BIM data asset depositing and operation management system for building full life cycle

Abstract

The application discloses a BIM data asset precipitation and operation management system for the whole life cycle of a building, which comprises six modules, namely, multi-source data conflict resolution, Beidou grid coding correlation, time-space fusion index, AEM asset integration, whole-cycle BIM processing and data asset operation. The system utilizes multi-source data conflict resolution and lightweight algorithm, Beidou grid coding time-space asset correlation model and data time-space fusion and space index model, and combines with the Adobe Experience Manager Assets platform to process the BIM data of the whole life cycle of the building. Through module cooperation, multi-source data conflicts are resolved, time-space correlation and fusion of data are realized, the data are integrated into a professional platform, a whole-cycle data correlation graph is formed and operation is carried out. The system overcomes the problems of low data integration efficiency and insufficient time-space correlation in the prior art, realizes effective precipitation and efficient operation of BIM data assets, and provides support for fine management of buildings.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of BIM data asset management, and particularly relates 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, and lacks a systematic sedimentation and operation mechanism throughout the whole life cycle, resulting in that the value of the data is difficult to fully release, and the demand of modern buildings for data-driven throughout the whole process cannot be met.

[0003] The prior art has obvious deficiencies in processing BIM data throughout the whole life cycle of a building. On the one hand, the multi-source data conflict resolution capability is weak, and BIM data from different stages and different sources often conflicts due to format differences, inconsistent space-time benchmarks, etc., and lacks effective lightweight processing means, resulting in low data integration efficiency and difficulty in forming a unified asset data set. On the other hand, there are defects in the space-time association and operation management of data assets, which cannot realize the dynamic association of data and building entities through accurate space-time coding, and lack deep integration mechanism with professional asset platforms, resulting in scattered data storage and chaotic access control, and 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 that the BIM data asset sedimentation and operation management system for the whole life cycle of a building comprises:

[0006] 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 whole cycle BIM processing module, and a data asset operation module.

[0007] 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 full-cycle BIM processing module; the full-cycle BIM processing module extracts and analyzes the data assets in stages according to the BIM data parameters in the building life cycle, generates a full-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 full-cycle data association graph, and forms a closed-loop management process.

[0008] 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 i-th BIM data and the j-th 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 and 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 k-th redundant data,

[0009] 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.

[0010] 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.

[0011] 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.

[0012] Further, in the full-cycle BIM processing module, the phased feature extraction uses a feature quantization formula: wherein, is the comprehensive feature value of the life cycle phase per unit time, is the weight of the pth feature, is the 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.

[0013] 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, and performs dimensional correlation on the registered spatial data, time series data, and attribute data, 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.

[0014] 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 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.

[0015] 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 feedback 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 with 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.

[0016] The BIM data asset sedimentation and operation management system for the whole life cycle of a building, which runs includes:

[0017] The first step, 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;

[0018] The second step, 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;

[0019] 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;

[0020] Fourth step, through the timed monitoring of the update state of the 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;

[0021] 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;

[0022] Sixth step, record the classification results, access logs and update records of the 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.

[0023] Beneficial effects: the present application proposes a BIM data asset sedimentation and operation management system for the whole life cycle of building, which uses the building multi-source data conflict resolution and lightweight algorithm to accurately identify and resolve conflicts of data from different stages and sources, and performs lightweight processing, thereby improving data integration efficiency and overcoming the shortcomings of weak multi-source data conflict resolution capability and low integration efficiency of the prior art. The Beidou grid coding correlation module realizes accurate spatio-temporal correlation of data and building entities through the Beidou grid coding spatio-temporal asset correlation model; the spatio-temporal fusion index module constructs a spatial index; the AEM asset integration module is deeply integrated with a professional platform; and the data asset operation module realizes classified storage, access control and dynamic update, thereby solving the problems of insufficient spatio-temporal correlation of data assets, scattered storage and chaotic access, supporting efficient operation of whole life cycle data assets, fully releasing data value and meeting the whole process data driven demand. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 The system unit of the present application is shown in the figure;

[0025] Figure 2 The system running flowchart of the present application is shown in the figure. DETAILED DESCRIPTION

[0026] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict, and the present application will be further described in detail in combination with the drawings and specific embodiments.

[0027] As Figure 1As shown, the building lifecycle-oriented BIM data asset deposition and operation management system comprises: a multi-source data conflict resolution module, a Beidou grid coding correlation module, a space-time fusion index module, an AEM asset integration module, a full-cycle BIM processing module, and a data asset operation module.

[0028] 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 building multi-source data conflict resolution and lightweight algorithms, and transmits the processed data to the Beidou grid coding correlation module.

[0029] The multi-source data conflict resolution module is the first step in processing building lifecycle BIM data, 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 maintenance, and various heterogeneous data (such as geographic information data and equipment monitoring data). It provides high-quality basic data for subsequent data correlation and fusion processing. By effectively resolving data conflicts and performing lightweight processing, it can reduce data storage pressure, improve data transmission efficiency, and ensure the accuracy and efficiency of subsequent module processing.

[0030] The specific implementation process of the module is as follows: first, receive multi-source data from the building design stage, such as BIM model data (containing 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), construction stage progress data (such as the planned start time and actual completion time of a certain sub-item engineering), and operation and maintenance stage equipment operation data (such as the operating temperature range of air conditioning equipment is 18-26℃, and the energy consumption data unit is kWh), etc. 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 in the BIM data as March 10, 2024, while the arrival time in the equipment procurement record is March 15, 2024, which is a time conflict. For the identified conflict data, modify and integrate according to the preset priority rules (such as actual construction data is prior to design model data). Subsequently, start the lightweight processing flow, and remove and simplify the redundant geometric information (such as repeated component models) and unnecessary detail parameters (such as decorative component texture data that has no effect on overall analysis) in the BIM model, control the data compression ratio to between 30%-50%, for example, reduce the BIM model data from 100MB to 40-70MB after lightweight processing. After processing, the integrated standardized data is transmitted to the Beidou grid coding association module, and data processing logs are recorded, including the number of conflicts, processing methods, data size before and after lightweight processing, etc. For subsequent tracing and verification.

[0031] The Beidou grid coding association module calls the Beidou grid coding space-time asset association 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;

[0032] The technical parameters of the Beidou grid coding association module include the accuracy level of grid coding (such as 1st to 32nd, different levels correspond to different spatial resolutions), response time of coding generation, accuracy of data association, etc. The module assigns a unique space-time identifier to the preprocessed BIM data through Beidou grid coding technology, realizes the precise association of BIM data and building entities in time and space dimensions, breaks down the time and space barriers between different stage data, 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.

[0033] The specific implementation process of the module is as follows: receiving the 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 the building components, with an accuracy of centimeters, such as the bottom center point coordinates of a column X = 35200mm, Y = 28600mm, Z = 0mm) and time information (such as data generation time, corresponding building stage time node, accurate to seconds, such as May 20, 2024 14:30:25) in the data. According to the scale and precision requirements of the building project, select the appropriate Beidou grid coding accuracy level, for large building groups, you can choose 10-15 level precision (corresponding to a spatial resolution of about 10-100 meters), for the details of the single building, you can choose 20-25 level precision (corresponding to a spatial resolution of about 0.1-1 meter). Call the Beidou grid coding space-time asset association model, convert the extracted spatial coordinates into corresponding Beidou grid codes, and the coding length varies with the accuracy level, such as the coding length of 20 level precision is set to about 20 bits. At the same time, embed the time information into the coding 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 asset with space-time identifier is transmitted to the space-time fusion index module, and the coding mapping relationship table is stored to record the correspondence between BIM data identifier and Beidou grid code, so as to quickly call for subsequent data query and correlation analysis.

[0034] The space-time fusion index module adopts the data space-time fusion and spatial index model to perform space-time dimension fusion and spatial index construction on the received data, and forms a structured data asset set which is then pushed to the AEM asset integration module;

[0035] The technical parameters of the space-time fusion index module include the dimension coverage rate of space-time fusion, the query response time of spatial index, and the stability of index structure. The module deeply fuses the BIM data asset with space-time identifier in time, space and attribute dimensions, constructs a unified data view, and establishes an efficient spatial index to improve the retrieval and access efficiency of data, so that the system can quickly locate and extract BIM data within a specific space-time range, providing a convenient data acquisition channel for subsequent data integration, analysis and operation.

[0036] The specific implementation process of the module is as follows: receiving the BIM data asset with space-time identification transmitted by the Beidou grid coding association module, first performing data preprocessing, and combing the time dimension information (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) in the data, 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 space fusion model, connect the BIM data of different stages in time sequence, form a continuous data chain in time dimension; in the spatial dimension, according to the spatial correlation of Beidou grid coding, the BIM data in the adjacent grid is aggregated, and the spatial topological relationship is constructed; in the attribute dimension, the attribute parameters of the same component or associated components are associated and integrated, forming a fusion data body containing multi-dimensional information, ensuring that the coverage rate of the fused data set in time, space and attribute dimensions reaches more than 95%. Then, start to build spatial index, adopt hierarchical index structure, first divide layers based on the precision level of Beidou grid coding, and in each level, according to the spatial distribution density of data, further divide the grid into sub-regions, each sub-region corresponds to an index node. Store the identification, space-time range and storage location of BIM data in each index node, and the number of index nodes is dynamically adjusted according to the data size, controlled between 100-1000 in each level. After completing the index construction, test the index performance to ensure that the response time is not more than 1 second when querying data in any space-time 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, so as to maintain and optimize the index in the future.

[0037] 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 to the platform storage and feeds back the storage path information to the whole-cycle BIM processing module.

[0038] The technical parameters of the AEM asset integration module include the interface adaptation rate with the Adobe Experience Manager Assets platform, the accuracy rate of data format conversion, the delay time of data synchronization, etc. The module realizes the seamless connection between the system and the professional asset platform, converts and integrates the structured BIM data asset set according to the platform specification, realizes the centralized storage and standardized management of BIM data assets through the powerful storage, management and distribution capability of the platform, and provides stable storage support for data sharing, access and subsequent whole-cycle processing.

[0039] The specific implementation process of the module is as follows: first, a communication connection is established with the Adobe Experience Manager Assets platform, the API interface specification and data storage requirements of the platform are parsed, the interface adaptation rate needs to reach 100%, and it is ensured that the system and the platform can normally interact with each other. Receive the structured data asset set pushed by the spatio-temporal fusion index module, which includes BIM model files (such as.dwg,.rvt format), attribute data table (such as.csv,.xlsx format), spatio-temporal correlation information table, etc. According to the file format and metadata standard supported by the platform, start the data format conversion program, convert the BIM model file to the format compatible with the platform (such as converting the.rvt format to the.ifc format or the.jpg preview picture format), and the geometric accuracy of the model and the integrity of the attribute information need to be maintained during the conversion process, with an accuracy of not less than 99%. For attribute data and spatio-temporal 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 the 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 the complete uploading of the data. After the data synchronization is completed, record the storage path information, data identifier and synchronization time returned by the platform (the synchronization delay time is controlled within 5 minutes), and feed back these information to the whole cycle BIM processing module, and generate an integrated report including the converted data volume, the number of successful items, the failure reason, etc., for the optimization and problem troubleshooting of the subsequent integration process.

[0040] The whole cycle BIM processing module extracts the features of the data assets stored in the storage path according to the BIM data parameters of the whole life cycle of the building, and performs correlation analysis to generate a whole cycle data correlation graph which is transmitted to the data asset operation module;

[0041] The technical parameters of the whole cycle BIM processing module include the coverage rate of the stage feature extraction, the confidence degree of the data correlation analysis, and the integrity of the whole cycle data correlation graph. Based on the stored BIM data assets, the module deeply mines the internal relationship between the data of each stage of the whole life cycle of the building, extracts the key features of each stage, and constructs a whole cycle data correlation graph, which provides data support for understanding the whole process from design to operation of the building, helps to find potential problems and optimization space between stages, and provides basis for decision-making of the whole life cycle of the building.

[0042] 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 asset from the Adobe Experience Manager Assets platform according to the path direction, covering data in various stages such as design, construction and operation, such as component size parameters in the design stage (the span of the beam is 8m, and the cross-sectional moment of inertia is a specific value), progress data in the construction stage (the concrete pouring amount of a floor is 500m³, and the number of construction personnel is 30), equipment failure data in the operation stage (the number of elevator failures is 5 times, and the average maintenance time is 4 hours), etc. According to the stage division of the whole life cycle of the building (design, construction preparation, construction implementation, completion acceptance, operation), the data called is processed in stages, and for each stage, a feature extraction index system is set, 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 in each stage is cleaned and standardized (such as converting energy consumption data in different units to kWh / ㎡), and then using correlation analysis method, the correlation between different stages is calculated, such as analyzing the relationship between component size in the design stage and material consumption in the construction stage, 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 result, a whole cycle data correlation graph is constructed, taking stage as node and feature correlation as edge, which contains key feature parameters in each stage, correlation strength between features and influence path. Finally, the integrity of the graph is verified to ensure that it covers the main stages and key features of the whole life cycle of the building. After passing the verification, the graph is transmitted to the data asset operation module, and the feature data and correlation analysis results in each stage are stored for subsequent graph updating and deep analysis.

[0043] The data asset operation module based on the received whole cycle data correlation graph performs data asset classification storage, access control and dynamic update operation, forming a closed loop management process.

[0044] 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 update, etc. The module systematically manages the whole cycle BIM data correlation graph and the data assets behind it, through classification storage, strict access control and dynamic update, to ensure the security, integrity and timeliness of the data assets, realize the efficient utilization and value maximization of the data assets, and provide reliable data services for all participants in the whole life cycle of the building.

[0045] The specific implementation process of the module is as follows: receiving the whole cycle data association graph transmitted by the whole cycle BIM processing module, analyzing the BIM data identification (such as component ID "beam-123") contained in the graph, the corresponding construction stage (such as "construction implementation stage"), the association relationship (such as the existence of spatial connection relationship with "column-456") and other information. According to the type of data (model data, attribute data, document data, etc.), the stage to which it belongs and the importance, a classification storage strategy is formulated, and the data assets are stored in different storage areas of the system (such as high-speed storage area for storing high-frequency access operation and maintenance data, and archival storage area for storing historical design data). The accuracy of classified 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, and management personnel), access permission rules are set, 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, and the permission rules are embedded in the access control engine of the system to perform real-time verification on user access requests (permission verification pass rate 100%, illegal access interception rate 100%). A dynamic data update mechanism is established to monitor the changes of data assets in the Adobe Experience Manager Assets platform (such as new operation and maintenance records and modified construction data) at regular intervals (such as every hour), and when data updates are detected, the updated data assets are automatically triggered to update the corresponding association relationship in the whole cycle data association graph. At the same time, record all data asset access logs (including access users, access time, operation content) and update records (update time, update content, update personnel), and the log information is saved for not less than 5 years for data tracing and security audit. The storage state, access situation and update frequency of data assets are statistically analyzed at regular intervals (such as every month) to optimize the storage strategy and access permission settings, form a closed-loop management of data asset operation, and ensure that data assets continue to serve various work in the whole life cycle of construction efficiently.

[0046] 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 simplification. 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.

[0047] 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.

[0048] 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, conflict degree of the i-th BIM data and the j-th heterogeneous data, 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 collection 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.

[0049] 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 collection 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, making the conflict degree calculation result between 0 and 1, which is convenient for determining 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 through the lightweight processing formula based on the weight and proportion of redundant data, with the data compression ratio controlled between 30% and 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.

[0050] 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.

[0051] 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, among which the three-dimensional coordinate precision reaches centimeter level, the time stamp is accurate to milliseconds, and the grid precision level is selected according to the size of the building project. A large building group usually uses 10-15 levels, and a single building detail part uses 20-25 levels to balance the coding length and spatial resolution. The coding generation function converts the three-dimensional coordinate into a multi-digit grid code based on the Beidou grid coding standard, while embedding the time stamp information to form a composite code containing space-time dimensions. The coding length increases with the increase of the precision level, and the coding length of the 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, and the time correlation weight is set between 0.3-0.5. 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 time information are extracted from the standardized BIM data, the Beidou grid code is generated combined with the selected grid precision level, and the matching degree of the coding and the BIM data space-time information 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.

[0052] Preferably, in the space-time fusion index module, the data space-time fusion and spatial index model integrates multi-dimensional data through a space-time fusion formula, which is: wherein, is the fused data, is the space-time fusion weight coefficient, is the spatial dimension data, is the time dimension data, is the space-time tensor product operation, is the attribute dimension data; the spatial index construction adopts a hierarchical index formula: wherein, is the spatial index set, are respectively the row and column numbers of the plane grid, is the grid unit of the mth row and nth column, is the spatial range of the BIM data.

[0053] 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 of large projects can be set to 100-200, and the number of rows and columns of small projects is 50-100. The intersection operation of grid unit and BIM data space range is realized through the judgment of spatial topological relationship, to ensure 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 unit is 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, the number of index nodes at each level is 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.

[0054] 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 key name of the metadata, is the value of the metadata; the data synchronization efficiency is controlled through a synchronization delay model: wherein, For synchronization delay time, For data transmission coefficients, For data size, For transmission bandwidth, To convert the complexity coefficients, For format conversion complexity.

[0055] Specifically, the data mapping and synchronization mechanism between the AEM asset integration module and the Adobe Experience Manager Assets platform achieves standardized data conversion and efficient transmission through metadata mapping formulas and synchronization delay models. The technical parameters associated with the metadata mapping formulas include metadata key mapping rules and metadata value conversion rules. The key mapping rules convert Chinese key names in BIM metadata to platform-supported English key names based on the platform's API documentation, such as converting "component material" to "material". The value conversion rules standardize data formats, such as unifying date formats 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 no less than 99%. The technical parameters of the synchronization delay model include 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, ranging from 0.8 to 1.2. The conversion complexity coefficient is related to the complexity of the data format; for simple formats such as .csv, the value is 0.3-0.5, and for complex formats such as .rvt, the value is 0.6-0.8. The format conversion complexity is quantified by the number of conversion steps; the more steps, the higher the complexity. During implementation, firstly, the metadata standards and interface specifications of the AEM platform are parsed, and mapping rules are formulated. Then, the format of the BIM model files and attribute data in the structured data asset set is converted, and the metadata mapping is completed simultaneously. Next, the expected synchronization time is calculated according to the synchronization delay model, and data is uploaded during periods with sufficient network bandwidth. The transmission status is monitored in real time to ensure that the data is completely uploaded to the designated storage path, and the synchronization delay time is controlled within 5 minutes. After the upload is completed, the storage path, data identifier, and synchronization time are recorded, and an integration report is generated. This process enables seamless integration between the system and professional asset platforms, ensuring the standardization and security of data storage, providing stable storage support for data sharing and full-cycle processing, and improving the professional level of data management.

[0056] Preferably, in the full-cycle BIM processing module, the feature extraction in stages adopts a feature quantization formula: ,in, This represents the comprehensive characteristic value of a life cycle stage per unit time. The weight of the p-th feature is... 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.

[0057] 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 comprehensive feature values of each stage are calculated by the feature quantization formula after standardization. Then, the corresponding parameters are selected for cross-stage correlation analysis, and the correlation degree value is obtained by substituting into 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 result, a whole-cycle data correlation graph is constructed, which contains the key feature parameters of each stage, the correlation strength and the influence path, and the integrity of the graph is verified to ensure that the main stages and key features are covered. This process reveals the internal law 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.

[0058] 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.

[0059] 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.

[0060] 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.

[0061] Specifically, the four units of the AEM asset integration module are the core of realizing the seamless connection between the system and the Adobe Experience Manager Assets platform, ensuring the standardized storage and efficient synchronization of BIM data assets. The technical parameters of the platform interface adaptation unit include interface call success rate, which needs to reach 100%. By analyzing the request format, parameter requirements, and return value specifications in the platform API document, the standard-compliant call function is generated, supporting HTTP / HTTPS protocol, with a timeout setting of 30 seconds to ensure stable and reliable communication connection. The calibration parameters of the data format conversion unit include format conversion accuracy, which needs to be no less than 99%. The supported BIM data formats include.dwg,.rvt,.ifc, etc. When converting to platform-compatible formats, the geometric precision error needs to be within 0.1 millimeters, and the spatial topological relationship needs to be complete, avoiding data distortion. The parameters of the metadata mapping unit involve metadata field matching rate, which needs to reach more than 95%. Referring to the platform metadata standards, the mapping relationship table between BIM metadata and platform metadata is established, including field name, data type, length limit, etc., to ensure complete mapping of metadata information, such as mapping "concrete strength grade" to "concrete_strength" and unifying data type to string with a length of no more than 50 characters. The parameters of the asset synchronization unit include synchronization success rate and synchronization delay, with a success rate of 100% and a delay time controlled within 5 minutes. By calling the functions generated by the adaptation unit to upload data, the upload progress is monitored in real time, and automatic retry is performed up to 3 times when failed. After uploading is completed, the storage path, data hash value, and synchronization time are recorded to form a complete synchronization log. In implementation, the interface adaptation unit establishes communication connection, the data format conversion unit processes data format, the metadata mapping unit completes metadata conversion, and the asset synchronization unit uploads data and feeds back information. This process realizes the standardized integration of BIM data assets into professional platforms, ensuring the security and consistency of data storage and providing stable storage support for data sharing and whole-cycle management.

[0062] Preferably, the whole-cycle BIM processing module includes three units: phased data extraction unit, feature correlation analysis unit, and whole-cycle graph generation unit. The phased data extraction unit extracts BIM data of corresponding stages from the storage path feedback by the AEM asset integration module according to the stage division of the building whole life cycle, and screens out pre-calibration parameters of different stages. The feature correlation analysis unit compares the pre-calibration parameters of different stages, identifies the causal and dependent relationships between 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 with 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.

[0063] 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, etc. The accuracy rate of parameter extraction needs to be not less than 99% to ensure 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 uses a graph database for storage, supports the add, delete, modify and query operations of nodes and edges, and 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.

[0064] 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 sorted out, the three are weighted and fused through the space-time fusion formula, and a fused data body containing multi-dimensional information is formed, ensuring that the coverage rate of each dimension information is 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, each layer is divided into sub-regions, and an index node is constructed for each sub-region to store data identification, space-time range and storage location and other information. 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.

[0065] 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 in 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 set into a platform compatible format, and 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 state in real time, ensures data complete synchronization, and records the storage path and other information feedback to the relevant module. 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.

[0066] 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:

[0067] In the first step, 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 a mapping index of the data asset and the correlation graph.

[0068] In the second step, 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, and an independent storage area is allocated for each type of data asset, and a storage format corresponding to the stage characteristics is set;

[0069] In the third step, based on the correlation relationship and importance of the data asset, a hierarchical access permission rule is formulated, the rule is embedded into the access control module, and the access request of different user roles is checked for permission;

[0070] In the fourth step, the update state of the data asset in the Adobe Experience Manager Assets platform is monitored in real time, the identifier and content of the updated data are obtained, and the update mechanism of the data asset operation module is triggered;

[0071] In the fifth step, the building multi-source data conflict resolution and lightweight algorithm is called to process the updated data, and the processed data is compared with the original data asset to update the corresponding correlation relationship and storage path in the correlation graph;

[0072] In the sixth step, the classification results, access logs and update records of the data asset are recorded, an operation report is generated, the report is stored in the system log library, and the updated correlation graph and data asset state are fed back to the multi-source data conflict resolution module, forming a closed-loop process of data asset operation.

[0073] The BIM data asset sedimentation and operation management system for the whole life cycle of building. Through the collaborative operation of the six modules, a BIM data asset management closed loop throughout the whole life cycle of 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.

[0074] In view of the shortcomings of weak multi-source data conflict resolution capability 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 of different stages and different sources, and through lightweight processing to simplify the data volume, greatly improves the data integration efficiency, and forms a unified and standardized asset data set, laying a solid foundation for subsequent processing.

[0075] 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.

[0076] 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.

[0077] 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. A BIM data asset depositing and operation management system for the whole life cycle of a building, characterized in that, Comprise: Multi-source data conflict resolution module, Beidou grid coding correlation module, space-time fusion index module, AEM asset integration module, whole cycle BIM processing module, data asset operation module; Among them, the multi-source data conflict resolution module receives the BIM data and associated heterogeneous data of the building design, construction and operation stage, and transmits the processed data to the Beidou grid coding correlation module after conflict identification and resolution by building multi-source data conflict resolution and lightweight algorithm; The Beidou grid coding correlation module calls the Beidou grid coding 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 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 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 the storage path according to the BIM data parameters of the building life cycle, generates a whole cycle data correlation 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 correlation graph, forming a closed-loop management process.

2. The building lifecycle-oriented BIM data asset sedimentation and operation management system according to claim 1, characterized in that, 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 measurement model, and the model formula is: Wherein, represents the conflict degree of the ith BIM data and the jth heterogeneous data, respectively are the weight coefficients of attribute value difference, time difference and spatial difference, is the attribute value of BIM data, is the attribute value of heterogeneous data, is the data acquisition time and the time distance function of, is the spatial position of data and the spatial similarity function of, After conflict identification, the lightweight processing formula is adopted: Wherein, is the data quantity after lightweight processing, is the original data quantity, is the weight of the kth redundant data, is the proportion of the kth redundant data.

3. The building lifecycle-oriented BIM data asset sedimentation and operation management system according to claim 1, characterized in that, The Beidou grid code correlation module, the Beidou grid code space-time asset correlation model is associated with BIM data and space-time assets through a coding mapping formula, and the formula is: Wherein, is the generated Beidou grid code, is the code generation function, is the unique identifier of the BIM data, is the three-dimensional coordinate of the building space, is the time stamp at the coordination time, is the grid precision level; at the same time, the module optimizes the correlation result through a correlation strength calculation model, and the formula is: Wherein, is the correlation strength value, , are the weights of spatial correlation and time correlation respectively, is the matching degree of the grid code and the BIM space information, is the degree of fit of the grid code and the BIM time information, is the BIM space information, is the BIM time information.

4. The building lifecycle-oriented BIM data asset sedimentation and operation management system according to claim 1, characterized in that, In the space-time fusion index module, the data space-time fusion and the space index model are integrated by a 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 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.

5. The building lifecycle-oriented BIM data asset sedimentation and operation management system according to claim 1, characterized in that, The data mapping with the Adobe Experience Manager Assets platform in the AEM asset integration module adopts a metadata mapping formula: wherein, is a metadata set of the AEM platform, is a mapping function, is a metadata set of the BIM data, and the mapping function satisfies and is a metadata key name mapping rule, is a metadata value conversion rule, is a key name of the metadata, is a value of the metadata; and the data synchronization efficiency is controlled through 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.

6. The building lifecycle-oriented BIM data asset sedimentation and operation management system according to claim 1, characterized in that, In the full-cycle BIM processing module, the phased feature extraction adopts a feature quantization formula: Wherein, is the comprehensive feature value of the life cycle stage per unit time, is the weight of the pth feature, is the quantized value of the pth 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 ith stage and the jth stage, is the kth parameter value of the ith stage, is the average value of the parameters of the ith stage, is the kth parameter value of the jth stage, is the average value of the parameters of the jth stage, is the number of parameters.

7. The building lifecycle-oriented BIM data asset sedimentation and operation management system according to claim 1, characterized in that, The space-time fusion index module includes three units: space-time data registration unit, multi-dimensional fusion unit, and spatial index construction unit; The space-time data registration unit receives the BIM data assets with space-time identifiers transmitted by the Beidou grid coding correlation module, extracts the timestamp and spatial coordinate information in the data, adjusts the data with different reference differences to a unified space-time coordinate system by comparing the space-time reference of different data, and forms a data set with consistent space-time reference; The multi-dimensional fusion unit calls the data space-time fusion and spatial index model to associate the registered spatial data, time series data and attribute data in different dimensions, and integrates the scattered single-dimensional data into multi-dimensional data body containing space-time attributes by establishing a space-time attribute correlation matrix; The spatial index construction unit divides the grid unit 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, and stores the index table and associates it to the multi-dimensional data body.

8. The building lifecycle-oriented BIM data asset sedimentation and operation management system according to claim 1, characterized in that, The AEM asset integration module includes four units: a platform interface adaptation unit, a data format conversion unit, a metadata mapping unit, and an asset synchronization unit; the platform interface adaptation unit parses API documents of the Adobe Experience Manager Assets platform, generates calling functions conforming to interface specifications, and establishes a communication connection between the system and the platform; the data format conversion unit reads structured data assets output by the spatio-temporal fusion index module, converts the data into corresponding formats according to supported format types of the platform, while retaining the spatial topological relationship of the data; The metadata mapping unit extracts original metadata in BIM data, establishes a mapping relationship of metadata fields by referring to platform metadata standards, and converts the original metadata into platform-recognizable metadata; the asset synchronization unit uploads the converted data and the mapped metadata to the Adobe Experience Manager Assets platform by using the calling functions generated by the platform interface adaptation unit, records the upload path and feeds back to the whole-cycle BIM processing module.

9. The building lifecycle-oriented BIM data asset sedimentation and operation management system according to claim 1, characterized in that, The whole-cycle BIM processing module includes three units: a phased data extraction unit, a feature correlation analysis unit, and a whole-cycle graph generation unit; the phased data extraction unit extracts BIM data of corresponding stages 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 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 with 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.

10. The building lifecycle-oriented BIM data asset sedimentation and operation management system according to any one of claims 1-9, characterized in that, The system operation 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 a 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, and 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, a hierarchical access permission rule is formulated, the rule is embedded into the access control module, and the access request of different user roles is checked for permission; Fourth, by monitoring the update state of the data assets in the Adobe Experience Manager Assets platform in real time, the identifier and content of the updated data are obtained, and the update mechanism of the data asset operation module is triggered; In the fifth step, the building multi-source data conflict resolution and lightweight algorithm is called to process the updated data, and the processed data is compared with the original data asset to update the corresponding association relationship and storage path in the association graph; In the sixth step, the classification results, access logs and update records of the data asset are recorded, an operation report is generated, the report is stored in the system log library, and the updated association graph and data asset state are fed back to the multi-source data conflict resolution module to form a closed-loop process of data asset operation.

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