution relationship indicates that the image acquisition coordinate point is located outside the closed area enclosed by the boundary of the target construction area, a location anomaly marker is generated. Obtain the construction procedure type and construction status information corresponding to the current engineering entity image node, and obtain the previous procedure corresponding to the current construction procedure in the preset standard procedure flow. Determine whether the engineering entity image node corresponding to the previous procedure exists and whether its construction status meets the preset completion conditions. When there is no corresponding previous procedure node or the construction status does not meet the preset completion conditions, generate a procedure abnormality mark. Based on the generated time anomaly markers, location anomaly markers, and process anomaly markers, a spatiotemporal consistency verification result is formed for the corresponding engineering entity image nodes; For example, NODE-20260318-0001 was collected at 14:26:35 on March 18, 2026; The data collection time for NODE-20260319-0005 was 09:12:18 on March 19, 2026. The data collection time for NODE-20260320-0012 was 16:35:42 on March 20, 2026. The data collection time for NODE-20260322-0008 was 08:25:10 on 2026-03-22. The time interval between NODE-20260319-0005 and NODE-20260318-0001 is 18 hours, 45 minutes, and 43 seconds; the time interval between NODE-20260320-0012 and NODE-20260319-0005 is 31 hours, 23 minutes, and 24 seconds; the time interval between NODE-20260322-0008 and NODE-20260320-0012 is 39 hours, 49 minutes, and 28 seconds. The minimum time requirement from the binding of foundation steel bars to the acceptance of steel bars is 4 hours; the minimum time requirement from the acceptance of steel bars to the pouring of foundation concrete is 8 hours; and the minimum time requirement from the pouring of foundation concrete to the inspection of concrete curing is 24 hours. The system compares the calculated time interval between procedures with the corresponding minimum construction time requirements. If all the above nodes meet the time requirements, no time anomaly mark is generated, and the time verification result is passed. The system locates the physical component of the third contract section—roadbed engineering—drainage engineering—culvert foundation construction—K15+320—No. 1 box culvert foundation slab project in the engineering structure system based on the unique identifier SG3-LJ-PS-HD-K15+320-JCDB-0001. It then retrieves the corresponding construction area boundary data from the design database. The design boundary control points of the construction area are P1 (112.568800°, 28.214500°), P2 (112.569050°, 28.214500°), P3 (112.569050°, 28.214700°), and P4 (112.568800°, 28.214700°). The system connects P1, P2, P3, and P4 in a clockwise direction and closes the boundary to form the target construction area boundary. The coordinates of NODE-20260318-0001 are (112.568921°, 28.214587°); the coordinates of NODE-20260319-0005 are (112.568935°, 28.214602°); the coordinates of NODE-20260320-0012 are (112.568947°, 28.214615°); and the coordinates of NODE-20260322-0008 are (112.568918°, 28.214594°). All four image acquisition coordinate points are located within the closed area enclosed by the construction area boundary. Therefore, the position verification passed and no position anomaly markers were generated. The next step after the basic reinforcement binding is reinforcement acceptance, the next step after reinforcement acceptance is foundation concrete pouring, and the next step after foundation concrete pouring is concrete curing. The existence and completion status of the corresponding previous steps at each node are checked in turn. For node NODE-20260319-0005, its corresponding process type is steel bar acceptance. The system determines that its preceding process is basic steel bar binding and finds that the corresponding node NODE-20260318-0001 exists and its status information is steel bar binding completed, which meets the preset completion conditions. Therefore, the process logic verification passes. For project entity number SG3-LJ-PS-HD-K15+320-JCDB-0001, the verification result is recorded as follows: Project entity name: 1# box culvert foundation slab; Number of verification nodes: 4; Number of time anomalies: 0; Number of location anomalies: 0; Number of process anomalies: 0; Overall verification conclusion: Pass; Verification time: 2026-03-22 08:30:16; Verification number: JCJG-20260322-000138.

[0020] Step S400: Construct a construction process traceability diagram based on the spatiotemporal consistency verification results, establish traceability association paths between construction process nodes, and generate corresponding image evidence chains; Step S400 includes: Acquire multiple engineering entity image nodes that have passed the spatiotemporal consistency verification, and obtain the unique identifier, construction process type, acquisition time information and associated structural information corresponding to each engineering entity image node; Based on the construction process type corresponding to the engineering entity image node, the sequential process relationship is matched from the preset process dependency relationship library. When the construction process types corresponding to two engineering entity image nodes satisfy the sequential dependency relationship, a directed process association edge is established between the corresponding engineering entity image nodes. For multiple engineering entity image nodes belonging to the same target engineering entity part, they are initially sorted according to the acquisition time information to generate an initial construction process node sequence. Based on the directed process association edges between the engineering entity image nodes, the initial construction process node sequence is sorted by topological constraints so that the preceding engineering entity image node with the directed process association edge connection relationship is placed before the subsequent engineering entity image node, thus generating a construction process node sequence. According to the engineering structure system, the construction process node sequence corresponding to each target engineering entity is aggregated level by level to form construction process association data covering the project level, section level, unit project level and engineering part level; Each construction process node in the construction process node sequence is used as a node in the construction process traceability diagram. The construction process traceability diagram is constructed by combining directed process association edges. Based on the construction process traceability diagram, the traceability association path from the preceding construction process node to the subsequent construction process node is determined. The image data corresponding to the traceability association path is associated and organized to generate an image evidence chain of the entire construction process of the hidden works. When responding to a traceability request, image data of the corresponding construction process node is extracted along the traceability path based on the unique identifier corresponding to the target engineering entity, and the corresponding construction process traceability result is output.

[0021] Step S500: Analyze and evaluate the integrity and authenticity of the construction process based on the image evidence chain, calculate construction risk indicators, and generate early warning information based on the construction risk indicators; Step S500 includes: Obtain a list of standard procedures corresponding to the target engineering entity, the list of standard procedures including all standard procedures required to complete the construction of the engineering entity; Obtain the image evidence chain of the corresponding engineering entity, extract the process node set in the image evidence chain, and match the process node set with the standard process list item by item. Determine the standard process that does not match the corresponding process node in the standard process list as the missing process, and record the process position of the missing process in the standard process list. Obtain the preceding and subsequent processes corresponding to the missing process, and determine whether the process node corresponding to the preceding process and the process node corresponding to the subsequent process exist simultaneously in the image evidence chain. When the process node corresponding to the preceding process and the process node corresponding to the subsequent process exist simultaneously in the image evidence chain, the process segment between the preceding process and the subsequent process that contains the missing process is determined as the broken chain interval. Obtain the position of the missing process in the standard process list and the break interval, collect the planned execution number and actual completion number of the missing process in historical engineering data, calculate the missing process rate, and use the missing process rate as a process type risk indicator for the missing process; The degree of impact of the chain break interval is determined by the proportion of the number of missing processes in the chain break interval to the total number of processes in the chain break interval, and the degree of impact of the chain break interval is used as a chain break risk indicator. The process type risk index and the chain break risk index are normalized and calculated separately. The normalized process type risk index and the chain break risk index are then weighted and summed according to preset weights to calculate the integrity risk index of the missing process. When there are multiple missing processes, the integrity risk index of each missing process is weighted and summed according to preset process position weights to calculate the integrity risk index of the target project entity. Based on the spatiotemporal consistency verification results corresponding to each process node, the number of time anomalies, the number of location anomalies, and the number of process anomalies in the image evidence chain are counted. The number of time anomalies, the number of location anomalies, and the number of process anomalies are normalized and calculated respectively. The normalized number of time anomalies, the number of location anomalies, and the number of process anomalies are then weighted and summed according to preset weights to calculate the authenticity risk index of the target engineering entity. The integrity risk index and authenticity risk index of the target project entity are weighted according to the preset evaluation weight to obtain the construction risk index of the target project entity. When the construction risk index is higher than the risk index threshold or the integrity risk index of the missing process is higher than the integrity threshold, an early warning information is generated. The risk index threshold is obtained by acquiring a sample set of construction risk indicators from historical engineering data, calculating the mean and standard deviation of the sample set, multiplying the standard deviation by a preset threshold adjustment coefficient to obtain an adjustment value, and adding the adjustment value to the mean to obtain the risk index threshold; the integrity threshold is obtained by acquiring a sample set of integrity risk indicators from historical engineering data, calculating the mean and standard deviation of the sample set, multiplying the standard deviation by a preset integrity threshold adjustment coefficient to obtain an adjustment value, and adding the adjustment value to the mean to obtain the integrity threshold. For example, for the foundation slab of the No. 1 box culvert corresponding to the project entity number SG3-LJ-PS-HD-K15+320-JCDB-0001, the standard procedure list includes 9 standard procedures: foundation surveying and setting out, foundation pit excavation, foundation acceptance, foundation reinforcement binding, reinforcement acceptance, foundation formwork installation, foundation concrete pouring, concrete curing, and concealed works acceptance. The identified process nodes include seven items: foundation surveying and setting out, foundation pit excavation, foundation reinforcement binding, reinforcement acceptance, foundation concrete pouring, concrete curing, and concealed works acceptance. It was found that the foundation acceptance and foundation formwork installation in the standard process could not be matched with the corresponding process nodes in the image evidence chain. Therefore, the foundation acceptance and foundation formwork installation were determined to be missing processes, and their process positions in the standard process list were recorded. The foundation acceptance was located in the 3rd standard process, and the foundation formwork installation was located in the 6th standard process. For the missing process of foundation acceptance, the preceding process of foundation pit excavation and the subsequent process of foundation steel reinforcement binding were obtained, and the corresponding process nodes were found to exist in the image evidence chain. Therefore, foundation pit excavation → foundation acceptance → foundation steel reinforcement binding was identified as the broken chain interval. The planned number of times for the base acceptance process was 1200, and the actual number of valid image records formed was 1116. The calculated missing rate for this process was (1200-1116)÷1200=0.07, and the risk index for the process type was 0.07. The basic template installation process was planned to be executed 1200 times, and the actual number of valid image records formed was 1020 times. The calculated missing rate was (1200-1020)÷1200=0.15, and the process type risk index was 0.15. For the missing process of foundation acceptance, the broken chain interval is excavation of foundation pit → foundation acceptance → foundation reinforcement binding. This broken chain interval contains a total of 3 processes, of which 1 process is missing. The impact of the broken chain interval is 1÷3=0.33, and the corresponding broken chain risk index is 0.33. The process type risk index and the chain break risk index were normalized and weighted according to preset weights. The process type risk index had a weight of 0.6 and the chain break risk index had a weight of 0.4. Since the process type risk index directly reflects the frequency of missing corresponding standard processes in historical projects, it can reflect the stability and reliability of the effective image records formed by the process in actual construction. The chain break risk index mainly reflects the degree of damage to the continuity of the process section where the missing process is located, and reflects the local impact range of the integrity of the image evidence chain structure. Therefore, the process type risk index was given a higher weight and the chain break risk index was given a relatively lower weight to highlight the dominant role of the historical missing patterns of the process itself on the integrity risk. The integrity risk index for the missing process base acceptance is 0.07×0.6+0.33×0.4=0.174; the integrity risk index for the missing process base formwork installation is 0.15×0.6+0.33×0.4=0.222. Since foundation acceptance is a critical early-stage process, its process position weight is set to 0.55; foundation formwork installation is a critical intermediate-stage process, and its process position weight is set to 0.45. Critical processes in the early stages of construction usually have fundamental and prerequisite characteristics; although intermediate or subsequent processes also affect construction quality, their impact is usually limited to local construction stages, and their propagation impact on the overall construction chain is relatively weak. Therefore, missing processes on the early critical path are given higher process position weights, while mid-to-late-stage processes are given relatively lower process position weights; the integrity risk index of the target project entity is calculated as 0.174×0.55+0.222×0.45=0.1956; The spatiotemporal consistency verification results of each process node in the image evidence chain of the physical part of the project are statistically analyzed. According to the verification results of step S300, the number of time anomalies is 0, the number of location anomalies is 0, and the number of process anomalies is 0, resulting in an authenticity risk index of 0. A comprehensive evaluation was conducted using a weighting of 0.6 for the integrity risk index and 0.4 for the authenticity risk index. The integrity risk index is mainly used to evaluate whether there are missing procedures, broken segments, or omissions of key procedures in the construction image evidence chain, which has a fundamental impact on construction quality supervision. The authenticity risk index focuses on reflecting the authenticity and credibility of the image data. The lack of a construction evidence chain usually directly leads to the inability to trace the construction process, and its risk impact is higher than that of authenticity deviations such as local time anomalies or location anomalies. Therefore, the integrity risk index is given a higher evaluation weight, while the authenticity risk index is given a relatively lower evaluation weight. The construction risk index of the target project entity is calculated as 0.196 × 0.6 + 0 × 0.4 = 0.1176. Assuming the construction risk warning threshold is 0.30 and the integrity risk warning threshold is 0.20, since the construction risk index of 0.118 is lower than the construction risk warning threshold of 0.30, but the integrity risk index of the missing process of foundation formwork installation of 0.222 is higher than the integrity risk warning threshold of 0.20, the system generates a warning message.

[0022] Step S600: Perform digest calculation and trusted evidence storage processing on the image evidence chain to generate construction traceability records, and verify and output the construction process traceability results based on the construction traceability records; Step S600 includes: Obtain the image evidence chain corresponding to the target engineering entity, and extract the image nodes of each engineering entity, node associations, spatiotemporal consistency verification results, and construction credibility evaluation results from the image evidence chain. According to the tracing and association path order in the image evidence chain, the node identifier, image file summary value, acquisition time information and spatiotemporal consistency verification result corresponding to each engineering entity image node are combined according to the preset coding rules to form the node data of the corresponding engineering entity image node. Hash operations are performed on the data of each node to generate node summary values ​​for the corresponding engineering entity image nodes. The first node summary value is used as the initial chain summary value. Following the order of the traceability path, the previous chain summary value is concatenated with the current node summary value and then hashed to generate the current chain summary value. The current chain summary value is used as the previous chain summary value for the next node for iterative calculation until the cascading calculation of all node summary values ​​is completed to obtain the evidence chain summary value of the corresponding image evidence chain. The evidence chain summary value is sent to the traceability management platform, which obtains the corresponding trusted timestamp certificate based on the evidence chain summary value. Obtain the information of the responsible party corresponding to the image evidence chain, and associate and encapsulate the image evidence chain, evidence chain summary value, credible timestamp certificate, responsible party information and construction credibility evaluation results to generate construction traceability records; When responding to a traceability verification request, the image evidence chain in the construction traceability record is read and the evidence chain digest value is recalculated. The recalculated evidence chain digest value is compared with the evidence chain digest value in the construction traceability record. If the comparison is consistent, the corresponding trusted timestamp certificate is read, and the digital signature in the trusted timestamp certificate is verified using the verification public key of the trusted timestamp service agency. If the verification is successful, the evidence chain digest value recorded in the trusted timestamp certificate is extracted, and it is verified whether the evidence chain digest value is consistent with the recalculated evidence chain digest value. When the evidence chain digest values ​​match and the trusted timestamp certificate is verified, it is determined that the construction traceability record has not been tampered with, and a corresponding traceability trusted prompt message is generated. When the evidence chain digest values ​​do not match or the trusted timestamp certificate verification fails, a traceability abnormal prompt message is generated. For example, for node NODE-20260318-0001, its corresponding image files include 6 photos and 2 video clips. The system first performs SHA-256 digest calculation on each of the 8 original image files to obtain a set of image file digests. After sorting and summarizing, the image file digest value corresponding to this node is generated as 8F3A7C12B85D9E44A5D7C8E16F5B3C9D2E7A6B1F5C8D9A7E4F2B6C1D9A8E5F31. The corresponding data collection time was 2026-03-18 14:26:35. The spatiotemporal consistency verification result was normal in time, location, and process. According to the preset format, the node data Data1 was generated as NODE-20260318-0001|8F3A7C12B85D9E44A5D7C8E16F5B3C9D2E7A6B1F5C8D9A7E4F2B6C1D9A8E5F31|2026-03-18 14:26:35|PASS; Data1 performs a SHA-256 hash operation, generating a node digest value of 4D9C73A81F6E22B4C9A57E18D231A5F8B60C9D2A7E81F3C45B6D8E12A4F93C71; Node NODE-20260319-0005 generates node data Data2 as NODE-20260319-0005|5A7E81C9F2B6D14A3E8C72B19D4F63E5A1C9B2D74F81E63A2D5C7B9E31F4A682|2026-03-19 09:12:18|PASS; Data2 performs a SHA-256 hash operation, generating a node digest value of 72E4D3B19F5C84A6E7D213C9A4B61F58E32A7D5C9F14B83E6D7A2C19E45F38B2; The digest value of the previous chain is then concatenated with the digest value of the current node to obtain 4D9C73A81F6E22B4C9A57E18D231A5F8B60C9D2A7E81F3C45B6D8E12A4F93C71||72E4D3B19F5C84A6E7D213C9A4B61F58E32A7D5C9F14B83E6D7A2C19E45F38B2; Perform SHA-256 operation on the spliced ​​result again to obtain a new chain digest value of 91C84F7D23A6E15B8D72F3C94E6A21D7C58F31A9E4B6D27C8F5A13E6D2B94C71; The evidence chain summary value of the image evidence chain obtained by iterative calculation is E8A73D5C2194F6B82A1D7E39C54F28B16A7D3C92E5F81B64A2C79D13E4F65B8A; At 08:31:20 on March 22, 2026, the above evidence chain digest value was sent to the traceability management platform. The evidence chain digest value and the standard time source time were digitally signed using the timestamp signature private key to generate a trusted timestamp certificate as TSA-20260322-000568. The trusted timestamp credential includes timestamp number TSA-20260322-000568, timestamp generation time 2026-03-22 08:31:22, evidence chain digest value E8A73D5C2194F6B82A1D7E39C54F28B16A7D3C92E5F81B64A2C79D13E4F65B8A, signature algorithm SHA256withRSA, and digital signature value SIG-9A83E71C5D24F6A8B13D7E92C54F18A7; The system associates and encapsulates the image evidence chain, evidence chain summary value, trusted timestamp certificate TSA-20260322-000568, responsible entity information, and construction credibility evaluation results to generate construction traceability record TRACE-20260322-000138. The construction unit initiated a traceability verification request. The system read all image evidence chain data from the construction traceability record TRACE-20260322-000138, and re-executed the node digest value calculation and cascade hash operation according to the original traceability association path. The recalculated evidence chain digest value is E8A73D5C2194F6B82A1D7E39C54F28B16A7D3C92E5F81B64A2C79D13E4F65B8A. The evidence chain digest value is completely consistent with the one stored in the construction traceability record, indicating that the content of the image evidence chain has not been modified. Subsequently, the system reads the trusted timestamp certificate TSA-20260322-000568 and calls the RSA public key in the publicly verified certificate of the trusted timestamp service provider to verify the digital signature value SIG-9A83E71C5D24F6A8B13D7E92C54F18A7. The verification result is successful. After the verification is successful, the evidence chain digest value of the record extracted from the trusted timestamp certificate is compared with the recalculated evidence chain digest value. The two are completely consistent. Therefore, the system determines that the construction traceability record TRACE-20260322-000138 has not been tampered with since it was stored at 08:31:22 on March 22, 2026, and generates a traceability trusted prompt message.

[0023] To better implement the above methods, an automatic acquisition and traceability management system for concealed engineering image data is also proposed. The system includes an operation log module, an engineering entity image node module, a spatiotemporal consistency verification module, an image evidence chain module, a construction risk indicator module, and a construction traceability module. Operation log module: acquires hidden engineering image data, constructs corresponding full-process management data based on the image data, and generates operation logs; Engineering entity image node module: acquires the image data and corresponding full-process management data, extracts engineering element features, establishes the association structure between engineering entities, construction procedures and image data, and generates engineering entity image nodes; The engineering entity image node module includes target engineering entity part units and generated engineering entity image node units: Target engineering entity unit: Acquire labeled image data, extract engineering element features from the labeled image data, the engineering element features include object name, process type, status information and acceptance information, integrate the extracted engineering element features with the corresponding acquisition time information and positioning information, and determine the corresponding target engineering entity unit in the engineering structure system based on the positioning information; The engineering entity image node generation unit obtains the unique identifier of the target engineering entity part, associates the engineering element features, acquisition time information and unique identifier to generate the corresponding engineering entity image node, sorts the engineering entity image nodes belonging to the same target engineering entity part according to the acquisition time order, establishes the temporal association relationship between the nodes, associates the engineering entity image node with the corresponding engineering part in the engineering structure system, forms the association structure between engineering entity, construction process and construction image data, establishes the corresponding process image ledger according to the association structure, and records the association relationship between engineering entity image nodes and construction process.

[0024] Spatiotemporal consistency verification module: Based on the project entity image nodes, it performs consistency verification on the time information, spatial location information and construction procedure logic of the image data, and generates the corresponding spatiotemporal consistency verification results; Image Evidence Chain Module: Constructs a construction process traceability diagram based on the spatiotemporal consistency verification results, establishes traceability association paths between construction process nodes, and generates corresponding image evidence chains; The image evidence chain module includes a directed process association edge unit and an image evidence chain generation unit: Directed process association edge unit: Obtain multiple engineering entity image nodes that have passed the spatiotemporal consistency verification, and obtain the unique identifier, construction process type, acquisition time information and association structure information corresponding to each engineering entity image node. Based on the construction process type corresponding to the engineering entity image node, match the preceding and following process relationships from the preset process dependency relationship library. When the construction process types corresponding to two engineering entity image nodes satisfy the preceding and following process dependency relationship, establish a directed process association edge between the corresponding engineering entity image nodes. The image evidence chain generation unit: For multiple engineering entity image nodes belonging to the same target engineering entity, they are initially sorted according to the acquisition time information to generate an initial construction process node sequence. Based on the directed process association edges between the engineering entity image nodes, the initial construction process node sequence is sorted by topological constraints, so that the preceding engineering entity image nodes with directed process association edge connections are placed before the following engineering entity image nodes, generating a construction process node sequence. The construction process node sequences corresponding to each target engineering entity are aggregated level by level according to the engineering structure system to form construction process association data covering the project level, section level, unit project level, and engineering part level. Each construction process node in the construction process node sequence is used as a node in the construction process traceability diagram, and the construction process traceability diagram is constructed in combination with the directed process association edges. Based on the construction process traceability diagram, the traceability association path from the preceding construction process node to the subsequent construction process node is determined, and the image data corresponding to the traceability association path is associated and organized to generate an image evidence chain for the entire construction process of the hidden works.

[0025] Construction risk indicator module: Based on the image evidence chain, analyze and evaluate the integrity and authenticity of the construction process, calculate construction risk indicators, and generate early warning information based on the construction risk indicators; Construction traceability module: performs summary calculation and reliable evidence storage processing on the image evidence chain, generates construction traceability records, and verifies and outputs the construction process traceability results based on the construction traceability records.

[0026] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for automatic acquisition and traceability management of concealed engineering image data, characterized in that, The methods include: Step S100: Obtain hidden engineering image data, and construct corresponding full-process management data based on the image data to generate operation logs; Step S200: Acquire the image data and corresponding full-process management data, extract engineering element features, establish the association structure between engineering entities, construction procedures and image data, and generate engineering entity image nodes; Step S300: Based on the engineering entity image nodes, perform consistency verification on the time information, spatial location information and construction procedure logic of the image data, and generate the corresponding spatiotemporal consistency verification result. Step S400: Construct a construction process traceability diagram based on the spatiotemporal consistency verification results, establish traceability association paths between construction process nodes, and generate corresponding image evidence chains; Step S500: Analyze and evaluate the integrity and authenticity of the construction process based on the image evidence chain, calculate construction risk indicators, and generate early warning information based on the construction risk indicators; Step S600: Perform digest calculation and credible evidence storage processing on the image evidence chain to generate construction traceability records, and verify and output the construction process traceability results based on the construction traceability records.

2. The method for automatic acquisition and traceability management of concealed engineering image data according to claim 1, characterized in that, Step S100 includes the following steps: The engineering structure system is constructed according to the project, section, unit project, sub-project, item project, chainage and location, and a unique identifier is configured for each engineering location. The system receives image data uploaded by mobile terminals, including photos and videos collected after the completion of the construction of the engineering location. The image data is bound to the unique identifier of the corresponding engineering location, and the collection time information, location information, equipment information and personnel information corresponding to the image data are obtained. Based on the unique identifier and the acquired information, an identifiable image is generated, and credible evidence information is generated for the identifiable image. The identifiable image and credible evidence information are named, stored and archived according to preset rules, and their association with the corresponding engineering business records is established. Based on the aforementioned relationship, respond to query requests, retrieve corresponding image data according to at least one of the following query conditions: project location, time range, construction procedure, and photographer, and generate an image ledger. User role-based access control is implemented for the acquisition, storage, query, and retrieval of the image data, and corresponding operation logs are recorded.

3. The method for automatic acquisition and traceability management of concealed engineering image data according to claim 1, characterized in that, Step S200 includes the following steps: Acquire labeled image data, extract engineering element features from the labeled image data, the engineering element features include object name, process type, status information and acceptance information, integrate the extracted engineering element features with the corresponding acquisition time information and positioning information, and determine the corresponding target engineering entity part in the engineering structure system based on the positioning information; Obtain the unique identifier of the target engineering entity part, associate the engineering element features, acquisition time information and unique identifier, and generate the corresponding engineering entity image node; The engineering entity image nodes belonging to the same target engineering entity are sorted according to the acquisition time sequence, and the temporal association relationship between the nodes is established. The engineering entity image nodes are associated with the corresponding engineering parts in the engineering structure system, forming an association structure between engineering entities, construction procedures and construction image data. According to the association structure, a corresponding procedure image ledger is established, and the association relationship between engineering entity image nodes and construction procedures is recorded.

4. The method for automatic acquisition and traceability management of concealed engineering image data according to claim 1, characterized in that, Step S300 includes the following steps: Acquire engineering entity image nodes belonging to the same target engineering entity part, arrange them in order of acquisition time, obtain the acquisition time information of adjacent engineering entity image nodes, calculate the difference between the acquisition time of the next engineering entity image node and the acquisition time of the previous engineering entity image node, and obtain the process time interval. Based on the construction process type, query the corresponding standard process time rule, compare the process time interval with the corresponding minimum construction time requirement, and generate a time anomaly mark when the process time interval is less than the minimum construction time requirement. Obtain the positioning information corresponding to the image nodes of the engineering entity; determine the corresponding target engineering entity part in the engineering structure system based on the unique identifier associated with the image nodes of the engineering entity; obtain the design coordinate information and construction area coordinate information corresponding to the target engineering entity part; and extract the boundary control points of the construction area based on the design coordinate information and construction area coordinate information. The control points of the construction area boundary are sequentially connected according to the preset boundary connection rules to generate a closed construction area boundary, and the target construction area boundary data is constructed based on the closed construction area boundary. The positioning information is analyzed to obtain the image acquisition coordinate points, and the image acquisition coordinate points are mapped to a unified coordinate reference system corresponding to the boundary data of the target construction area, thereby establishing a spatial positional relationship model between the boundary data of the target construction area and the image acquisition coordinate points. Based on the spatial location relationship model, the regional attribution relationship of the image acquisition coordinate point relative to the boundary of the target construction area is calculated. When the regional attribution relationship indicates that the image acquisition coordinate point is located within the closed area enclosed by the boundary of the target construction area, the location verification is confirmed to be successful. When the regional attribution relationship indicates that the image acquisition coordinate point is located outside the closed area enclosed by the boundary of the target construction area, a location anomaly marker is generated. Obtain the construction procedure type and construction status information corresponding to the current engineering entity image node, and obtain the previous procedure corresponding to the current construction procedure in the preset standard procedure flow. Determine whether the engineering entity image node corresponding to the previous procedure exists and whether its construction status meets the preset completion conditions. When there is no corresponding previous procedure node or the construction status does not meet the preset completion conditions, generate a procedure abnormality mark. Based on the generated time anomaly markers, location anomaly markers, and process anomaly markers, a spatiotemporal consistency verification result is formed for the corresponding engineering entity image nodes.

5. The method for automatic acquisition and traceability management of concealed engineering image data according to claim 1, characterized in that, Step S400 includes the following steps: Acquire multiple engineering entity image nodes that have passed the spatiotemporal consistency verification, and obtain the unique identifier, construction process type, acquisition time information and associated structural information corresponding to each engineering entity image node; Based on the construction process type corresponding to the engineering entity image node, the sequential process relationship is matched from the preset process dependency relationship library. When the construction process types corresponding to two engineering entity image nodes satisfy the sequential dependency relationship, a directed process association edge is established between the corresponding engineering entity image nodes. For multiple engineering entity image nodes belonging to the same target engineering entity part, they are initially sorted according to the acquisition time information to generate an initial construction process node sequence. Based on the directed process association edges between the engineering entity image nodes, the initial construction process node sequence is sorted by topological constraints so that the preceding engineering entity image node with the directed process association edge connection relationship is placed before the subsequent engineering entity image node, thus generating a construction process node sequence. According to the engineering structure system, the construction process node sequence corresponding to each target engineering entity is aggregated level by level to form construction process association data covering the project level, section level, unit project level and engineering part level; Each construction process node in the construction process node sequence is used as a node in the construction process traceability diagram. The construction process traceability diagram is constructed by combining directed process association edges. Based on the construction process traceability diagram, the traceability association path from the preceding construction process node to the subsequent construction process node is determined. The image data corresponding to the traceability association path is associated and organized to generate an image evidence chain of the entire construction process of the hidden works. When responding to a traceability request, image data of the corresponding construction process node is extracted along the traceability path based on the unique identifier corresponding to the target engineering entity, and the corresponding construction process traceability result is output.

6. The method for automatic acquisition and traceability management of concealed engineering image data according to claim 1, characterized in that, Step S500 includes the following steps: Obtain a list of standard procedures corresponding to the target engineering entity, the list of standard procedures including all standard procedures required to complete the construction of the engineering entity; Obtain the image evidence chain of the corresponding engineering entity, extract the process node set in the image evidence chain, and match the process node set with the standard process list item by item. Determine the standard process that does not match the corresponding process node in the standard process list as the missing process, and record the process position of the missing process in the standard process list. Obtain the preceding and subsequent processes corresponding to the missing process, and determine whether the process node corresponding to the preceding process and the process node corresponding to the subsequent process exist simultaneously in the image evidence chain. When the process node corresponding to the preceding process and the process node corresponding to the subsequent process exist simultaneously in the image evidence chain, the process segment between the preceding process and the subsequent process that contains the missing process is determined as the broken chain interval. Obtain the position of the missing process in the standard process list and the break interval, collect the planned execution number and actual completion number of the missing process in historical engineering data, calculate the missing process rate, and use the missing process rate as a process type risk indicator for the missing process; The degree of impact of the chain break interval is determined by the proportion of the number of missing processes in the chain break interval to the total number of processes in the chain break interval, and the degree of impact of the chain break interval is used as a chain break risk indicator. The process type risk index and the chain break risk index are normalized and calculated separately. The normalized process type risk index and the chain break risk index are then weighted and summed according to preset weights to calculate the integrity risk index of the missing process. When there are multiple missing processes, the integrity risk index of each missing process is weighted and summed according to preset process position weights to calculate the integrity risk index of the target project entity. Based on the spatiotemporal consistency verification results corresponding to each process node, the number of time anomalies, the number of location anomalies, and the number of process anomalies in the image evidence chain are counted. The number of time anomalies, the number of location anomalies, and the number of process anomalies are normalized and calculated respectively. The normalized number of time anomalies, the number of location anomalies, and the number of process anomalies are then weighted and summed according to preset weights to calculate the authenticity risk index of the target engineering entity. The integrity risk index and authenticity risk index of the target project entity are weighted according to the preset evaluation weight to obtain the construction risk index of the target project entity. When the construction risk index is higher than the risk index threshold or the integrity risk index of the missing process is higher than the integrity threshold, an early warning information is generated. The risk index threshold is obtained by acquiring a sample set of construction risk indicators from historical engineering data, calculating the mean and standard deviation of the sample set, multiplying the standard deviation by a preset threshold adjustment coefficient to obtain an adjustment value, and adding the adjustment value to the mean to obtain the risk index threshold. The integrity threshold is obtained by acquiring a sample set of integrity risk indicators from historical engineering data, calculating the mean and standard deviation of the sample set, multiplying the standard deviation by a preset integrity threshold adjustment coefficient to obtain an adjustment value, and adding the adjustment value to the mean to obtain the integrity threshold.

7. The method for automatic acquisition and traceability management of concealed engineering image data according to claim 1, characterized in that, Step S600 includes the following steps: Obtain the image evidence chain corresponding to the target engineering entity, and extract the image nodes of each engineering entity, node associations, spatiotemporal consistency verification results, and construction credibility evaluation results from the image evidence chain. According to the tracing and association path order in the image evidence chain, the node identifier, image file summary value, acquisition time information and spatiotemporal consistency verification result corresponding to each engineering entity image node are combined according to the preset coding rules to form the node data of the corresponding engineering entity image node. Hash operations are performed on the data of each node to generate node summary values ​​for the corresponding engineering entity image nodes. The first node summary value is used as the initial chain summary value. Following the order of the traceability path, the previous chain summary value is concatenated with the current node summary value and then hashed to generate the current chain summary value. The current chain summary value is used as the previous chain summary value for the next node for iterative calculation until the cascading calculation of all node summary values ​​is completed to obtain the evidence chain summary value of the corresponding image evidence chain. The evidence chain summary value is sent to the traceability management platform, which obtains the corresponding trusted timestamp certificate based on the evidence chain summary value. Obtain the information of the responsible party corresponding to the image evidence chain, and associate and encapsulate the image evidence chain, evidence chain summary value, credible timestamp certificate, responsible party information and construction credibility evaluation results to generate construction traceability records; When responding to a traceability verification request, the image evidence chain in the construction traceability record is read and the evidence chain digest value is recalculated. The recalculated evidence chain digest value is compared with the evidence chain digest value in the construction traceability record. If the comparison is consistent, the corresponding trusted timestamp certificate is read, and the digital signature in the trusted timestamp certificate is verified using the verification public key of the trusted timestamp service agency. If the verification is successful, the evidence chain digest value recorded in the trusted timestamp certificate is extracted, and it is verified whether the evidence chain digest value is consistent with the recalculated evidence chain digest value. When the evidence chain digest values ​​match and the trusted timestamp certificate is verified, it is determined that the construction traceability record has not been tampered with, and a corresponding traceability trusted prompt message is generated. When the evidence chain digest values ​​do not match or the trusted timestamp certificate verification fails, a traceability abnormal prompt message is generated.

8. An automatic acquisition and traceability management system for concealed engineering image data, used to implement the automatic acquisition and traceability management system for concealed engineering image data as described in any one of claims 1-7, characterized in that, The system includes an operation log module, an engineering entity image node module, a spatiotemporal consistency verification module, an image evidence chain module, a construction risk indicator module, and a construction traceability module. The operation log module: acquires hidden engineering image data, constructs corresponding full-process management data based on the image data, and generates operation logs; The engineering entity image node module: acquires the image data and corresponding full-process management data, extracts engineering element features, establishes the association structure between engineering entities, construction procedures and image data, and generates engineering entity image nodes; The spatiotemporal consistency verification module: Based on the engineering entity image nodes, performs consistency verification on the time information, spatial location information and construction procedure logic of the image data, and generates the corresponding spatiotemporal consistency verification results; The image evidence chain module: constructs a construction process traceability diagram based on the spatiotemporal consistency verification results, establishes traceability association paths between construction process nodes, and generates corresponding image evidence chains; The construction risk indicator module analyzes and evaluates the integrity and authenticity of the construction process based on the image evidence chain, calculates construction risk indicators, and generates early warning information based on the construction risk indicators. The construction traceability module performs summary calculation and reliable evidence storage processing on the image evidence chain, generates construction traceability records, and verifies and outputs the construction process traceability results based on the construction traceability records.

9. The automatic acquisition and traceability management system for concealed engineering image data according to claim 8, characterized in that, The engineering entity image node module includes target engineering entity part units and engineering entity image generation node units: The target engineering entity unit: acquires labeled image data, extracts engineering element features from the labeled image data, the engineering element features include object name, process type, status information and acceptance information, integrates the extracted engineering element features with the corresponding acquisition time information and positioning information, and determines the corresponding target engineering entity unit in the engineering structure system based on the positioning information; The unit for generating engineering entity image nodes: obtains the unique identifier of the target engineering entity part, associates the engineering element features, acquisition time information and unique identifier to generate corresponding engineering entity image nodes, sorts engineering entity image nodes belonging to the same target engineering entity part according to the acquisition time order, establishes the temporal association relationship between nodes, associates the engineering entity image nodes with the corresponding engineering parts in the engineering structure system, forms the association structure between engineering entities, construction procedures and construction image data, establishes the corresponding procedure image ledger according to the association structure, and records the association relationship between engineering entity image nodes and construction procedures.

10. The automatic acquisition and traceability management system for concealed engineering image data according to claim 8, characterized in that, The image evidence chain module includes a directed process association edge unit and an image evidence chain generation unit: The directed process association edge unit: acquires multiple engineering entity image nodes that have passed the spatiotemporal consistency verification, and acquires the unique identifier, construction process type, acquisition time information and association structure information corresponding to each engineering entity image node. Based on the construction process type corresponding to the engineering entity image node, it matches the sequential process relationship from the preset process dependency relationship library. When the construction process types corresponding to two engineering entity image nodes satisfy the sequential dependency relationship, a directed process association edge is established between the corresponding engineering entity image nodes. The image evidence chain generation unit: For multiple engineering entity image nodes belonging to the same target engineering entity, initial sorting is performed according to the acquisition time information to generate an initial construction process node sequence. Based on the directed process association edges between the engineering entity image nodes, the initial construction process node sequence is sorted by topological constraints, so that the preceding engineering entity image node with the directed process association edge connection relationship is placed before the subsequent engineering entity image node, generating a construction process node sequence. The construction process node sequences corresponding to each target engineering entity are aggregated level by level according to the engineering structure system to form construction process association data covering the project level, section level, unit project level, and engineering part level. Each construction process node in the construction process node sequence is used as a node in the construction process traceability diagram, and the construction process traceability diagram is constructed in combination with the directed process association edges. Based on the construction process traceability diagram, the traceability association path from the preceding construction process node to the subsequent construction process node is determined, and the image data corresponding to the traceability association path is associated and organized to generate an image evidence chain of the entire construction process of the hidden works.

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