BIM (Building Information Modeling) data asset precipitation and operation management system for full life cycle of building

Abstract

The invention discloses a building full life cycle-oriented BIM data asset precipitation and operation management system. The system comprises six modules including a multi-source data conflict resolution module, a Beidou grid coding association module, a space-time fusion index module, an AEM asset integration module, a full cycle BIM processing module and a data asset operation module. According to the system, a building multi-source data conflict resolution and lightweight algorithm, a Beidou grid coding space-time asset association model and a data space-time fusion and spatial index model are utilized, and an Adobe Explosion Manager Assets platform is combined, so that BIM data of the whole life cycle of a building is processed. Through module collaboration, multi-source data conflicts are eliminated, data space-time association and fusion are achieved, the data are integrated to a professional platform, and a full-cycle data association graph is formed and operated. According to the system, the problems of low data integration efficiency, insufficient time-space association and the like in the prior art are solved, effective precipitation and efficient operation of BIM data assets are realized, and support is provided for refined management of buildings.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of BIM data asset management, in particular to a BIM data asset sedimentation and operation management system for the whole life cycle of a building. BACKGROUND

[0002] In the process of digital transformation of the construction industry, the whole life cycle of a building covers multiple stages such as design, construction, operation and maintenance, and the BIM data generated in each stage has the characteristics of multi-source heterogeneity, and the data volume grows exponentially as the stage progresses. These data contain key content such as building component parameters, construction progress information, and equipment operating status, and are the core assets for realizing fine management and decision optimization of buildings. However, the current industry's management of BIM data is mostly limited to the application level of a single stage, lacking a systematic sedimentation and operation mechanism throughout the whole life cycle, which makes it difficult to fully realize the value of data and cannot meet the needs of modern buildings for data-driven whole-process management.

[0003] The prior art has obvious deficiencies in handling BIM data throughout the whole life cycle of a building. On the one hand, the ability to resolve multi-source data conflicts is weak, and BIM data from different stages and different sources often conflict due to format differences and inconsistent space-time benchmarks, and lack effective lightweight processing means, resulting in low data integration efficiency and difficulty in forming a unified asset dataset. On the other hand, there are defects in the spatio-temporal correlation and operation management of data assets, which cannot achieve dynamic correlation between data and building entities through precise spatio-temporal coding, and lack deep integration mechanisms with professional asset platforms, resulting in scattered data storage and chaotic access control, making it difficult to support efficient operation and value mining of data assets throughout the whole life cycle. SUMMARY

[0004] In order to overcome the shortcomings and deficiencies of the prior art, the present application provides a BIM data asset sedimentation and operation management system for the whole life cycle of a building.

[0005] The technical solution adopted by the present application is a BIM data asset sedimentation and operation management system for the whole life cycle of a building, including: a multi-source data conflict resolution module, a Beidou grid coding correlation module, a spatio-temporal fusion index module, an AEM asset integration module, a whole-cycle BIM processing module, and a data asset operation module. The multi-source data conflict resolution module receives BIM data and associated heterogeneous data in the building design, construction and operation stages, identifies and resolves conflicts through building multi-source data conflict resolution and lightweight algorithm, and transmits the processed data to the Beidou grid coding association module; the Beidou grid coding association module calls the Beidou grid coding space-time asset association model to code the received data in space-time, generates BIM data assets with space-time identifiers, and transmits them to the space-time fusion index module; the space-time fusion index module uses a data space-time fusion and spatial index model to fuse the received data in space-time dimensions and construct a spatial index, forms a structured data asset set, and pushes it to the AEM asset integration module; the AEM asset integration module establishes a data interaction channel with the Adobe Experience Manager Assets platform, converts and maps the structured data asset set according to the platform interface specification, synchronizes it to the platform storage, and feeds back the storage path information to the whole-cycle BIM processing module; the whole-cycle BIM processing module extracts and analyzes the data assets in stages according to the BIM data parameters in the whole life cycle of the building, generates a whole-cycle data association graph, and transmits it to the data asset operation module; the data asset operation module performs classification storage, access control and dynamic update operations based on the received whole-cycle data association graph, and forms a closed-loop management process.

[0006] Further, in the multi-source data conflict resolution module, the building multi-source data conflict resolution and lightweight algorithm identify data conflicts by constructing a conflict metric model, and the model formula is: wherein, represents the conflict degree of the ith BIM data and the jth heterogeneous data, are the weight coefficients of the attribute value difference, the time difference and the space difference, respectively, is the attribute value of the BIM data, is the attribute value of the heterogeneous data, is the data collection time and are the time distance functions of and are the space similarity functions of After conflict identification, the lightweight processing formula is: wherein, is the data volume after lightweight processing, is the original data volume, is the weight of the kth redundant data, is the proportion of the kth redundant data.

[0007] Further, in the Beidou grid encoding association module, the Beidou grid encoding space-time asset association model associates BIM data and space-time assets through an encoding mapping formula, and the formula is: wherein, is the generated Beidou grid encoding, is an encoding generation function, is a BIM data unique identifier, is a building space three-dimensional coordinate, is a time stamp at a coordination time, is a grid precision level; at the same time, the module optimizes the association result through an association strength calculation model, and the formula is: wherein, is an association strength value, , are respectively weights of space association and time association, is a matching degree of the grid encoding and BIM space information, is a matching degree of the grid encoding and BIM time information, is BIM space information, is BIM time information.

[0008] Further, in the space-time fusion index module, a data space-time fusion and space index model integrates multi-dimensional data through a space-time fusion formula, and the formula is: wherein, is the fused data, is a space-time fusion weight coefficient, is spatial dimension data, is time dimension data, is a space-time tensor product operation, is attribute dimension data; a space index construction adopts a hierarchical index formula: wherein, is a space index set, are respectively a row number and a column number of a plane grid, is an mth row and nth column grid unit, is a space range of BIM data.

[0009] Further, in the AEM asset integration module, a data mapping with an Adobe Experience Manager Assets platform adopts a metadata mapping formula: wherein, is a metadata set of the AEM platform, is a mapping function, is a metadata set of BIM data, and the mapping function satisfies and a metadata key name mapping rule, a metadata value conversion rule, a key name of the metadata, a value of the metadata; the data synchronization efficiency is controlled by a synchronization delay model: wherein, is a synchronization delay time, is a data transmission coefficient, is a data size, is a transmission bandwidth, is a conversion complexity coefficient, is a format conversion complexity.

[0010] Further, in the full-cycle BIM processing module, the phased feature extraction adopts a feature quantization formula: wherein, is a comprehensive feature value of the life cycle phase per unit time, is a weight of the pth feature, is a quantized value of the pth feature in the phase; the data correlation analysis is calculated by a correlation degree calculation model, and the expression is: wherein, is the correlation degree of the BIM data of the ith phase and the jth phase, is the kth parameter value of the ith phase, is the parameter mean value of the ith phase, is the kth parameter value of the jth phase, is the parameter mean value of the jth phase, is the number of parameters.

[0011] Further, the space-time fusion index module includes three units: a space-time data registration unit, a multi-dimensional fusion unit, and a spatial index construction unit; the space-time data registration unit receives the BIM data assets with space-time identifiers transmitted by the Beidou grid code correlation module, extracts the timestamp and spatial coordinate information in the data, adjusts the data with reference differences to a unified space-time coordinate system by comparing the space-time references of different data, and forms a data set with consistent space-time references; the multi-dimensional fusion unit calls the data space-time fusion and spatial index model, associates the registered spatial data, time series data, and attribute data in dimensions, and integrates the scattered single-dimensional data into multi-dimensional data volume containing space-time attributes by establishing a space-time attribute correlation matrix; the spatial index construction unit divides the grid units according to the building space distribution characteristics based on the fused multi-dimensional data volume, calculates the spatial proportion of each BIM data asset in the grid unit, generates an index table containing the correspondence relationship between the data identifier and the grid unit, stores the index table and associates it to the multi-dimensional data volume.

[0012] Further, the AEM asset integration module includes 4 units: platform interface adaptation unit, data format conversion unit, metadata mapping unit, asset synchronization unit; the platform interface adaptation unit parses the API document of Adobe Experience Manager Assets platform, generates a calling function conforming to the interface specification, and establishes the communication connection between the system and the platform; the data format conversion unit reads the structured data asset set output by the spatio-temporal fusion index module, converts the data into the corresponding format according to the format type supported by the platform, while retaining the spatial topological relationship of the data; the metadata mapping unit extracts the original metadata in the BIM data, refers to the platform metadata standard, establishes the mapping relationship of the metadata fields, and converts the original metadata into the metadata recognizable by the platform; the asset synchronization unit uploads the converted data and the mapped metadata to the Adobe Experience Manager Assets platform by using the calling function generated by the platform interface adaptation unit, records the upload path and feeds back to the whole-cycle BIM processing module.

[0013] Further, the whole-cycle BIM processing module includes 3 units: phased data extraction unit, feature correlation analysis unit, whole-cycle graph generation unit; the phased data extraction unit extracts the BIM data of the corresponding stage from the storage path fed back by the AEM asset integration module according to the stage division of the building whole life cycle, and screens out the pre-designated parameters of different stages; the feature correlation analysis unit compares the pre-designated parameters of different stages, identifies the causal relationship and dependency relationship between the parameters of different stages, calculates the correlation degree of parameter changes, and forms the feature correlation rules between stages; the whole-cycle graph generation unit constructs a whole-cycle data correlation graph taking stages as nodes and parameter correlations as edges based on the correlation rules obtained by the feature correlation analysis unit, marks the spatio-temporal attributes of each parameter in the graph, and transmits the graph to the data asset operation module.

[0014] The BIM data asset sedimentation and operation management system for the whole life cycle of a building, which runs includes: First, the data asset operation module receives the whole-cycle data correlation graph transmitted by the whole-cycle BIM processing module, parses the BIM data identifier, stage information and correlation relationship contained in the graph, and establishes the mapping index of the data asset and the correlation graph; Second, according to the stage information obtained by parsing, the data assets are classified according to the stage division standard of the building whole life cycle, each type of data asset is allocated an independent storage area, and the storage format corresponding to the stage characteristics is set; Third, based on the correlation relationship and importance of the data assets, the hierarchical access permission rules are formulated, the rules are embedded into the access control module, and the access requests of different user roles are checked for permission; The fourth step is to regularly monitor the update status of data assets in the Adobe Experience Manager Assets platform, obtain the identifier and content of the updated data, and trigger the update mechanism of the data asset operation module; The fifth step is to use the building multi-source data conflict resolution and lightweight algorithm to process the updated data, compare the processed data with the original data assets, and update the corresponding association relationships and storage paths in the association map; The sixth step is to record the classification results, access logs and update records of data assets, generate an operation report, store the report in the system log library, and at the same time feed back the updated association map and data asset status to the multi-source data conflict resolution module to form a closed-loop process for data asset operation.

[0015] Beneficial effects: The present invention proposes a BIM data asset sedimentation and operation management system for the entire life cycle of a building. The system uses a multi-source data conflict resolution module and a lightweight algorithm to accurately identify and resolve conflicts in data from different stages and sources. At the same time, it performs lightweight processing to improve data integration efficiency, overcoming the shortcomings of weak multi-source data conflict resolution capabilities and low integration efficiency in existing technologies. The Beidou grid coding association module uses the Beidou grid coding spatiotemporal asset association model to achieve accurate spatiotemporal association between data and building entities; the spatiotemporal fusion index module constructs a spatial index, the AEM asset integration module is deeply integrated with the professional platform, and the data asset operation module implements classified storage, access control, and dynamic updates, solving the problems of insufficient spatiotemporal association of data assets, scattered storage, and chaotic access, supporting efficient operation of data assets throughout the life cycle, fully releasing data value, and meeting the data-driven needs of the entire process. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a diagram of the system unit composition of the present invention; Figure 2 This is a flow chart of the system operation of the present invention. DETAILED DESCRIPTION

[0017] It should be noted that, unless there is a conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The application is further described in detail below with reference to the drawings and specific embodiments.

[0018] like Figure 1 As shown, the BIM data asset accumulation and operation management system for the entire life cycle of buildings includes: multi-source data conflict resolution module, Beidou grid coding association module, spatiotemporal fusion index module, AEM asset integration module, full-cycle BIM processing module, and data asset operation module; The multi-source data conflict resolution module receives BIM data and associated heterogeneous data in the building design, construction, and operation stages, identifies and resolves conflicts through building multi-source data conflict resolution and lightweight algorithms, and transmits the processed data to the Beidou grid coding association module. The multi-source data conflict resolution module is the first step in processing BIM data throughout the building lifecycle, involving data conflict identification sensitivity, lightweight processing compression ratio, and data throughput. This module is used to solve the format incompatibility and information inconsistency between BIM data generated in different stages such as building design, construction, and operation, and various heterogeneous data (such as geographic information data, equipment monitoring data, etc.), providing high-quality basic data for subsequent data association and fusion processing. By effectively resolving data conflicts and performing lightweight processing, data storage pressure can be reduced, data transmission efficiency can be improved, and the accuracy and efficiency of subsequent module processing can be ensured.

[0019] The specific implementation process of this module is as follows: First, receive multi-source data from the BIM model data in the building design stage (including component size, material properties, spatial position, etc. parameters, such as the cross-sectional size of the beam is 300mm x 600mm, the concrete strength grade is C30), the progress data in the construction stage (such as the planned start time and actual completion time of a sub-item project), and the equipment operation data in the operation stage (such as the operating temperature range of air conditioning equipment is 18-26℃, and the energy consumption data unit is kWh). Then, start the building multi-source data conflict resolution algorithm, identify the conflict type by comparing the attribute parameters of different data, for example, the thickness parameter of a certain wall in the design stage BIM model is 240mm, while the actual measurement data in the construction stage is 235mm, which is an attribute value conflict; for example, the installation time of a certain equipment is recorded as March 10, 2024 in the BIM data, while the arrival time in the equipment procurement record is March 15, 2024, which is a time conflict. For the identified conflict data, correct and integrate them according to the preset priority rules (such as actual construction data is prior to design model data). Then, start the lightweight processing procedure, remove and simplify redundant geometric information (such as repeated component models) and unnecessary detail parameters (such as decorative component texture data that has no impact on overall analysis) in the BIM model, control the data compression ratio to between 30%-50%, for example, reduce the 100MB BIM model data to 40-70MB after lightweight processing. After processing, transmit the integrated standardized data to the Beidou grid coding association module, and record the data processing log, including the number of conflicts, processing method, data volume before and after lightweight processing, etc. for subsequent tracing and verification.

[0020] The Beidou grid code correlation module calls the Beidou grid code space-time asset correlation model to perform space-time coding on the received data, generates BIM data assets with space-time identifiers, and transmits them to the space-time fusion index module; The technical parameters of the Beidou grid code correlation module include the precision level of the grid code (such as 1st to 32nd level, different levels correspond to different spatial resolutions), the response time of code generation, the accuracy of data correlation, etc. This module uses Beidou grid coding technology to give the preprocessed BIM data a unique space-time identifier, realizes the precise correlation of BIM data and building entities in time and space dimensions, breaks down the space-time barriers between data at different stages, and enables scattered data to be integrated and managed based on a unified space-time reference, providing key space-time coordinate information for subsequent space-time fusion, index construction, etc.

[0021] The specific implementation process of this module is as follows: receiving standardized BIM data transmitted by the multi-source data conflict resolution module, first extracting the spatial position information (such as the three-dimensional coordinates of building components, with an accuracy of centimeters, such as the bottom center point coordinates of a certain column body X=35200mm, Y=28600mm, Z=0mm) and time information (such as data generation time, time node corresponding to the construction stage, accurate to seconds, such as May 20, 2024, 14:30:25) in the data. According to the scale and precision requirements of the construction project, select the appropriate Beidou grid coding precision level, for large building groups, select 10-15 level precision (corresponding to a spatial resolution of about 10-100 meters), for the details of single building, select 20-25 level precision (corresponding to a spatial resolution of about 0.1-1 meter). Call the Beidou grid coding space-time asset correlation model to convert the extracted spatial coordinates into corresponding Beidou grid codes, and the code length varies with the precision level, such as the code length of 20th level precision is set to about 20 bits. At the same time, embed the time information into the code structure to form a composite code containing space-time information, ensuring that each BIM data asset has a unique space-time identifier. Then, check the generated code for accuracy, check the accuracy of the code and the original spatial position, time information, and the accuracy rate should be above 99.9%. After passing the verification, the BIM data assets with space-time identifiers are transmitted to the space-time fusion index module, and the code mapping relationship table is stored to record the correspondence between BIM data identifiers and Beidou grid codes for subsequent data query and correlation analysis.

[0022] The space-time fusion index module uses the data space-time fusion and spatial index model to perform space-time dimension fusion and spatial index construction on the received data, forms a structured data asset set, and then pushes it to the AEM asset integration module; The technical parameters of the spatio-temporal fusion index module include the dimension coverage of spatio-temporal fusion, the query response time of spatial index, the stability of index structure, etc. This module deeply fuses the BIM data assets with spatio-temporal identifiers in the time, space and attribute dimensions, constructs a unified data view, and improves the retrieval and access efficiency of data by establishing an efficient spatial index, so that the system can quickly locate and extract BIM data within a specific spatio-temporal range, providing a convenient data acquisition channel for subsequent data integration, analysis and operation.

[0023] The specific implementation process of this module is as follows: receiving the BIM data assets with spatio-temporal identifiers transmitted by the Beidou grid coding association module, first performing data preprocessing, sorting the time dimension information in the data (such as the time interval of each stage, the design stage is January 2023-June 2023, and the construction stage is July 2023-December 2024), the spatial dimension information (spatial distribution based on Beidou grid coding) and the attribute dimension information (such as the material and performance parameters of the component). Start the data spatio-temporal fusion model, connect the BIM data of different stages in time sequence to form a continuous data chain in the time dimension; in the spatial dimension, according to the spatial correlation of Beidou grid coding, aggregate the BIM data within adjacent grids to construct the spatial topology relationship; in the attribute dimension, associate and integrate the attribute parameters of the same component or associated components to form a fusion data body containing multi-dimensional information, ensuring that the coverage rate of the fused data set in the time, space and attribute dimensions reaches more than 95%. Then, start to build the spatial index, adopt a hierarchical index structure, first divide it into layers based on the precision level of Beidou grid coding, and in each layer, further divide the grid into sub-regions according to the spatial distribution density of the data, with each sub-region corresponding to an index node. Store the identification, spatio-temporal range and storage location of the BIM data in each index node, and dynamically adjust the number of index nodes according to the data size, controlling between 100-1000 in each layer. After completing the index construction, test the index performance to ensure that the response time is not more than 1 second when querying data within any spatio-temporal range. Finally, push the structured data asset set and the corresponding spatial index formed to the AEM asset integration module, and record the calibration parameters and index structure information in the fusion process for subsequent index maintenance and optimization.

[0024] The AEM asset integration module establishes a data interaction channel with the Adobe Experience Manager Assets platform, converts and maps the structured data asset set according to the platform interface specification, synchronizes it to the platform storage and feeds back the storage path information to the whole-cycle BIM processing module; The technical parameters of the AEM asset integration module include interface adaptation rate with the Adobe Experience Manager Assets platform, data format conversion accuracy, data synchronization delay time, etc. The module realizes seamless connection between the system and the professional asset platform, converts and integrates structured BIM data assets according to platform specifications, and realizes centralized storage and standardized management of BIM data assets through the powerful storage, management and distribution capabilities of the platform, providing stable storage support for data sharing, access and subsequent full-cycle processing.

[0025] The specific implementation process of the module is as follows: First, establish a communication connection with the Adobe Experience Manager Assets platform, parse the API interface specification and data storage requirements of the platform, and the interface adaptation rate needs to reach 100%, to ensure that the system and the platform can normally interact with data. Receive the structured data asset set pushed by the space-time fusion index module, which includes BIM model files (such as.dwg,.rvt format), attribute data tables (such as.csv,.xlsx format), space-time correlation information table, etc. According to the file format and metadata standards supported by the platform, start the data format conversion program, convert the BIM model file to a platform-compatible format (such as converting.rvt format to.ifc format or.jpg preview graph format), and the conversion process needs to maintain the geometric accuracy of the model and the integrity of the attribute information, with an accuracy of not less than 99%. For attribute data and space-time correlation information, map and convert according to the platform metadata field requirements, such as mapping the "component material" field to the platform "material" field, and storing the Beidou grid code information into the platform "spatial_code" custom field. After completing the format conversion and metadata mapping, upload the converted data assets to the specified storage path of the Adobe Experience Manager Assets platform through the platform API (such as folder division according to building stage and component type, path format is " / projectA / design / structure / beams / "), and monitor the data transmission status in real time during the uploading process to ensure complete data uploading. After data synchronization is completed, record the storage path information, data identifier and synchronization time returned by the platform (synchronization delay time is controlled within 5 minutes), and feed back these information to the full-cycle BIM processing module, and generate an integration report containing the converted data volume, success number, failure reason, etc., for subsequent integration process optimization and problem troubleshooting.

[0026] The full-cycle BIM processing module extracts and analyzes the features of the data assets pointed by the storage path according to the BIM data parameters of the building full life cycle, generates a full-cycle data correlation graph and transmits it to the data asset operation module; The technical parameters of the whole-cycle BIM processing module include coverage rate of phased feature extraction, confidence level of data correlation analysis, and integrity of whole-cycle data correlation graph, etc. Based on the stored BIM data assets, the module deeply mines the internal relationship between the data of each stage of the building life cycle, extracts the key features of each stage, and constructs a whole-cycle data correlation graph, providing data support for understanding the entire process of the building from design to operation, helping to discover potential problems and optimization space between stages, and providing basis for decision-making in the building life cycle.

[0027] The specific implementation process of the module is as follows: receiving the storage path information fed back by the AEM asset integration module, calling the corresponding BIM data assets from the Adobe Experience Manager Assets platform according to the path direction, covering data of each stage such as design, construction, and operation, such as component size parameters in the design stage (the span of the beam is 8m, the cross-sectional moment of inertia is a certain value), progress data in the construction stage (the concrete pouring amount of a floor is 500m³, the number of construction personnel is 30), equipment failure data in the operation stage (the number of elevator failures is 5 times, the average maintenance time is 4 hours), etc. According to the stage division of the building life cycle (design, construction preparation, construction implementation, completion acceptance, operation), the called data is processed in stages, and for each stage, a feature extraction index system is set up, including component size, material consumption, design cost, etc. in the design stage, construction progress deviation, resource consumption, quality acceptance result, etc. in the construction stage, and equipment failure rate, energy consumption index, maintenance cost, etc. in the operation stage, to ensure that the coverage rate of feature extraction in each stage reaches more than 90%. The extracted feature data of each stage is cleaned and standardized (such as converting energy consumption data in different units to kWh / ㎡), and then correlation analysis method is used to calculate the correlation between different stage features, such as analyzing the relationship between component size in the design stage and material consumption in the construction stage, and the relationship between quality acceptance result in the construction stage and equipment failure rate in the operation stage, etc. The correlation confidence in the analysis process needs to reach more than 80%. According to the analysis results, a whole-cycle data correlation graph is constructed, with stages as nodes and feature correlations as edges. The graph contains key feature parameters of each stage, correlation strength between features, and influence paths. Finally, the integrity of the graph is verified to ensure that it covers the main stages and key features of the building life cycle. After verification, the graph is transmitted to the data asset operation module, and the feature data and correlation analysis results of each stage are stored for subsequent graph updating and in-depth analysis.

[0028] The data asset operation module performs classification storage, access control, and dynamic update operations on the received whole-cycle data correlation graph, forming a closed-loop management process.

[0029] The technical parameters of the data asset operation module include the accuracy of data classification storage, the security of access control (such as permission verification pass rate, illegal access interception rate), the timeliness of data dynamic updating, etc. This module systematically manages the whole-cycle BIM data correlation graph and the underlying data assets. Through classification storage, strict access control and dynamic updating, it ensures the security, integrity and timeliness of data assets, realizes the efficient use and value maximization of data assets, and provides reliable data services for all participants in the building life cycle.

[0030] The specific implementation process of this module is as follows: receiving the whole-cycle data correlation graph transmitted by the whole-cycle BIM processing module, parsing the BIM data identifiers (such as component ID "beam-123") contained in the graph, corresponding building stages (such as "construction implementation stage"), correlation relationships (such as spatial connection relationship with "column-456"), etc. According to the type of data (model data, attribute data, document data, etc.), the stage it belongs to and the importance, develop a classification storage strategy, store the data assets to different storage areas of the system (such as high-speed storage area for storing high-frequency access operation and maintenance data, archival storage area for storing historical design data), the accuracy of classification storage needs to reach more than 99.5%. Based on the sensitivity of data and user roles (such as designers, construction parties, operation and maintenance personnel, management personnel), set access permission rules, such as designers can modify design stage data but cannot access operation and maintenance stage cost data, operation and maintenance personnel can view equipment operation data but cannot modify design parameters, the permission rules are embedded in the access control engine of the system, and the access requests of users are checked in real time (permission verification pass rate 100%, illegal access interception rate 100%). Establish a data dynamic updating mechanism, monitor the changes of data assets in Adobe Experience Manager Assets platform (such as new operation records, modified construction data) at regular intervals (such as every hour), when detecting data update, automatically trigger the update process, call the updated data assets, re-process conflict resolution, coding correlation, etc., and update the corresponding correlation in the whole-cycle data correlation graph. At the same time, record all data asset access logs (including access user, access time, operation content) and update records (update time, update content, update personnel), log information is saved for not less than 5 years, used for data tracing and security audit. Regularly (such as every month) statistical analysis of the storage state, access situation, update frequency of data assets, optimization of storage strategy and access permission setting, forming a closed-loop management of data asset operation, ensuring that data assets continue to serve the various work of building life cycle efficiently.

[0031] The building multi-source data conflict resolution and lightweight algorithm is one of the core technologies of the application for processing multi-source heterogeneous BIM data. Specifically, it refers to a set of rules and steps for identifying and eliminating conflicts between BIM data of different sources and different stages in the whole life cycle of buildings and associated heterogeneous data, and performing data refinement. In terms of implementation, first, a conflict measurement model is constructed, considering data attribute value difference, time difference and space difference, setting appropriate weight coefficients, calculating the conflict degree between different data, and when the conflict degree exceeds the preset threshold, the conflict is resolved according to the rules such as construction data prior to design data, measured data prior to simulated data; then, lightweight processing is performed, the weight and proportion of redundant data are determined according to the importance of the data to building management, and redundant information is removed or simplified, thereby reducing the data volume on the premise of ensuring the integrity of core parameters. The algorithm is used to solve the problems of incompatible formats and inconsistent information of multi-source data, reduce the data storage and transmission pressure, and improve the data integration efficiency. The building multi-source data conflict resolution and lightweight algorithm provides high-quality basic data for subsequent data association and fusion processing, ensures the accuracy and efficiency of the whole system data processing, and lays a foundation for effective management of building whole life cycle data.

[0032] The Beidou grid coding space-time asset association model of the application is a key model for realizing accurate association of BIM data and space-time assets. The model is based on Beidou grid coding technology, binds BIM data with time and space information of building entities, and gives BIM data a unique space-time identifier. To achieve this, the spatial three-dimensional coordinates (with an accuracy of centimeters) and time information (accurate to seconds) are extracted from standardized BIM data, the appropriate grid precision level is selected according to the scale of the building project, the spatial coordinates are converted into Beidou grid codes by calling the coding generation function, the time information is embedded to form a composite code, and the matching degree of the code and the space-time information of the BIM data is evaluated by the association strength calculation model to ensure the accuracy of the association. The model breaks down the space-time barriers of data at different stages, enabling scattered BIM data to be integrated and managed based on a unified space-time reference. The Beidou grid coding space-time asset association model provides a unique space-time "identity card" for BIM data, facilitating subsequent space-time fusion, index construction and association analysis of data, improving the accuracy and consistency of data management, and providing a space-time reference for understanding the development process of the whole life cycle of buildings.

[0033] Preferably, in the multi-source data conflict resolution module, the building multi-source data conflict resolution and lightweight algorithm identifies data conflicts by constructing a conflict measurement model, and the model formula is: wherein, represents the conflict degree of the i-th BIM data and the j-th heterogeneous data, are weight coefficients of attribute value difference, time difference and space difference, respectively, is a property value of the BIM data, is a property value of the heterogeneous data, is a data acquisition time is a time distance function of is a spatial similarity function of ; after conflict identification, a lightweight processing formula is adopted: wherein, is a data volume after lightweight processing, is an original data volume, is a weight of the kth redundant data, is a proportion of the kth redundant data.

[0034] Specifically, the implementation of building multi-source data conflict resolution and lightweight algorithm in the multi-source data conflict resolution module improves the accuracy of data conflict identification and the efficiency of data processing by constructing a conflict measurement model and a lightweight processing mechanism. The technical parameters associated with the conflict measurement model include the weight coefficients of attribute value difference, time difference, and spatial difference. These coefficients are set according to the characteristics of building data and actual application scenarios. The attribute value difference weight coefficient ranges from 0.4 to 0.6, and the time difference and spatial difference weight coefficients range from 0.2 to 0.3, to ensure a reasonable trade-off for different types of conflicts. The time distance function is used to quantify the difference in data acquisition time, calculated by the ratio of the time stamp difference to the unit time. The spatial similarity function is normalized based on the Euclidean distance of spatial coordinates, so that the conflict degree calculation result is between 0 and 1, making it easy to determine the severity of the conflict. In lightweight processing, the weight of redundant data is determined according to the importance of the data to building lifecycle management. Core parameters such as structural size and material strength have a weight close to 0, while non-core parameters such as decorative texture have a weight between 0.3 and 0.7. The proportion of redundant data is obtained by statistical analysis of the ratio of redundant data volume to original data volume. In implementation, first, the attributes of the input BIM data and heterogeneous data are extracted to determine the parameter values, which are then substituted into the conflict measurement model to calculate the conflict degree. When the conflict degree exceeds the preset threshold (set to 0.6), it is determined that there is a significant conflict and the resolution process is started. The correction is performed according to the rules that construction data takes priority over design data and measured data takes priority over simulated data. Subsequently, for the resolved data, the data volume is reduced by the lightweight processing formula based on the weight and proportion of redundant data, with the data compression ratio controlled at 30%-50% while ensuring the integrity of core parameters. The processed lightweight data needs to meet the requirements of subsequent modules for data accuracy and transmission efficiency, providing high-quality input data for the Beidou grid coding association module. This process reduces data redundancy, reduces storage and transmission costs, and lays a reliable foundation for the data processing of the entire system. ​​

[0035] Preferably, in the Beidou grid code correlation module, the Beidou grid code space-time asset correlation model correlates BIM data and space-time assets through an encoding mapping formula, which is: wherein, is the generated Beidou grid code, is an encoding generation function, is a unique identifier of BIM data, is a three-dimensional coordinate of a building space, is a time stamp at a coordination time, is a grid precision level; at the same time, the module optimizes the correlation result through a correlation strength calculation model, which is: wherein, is a correlation strength value, , are respectively weights of spatial correlation and time correlation, is a matching degree of the grid code and BIM space information, is a degree of agreement of the grid code and BIM time information, is BIM space information, is BIM time information.

[0036] Specifically, the Beidou grid coding space-time asset correlation model in the Beidou grid coding correlation module realizes the accurate correlation of BIM data and space-time assets and the optimization of the correlation results through a coding mapping formula and a correlation strength calculation model. The technical parameters related to the coding mapping formula include a BIM data unique identifier, a building space three-dimensional coordinate, a time stamp at a coordinated time, and a grid precision level, wherein the three-dimensional coordinate precision reaches a centimeter level, the time stamp is accurate to a millisecond, and the grid precision level is selected according to the size of a building project, and a large building group usually uses a level of 10-15, and a single building detail part uses a level of 20-25, so as to balance the coding length and the spatial resolution. The coding generation function converts the three-dimensional coordinate into a multi-digit grid code based on the Beidou grid coding standard, and embeds the time stamp information at the same time, to form a composite code containing space-time dimensions, and the coding length increases with the increase of the precision level, and the coding length of a 20-level precision is about 20 bits. In the correlation strength calculation model, the spatial correlation and time correlation weight coefficients are set according to the space-time characteristics of the building data, the spatial correlation weight is set between 0.5-0.7, the time correlation weight is set between 0.3-0.5, and the matching degree and the fitting degree are calculated by the overlap of the coding and the BIM space information and the time information, and the value range is 0-1. In implementation, the spatial coordinate and the time information are extracted from the standardized BIM data, the Beidou grid code is generated in combination with the selected grid precision level, and the matching degree of the coding and the space-time information of the BIM data is evaluated through the correlation strength calculation model, when the correlation strength value is lower than 0.6, the coding parameters are adjusted or manually checked until the preset threshold is reached. This process gives the BIM data a unique space-time identifier, breaks the space-time barriers of data at different stages, ensures that the data can be processed based on a unified benchmark in subsequent fusion, indexing and other links, and improves the accuracy and consistency of data management.

[0037] Preferably, in the space-time fusion indexing module, the data space-time fusion and spatial indexing model integrates multi-dimensional data through a space-time fusion formula, and the formula is: wherein, is the fused data, is a space-time fusion weight coefficient, is a spatial dimension data, is a time dimension data, is a space-time tensor product operation, is an attribute dimension data; the spatial indexing construction adopts a hierarchical indexing formula: wherein, is a spatial index set, are respectively the row and column numbers of a plane grid, is a grid unit of the mth row and the nth column, is a spatial range of the BIM data.

[0038] Specifically, the operation of data spatio-temporal fusion and spatial index model in the spatio-temporal fusion index module realizes the effective integration and efficient retrieval of multi-dimensional data through the spatio-temporal fusion formula and the hierarchical index formula. The technical parameters of the spatio-temporal fusion formula include the spatio-temporal fusion weight coefficient, which is set according to the importance of the spatio-temporal information and attribute information in the building data, and the value is between 0.5-0.7, to highlight the core role of the spatio-temporal dimension in the building life cycle management. The spatial dimension data covers the three-dimensional coordinates and topological relationship of building components, the time dimension data includes the time interval and key nodes of each stage, and the attribute dimension data includes material performance, structure parameters, etc. The spatio-temporal tensor product operation realizes the coupling of space and time dimensions through matrix multiplication, forms a spatio-temporal matrix, and then performs weighted fusion with attribute data, so that the fused data contains the calibration information of the three. In the hierarchical index formula, the number of rows and columns of the plane grid is determined according to the spatial range of the building project, and the number of rows and columns can be set to 100-200 for large projects and 50-100 for small projects. The intersection operation of grid units and BIM data space range is realized through the judgment of spatial topological relationship, which ensures that the index can accurately correspond to the spatial distribution of data. In implementation, first, the BIM data with spatio-temporal identifier is dimensionally split, the spatial, temporal and attribute data are extracted and preprocessed respectively, and then the multi-dimensional integration is performed through the spatio-temporal fusion formula to generate a fused data body, ensuring that the coverage rate of each dimension information reaches more than 95%; then the grid units are divided according to the spatial distribution characteristics of the building, the spatial proportion of BIM data in each grid unit is calculated, and the hierarchical index structure is constructed, with the number of index nodes in each level controlled in 100-1000 to ensure the retrieval efficiency. After completing the index construction, the index performance is tested through simulation query, and the query response time of data in any spatio-temporal range is required to be not more than 1 second. This process forms a unified data view, improves the data retrieval speed, provides a fast data acquisition channel for subsequent data integration, analysis and operation, and enhances the processing capacity of the system for complex building data.

[0039] Preferably, in the AEM asset integration module, the data mapping with the Adobe Experience Manager Assets platform adopts a metadata mapping formula: wherein, is the metadata set of the AEM platform, is the mapping function, is the metadata set of the BIM data, the mapping function satisfies and is the metadata key name mapping rule, is the metadata value conversion rule, is the metadata key name, is the metadata value; the data synchronization efficiency is controlled through a synchronization delay model: wherein, is the synchronization delay time, is the data transmission coefficient, is the data size, is the transmission bandwidth, is the conversion complexity coefficient, The complexity of format conversion.

[0040] Specifically, the data mapping and synchronization mechanism between the AEM Asset Integration module and the Adobe Experience Manager Assets platform utilizes metadata mapping formulas and synchronization delay models to achieve standardized data conversion and efficient transmission. The technical parameters associated with the metadata mapping formula include metadata key mapping rules and metadata value conversion rules. The key mapping rules convert Chinese BIM metadata key names into platform-supported English key names based on the platform API documentation, such as converting "component material" to "material." The value conversion rules standardize data formats, such as standardizing the date format to "YYYY-MM-DD" and converting numerical units to international standard units. The mapping function must ensure a one-to-one correspondence between BIM metadata and AEM platform metadata, with a conversion accuracy of at least 99%. The technical parameters of the synchronization delay model include the data transmission coefficient, data size, transmission bandwidth, conversion complexity coefficient, and format conversion complexity. The data transmission coefficient is set according to the network environment and is set between 0.8 and 1.2. The conversion complexity coefficient is related to the complexity of the data format, ranging from 0.3 to 0.5 for simple formats such as .csv and 0.6 to 0.8 for complex formats such as .rvt. Format conversion complexity is quantified by counting the number of conversion steps; the greater the number of steps, the higher the complexity. During implementation, the metadata standards and interface specifications of the AEM platform are analyzed and mapping rules are established. The BIM model files and attribute data in the structured data asset set are then formatted and metadata mapping is completed. The expected synchronization time is then calculated based on the synchronization delay model. Data upload is performed during a period with sufficient network bandwidth. The transmission status is monitored in real time to ensure that the data is fully uploaded to the designated storage path and that the synchronization delay is kept within 5 minutes. After the upload is complete, the storage path, data identifier, and synchronization time are recorded, and an integration report is generated. This process achieves seamless integration of the system and professional asset platforms, ensures the standardization and security of data storage, provides stable storage support for data sharing and full-cycle processing, and improves the professional level of data management.

[0041] Preferably, in the full-cycle BIM processing module, the feature quantification formula is used for stage-by-stage feature extraction: ,in, is the comprehensive characteristic value of the life cycle stage per unit time, is the weight of the p-th feature, is the quantized value of the p-th feature in the stage; the data correlation analysis is calculated by a correlation degree calculation model, and the expression is: wherein, is the correlation degree of the BIM data of the i-th stage and the j-th stage, is the k-th parameter value of the i-th stage, is the parameter mean value of the i-th stage, is the k-th parameter value of the j-th stage, is the parameter mean value of the j-th stage, is the number of parameters.

[0042] Specifically, the implementation of the phased feature extraction and data correlation analysis in the whole-cycle BIM processing module mines the internal relationship of the data of each stage of the building life cycle through the feature quantization formula and the correlation degree calculation model. The technical parameters of the feature quantization formula include the weights of the features of each stage, and the weights of the core features such as the component size and the material consumption in the design stage are 0.6-0.8, the weights of the progress deviation and the resource consumption in the construction stage are 0.5-0.7, and the weights of the equipment failure rate and the energy consumption index in the operation and maintenance stage are between 0.4-0.6, so as to ensure the key features. The feature quantization value is obtained by standardizing the original data to the interval of 0-1, so that features of different magnitudes can be weighted and summed, and the comprehensive feature value reflects the overall characteristics of the stage. In the correlation degree calculation model, the number of parameters is determined according to the feature dimension of each stage, and the design and construction stages contain 20-30 calibration parameters. The parameter values are standardized to eliminate the dimension influence, and the arithmetic mean method is used for mean value calculation to ensure that the correlation degree result is between-1 and 1. A positive value indicates a positive correlation, a negative value indicates a negative correlation, and the greater the absolute value, the stronger the correlation. In implementation, the BIM data of each stage is called from the AEM platform, the calibration parameters are extracted according to the preset feature index system, and the standardized parameters are substituted into the feature quantization formula to calculate the comprehensive feature value of each stage. Then, the corresponding parameters are selected for cross-stage correlation analysis, and the correlation degree value is obtained by substituting the correlation degree calculation model. When the absolute value of the correlation degree is greater than 0.5, it is determined that there is a significant correlation, and the correlation relationship and strength are recorded. According to the analysis results, a whole-cycle data correlation graph is constructed, which contains key feature parameters, correlation strength and influence path of each stage, and the integrity of the graph is verified to ensure that the main stages and key features are covered. This process reveals the internal rules of the building life cycle data, provides data support for discovering potential problems in each stage and optimizing decisions, and promotes the refinement and intelligentization of building management.

[0043] Preferably, the spatio-temporal fusion index module comprises three units: a spatio-temporal data registration unit, a multi-dimensional fusion unit, and a spatial index construction unit; the spatio-temporal data registration unit receives the BIM data assets with spatio-temporal identifiers transmitted by the Beidou grid code association module, extracts the timestamp and spatial coordinate information in the data, adjusts the data with reference differences to a unified spatio-temporal coordinate system through comparison of the spatio-temporal references of different data, and forms a data set with consistent spatio-temporal references; the multi-dimensional fusion unit calls the data spatio-temporal fusion and spatial index model, dimensionally associates the registered spatial data, time series data, and attribute data, integrates the scattered single-dimensional data into multi-dimensional data volumes containing spatio-temporal attributes through the establishment of a spatio-temporal attribute association matrix; and the spatial index construction unit divides grid units according to the building space distribution characteristics based on the fused multi-dimensional data volumes, calculates the spatial proportion of each BIM data asset in the grid units, generates an index table containing the correspondence relationship between the data identifiers and the grid units, stores the index table, and associates it to the multi-dimensional data volumes.

[0044] Specifically, the three units of the spatio-temporal fusion index module are described, focusing on the accurate registration of data in the spatio-temporal dimension, multi-dimensional fusion and efficient index construction, aiming to provide structured and easily searchable data sets for subsequent data processing. The technical parameters of the spatio-temporal data registration unit include the spatio-temporal reference difference threshold, the time reference difference needs to be controlled within 1 second, the spatial coordinate reference difference does not exceed 5 centimeters, by comparing the time stamps and spatial coordinate systems of different data, the data with deviation is adjusted to the unified UTC time and WGS84 coordinate system, to ensure the consistency of the data in the spatio-temporal reference, the data before and after adjustment needs to be recorded, the deviation correction accuracy needs to reach 100%. The calibration parameters of the multi-dimensional fusion unit include the dimension of the spatio-temporal attribute association matrix, the number of rows of the matrix corresponds to the amount of data samples, the number of columns covers all feature items in the spatial, temporal and attribute dimensions, the dimension number is between 50-100, through matrix operation, single-dimensional data is associated and integrated, the data information retention rate in the fusion process is not less than 98%, to ensure that no calibration information is lost. The parameters of the spatial index construction unit involve the size of the grid unit, according to the building space scale setting, the grid side length of large buildings can be set to 5-10 meters, and the grid side length of small buildings can be set to 1-3 meters, when calculating the spatial proportion of each BIM data asset in the grid unit, the volume proportion or area proportion calculation method is adopted, the precision is retained to two decimal places, the generated index table needs to contain data unique identifier, belonging grid unit number and data storage address, the query response time of the index table needs to be controlled within 0.5 seconds. In implementation, the spatio-temporal data registration unit first receives BIM data with spatio-temporal identifier, extracts and compares spatio-temporal information, and converts data with inconsistent reference; the multi-dimensional fusion unit constructs an association matrix based on the registered data to complete multi-dimensional integration; the spatial index construction unit divides the grid and calculates the proportion to generate the index table associated with the data body. This process eliminates the spatio-temporal reference difference of data, realizes the organic fusion of multi-dimensional data, improves the data retrieval speed through efficient index, and provides a reliable data basis for data integration and analysis.

[0045] Preferably, the AEM asset integration module includes 4 units: platform interface adaptation unit, data format conversion unit, metadata mapping unit, asset synchronization unit; the platform interface adaptation unit parses the API document of the Adobe Experience Manager Assets platform, generates a calling function conforming to the interface specification, and establishes a communication connection between the system and the platform; the data format conversion unit reads the structured data asset set output by the space-time fusion index module, converts the data into the corresponding format according to the format type supported by the platform, while retaining the spatial topological relationship of the data; the metadata mapping unit extracts the original metadata in the BIM data, refers to the platform metadata standard, establishes the mapping relationship of the metadata fields, and converts the original metadata into platform-identifiable metadata; the asset synchronization unit uploads the converted data and the mapped metadata to the Adobe Experience Manager Assets platform by using the calling function generated by the platform interface adaptation unit, records the upload path and feeds back to the whole-cycle BIM processing module.

[0046] Specifically, the core of the four units of the AEM asset integration module is to achieve seamless integration between the system and the Adobe ExperienceManager Assets platform, ensuring the standardized storage and efficient synchronization of BIM data assets. The technical parameters of the platform interface adaptation unit include the interface call success rate, which must reach 100%. By parsing the request format, parameter requirements and return value specifications in the platform API document, a standard-compliant call function is generated, supporting HTTP / HTTPS protocols, and the timeout period is set to 30 seconds to ensure a stable and reliable communication connection. The calibration parameters of the data format conversion unit include the format conversion accuracy rate, which must be no less than 99%. The supported BIM data formats include .dwg, .rvt, .ifc, etc. When converting to a platform-compatible format, the accuracy error of the geometric figures must be kept within 0.1 mm, and the spatial topology relationship must be 100% complete to avoid data distortion. The metadata mapping unit's parameters involve a metadata field matching rate of at least 95%. Based on platform metadata standards, a mapping table between BIM metadata and platform metadata is established, including field names, data types, and length limits to ensure complete metadata mapping. For example, "concrete strength grade" is mapped to "concrete_strength." The data type is uniformly string, with a maximum length of 50 characters. The asset synchronization unit's parameters include synchronization success rate and synchronization delay. The success rate must be 100%, and the delay must be within 5 minutes. Data is uploaded by calling a function generated by the adapter unit, with real-time monitoring of upload progress. Failures are automatically retried, up to three times. After the upload is complete, the storage path, data hash value, and synchronization time are recorded to form a complete synchronization log. During implementation, the interface adapter unit establishes a communication connection, the data format conversion unit processes the data format, the metadata mapping unit completes the metadata conversion, and the asset synchronization unit uploads the data and provides feedback. This process ensures the standardized integration of BIM data assets into the professional platform, ensuring the security and consistency of data storage and providing stable storage support for data sharing and end-of-life management.

[0047] Preferably, the full-cycle BIM processing module includes three units: a phased data extraction unit, a feature association analysis unit, and a full-cycle graph generation unit; the phased data extraction unit extracts the BIM data of the corresponding stage from the storage path fed back by the AEM asset integration module according to the stage division of the building's full life cycle, and screens out the pre-calibrated parameters of different stages; the feature association analysis unit compares the extracted pre-calibrated parameters of different stages, identifies the causal relationship and dependency relationship between the parameters of different stages, calculates the correlation degree of parameter changes, and forms feature association rules between stages; the full-cycle graph generation unit constructs a full-cycle data association graph with stages as nodes and parameter associations as edges based on the association rules obtained by the feature association analysis unit, marks the spatiotemporal attributes of each parameter in the graph, and transmits the graph to the data asset operation module.

[0048] Specifically, the three units of the whole-cycle BIM processing module are used to mine the characteristics and correlation of BIM data in each stage of the building life cycle, and construct a complete data correlation atlas. The technical parameters of the staged data extraction unit include the calibration parameter extraction coverage, which needs to reach more than 90%. According to the stage division of the building life cycle (design, construction, operation and maintenance, etc.), the data of the corresponding stage is extracted from the storage path. The calibration parameters include the component size in the design stage, the material consumption in the construction stage, the operation parameter of the equipment in the operation and maintenance stage, and the fault record. The accuracy rate of parameter extraction needs to be not less than 99%, which ensures the reliability of data. The calibration parameters of the feature correlation analysis unit include the correlation rule confidence, which needs to reach more than 80%. By comparing the calibration parameters in different stages, the statistical analysis method is used to identify the cause-effect relationship and the dependency relationship. When calculating the correlation degree, the correlation coefficient method is used, and the value range is between-1 and 1. The greater the absolute value is, the stronger the correlation is. For example, the correlation coefficient between the concrete strength in the construction stage and the strength standard in the design stage needs to be greater than 0.8. The parameters of the whole-cycle atlas generation unit include the atlas node coverage rate and the edge accuracy rate. The nodes need to cover all stages and calibration parameters, and the coverage rate is 100%. The edge accuracy rate needs to be more than 95%. The stages are used as nodes, and the parameter correlation is used as edges. The weight of the edge represents the correlation strength, and different line thicknesses are used to represent it. At the same time, the space-time attributes (such as time stamp and Beidou grid code) of each parameter are marked. The atlas is stored in a graph database, which supports the add, delete, modify and query operations of nodes and edges. The query response time is not more than 1 second. In implementation, the staged data extraction unit extracts the calibration parameters in each stage, the feature correlation analysis unit analyzes the correlation, and the whole-cycle atlas generation unit constructs and transmits the atlas. This process reveals the internal relationship of the building life cycle data, provides data support for decision optimization in each stage, and promotes the refinement and intelligentization of building management.

[0049] The data space fusion and space index model of the application is an important technical means to realize multi-dimensional data integration and efficient retrieval. It is a model that deeply fuses BIM data with time, space and attribute dimensions and constructs an efficient space index. In the implementation process, the data is first preprocessed, the time, space and attribute dimension information is combed, the three are weighted and fused through a space-time fusion formula, a fused data body containing multi-dimensional information is formed, and the coverage rate of each dimension information is ensured to be more than 95%; then a hierarchical index structure is adopted, the Beidou grid coding precision level is used as the basis for layering, and according to the data space distribution density, a sub-region is divided in each level, an index node is constructed for each sub-region, and information such as data identifier, space-time range and storage location is stored. The role of the model is to form a unified data view, improve data retrieval and access efficiency, and enable the system to quickly locate BIM data in a specific space-time range. The data space fusion and space index model provides a convenient data acquisition channel for data integration, analysis and operation, enhances the system's processing capacity for complex building data, and helps to more comprehensively and efficiently mine data value.

[0050] The Adobe Experience Manager Assets platform of the application is a professional platform for centralized storage and management of BIM data assets. It is a powerful digital asset management platform launched by Adobe, which can support storage, management, distribution and sharing of files in multiple formats. In the implementation mode of the application, the AEM asset integration module first analyzes the API interface specification and data storage requirements of the platform, establishes a communication connection, converts the BIM model files in the structured data asset into a platform compatible format, maps and converts the BIM metadata according to the platform standard, uploads the converted data to the specified storage path through the platform API, monitors the transmission status in real time, ensures complete synchronization of data, and records the storage path and other information to feedback to the relevant modules. The role of the platform is to provide a stable and safe storage environment, realize centralized storage and standardized management of BIM data assets. Through the powerful functions of the professional platform, the Adobe Experience Manager Assets platform solves the problem of scattered data storage, facilitates data sharing, access and subsequent processing, provides reliable storage support for efficient operation of building full life cycle data assets, and improves the professional level of data management.

[0051] As shown in Figure 2 , the BIM data asset sedimentation and operation management system for the whole life cycle of building, the system runs includes: First, the data asset operation module receives the whole cycle data correlation graph transmitted by the whole cycle BIM processing module, parses the BIM data identifier, stage information and correlation in the graph, and establishes a mapping index of the data asset and the correlation graph; Second step, according to the parsed stage information, the data assets are classified according to the stage division standard of the whole life cycle of the building, and an independent storage area is allocated for each type of data assets, and the storage format corresponding to the stage characteristics is set; Third step, based on the correlation and importance of data assets, formulate hierarchical access permission rules, embed the rules into the access control module, and check the access request of different user roles; Fourth step, through the timed monitoring of the update state of data assets in the Adobe Experience Manager Assets platform, the identification and content of the updated data are obtained, and the update mechanism of the data asset operation module is triggered; Fifth step, call the building multi-source data conflict resolution and lightweight algorithm to process the updated data, compare the processed data with the original data assets, and update the corresponding correlation and storage path in the correlation graph; Sixth step, record the classification results, access logs and update records of data assets, generate operation reports, store the reports in the system log library, and feed back the updated correlation graph and data asset state to the multi-source data conflict resolution module, forming a closed loop process of data asset operation.

[0052] The BIM data asset sedimentation and operation management system for the whole life cycle of the building. Through the collaborative operation of the six modules, a BIM data asset management closed loop throughout the whole life cycle of the building is formed, which has the advantages of being able to overcome the shortcomings in the background technology. The functions of each module are clear and closely connected, from data reception, processing, correlation, fusion to integration, analysis and operation, a complete management process is constructed, which provides comprehensive support for the effective sedimentation and efficient operation of BIM data assets.

[0053] In view of the shortcomings of weak multi-source data conflict resolution ability and low integration efficiency in the prior art, the multi-source data conflict resolution module plays a key role. It uses the building multi-source data conflict resolution and lightweight algorithm to accurately identify and resolve conflicts between BIM data and heterogeneous data from different stages and different sources, and through lightweight processing to simplify the data volume, greatly improve the data integration efficiency, and form a unified and standardized asset data set, laying a solid foundation for subsequent processing.

[0054] For the problems of insufficient spatio-temporal association, scattered storage and chaotic access of data assets, multiple modules of the system work collaboratively. The Beidou grid code association module realizes the accurate spatio-temporal association of data and building entities through a correlation model, and gives the data clear spatio-temporal attributes; the spatio-temporal fusion index module constructs a spatial index and optimizes data retrieval; the AEM asset integration module is deeply integrated with professional platforms, solving the problem of scattered storage; the data asset operation module regulates data access and update through classified storage, access control and dynamic update. These modules work collaboratively, effectively regulating data management, supporting efficient operation of data assets in the whole life cycle, releasing data value, and providing strong support for fine management and decision optimization of buildings.

[0055] In the description of the present application, it should be noted that unless otherwise explicitly specified and limited, the terms "arrangement", "installation", "connection", "link", "fixing" should be understood broadly, for example, can be fixed connection, can also be detachable connection, or integrally connected; can be mechanical connection, can also be electrical connection; can be directly connected, can also be indirectly connected through an intermediate medium, can be internal communication of two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0056] Although the embodiments of the present application have been shown and described, it can be understood by those skilled in the art that various equivalent changes, modifications, replacements and variations of the embodiments can be made without departing from the principles and spirits of the present application, and the scope of the present application is defined by the appended claims and their equivalent scope.

Claims

1. BIM data asset accumulation and operation management system for the entire life cycle of buildings, characterized by: include: Multi-source data conflict resolution module, Beidou grid coding association module, spatiotemporal fusion index module, AEM asset integration module, full-cycle BIM processing module, data asset operation module; among them, the multi-source data conflict resolution module receives BIM data and associated heterogeneous data in the building design, construction, and operation and maintenance stages, identifies and resolves conflicts through the building multi-source data conflict resolution and lightweight algorithm, and then transmits the processed data to the Beidou grid coding association module; the Beidou grid coding association module calls the Beidou grid coding spatiotemporal asset association model to perform spatiotemporal encoding on the received data, generates BIM data assets with spatiotemporal identification and transmits them to the spatiotemporal fusion index module; the spatiotemporal fusion index module uses data spatiotemporal fusion and spatial index models to perform spatiotemporal dimension fusion and spatial index construction on the received data, forming a structured data asset set and pushing it to the AEM asset integration module; the AEM asset integration module and Adobe Experience Manager The Assets platform establishes a data interaction channel, converts and maps the structured data asset set in accordance with the platform interface specifications, synchronizes it to the platform storage, and feeds back the storage path information to the full-cycle BIM processing module; the full-cycle BIM processing module performs phased feature extraction and association analysis on the data assets pointed to by the storage path based on the various parameters of the BIM data of the entire life cycle of the building, generates a full-cycle data association map and transmits it to the data asset operation module; the data asset operation module performs classified storage, access control and dynamic update operations on the data assets based on the received full-cycle data association map, forming a closed-loop management process.

2. The BIM data asset sedimentation and operation management system for the entire building life cycle according to claim 1 is characterized in that: In the multi-source data conflict resolution module, the building multi-source data conflict resolution and lightweight algorithm identifies data conflicts by constructing a conflict measurement model. The model formula is: ,in, represents the conflict degree between the i-th BIM data and the j-th heterogeneous data, are the weight coefficients of attribute value difference, time difference, and spatial difference, respectively. is the attribute value of BIM data, is the attribute value of heterogeneous data, Data collection time and The time distance function, Data space location and The spatial similarity function of ; after conflict identification, the lightweight processing formula is adopted: ,in, is the amount of data after lightweighting, is the original data volume, is the weight of the k-th redundant data, is the proportion of redundant data in the kth item.

3. The BIM data asset accumulation and operation management system for the entire building life cycle according to claim 1 is characterized in that: In the BeiDou grid coding association module, the BeiDou grid coding spatiotemporal asset association model associates BIM data with spatiotemporal assets through a coding mapping formula, which is: ,in, Code the generated BeiDou grid. is the encoding generation function, It is the unique identifier of BIM data. is the three-dimensional coordinate of the building space, is the coordinated time timestamp, is the grid accuracy level; at the same time, the module optimizes the association results through the association strength calculation model, the formula is: ,in, is the association strength value, 、 are the weights of spatial association and temporal association respectively, is the matching degree between grid code and BIM space information, is the consistency between the grid code and BIM time information, For BIM space information, It is BIM time information.

4. The BIM data asset accumulation and operation management system for the entire building life cycle according to claim 1 is characterized in that: In the spatiotemporal fusion index module, the data spatiotemporal fusion and spatial index model perform multi-dimensional data integration through the spatiotemporal fusion formula, which is: ,in, is the fused data, is the spatiotemporal fusion weight coefficient, is the spatial dimension data, is the time dimension data, is the space-time tensor product operation, It is attribute dimension data; the spatial index is constructed using the hierarchical index formula: ,in, is a spatial index set, are the number of rows and columns of the plane grid, is the grid cell at row m and column n, The spatial extent of the BIM data.

5. The BIM data asset accumulation and operation management system for the entire building life cycle according to claim 1 is characterized in that: In the AEM Assets integration module, data mapping with the Adobe Experience Manager Assets platform uses the metadata mapping formula: ,in, AEM platform metadata collection. is the mapping function, is the metadata set of BIM data, and the mapping function satisfies and For metadata key name mapping rules, is the metadata value conversion rule, is the metadata key name, is the value of metadata; data synchronization efficiency is controlled by the synchronization delay model: ,in, is the synchronization delay time, is the data transmission coefficient, is the data size, is the transmission bandwidth, is the conversion complexity coefficient, The complexity of format conversion.

6. The BIM data asset accumulation and operation management system for the entire building life cycle according to claim 1 is characterized in that: In the full-cycle BIM processing module, the feature quantification formula is used for stage-by-stage feature extraction: ,in, is the comprehensive characteristic value of the life cycle stage per unit time, is the weight of the p-th feature, is the quantitative value of the p-th feature at this stage; data association analysis is calculated through the association calculation model, the expression is: ,in, is the correlation between the BIM data of stage i and stage j, is the kth parameter value in the i-th stage, is the mean parameter value of stage i, is the kth parameter value in the jth stage, is the mean value of the parameters in the jth stage, is the number of parameters.

7. The BIM data asset accumulation and operation management system for the entire building life cycle according to claim 1 is characterized in that: The spatiotemporal fusion index module includes three units: a spatiotemporal data alignment unit, a multi-dimensional fusion unit, and a spatial index construction unit; the spatiotemporal data alignment unit receives BIM data assets with spatiotemporal identifiers transmitted by the Beidou grid coding association module, extracts the timestamp and spatial coordinate information in the data, and adjusts the data with benchmark differences to a unified spatiotemporal coordinate system by comparing the spatiotemporal benchmarks of different data to form a data set with consistent spatiotemporal benchmarks; the multi-dimensional fusion unit calls the data spatiotemporal fusion and spatial index model to dimensionally associate the aligned spatial data, time series data, and attribute data, and integrates the scattered single-dimensional data into a multi-dimensional data body containing spatiotemporal attributes by establishing a spatiotemporal attribute association matrix; the spatial index construction unit divides the grid units according to the building space distribution characteristics based on the fused multi-dimensional data body, calculates the spatial proportion of each BIM data asset in the grid unit, generates an index table containing the correspondence between data identifiers and grid units, stores the index table, and associates it to the multi-dimensional data body.

8. The BIM data asset accumulation and operation management system for the entire building life cycle according to claim 1 is characterized in that: The AEM asset integration module includes four units: a platform interface adapter unit, a data format conversion unit, a metadata mapping unit, and an asset synchronization unit. The platform interface adapter unit parses the API documentation of the Adobe Experience Manager Assets platform, generates call functions that comply with the interface specifications, and establishes a communication connection between the system and the platform. The data format conversion unit reads the structured data asset set output by the spatiotemporal fusion index module and converts the data into the corresponding format based on the format type supported by the platform, while preserving the spatial topology of the data. The metadata mapping unit extracts the original metadata from the BIM data, establishes a mapping relationship between metadata fields based on the platform metadata standard, and converts the original metadata into metadata that can be recognized by the platform; the asset synchronization unit uses the call function generated by the platform interface adapter unit to upload the converted data and mapped metadata to the Adobe Experience Manager Assets platform, record the upload path, and feed it back to the full-cycle BIM processing module.

9. The BIM data asset accumulation and operation management system for the entire building life cycle according to claim 1 is characterized in that: The full-cycle BIM processing module includes three units: a phased data extraction unit, a feature correlation analysis unit, and a full-cycle graph generation unit. The phased data extraction unit extracts the BIM data of the corresponding phase from the storage path fed back by the AEM asset integration module based on the phases of the building life cycle, and screens out pre-calibrated parameters for different phases. The feature association analysis unit compares the pre-calibrated parameters extracted from different stages, identifies the causal and dependency relationships between parameters in different stages, calculates the correlation degree of parameter changes, and forms feature association rules between stages; the full-cycle graph generation unit constructs a full-cycle data association graph with stages as nodes and parameter associations as edges based on the association rules obtained by the feature association analysis unit, marks the spatiotemporal attributes of each parameter in the graph, and transmits the graph to the data asset operation module.

10. The BIM data asset accumulation and operation management system for the entire building life cycle according to any one of claims 1 to 9, characterized in that: The system operation includes: In the first step, the data asset operation module receives the full-cycle data association graph transmitted by the full-cycle BIM processing module, parses the BIM data identifiers, stage information, and association relationships contained in the graph, and establishes a mapping index between data assets and the association graph; The second step is to classify data assets based on the stage information obtained from the analysis and the stage classification standards of the building life cycle. An independent storage area is allocated for each type of data asset, and a storage format corresponding to the stage characteristics is set. The third step is to develop hierarchical access permission rules based on the relationships and importance of data assets. These rules are embedded in the access control module to verify the permissions of access requests from different user roles. The fourth step is to regularly monitor the update status of data assets in the Adobe Experience Manager Assets platform, obtain the identifier and content of the updated data, and trigger the update mechanism of the data asset operation module; The fifth step is to use the building multi-source data conflict resolution and lightweight algorithm to process the updated data, compare the processed data with the original data assets, and update the corresponding association relationships and storage paths in the association map; The sixth step is to record the classification results, access logs and update records of data assets, generate an operation report, store the report in the system log library, and at the same time feed back the updated association map and data asset status to the multi-source data conflict resolution module to form a closed-loop process for data asset operation.

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