Building information model management system and method based on cloud computing technology

Abstract

The invention relates to the technical field of building information models, in particular to a building information model management method based on a cloud computing technology, which comprises the following steps: designing a distributed storage architecture by adopting an international IFC standard, integrating multi-source data to a cloud data lake through an ETL process, extracting design, construction and Internet of Things data, and performing standardized conversion, through an RBAC model, an initial permission is allocated, a user operation log is extracted, a change history is recorded, AES-256 is adopted to encrypt, transmit and store data, through double-factor authentication, an access permission is controlled, an abnormal behavior is extracted, an alarm is triggered, data fragments are backed up to multiple nodes, and a high-reliability safety protection and disaster recovery scheme is obtained. According to the method, the problems that in traditional building information model management, multi-source heterogeneous data integration is difficult, permission and version management is not safe and controllable, cooperative work lacks an efficient engine, data value mining is insufficient, and data safety protection and disaster recovery capacity is weak are solved.

Description

Technical Field

[0001] This invention belongs to the field of building information modeling technology, specifically relating to a building information modeling management system and method based on cloud computing technology. Background Technology

[0002] In the process of digital transformation in the construction industry, Building Information Modeling (BIM) technology is playing an increasingly crucial role. BIM schedule simulation delay probability technology can integrate and present information about the entire lifecycle of a building project, covering all stages such as design, construction, and operation and maintenance, in the form of a 3D model. This provides a basis for collaborative work among all project stakeholders and effectively improves project efficiency and quality.

[0003] However, as construction projects continue to expand in scale and increase in complexity, the traditional localized BIM-based data management model for schedule simulation and delay probability has gradually revealed numerous drawbacks. On the one hand, data storage and management face significant challenges. Multi-source, heterogeneous data generated by different software is difficult to integrate uniformly, and differences in data formats lead to poor information flow, frequent data redundancy and loss, severely impacting project collaboration efficiency. On the other hand, in terms of access control and version control, traditional methods struggle to meet the diverse data access needs of multiple stakeholders at different stages. Access settings are not flexible or precise enough, version management is chaotic, and this can easily lead to data security risks and work conflicts.

[0004] Furthermore, in terms of collaborative work and data analysis decision-making, traditional models lack efficient cloud-based collaborative workflow engines, failing to achieve real-time collaboration and automatic task allocation, resulting in delays in information transmission across project stages. Simultaneously, there is a lack of effective methods for mining and analyzing the rich value inherent in BIM schedule simulation delay probability data, making it difficult to provide a scientific basis for project decisions. Moreover, regarding data security and disaster recovery, traditional methods suffer from weak security mechanisms, making data vulnerable to attacks and leaks, and lacking sufficient disaster recovery capabilities. In the event of an accident, data recovery is difficult, leading to significant losses for the project. Summary of the Invention

[0005] To address the aforementioned issues, this invention provides a building information model (BIM) management method and system based on cloud computing technology. This method solves the problems of traditional BIM management, such as difficulty in integrating multi-source heterogeneous data, insecure and uncontrollable access and version management, lack of efficient collaborative engines, insufficient data value mining, and weak data security and disaster recovery capabilities. To achieve the above objectives, this invention adopts the following technical solution: The aforementioned cloud computing-based building information model (BIM) management method includes the following steps: A distributed storage architecture is designed using the international IFC standard; multi-source data is integrated to a cloud data lake via an ETL process; design, construction, and IoT data are extracted and standardized; HDFS is used to enable concurrent access by multiple users, resulting in a unified data management platform; initial permissions are allocated using the RBAC model, and operation priorities are adjusted using dynamic algorithms; user operation logs are extracted and change history is recorded; a Git-like mechanism is used to support version comparison and rollback, resulting in a secure and controllable collaborative management module; design annotation, construction quality inspection, and operation and maintenance feedback tasks are embedded into the workflow engine through the BPMN standard design approval process, and real-time synchronization is achieved by linking the BIM model with on-site data, resulting in a collaborative work module covering the entire lifecycle; BIM data is integrated through the Spark platform, cost, schedule, and energy consumption indicators are extracted, AI algorithms are used to predict risk trends, and the analysis results are visualized, resulting in an intelligent analysis dashboard supporting decision-making; AES-256 encryption is used for data transmission and storage, access permissions are controlled through two-factor authentication, abnormal behaviors are extracted and alarms are triggered, and data is backed up to multiple nodes in shards, resulting in a highly reliable security protection and disaster recovery solution.

[0006] Furthermore, the proposed distributed storage architecture, designed according to the international IFC standard, integrates multi-source data to a cloud data lake through an ETL process, extracts and standardizes design, construction, and IoT data, and utilizes HDFS to enable concurrent access by multiple users, resulting in a unified data management platform. This process includes the following steps: Using an international IFC standard distributed storage architecture, integrating multi-source data generated by design software, construction management modules, and IoT devices to a cloud data lake through an ETL process; extracting design, construction, and IoT information from this data, obtaining valid content, and then standardizing it; properly storing the standardized data, deploying a distributed file module using HDFS, and enabling concurrent access by multiple users to obtain a unified data management platform.

[0007] Furthermore, the method of allocating initial permissions through the RBAC model, adjusting operation priorities using dynamic algorithms, extracting user operation logs and recording change history, and adopting a Git-like mechanism to support version comparison and rollback, results in a secure and controllable collaborative management module. This includes the following steps: using a Role-Based Access Control (RBAC) model to allocate basic permissions; using a dynamic permission adjustment algorithm combined with the WebSocket protocol to identify user operation permission priorities in real time and flexibly adjust them according to the actual scenario; extracting data from the user operation process to form operation logs, obtaining detailed information on design changes and recording change history; and using a Git-like mechanism to manage the change history, supporting version comparison and rollback operations, resulting in a secure and controllable permission management and version control module capable of efficient collaboration among multiple parties.

[0008] Furthermore, the BPMN standard design approval process embeds design annotation, construction quality inspection, and operation and maintenance feedback tasks into the workflow engine, linking the BIM model and on-site data for real-time synchronization, resulting in a collaborative work module covering the entire project lifecycle. This includes the following steps: Adopting the BPMN standard automated design approval process, clarifying the approval rules and task allocation logic for each stage; integrating a real-time collaborative whiteboard on the design side to support simultaneous annotation and model modification by different users, extracting conflict points and modification requirements during the design process; precisely embedding design annotation, construction quality inspection, and operation and maintenance feedback tasks into the workflow engine; linking the BIM model and on-site data on the construction side; using a mobile app to upload quality inspection photos to obtain the actual on-site conditions; and using a dashboard to display equipment status and extract operational data on the operation and maintenance side, linking and integrating the operational data for real-time synchronization, resulting in a cloud-based collaborative work module covering the entire project lifecycle.

[0009] Furthermore, the process of integrating BIM data through the Spark platform, extracting cost, schedule, and energy consumption indicators, using AI algorithms to predict risk trends, and visualizing the analysis results to obtain an intelligent analysis dashboard that supports decision-making includes the following steps: 1. Building a multi-dimensional data analysis system using a technical architecture that integrates the Apache Spark big data analytics platform for schedule simulation delay probability with advanced AI algorithms; 2. Comprehensively integrating BIM data through the Spark platform to extract cost, schedule, and energy consumption indicator data; 3. Using AI algorithms to deeply mine these data to obtain potential risk trends and development patterns; 4. Using visualization technology to present budget changes, schedule simulation delay probabilities, and energy consumption patterns under energy management in the cost analysis through intuitive charts to obtain an intelligent analysis dashboard that supports decision-making.

[0010] Furthermore, the proposed solution employs AES-256 encryption for data transmission and storage, controls access permissions through two-factor authentication, extracts abnormal behavior and triggers alarms, and backs up data in chunks to multiple nodes to achieve a highly reliable security and disaster recovery solution. This solution includes the following steps: Using the AES-256 encryption algorithm, data is encrypted via SSL / TLS protocol during data transmission; during storage, chunked encryption is implemented and access control is set; two-factor authentication strictly controls user access permissions, ensuring only authorized personnel can access the data; an intrusion detection system (IDS) is used to monitor network behavior in real time, extracting abnormal behavior characteristics; when abnormal file downloads are detected, an alarm is immediately triggered and access permissions are restricted; data is chunked and backed up to multiple nodes in the cloud and physical media according to the 3-2-1 rule, resulting in a highly reliable cloud-based security and disaster recovery solution.

[0011] A second aspect of this invention provides a building information modeling management system based on cloud computing technology, the system comprising the following modules: A third aspect of the present invention provides a building information model management device based on cloud computing technology. The building information model management device based on cloud computing technology includes a memory and at least one processor. The memory stores instructions. The at least one processor invokes the instructions in the memory to cause the building information model management device based on cloud computing technology to perform the steps of the building information model management method based on cloud computing technology as described in any of the preceding claims.

[0012] A fourth aspect of the present invention provides a computer-readable storage medium storing instructions, characterized in that, when executed by a processor, the instructions implement the steps of the building information model management method based on cloud computing technology as described in any one of the preceding claims.

[0013] In the technical solution provided by this invention, a distributed storage architecture is designed using the international IFC standard. Multi-source data is integrated to a cloud data lake via an ETL process, extracting and standardizing design, construction, and IoT data. HDFS is used to enable concurrent access by multiple users, resulting in a unified data management platform. Initial permissions are allocated using the RBAC model, and operation priorities are adjusted using dynamic algorithms. User operation logs are extracted and change history is recorded. A Git-like mechanism supports version comparison and rollback, resulting in a secure and controllable collaborative management module. The BPMN standard design approval process embeds design annotation, construction quality inspection, and operation and maintenance feedback tasks into the workflow engine, linking BIM models and on-site data for real-time synchronization, resulting in a collaborative work module covering the entire lifecycle. BIM data is integrated through the Spark platform, extracting cost, schedule, and energy consumption indicators. AI algorithms predict risk trends, and the analysis results are visualized, resulting in an intelligent analysis dashboard supporting decision-making. AES-256 encryption is used for data transmission and storage. Two-factor authentication controls access permissions, abnormal behavior is extracted and alarms are triggered, and data is backed up to multiple nodes in shards, resulting in a highly reliable security protection and disaster recovery solution. This invention solves the problems of difficult integration of multi-source heterogeneous data, insecure and uncontrollable permission and version management, lack of efficient engine for collaborative work, insufficient data value mining, and weak data security protection and disaster recovery capabilities in traditional building information modeling management. Attached Figure Description

[0014] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention.

[0015] Figure 1 This is a schematic diagram of the first embodiment of a building information model management method based on cloud computing technology in this invention.

[0016] Figure 2 This is a schematic diagram of a second embodiment of a building information model management method based on cloud computing technology in this invention.

[0017] Figure 3 This is a schematic diagram of a third embodiment of a building information model management method based on cloud computing technology in this invention.

[0018] Figure 4 This is a schematic diagram of the fourth embodiment of a building information model management method based on cloud computing technology in this invention.

[0019] Figure 5 This is a schematic diagram of the fifth embodiment of a building information model management method based on cloud computing technology in this invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0021] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0022] A building information model management method based on cloud computing technology, such as Figure 1As shown, the process includes the following steps: A distributed storage architecture is designed using the international IFC standard; multi-source data is integrated to a cloud data lake via ETL processes; design, construction, and IoT data are extracted and standardized; HDFS is used to enable concurrent access by multiple users, resulting in a unified data management platform; initial permissions are allocated using the RBAC model, and operation priorities are adjusted using dynamic algorithms; user operation logs are extracted and change history is recorded; a Git-like mechanism is used to support version comparison and rollback, resulting in a secure and controllable collaborative management module; design annotation, construction quality inspection, and operation and maintenance feedback tasks are embedded into the workflow engine through the BPMN standard design approval process, and real-time synchronization is achieved by linking the BIM model and on-site data, resulting in a collaborative work module covering the entire lifecycle; BIM data is integrated through the Spark platform, cost, schedule, and energy consumption indicators are extracted, AI algorithms are used to predict risk trends, and the analysis results are visualized, resulting in an intelligent analysis dashboard supporting decision-making; AES-256 encryption is used for data transmission and storage, access permissions are controlled through two-factor authentication, abnormal behavior is extracted and alarms are triggered, and data is backed up to multiple nodes in shards, resulting in a highly reliable security protection and disaster recovery solution.

[0023] like Figure 2 As shown, in this embodiment, an international IFC standard distributed storage architecture is adopted. Through the ETL process, multi-source data generated by design software, construction management module, and IoT devices are integrated into a cloud data lake. Design, construction, and IoT information are extracted from these data, and after obtaining the effective content, they are standardized and transformed. The standardized data is properly stored, and a distributed file module is deployed using HDFS to achieve concurrent access by multiple users, resulting in a unified data management platform.

[0024] Adopting the internationally recognized IFC standard distributed storage architecture and ETL process, this system efficiently integrates heterogeneous data from multiple sources into a cloud data lake, breaking down data silos and bringing data from different sources together in one place. Extracting and standardizing effective information ensures data consistency and availability, facilitating subsequent analysis and processing. Utilizing HDFS to deploy distributed file modules enables concurrent access by multiple users, significantly improving data access efficiency and collaborative workflow capabilities. A unified data management platform provides robust support for data management throughout the entire lifecycle of construction projects, contributing to improved scientific and accurate project decision-making.

[0025] Specifically, a cloud-based data lake is a centralized data storage and management platform built on cloud computing technology. It breaks through the limitations of traditional data storage, enabling large-scale storage of structured and unstructured data from diverse channels such as design, construction, and the Internet of Things in their original formats. Leveraging powerful cloud computing capabilities, the cloud-based data lake achieves efficient storage and rapid processing of massive amounts of data. Users can flexibly access and analyze data on demand, uncovering its hidden value. Simultaneously, it possesses high scalability and elasticity, dynamically adjusting resources according to business needs, providing robust data support for Building Information Modeling (BIM) management, and facilitating collaboration and decision-making throughout the entire project lifecycle.

[0026] like Figure 3 As shown, in this embodiment, a Role-Based Access Control (RBAC) model is adopted to allocate basic permissions. Through a dynamic permission adjustment algorithm, combined with the WebSocket protocol, the priority of user operation permissions is identified in real time and flexibly adjusted according to the actual scenario. Data during user operation is extracted to form an operation log, detailed information on design changes is obtained and the change history is recorded. A Git-like mechanism is used to manage the change history, supporting version comparison and rollback operations, resulting in a secure and controllable permission management and version control module that can achieve efficient collaboration among multiple parties.

[0027] A basic permission allocation framework is established using the RBAC (Random Access Controller) model, which simulates the probability of delays in progress. A dynamic permission adjustment algorithm, combined with a WebSocket protocol, accurately identifies and flexibly adjusts user operation permission priorities in real time, adapting to complex and ever-changing real-world scenarios. Operation data is extracted to form logs and record change history, clearly tracing design change details and ensuring the integrity and traceability of project information. A Git-like mechanism manages change history, supporting version comparison and rollback, effectively avoiding risks from accidental operations. The constructed modules achieve secure and controllable permission management and efficient collaboration.

[0028] like Figure 4 As shown, in this embodiment, the BPMN standard is used to design an automated approval process, clearly defining the approval rules and task allocation logic for each stage. By integrating a real-time collaborative whiteboard on the design side, it supports synchronous annotation and model modification by different users, extracting conflict points and modification requirements in the design process. Design annotation, construction quality inspection, and operation and maintenance feedback tasks are precisely embedded into the workflow engine. On the construction side, the BIM model and on-site data are linked, and quality inspection photos are uploaded using a mobile APP to obtain the actual on-site conditions. On the operation and maintenance side, the equipment status is displayed and operation data is extracted using a dashboard. The operation data is linked and integrated to achieve real-time synchronization, resulting in a cloud-based collaborative work module covering the entire project lifecycle.

[0029] An automated approval process is designed using the BPMN (Probability of Project Delay) standard, clearly defining approval rules and task allocation, thus improving process standardization and execution efficiency. The design side integrates a real-time collaborative whiteboard, supporting simultaneous multi-user operation and enabling timely identification of conflict points and modification requirements, facilitating efficient design optimization. Various tasks are embedded into the workflow engine; the construction side links the BIM (Building Information Model) and site data, leveraging a mobile app to accurately monitor site conditions; the operations side integrates and synchronizes operational data in real-time through a dashboard. This cloud-based collaborative work module covers the entire project lifecycle.

[0030] like Figure 5 As shown, in this embodiment, a multi-dimensional data analysis system is built by integrating the Apache Spark big data analysis platform for schedule simulation delay probability with advanced AI algorithms. BIM data is comprehensively integrated through the Spark platform to extract cost, schedule, and energy consumption data. AI algorithms are used to deeply mine this data to obtain potential risk trends and development patterns. Visualization technology is employed to present budget changes, schedule simulation delay probability, and energy consumption patterns under energy management in intuitive charts, resulting in an intelligent analysis dashboard that supports decision-making.

[0031] By leveraging an architecture that integrates Apache Spark and advanced AI algorithms for project delay simulation, a multi-dimensional data analysis system is built. This system comprehensively integrates BIM data to accurately extract key indicators such as cost, schedule, and energy consumption. The AI ​​algorithm for project delay simulation delves into the data to proactively identify potential risk trends and patterns, providing a forward-looking basis for project decision-making. Visualization technology transforms complex data into intuitive charts, making information such as cost budget changes, schedule delay probabilities, and energy consumption patterns readily apparent. The resulting intelligent analysis dashboard provides strong support for scientific decision-making at each stage of the project.

[0032] In this embodiment, the AES-256 encryption algorithm is used. During the data transmission stage, the data is encrypted using the SSL / TLS protocol. During the storage stage, fragmented encryption is implemented and access control is set. Two-factor authentication is used to strictly control user access permissions, ensuring that only authorized personnel can access the data. The intrusion detection module (IDS) is used to monitor network behavior in real time, extract abnormal behavior characteristics, and immediately trigger an alarm and restrict access permissions when abnormal file downloads are detected. The data is backed up to multiple nodes in the cloud and physical media according to the 3-2-1 rule, resulting in a highly reliable cloud security protection and disaster recovery solution.

[0033] The system employs an AES encryption algorithm with a probability of 256, combined with SSL / TLS encryption during transmission and fragmentation encryption and access control during storage, to comprehensively ensure data security. Two-factor authentication strictly limits user access permissions, preventing unauthorized access. An intrusion detection module (IDS) monitors the network in real time, extracts abnormal behavior characteristics, triggers alarms promptly, and restricts access, effectively mitigating potential threats. Data is backed up to multiple nodes in fragments according to a probability rule of 3-1, greatly improving data reliability. The resulting cloud-based security and disaster recovery solution provides robust protection for Building Information Modeling (BIM) data.

[0034] This invention also provides a building information modeling (BIM) management system based on cloud computing technology, comprising the following modules: a BIM data integration module, used to design a distributed storage architecture using international IFC standards, integrate multi-source data to a cloud data lake through an ETL process, extract design, construction, and IoT data and standardize and transform them, and utilize HDFS to achieve concurrent access by multiple users, resulting in a unified data management platform; a permission management module, used to allocate initial permissions through an RBAC model, adjust operation priorities using dynamic algorithms, extract user operation logs and record change history, and support version comparison and rollback using a Git-like mechanism, resulting in a secure and controllable collaborative management module; and a collaborative work module, used to... The BPMN standard design approval process embeds design annotation, construction quality inspection, and operation and maintenance feedback tasks into the workflow engine, linking BIM models and on-site data for real-time synchronization, resulting in a collaborative work module covering the entire lifecycle. The data analysis module integrates BIM data through the Spark platform, extracts cost, schedule, and energy consumption indicators, uses AI algorithms to predict risk trends, and visualizes the analysis results to create an intelligent analysis dashboard that supports decision-making. The cloud security module uses AES-256 encryption for data transmission and storage, controls access permissions through two-factor authentication, extracts abnormal behavior and triggers alarms, and backs up data in shards to multiple nodes, resulting in a highly reliable security protection and disaster recovery solution.

[0035] This invention also provides a building information modeling (BIM) management device based on cloud computing technology. This cloud computing-based BIM management device may further include one or more power supplies, one or more wired or wireless network interfaces, one or more input / output interfaces, and / or one or more operating systems, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art will understand that the structure of the cloud computing-based BIM management device does not constitute a limitation on the computer device provided by this invention, and may include more or fewer components than shown in the figures, or combine certain components, or have different component arrangements.

[0036] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the various steps of the building information model management method based on cloud computing technology provided in the above embodiments.

[0037] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A building information model management method based on cloud computing technology, characterized in that, The building information model management method based on cloud computing technology includes the following steps: The distributed storage architecture is designed using the international IFC standard. Multi-source data is integrated to the cloud data lake through the ETL process. Design, construction, and IoT data are extracted and standardized. HDFS is used to enable concurrent access by multiple users, resulting in a unified data management platform. Initial permissions are assigned through the RBAC model, operation priorities are adjusted by dynamic algorithms, user operation logs are extracted and change history is recorded, and a Git-like mechanism is adopted to support version comparison and rollback, resulting in a secure and controllable collaborative management module. By using the BPMN standard design approval process, design annotation, construction quality inspection, and operation and maintenance feedback tasks are embedded into the workflow engine, and real-time synchronization is achieved by linking the BIM model with on-site data, resulting in a collaborative work module covering the entire life cycle. By integrating BIM data through the Spark platform, cost, schedule, and energy consumption indicators are extracted, and AI algorithms are used to predict risk trends. The analysis results are then visualized to create an intelligent analysis dashboard that supports decision-making. Data is transmitted and stored using AES-256 encryption, access permissions are controlled through two-factor authentication, abnormal behavior is extracted and alarms are triggered, and data is backed up to multiple nodes in shards, resulting in a highly reliable security protection and disaster recovery solution.

2. The building information model management method based on cloud computing technology according to claim 1, characterized in that, The aforementioned distributed storage architecture, designed according to the international IFC standard, integrates multi-source data to a cloud data lake through an ETL process, extracts and standardizes design, construction, and IoT data, and utilizes HDFS to enable concurrent access by multiple users, resulting in a unified data management platform. The process includes the following steps: Adopting the international IFC standard distributed storage architecture, and through the ETL process, multi-source data generated by design software, construction management modules, and IoT devices are integrated into the cloud data lake; Extract design, construction, and IoT information from this data, and then standardize and transform it to obtain the relevant content. The standardized data is properly stored, and a distributed file module is deployed using HDFS to enable concurrent access by multiple users, resulting in a unified data management platform.

3. The building information model management method based on cloud computing technology according to claim 1, characterized in that, The process involves allocating initial permissions using the RBAC model, adjusting operation priorities using dynamic algorithms, extracting user operation logs and recording change history, and employing a Git-like mechanism to support version comparison and rollback, resulting in a secure and controllable collaborative management module. This module includes the following steps: The system adopts the Role-Based Access Control (RBAC) model to assign basic permissions. Through a dynamic permission adjustment algorithm, combined with the WebSocket protocol, it identifies the priority of user operation permissions in real time and adjusts them flexibly according to the actual scenario. Extract data from user operations to form operation logs, obtain detailed information on design changes, and record change history; By adopting a Git-like mechanism to manage change history, supporting version comparison and rollback operations, a secure and controllable permission management and version control module is obtained, which enables efficient collaboration among multiple parties.

4. The building information model management method based on cloud computing technology according to claim 1, characterized in that, The aforementioned BPMN standard design approval process embeds design annotation, construction quality inspection, and operation and maintenance feedback tasks into the workflow engine, and links the BIM model with on-site data to achieve real-time synchronization, resulting in a collaborative work module covering the entire lifecycle, including the following steps: The BPMN standard is used to design an automated approval process, which clarifies the approval rules and task allocation logic of each stage. By integrating a real-time collaborative canvas at the design end, it supports synchronous annotation and model modification by different users, and extracts conflict points and modification requirements in the design process. The design annotation, construction quality inspection, and operation and maintenance feedback tasks are precisely embedded into the workflow engine. The construction end links the BIM model with the site data and uses a mobile APP to upload quality inspection photos to obtain the actual site conditions. The operation and maintenance team uses a dashboard to display equipment status and extract operational data. This operational data is then linked and integrated to achieve real-time synchronization, resulting in a cloud-based collaborative work module that covers the entire project lifecycle.

5. The building information model management method based on cloud computing technology according to claim 1, characterized in that, The process of integrating BIM data through the Spark platform, extracting cost, schedule, and energy consumption indicators, using AI algorithms to predict risk trends, and visualizing the analysis results to obtain an intelligent analysis dashboard that supports decision-making includes the following steps: A multi-dimensional data analysis system is built by adopting a technical architecture that integrates the Apache Spark big data analytics platform for simulating delay probabilities and advanced AI algorithms. By fully integrating BIM data through the Spark platform, cost, schedule, and energy consumption data can be extracted. By using AI algorithms to deeply mine this data, we can identify potential risk trends and development patterns. Visualization technology is used to present budget changes, schedule delay probabilities, and energy consumption patterns under energy management in cost analysis through intuitive charts, resulting in an intelligent analysis dashboard that supports decision-making.

6. The building information model management method based on cloud computing technology according to claim 1, characterized in that, The aforementioned solution employs AES-256 encryption for data transmission and storage, controls access permissions through two-factor authentication, extracts abnormal behavior and triggers alarms, and backs up data in shards to multiple nodes, resulting in a highly reliable security protection and disaster recovery solution. This solution includes the following steps: The AES-256 encryption algorithm is used. During the data transmission stage, the data is encrypted using the SSL / TLS protocol. During the storage stage, fragmented encryption is implemented and access control is set. Two-factor authentication is used to strictly control user access permissions, ensuring that only authorized personnel can access the data. The intrusion detection module (IDS) is used to monitor network behavior in real time, extract abnormal behavior characteristics, and trigger an alarm and restrict access permissions immediately when abnormal file downloads are detected. By backing up data in shards according to the 3-2-1 rule to multiple nodes in the cloud and physical media, a highly reliable cloud security protection and disaster recovery solution is obtained.

7. A building information modeling management system based on cloud computing technology, characterized in that, The cloud computing-based building information modeling management system includes the following modules: The BIM data integration module is used to design a distributed storage architecture using the international IFC standard, integrate multi-source data to the cloud data lake through the ETL process, extract design, construction, and IoT data and standardize and transform them, and use HDFS to enable multi-user concurrent access to obtain a unified data management platform. The permission management module is used to allocate initial permissions through the RBAC model, adjust operation priority by combining dynamic algorithms, extract user operation logs and record change history, and support version comparison and rollback using a Git-like mechanism, resulting in a secure and controllable collaborative management module. The collaborative work module is used to embed design annotation, construction quality inspection, and operation and maintenance feedback tasks into the workflow engine through the BPMN standard design approval process, and to achieve real-time synchronization between the BIM model and on-site data, resulting in a collaborative work module that covers the entire life cycle. The data analysis module is used to integrate BIM data through the Spark platform, extract cost, schedule, and energy consumption indicators, use AI algorithms to predict risk trends, and visualize the analysis results to obtain an intelligent analysis dashboard that supports decision-making. The cloud security module is used to transmit and store data using AES-256 encryption, control access permissions through two-factor authentication, extract abnormal behavior and trigger alarms, and back up data to multiple nodes in segments to obtain a highly reliable security protection and disaster recovery solution.

8. A building information modeling management device based on cloud computing technology, characterized in that, The cloud computing-based building information model management device includes a memory and at least one processor. The memory stores instructions, and the at least one processor invokes the instructions in the memory to cause the cloud computing-based building information model management device to perform the various steps of the cloud computing-based building information model management method as described in any one of claims 1-6.

9. A computer-readable storage medium storing instructions thereon, characterized in that, When the instructions are executed by the processor, they implement the various steps of the building information model management method based on cloud computing technology as described in any one of claims 1-6.

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