Fabricated building design construction optimization management system and method based on BIM

Abstract

The invention relates to the technical field of BIM building optimization, in particular to a BIM-based prefabricated building design construction optimization management system and method. The method comprises the following steps: acquiring a panoramic monitoring image of a building area and a construction design initial BIM model; carrying out regional space structure evolution and construction scene three-dimensional simulation on the panoramic monitoring image of the building region, and constructing a three-dimensional construction scene graph; identifying assembly type building component information according to the construction design initial BIM model so as to generate building component assembly demand characteristics; performing dynamic construction sequence simulation optimization on the three-dimensional construction scene graph and the construction design initial BIM model based on building component assembly demand characteristics, and constructing a dynamic optimization construction sequence; and carrying out available material transportation path analysis on the three-dimensional construction scene graph so as to generate an optimal operation path of each material. According to the invention, real-time collaborative management based on the BIM and the cloud is realized, the building construction quality is improved, and the construction design decision is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of BIM building optimization, and particularly to an optimized management system and method for the design and construction of prefabricated buildings based on BIM. Background Art

[0002] With the rapid development of Building Information Modeling (BIM) technology, the application of BIM in the design and construction of prefabricated buildings has gradually gained attention. Through means such as digital three-dimensional modeling, information integration, and collaborative management, BIM technology provides strong support for the design, construction, and operation of prefabricated buildings. Especially in the design stage, BIM can accurately simulate information such as building components, assembly sequences, and spatial layouts, and identify potential conflicts and problems in advance, thus providing optimized solutions for subsequent construction. However, existing BIM applications mostly focus on the design stage, and how to effectively extend it to construction management and conduct optimized management throughout the life cycle is still an urgent problem to be solved.

[0003] In order to adapt to the variability and complexity in modern prefabricated building construction, the traditional management mode needs to transform towards intelligence and automation. The optimized management method for the design and construction of prefabricated buildings based on BIM has emerged. It not only utilizes the digital modeling and information sharing functions of BIM, but also combines technologies such as intelligent decision support, optimized material transportation, and real-time monitoring of the construction process, with the expectation of improving the construction efficiency, quality, and sustainability of prefabricated buildings through comprehensive optimized management. The core of this method lies in integrating multi-dimensional information such as design, construction, materials, and equipment on a shared platform, breaking the situation of information silos in traditional management, and achieving more refined and intelligent construction management.

[0004] However, there are still certain limitations in the current research and application of the optimized management method for the construction of prefabricated buildings based on BIM, especially in aspects such as dynamic optimization of the construction process, real-time monitoring, and material transportation route planning. Further technological breakthroughs and practical verification are still required. Therefore, developing an innovative optimized management method for the design and construction of prefabricated buildings based on BIM can better handle complex and changing construction scenarios, improve construction efficiency, reduce resource waste, lower project risks, and provide effective solutions for the digital transformation of the construction industry. Summary of the Invention

[0005] To solve the above technical problems, the present invention proposes an optimized management system and method for the design and construction of prefabricated buildings based on BIM to solve at least one of the above technical problems.

[0006] To achieve the above object, the present invention provides an optimized management method for the design and construction of prefabricated buildings based on BIM, including the following steps: Step S1: Obtain the panoramic monitoring image of the construction area and the initial BIM model of the construction design; conduct regional spatial structure evolution and three-dimensional simulation of the construction scene for the panoramic monitoring image of the construction area to construct a three-dimensional construction scene diagram; Step S2: Identify the information of prefabricated building components according to the initial BIM model of the construction design, and conduct the evolution of component assembly requirements, so as to generate the characteristics of building component assembly requirements; Step S3: Based on the characteristics of building component assembly requirements, conduct dynamic construction sequence simulation and optimization for the three-dimensional construction scene diagram and the initial BIM model of the construction design to construct a dynamically optimized construction sequence; Step S4: Analyze the transportation path of available materials for the three-dimensional construction scene diagram, and plan the optimal operation path for each material one by one, so as to generate the optimal operation path for each material; Step S5: Make a decision on the intelligent construction design plan according to the dynamically optimized construction sequence and the optimal operation path of each material, and synchronize the detection of component position deviation to generate an instantaneously synchronized twin construction model; Step S6: Based on the instantaneously synchronized twin construction model, conduct on-site construction deviation elimination and compensation processing, and conduct cloud data collaborative management synchronization to construct an instant construction optimization management engine.

[0007] The present invention can accurately capture the actual situation of the construction site by acquiring panoramic monitoring images of the construction area and combining with the initial BIM model, which provides real and complete site data for subsequent construction planning and reduces the error of traditional manual measurement. Through the evolution analysis of spatial structure, the spatial changes of the construction site can be fully understood, which can not only identify potential spatial conflicts, but also provide data support for construction progress and resource deployment. Using three-dimensional construction scene diagrams for simulation, it is possible to discover and solve problems such as obstacles and complex terrain changes that may occur on site in advance, enhancing the foresight of construction management. The BIM model provides standardized design information for each component, identifies the specifications, materials, dimensions, functions, etc. of the components, and provides basic data for subsequent assembly. According to the actual situation and design requirements of the construction site, the assembly requirements are evolved, and the assembly order and demand of each component can be accurately calculated, avoiding the inefficiency and errors of traditional manual judgment. The assembly requirements of the components are dynamically evolved, and the assembly plan can be adjusted in real time to maximize construction efficiency and reduce resource waste. Through dynamic simulation of three-dimensional construction scene diagrams and BIM models, the construction steps and sequences can be intelligently optimized, avoiding construction bottlenecks and resource waste caused by unreasonable sequences in traditional construction. The dynamically optimized construction sequence can be adjusted in real time according to the actual situation on site. When encountering emergencies (such as material delays, equipment failures, etc.) during construction, the construction plan can be quickly adjusted to ensure the consistency of the progress. Through the optimization of the construction sequence, conflicts, bottlenecks and delays that may occur during the construction process can be discovered in advance, so that preventive measures can be taken to improve the safety and controllability of construction. Analysis of available material transportation paths helps to identify the most suitable path for each material transportation, avoids congestion and poor paths in on-site material transportation, and reduces logistics costs. Optimal material operation path planning can reduce transportation time, reduce possible delays during transportation, and improve on-site construction efficiency. At the same time, by optimizing the transportation path, the energy consumption of equipment is saved. The optimized material transportation path enables the on-site construction team to work more efficiently, and materials can reach the construction site more smoothly, avoiding material accumulation and traffic jams. Based on the comprehensive analysis of dynamically optimized construction sequences and optimal material operation paths, intelligent construction plans can be provided to maximize construction efficiency and resource utilization. Intelligent decision-making can adjust construction plans based on real-time data to avoid errors in manual decision-making. Through component position deviation detection technology, position errors in the construction process, such as component installation offsets, can be discovered in a timely manner to ensure accuracy and quality during the construction process. By building an instant and synchronized twin construction model, the virtual model and the actual construction site are synchronized. Managers can check the differences between the virtual and the actual at any time, and make instant adjustments to ensure that the project progress is consistent with the plan.Through real-time feedback based on the twin model, it is possible to accurately identify the deviations generated during the construction process and perform intelligent compensation processing to ensure construction accuracy and reduce post-construction maintenance costs. Upload the construction data to the cloud and conduct collaborative management to ensure that all parties (designers, constructors, suppliers, etc.) can share data in real time, improve cross-departmental coordination efficiency, and reduce the phenomenon of information silos. The instant construction optimization management engine can continuously optimize the construction plan through big data and AI algorithms and provide decision-making support for subsequent construction stages to ensure that the optimization process of the entire building project is continuous and dynamic.

[0008] In this specification, a BIM-based prefabricated building design and construction optimization management system is provided for implementing the BIM-based prefabricated building design and construction optimization management method as described above, including: A construction scenario module for obtaining panoramic monitoring images of the construction area and the initial BIM model of the construction design; performing regional space structure evolution and three-dimensional simulation of the construction scenario on the panoramic monitoring images of the construction area to construct a three-dimensional construction scenario map; An assembly requirement module for identifying prefabricated building component information based on the initial BIM model of the construction design and evolving the component assembly requirements to generate the assembly requirement characteristics of the building components; A construction sequence optimization module for dynamically simulating and optimizing the construction sequence of the three-dimensional construction scenario map and the initial BIM model of the construction design based on the assembly requirement characteristics of the building components to construct a dynamically optimized construction sequence; An operation path planning module for analyzing the available material transportation paths of the three-dimensional construction scenario map and planning the optimal operation paths for each material one by one to generate the optimal operation path for each material; An error identification module for making intelligent construction design plan decisions based on the dynamically optimized construction sequence and the optimal operation path of each material and synchronously detecting the component position deviation to generate an instant synchronous twin construction model; A construction deviation compensation module for eliminating and compensating the on-site construction deviations based on the instant synchronous twin construction model and synchronously managing the cloud data collaboration to construct an instant construction optimization management engine.

[0009] By obtaining the panoramic monitoring images of the construction area, the present invention can comprehensively and real-time understand the environmental characteristics and surrounding conditions of the construction site, which provides accurate site data for construction design and ensures the rationality of the construction plan. Using image analysis technology and BIM technology for regional space structure evolution can deeply analyze the space constraints, obstacles, etc. at the construction site, predict in advance the space limiting factors during the construction process, and thus provide optimization suggestions for subsequent construction. Based on the fusion of panoramic images and BIM models, a three-dimensional construction scene diagram is constructed, which can truly restore the space layout and construction process of the construction site, helping the project team intuitively understand how each link unfolds and identify potential conflicts and risks. By accurately identifying the information of all prefabricated building components in the BIM model, such as the type, specification, material, weight, etc. of the components, in this way, the construction team can clearly understand the specific requirements and characteristics of each component at the design stage. According to the actual situation of the construction site and the project progress, the assembly requirements of the components are updated in real time to avoid resource waste caused by changes during the design or construction process. The assembly sequence of the components can be flexibly adjusted to ensure the efficiency of construction. Through the evolutionary analysis of the component assembly requirements, the material procurement, transportation, assembly plan, etc. can be dynamically adjusted, effectively reducing surplus or insufficient resources and improving the utilization rate of construction resources. Through dynamic construction sequence simulation, bottlenecks in the construction process can be identified and eliminated. For example, avoid the interference caused by multiple tasks being carried out simultaneously, and optimize the workflow and working procedures. Using the three-dimensional construction scene diagram and BIM model for all-round conflict detection and risk warning can detect possible space conflicts, time conflicts or resource conflicts before construction and propose optimization plans to ensure the smooth progress of construction. By optimizing the construction sequence, unnecessary waiting time and repetitive labor are reduced, making the construction process more efficient and smooth, and ensuring the completion of the construction task in the shortest time. By analyzing the transportation routes and material requirements at the construction site, the shortest and most effective transportation route can be planned for each type of material, reducing the time loss and traffic bottlenecks during transportation. Through reasonable material transportation route planning, the stacking and moving times of materials at the site can be reduced, reducing waste and time delays, and thus ensuring that each construction work can be carried out on time. Route planning can reasonably allocate transportation resources, avoid multiple materials crossing on the same route at the same time, and improve the fluidity of on-site materials and construction efficiency. By deploying sensors and monitoring devices, the system can real-time detect the position and installation accuracy of components at the construction site. The immediate identification and feedback of component position deviation can avoid the accumulation of errors and rework in the later stage. Through the combination of BIM and real-time data, the error identification module can provide intelligent decision-making support, helping the construction team make timely adjustments when problems occur and avoiding delays in the construction progress. By real-time synchronizing the twin model, the actual construction progress on site can be docked with the virtual design model in real time, ensuring a high degree of consistency between design and construction and effectively eliminating non-compliance phenomena during the construction process.Through the instant synchronous twin construction model, the system can identify various errors in on-site construction in real time (such as geometric deviations and position deviations of components), calculate the compensation values, and make dynamic adjustments to ensure that the construction accuracy meets the expected standards. The deviation compensation module can directly feedback the compensation plan to the construction team and guide the on-site staff to make precise adjustments, avoiding excessive manual intervention and delays, and improving construction efficiency. All construction data, error information, optimization strategies, etc. are managed in real-time collaboration through the cloud to ensure efficient communication and resource sharing among project teams. At the same time, the optimization management engine can provide precise support for project decision-making based on real-time data and historical data analysis, realizing global construction optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 It is a schematic diagram of the step flow of a BIM-based prefabricated building design and construction optimization management method of the present invention; Figure 2 It is a schematic diagram of the detailed implementation steps of step S1; Figure 3 It is a schematic diagram of the detailed implementation steps of step S2; Figure 4 It is a schematic diagram of the detailed implementation steps of step S3. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0011] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0012] This application example provides a BIM-based prefabricated building design and construction optimization management system and method. The execution subjects of the BIM-based prefabricated building design and construction optimization management system and method include but are not limited to: mechanical equipment, data processing platforms, cloud server nodes, network upload devices, etc. that can be regarded as general computing nodes of this application. The data processing platform includes but is not limited to: at least one of an audio and image management system, an information management system, and a cloud data management system.

[0013] Please refer to Figures 1 to 4 , the present invention provides a BIM-based prefabricated building design and construction optimization management method, and the BIM-based prefabricated building design and construction optimization management method includes the following steps: Step S1: Obtain the panoramic monitoring image of the building area and the initial BIM model of the construction design; perform regional spatial structure evolution and three-dimensional simulation of the construction scene on the panoramic monitoring image of the building area to construct a three-dimensional construction scene diagram; Step S2: Identify the prefabricated building component information according to the initial BIM model of the construction design, and perform component assembly requirement evolution to generate the building component assembly requirement characteristics; Step S3: Based on the assembly requirement characteristics of building components, dynamically simulate and optimize the three-dimensional construction scene diagram and the initial BIM model of the construction design to construct a dynamically optimized construction sequence; Step S4: Analyze the transportation paths of available materials for the three-dimensional construction scene diagram, and plan the optimal operation paths for each material one by one, so as to generate the optimal operation path for each material; Step S5: Make decisions on the intelligent construction design plan according to the dynamically optimized construction sequence and the optimal operation path of each material, and synchronize the detection of component position deviation to generate an instant synchronous twin construction model; Step S6: Based on the instant synchronous twin construction model, conduct on-site construction deviation elimination and compensation processing, and synchronize cloud data collaborative management to construct an instant construction optimization management engine.

[0014] The present invention can accurately capture the actual situation of the construction site by acquiring panoramic monitoring images of the construction area and combining with the initial BIM model, which provides real and complete site data for subsequent construction planning and reduces the error of traditional manual measurement. Through the evolution analysis of spatial structure, the spatial changes of the construction site can be fully understood, which can not only identify potential spatial conflicts, but also provide data support for construction progress and resource deployment. Using three-dimensional construction scene diagrams for simulation, it is possible to discover and solve problems such as obstacles and complex terrain changes that may occur on site in advance, enhancing the foresight of construction management. The BIM model provides standardized design information for each component, identifies the specifications, materials, dimensions, functions, etc. of the components, and provides basic data for subsequent assembly. According to the actual situation and design requirements of the construction site, the assembly requirements are evolved, and the assembly order and demand of each component can be accurately calculated, avoiding the inefficiency and errors of traditional manual judgment. The assembly requirements of the components are dynamically evolved, and the assembly plan can be adjusted in real time to maximize construction efficiency and reduce resource waste. Through dynamic simulation of three-dimensional construction scene diagrams and BIM models, the construction steps and sequences can be intelligently optimized, avoiding construction bottlenecks and resource waste caused by unreasonable sequences in traditional construction. The dynamically optimized construction sequence can be adjusted in real time according to the actual situation on site. When encountering emergencies (such as material delays, equipment failures, etc.) during construction, the construction plan can be quickly adjusted to ensure the consistency of the progress. Through the optimization of the construction sequence, conflicts, bottlenecks and delays that may occur during the construction process can be discovered in advance, so that preventive measures can be taken to improve the safety and controllability of construction. Analysis of available material transportation paths helps to identify the most suitable path for each material transportation, avoids congestion and poor paths in on-site material transportation, and reduces logistics costs. Optimal material operation path planning can reduce transportation time, reduce possible delays during transportation, and improve on-site construction efficiency. At the same time, by optimizing the transportation path, the energy consumption of equipment is saved. The optimized material transportation path enables the on-site construction team to work more efficiently, and materials can reach the construction site more smoothly, avoiding material accumulation and traffic jams. Based on the comprehensive analysis of dynamically optimized construction sequences and optimal material operation paths, intelligent construction plans can be provided to maximize construction efficiency and resource utilization. Intelligent decision-making can adjust construction plans based on real-time data to avoid errors in manual decision-making. Through component position deviation detection technology, position errors in the construction process, such as component installation offsets, can be discovered in a timely manner to ensure accuracy and quality during the construction process. By building an instant and synchronized twin construction model, the virtual model and the actual construction site are synchronized. Managers can check the differences between the virtual and the actual at any time, and make instant adjustments to ensure that the project progress is consistent with the plan.Through real-time feedback based on the twin model, it is possible to accurately identify deviations during the construction process and perform intelligent compensation processing to ensure construction accuracy and reduce subsequent maintenance costs. Upload construction data to the cloud and conduct collaborative management to ensure that all parties (designers, construction workers, suppliers, etc.) can share data in real time, improve cross-departmental coordination efficiency, and reduce information islands. The real-time construction optimization management engine can continuously optimize construction plans through big data and AI algorithms, and provide decision support for subsequent construction stages, ensuring that the optimization process of the entire construction project is continuous and dynamic.

[0015] In the embodiment of the present invention, refer to Figure 1 , is a schematic diagram of the steps of a BIM-based prefabricated building design and construction optimization management method of the present invention. In this example, the steps of the BIM-based prefabricated building design and construction optimization management method include: Step S1: Obtain a panoramic monitoring image of the building area and an initial BIM model of the construction design; perform a three-dimensional simulation of the regional spatial structure evolution and the construction scene on the panoramic monitoring image of the building area to construct a three-dimensional construction scene diagram; In this embodiment, suitable monitoring devices are selected, such as high-resolution panoramic cameras or drone imaging systems. These devices should have high resolution and wide angles to obtain detailed images of the construction area. Configure the parameters of the monitoring devices, such as shooting height, shooting angle, and shooting interval. Usually, shooting is selected at critical moments of construction progress (such as weekly or monthly) for subsequent change comparison. Conduct panoramic image acquisition at the construction site to ensure coverage of the entire construction area, including the surrounding environment, construction material stacking areas, and construction equipment. Each image should contain at least two perspectives in the main directions for subsequent stitching and processing. During the acquisition process, maintain stable shooting conditions and avoid strong light, shadows, or other interfering factors that may affect the image quality and the accuracy of subsequent processing. Organize the acquired panoramic monitoring images, file them in chronological order, and record the shooting time and specific location of each image. This process helps with subsequent image analysis and comparison. Store the image data in a high-capacity storage device and make a backup to prevent data loss. Ensure that the data format is compatible with subsequent analysis tools (such as JPEG or PNG format). Obtain the initial BIM model of the construction design from the design team. This model should contain information on all key components, such as walls, columns, beams, pipes, and electrical systems. Use BIM software (such as Revit or Navisworks) to import this model. During the import process, ensure the integrity and accuracy of the model, especially paying attention to the attributes and relationships of the components. Verify the imported BIM model to ensure that the dimensions, materials, and positions of all components meet the design requirements. Compare with the design drawings to promptly discover and correct possible errors. Adjust the details of the model according to the construction requirements to ensure that the BIM model can effectively reflect the actual situation during the construction process. Archive the verified BIM model and record the relevant version information for subsequent iteration and update. During the project progress, update the model regularly to ensure that it reflects the latest design changes. Use image processing software (such as Photoshop or GIMP) to process the obtained panoramic monitoring images, including denoising, enhancing contrast, and detail clarity to improve the effect of subsequent analysis. Apply region segmentation algorithms (such as K-means clustering or image threshold segmentation) to analyze the images and identify different regions, such as buildings, construction areas, and the surrounding environment. Based on the processed image data, construct a three-dimensional model of the regional spatial structure. Use modeling software (such as SketchUp or 3dsMax) to three-dimensionalize the identified regions to ensure that the true situation of the spatial structure is reflected. During the modeling process, consider the functions and usage conditions of different regions to ensure the accuracy of the model. At the same time, record the characteristics and attributes of each region for subsequent use. Import the processed regional spatial structure model into the BIM software and combine it with the initial BIM model of the construction design to construct a complete construction scenario.Configure simulation parameters, including time settings, construction steps, and resource allocation, for real-time construction simulation. Run the 3D simulation, observe each link in the construction process, and identify potential conflicts and problems. By adjusting the simulation parameters, simulate different construction scenarios and conditions to ensure a comprehensive assessment of the feasibility of the construction process. Record the key data during the simulation, such as construction time, resource usage, and possible bottlenecks, for subsequent analysis and optimization. Export the simulation results as a 3D construction scene diagram, including images from different perspectives and key data, which can be used for the display of construction plans and decision-making support. Generate a detailed simulation report, including the simulation process, key data, and recommended optimization measures, to ensure the integrity and clarity of the information for the reference of the project team.

[0016] Step S2: Identify the information of prefabricated building components based on the initial BIM model of the construction design, and conduct the evolution of component assembly requirements to generate the characteristics of building component assembly requirements. In this embodiment, the initial BIM model of the construction design is imported into BIM software (such as Revit or Navisworks). Ensure that the model contains all necessary component information, including walls, beams, columns, floors, pipes, and electrical systems, etc. Conduct a comprehensive inspection of the imported model to confirm the integrity of information such as component types, dimensions, materials, and properties. Pay particular attention to the identifiers and classifications of components for subsequent identification and analysis. Use the data extraction tool in the BIM software to extract information on all prefabricated building components. Create a structured data table to record the type, material, dimension, quantity, and other relevant properties of each component. Combine the parametric design characteristics of the components to ensure that the extracted data can be flexibly updated to adapt to changes in the construction design. In this step, it is recommended to use the data screening and classification functions to more efficiently identify prefabricated components. Classify the extracted component information and mark prefabricated building components and non-prefabricated components. Ensure the accurate identification of all prefabricated components by comparing design standards and construction requirements. Assign a unique identifier to each prefabricated component and record its connection relationship with other components for subsequent assembly requirement analysis. Define the assembly requirements for each component based on the identified prefabricated building component information, which includes the installation sequence of components, required tools, mechanical equipment, and personnel allocation, etc. Determine the key parameters of the assembly requirements, such as the bearing capacity, fit accuracy, and installation time of each component. These parameters will be used for subsequent evolutionary analysis. Use system modeling tools (such as simulation software) to construct an assembly requirement evolution model. This model should consider the dependencies between components, changes in the construction environment, and possible risk factors for comprehensive analysis. Input the parameters of the assembly requirements into the model to simulate the component assembly process under different construction conditions and evaluate its impact on construction efficiency and safety. Run the assembly requirement evolution model to simulate the component assembly process. Observe the impact of different assembly sequences and methods on construction efficiency, time, and resource use. Based on the simulation results, adjust the assembly requirement parameters, optimize the component assembly sequence and method to determine the best assembly strategy. For example, different construction scenarios can be set to evaluate the assembly effect under different environmental conditions. According to the results of the evolutionary analysis, extract and organize the assembly requirement characteristics of building components, which include the assembly sequence of each component, required tools, time arrangement, and safety measures, etc. To ensure the integrity of information, record the source and calculation basis of each characteristic for subsequent verification and use. Organize the generated assembly requirement characteristics into a document to ensure that the information is clear and easy to understand. The document should contain the detailed assembly requirements and relevant parameters of each component for the construction team to refer to. Store the document and data in the project management system for all relevant personnel to access and update. Ensure the timeliness and accuracy of the information to support subsequent construction planning and management. After the assembly requirement characteristics are generated, communicate with the construction team regularly to collect feedback.Iteratively update the assembly requirement characteristics according to the problems and changes encountered during the construction process to ensure that they always meet the actual construction needs. Establish a continuous improvement mechanism to continuously optimize the assembly requirement characteristics during the construction process and improve construction efficiency and safety.

[0017] Step S3: Dynamically simulate and optimize the construction sequence of the three-dimensional construction scene diagram and the initial BIM model of the construction design based on the assembly requirement characteristics of building components, and construct a dynamically optimized construction sequence; In this embodiment, the integrity and consistency of the 3D construction scene diagram and the initial BIM model of the construction design are ensured. Import both into the same BIM software environment (such as Revit, Navisworks) to ensure that the components, spatial layout, and assembly requirement characteristics of the models can be effectively combined. Align the 3D scene diagram with the BIM model to confirm the accurate positions of the components in the 3D scene. At this time, pay special attention to the dimensions, materials, and assembly sequence of the components to ensure the accuracy of subsequent simulations. According to the assembly requirement characteristics generated in the previous steps, confirm information such as the assembly sequence, required tools, and resources for each component. Ensure that these characteristics can provide the necessary basis and parameters for the dynamic construction sequence. In the BIM software, add relevant assembly requirement characteristic tags to each component for subsequent dynamic simulation and optimization. Determine the specific parameters for the dynamic construction sequence simulation, including simulation time, resource allocation, construction steps, and their related constraints (such as weather, personnel, equipment, etc.). Record the numerical values and units of each parameter for subsequent analysis and optimization. For example, set the time for each construction step as the time required for each component's assembly, the availability of equipment, and the working hours of personnel, etc. In the BIM software, based on the assembly requirement characteristics and the set parameters, construct a simulation model of the dynamic construction sequence. This model will combine the assembly processes of all components to form a time-series construction plan. Use construction simulation tools (such as Synchro or Navisworks Simulate) to visualize the assembly process of the components to ensure the logic and feasibility of the construction sequence. Start the dynamic construction sequence simulation and observe the assembly process of the components. The system will automatically generate the construction progress according to the set parameters and assembly requirement characteristics and conduct real-time monitoring. During the simulation process, record the assembly time, resource usage, and possible conflicts of each component. This process will help identify potential bottlenecks and construction efficiency problems. According to the simulation results, analyze the assembly process of each component and evaluate its impact on the overall construction progress. Pay special attention to the assembly sequence, resource utilization rate, and time arrangement to identify areas that can be optimized. Collect simulation data, including the assembly time of each component, the usage efficiency of workers and equipment, etc. These data will provide a basis for subsequent optimization. After the dynamic simulation is completed, conduct an in-depth analysis of the recorded data to identify the bottlenecks and inefficient links in the construction sequence. For example, find out which components have too long assembly times or which resources are not fully utilized. Compare the simulation results of different construction sequences and analyze which adjustments can improve the overall construction efficiency, such as changing the assembly sequence, optimizing resource allocation, or adjusting the construction time. Based on the identified optimization opportunities, formulate specific optimization plans, which include rearranging the assembly sequence of the components, adjusting the working hours and task assignments of the construction team, etc. Verify the optimized construction sequence by running the simulation again to ensure the effectiveness and feasibility of the optimization measures. Record the optimized indicators for effect evaluation.Organize and document the optimized dynamic construction sequence, recording the assembly sequence, required resources, time schedule, and relevant parameters of each component. Ensure that the information is complete and clear for easy understanding and implementation by the construction team. Save the generated dynamic optimized construction sequence into the project management system for subsequent construction plan execution and monitoring. Ensure that all relevant personnel can access and update the latest construction plan in real time.

[0018] Step S4: Analyze the transportation paths of available materials for the three-dimensional construction scene diagram and plan the optimal operation paths for each material one by one, thereby generating the optimal operation path for each material; In this embodiment, to ensure the integrity of the 3D construction scene diagram, special attention is paid to all important elements within the construction area, including building components, passageways, obstacles, and storage areas. Use BIM software (such as Navisworks or Revit) to import the construction scene diagram. Update the construction scene in real time to ensure that all information (such as newly added components and materials) is up-to-date and accurate. Pay particular attention to the storage locations of materials and the availability of transportation tools. Employ path analysis tools to identify the available transportation paths in the construction scene diagram, and these paths should cover all possible routes from the material storage area to the construction points. Use image processing or spatial analysis techniques (such as Voronoi diagrams or Dijkstra's algorithm) for path identification. Mark all available paths and record the key parameters of each path, including the starting point, ending point, length, traffic capacity, and potential obstacles. This process will provide the basic data for subsequent optimal operation path planning. Organize the identified available material transportation paths into a data table to ensure the structuring of the information for each path. The table should contain information such as path ID, starting point, ending point, length, traffic conditions, and remarks. Visualize these paths in the 3D construction scene diagram to facilitate the construction team to quickly identify and select appropriate transportation routes during actual operations. According to the construction plan, identify the types, quantities of materials to be transported and their corresponding transportation requirements. Ensure that the transportation requirements for each material are accurately recorded, including the specific requirements from the storage area to the construction points. Determine the transportation tools and transportation conditions for each material, such as the type, load capacity, speed, and availability of transport vehicles. This information will be used for subsequent path planning. For each material, use the shortest path algorithm (such as the A* algorithm or Bellman-Ford algorithm) for operation path planning. Input the data of the available transportation paths, including the starting point, ending point, path length, and traffic conditions. Run the algorithm to calculate the optimal operation path for each material and record its path length, estimated transportation time, and possible bottlenecks. This process will help identify the factors affecting transportation efficiency. Compare the generated optimal operation path for each material with the actual conditions in the construction scene to evaluate its feasibility and efficiency. Pay attention to the transportation time, resource utilization, and potential conflict points. According to the analysis results, conduct necessary path optimization. For example, if certain paths are congested during peak hours, consider adjusting the transportation time or choosing alternative paths to improve transportation efficiency. Organize the results of the optimal operation path for each material into a data table, recording information such as path ID, starting point, ending point, path length, estimated transportation time, and transportation tools used for each material. Ensure that the information is structured and easy to understand, facilitating the construction team to refer to and use it during actual operations. Visualize the optimal operation path for each material in the 3D construction scene diagram to ensure that the construction team can clearly see the recommended transportation routes, which will help improve the coordination efficiency and safety of construction. Provide multiple perspectives of the paths to facilitate evaluation and selection under different construction conditions. Establish a real-time monitoring mechanism to track the actual situation of material transportation.Record any problems that occur during transportation, such as delays, conflicts, or poor paths, and compare the differences between the actual path and the optimal path. Based on the feedback information, continuously optimize the path planning and transportation plan to ensure that changes can be flexibly handled during the construction process and improve the overall construction efficiency.

[0019] Step S5: Make a decision on the intelligent construction design plan according to the dynamically optimized construction sequence and the optimal operation path of each material, and synchronize the detection of component position deviation to generate an instant synchronous twin construction model; In this embodiment, the dynamic optimization of the construction sequence and the optimal operation path of each material are integrated to ensure that all data is available on the same platform, which can be achieved through BIM software (such as Revit, Navisworks), ensuring the integrity and consistency of information. Confirm the specific parameters of the dynamic construction sequence, including the time arrangement, resource requirements, and material transportation path of each construction link. This information will provide basic data for the decision-making of intelligent construction design solutions. Establish an artificial intelligence-based decision support system (DSS) that can analyze the current construction data, combine the dynamic optimization of the construction sequence and the material transportation path, and generate intelligent construction design solutions. Use machine learning algorithms (such as decision trees, random forests, etc.) to analyze historical construction data, identify key factors affecting construction efficiency, and assist the decision-making process. Set reasonable decision-making indicators, such as construction period, cost, and safety. According to the analysis results, generate multiple intelligent construction design solutions and evaluate each solution. The evaluation criteria include construction efficiency, resource utilization rate, cost, and risk. Record the key parameters and expected effects of each solution to ensure the transparency and traceability of information. During this process, sensitivity analysis can be used to evaluate the impact of different parameter changes on the construction plan. Collect real-time data on the construction site, including the actual position and design position of components, which can be achieved through laser scanning, drone photography, or other measurement technologies, ensuring the accuracy and reliability of the data obtained. Set the deviation detection standard in the BIM software, define the allowable error range, such as the position deviation not exceeding 5 cm. Use computer vision technology or 3D scanning technology to monitor the construction site in real time and obtain the actual position data of components. Compare and analyze this data with the design position in the BIM model. Use data processing algorithms (such as the least squares method, Kalman filter, etc.) for deviation analysis, identify components with deviations, and record their specific deviation values and positions. Feed back the detected deviation information to the intelligent construction design solution for necessary adjustments, which includes rearranging the construction sequence, adjusting construction parameters, or dispatching additional resources for correction. Ensure that all relevant personnel can access the deviation detection results in real time to facilitate timely adjustment of the construction plan and ensure the smooth progress of the construction process. Based on the dynamic optimization of the construction sequence, the optimal operation path of materials, and real-time deviation detection data, construct an instantaneously synchronized twin construction model. The model should include all key parameters, such as component position, status, and assembly sequence. In the BIM software, compare the real-time data with the original model to ensure that the twin model can accurately reflect the actual situation of the construction site. Regularly update the data of the twin model to ensure its synchronization with the changes on the construction site, which can be achieved through an automated data collection and update system, ensuring the timeliness and accuracy of information. Each time an update is made, record the time, content, and reason for the update for subsequent auditing and traceability. Verify the generated instantaneously synchronized twin construction model to ensure its accuracy and reliability.The effectiveness of the model can be evaluated by comparing it with the on-site feedback from the construction team and the actual construction situation. Applying the twin model to construction management and decision support helps the construction team to keep track of the construction progress, resource usage, and potential risks in real time, improving construction efficiency and safety.

[0020] Step S6: Based on the instant synchronous twin construction model, perform on-site construction deviation elimination and compensation processing, and conduct cloud data collaborative management synchronization to build an instant construction optimization management engine.

[0021] In this embodiment, by using the instant synchronous twin construction model, the on-site construction deviations are first comprehensively analyzed, which includes comparing the actual positions of the components with the designed positions to confirm the deviation conditions of each component. At this time, the deviation values, types (such as horizontal deviation, vertical deviation), and influence degrees of each component should be recorded. Set the processing standards for deviation elimination, such as the allowable deviation range (such as ±5 cm), and formulate corresponding compensation strategies, which include adjusting the positions of components, redesigned connection methods, or adding support structures, etc. According to the results of the deviation analysis, implement specific compensation measures. For components with large deviations, it may be necessary to use laser measurement tools for precise positioning and adjust the positions by mechanical means (such as cranes or electric pulleys). When implementing the compensation, ensure that all relevant personnel understand the compensation plan and carry out effective collaboration and communication to avoid confusion and misunderstandings during the construction process. During the compensation process, record the adjustment situation and tools used at each step for subsequent tracking. During the compensation process, use real-time monitoring devices (such as laser scanners or drones) to re-detect the adjusted components to ensure that their positions meet the design requirements. Make necessary adjustments according to the real-time monitoring data. If new deviations are found, make secondary adjustments in a timely manner to ensure that the construction quality meets the expected standards. Record the data of each adjustment for subsequent analysis and optimization. After the compensation process is completed, collect all relevant data, including deviation detection results, implementation of compensation measures, real-time monitoring data, etc. These data should be sorted in a structured form to ensure the clarity and traceability of information. Upload all data to the cloud data management platform to ensure that all team members participating in the project can access the latest data in real time. Use a secure API interface for data interaction to ensure the security and integrity of the data. On the cloud platform, establish a data sharing mechanism that allows different teams (such as construction, design, and management teams) to access and edit the data in real time. Ensure the timeliness and accuracy of information sharing to improve the efficiency of collaborative work. Set the data update frequency (such as every hour or every time the status changes) to ensure that all relevant personnel always have the latest construction progress and deviation handling situation. Use the analysis tools on the cloud platform to deeply analyze the uploaded data, identify common problems and potential risks that occur during the construction process, which can be achieved through machine learning algorithms and data visualization tools, and help the team adjust the construction strategy in a timely manner. Feed back the analysis results to the on-site construction team to provide data-driven decision-making support to ensure the efficiency and accuracy of the construction process. Build an instant construction optimization management engine that integrates real-time monitoring data, cloud analysis results, and construction progress information. The engine should have real-time data processing, analysis, and decision-making support functions to improve the intelligent level of construction management. Design the user interface of the engine to ensure easy operation and understanding, so that the construction team can quickly obtain the required information and suggestions.The functional modules of the development engine include a data collection and processing module, a real-time monitoring module, an analysis and prediction module, and a decision support module. Ensure that each module can be seamlessly integrated and share data in real time. Integrate a feedback mechanism that allows the construction team to adjust the construction plan based on real-time data and analysis results, enhancing the flexibility and response speed of the construction process. After the engine is built, conduct system testing to ensure that the functions of each module are normal, and the timeliness and accuracy of data transmission and processing. Verify the effectiveness and reliability of the engine by simulating different construction scenarios. Make necessary optimizations based on the test results to ensure the efficient operation of the engine in actual construction. Record the problems encountered during the test and the solutions to form a document for system optimization for future reference.

[0022] In this embodiment, refer to Figure 2 , which is a schematic diagram of the detailed implementation steps of step S1. In this embodiment, the detailed implementation steps of step S1 include: Step S11: Obtain the panoramic monitoring image of the building area and the initial BIM model of the construction design; Step S12: Perform regional spatial structure evolution on the panoramic monitoring image of the building area to generate building area spatial structure data; Step S13: Calculate the floor area of the building to be constructed according to the initial BIM model of the construction design and extract the floor area; Step S14: Analyze the spatial boundary conditions of the initial BIM model of the construction design to generate the building construction spatial boundary conditions; Step S15: Identify construction space restrictions based on the building floor area and the building construction spatial boundary conditions to generate construction space restriction features; Step S16: Perform 3D simulation of the construction scenario on the building area spatial structure data and the construction space restriction features to construct a 3D construction scenario diagram.

[0023] In this embodiment, multiple monitoring points are set at the construction site, and high-resolution panoramic cameras are used for image acquisition. These monitoring points should cover the entire building area to ensure a comprehensive perspective. Each camera should be able to capture 360 ​​degrees of the surrounding environment and record the construction progress and changes in the surrounding environment. Ensure that the lighting and weather conditions are good during video shooting to improve image quality. During shooting, multiple acquisitions can be performed at different time periods to provide time series data for subsequent analysis. Obtain the initial BIM (Building Information Model) model of the construction project from the design team. The model should contain the geometric information, material information, construction requirements and other important parameters of the building. Ensure that the acquired BIM model format is compatible with subsequent analysis software (such as Revit, Navisworks, etc.), and perform necessary checks on the model to ensure its integrity and accuracy. Use computer vision technology to process the acquired panoramic monitoring images. Through the image segmentation algorithm, the building area is extracted from the background, and the outline and main structure of the building are identified. A deep learning model (such as a convolutional neural network) is used for feature recognition to extract the spatial relationship and position of different structural elements (such as walls, ground, columns, etc.) in the building area. Combined with time series monitoring data, analyze the spatial structural evolution of the building area. By comparing the panoramic views at different time points, identify the changes in the building structure (such as new components, demolished parts, etc.). Generate spatial structural data of the building area, including the location, size and relationship of spatial elements, and store them in appropriate data formats (such as CSV, JSON, etc.) for subsequent analysis and simulation. Use BIM software (such as Revit or Navisworks) to import the initial BIM model and use the area calculation function of the software to automatically calculate the building's footprint. Make sure to select the correct view (such as the floor plan view) to accurately reflect the boundaries of the building. According to the building design specifications, confirm whether the relevant parameters of the building's exterior (such as balconies, eaves, etc.) are considered during the calculation process to ensure that the extracted footprint meets the actual construction requirements. Cross-validate the calculated building footprint with the design drawings to ensure the accuracy and consistency of the data. If differences are found, communicate with the design team in a timely manner to find out the reasons and make adjustments. Record the footprint calculation results and organize them into a report for subsequent construction planning and resource allocation. Define the boundary conditions of the construction space in the BIM model, mainly including the external boundaries of the building, internal partitions, and the distance to other buildings. Use the analysis tools of the BIM software to visualize the spatial boundary conditions of the model. Set the spatial restriction factors that may be encountered during the construction process, such as the safe distance to adjacent buildings and traffic flow lines, so that they can be followed in subsequent construction. Use the analysis plug-in in the BIM software (such as Navisworks' conflict detection) to conduct a comprehensive analysis of the spatial boundary conditions, identify potential spatial conflicts and restrictions, and ensure the safety and feasibility of the construction process.Generate a boundary condition analysis report, record the specific parameters and restrictions of the spatial conditions for reference in the construction plan design. Combine the building floor area and spatial boundary conditions to identify restrictions in the construction area. Determine which areas can be constructed and which areas are restricted from construction due to safety or legal reasons. Use spatial analysis tools (such as GIS software) to overlay the building floor area with the surrounding environment to identify the spatial restriction characteristics of the construction area. Determine the construction space restriction characteristics and record which areas are restricted due to proximity to buildings, public facilities, traffic flow lines, etc. Organize these characteristics in graphical and text forms to form a construction space restriction characteristics report. This report should list in detail all restricted areas and their reasons to provide a basis for the subsequent formulation of the construction plan. Utilize the spatial structure data of the building area and the construction space restriction characteristics to construct a 3D model of the construction scenario in 3D modeling software (such as SketchUp, 3dsMax, etc.). Ensure that the model accurately reflects the actual building structure and construction restrictions. Apply materials and lighting effects in the model to enhance the realism of the scenario and make the simulation effect more intuitive. Run the 3D simulation program to simulate various links in the construction process, including equipment layout, personnel flow, material storage, etc. Observe possible problems during the construction process, such as space conflicts and flow bottlenecks. Record the simulation results, generate construction scenario diagrams, and attach analysis conclusions in the report, such as data on construction efficiency, space utilization rate, etc., to provide decision-making support for construction management.

[0024] In this embodiment, the specific steps of step S12 are as follows: Perform global brightness enhancement processing on the panoramic monitoring image of the building area to obtain a globally brightness-enhanced monitoring image; Perform regional terrain visual recognition on the globally brightness-enhanced monitoring image to generate regional terrain features; Mark the surrounding buildings according to the globally brightness-enhanced monitoring image; Calculate the spatial area parameters of the surrounding buildings; Perform regional obstacle analysis based on the globally brightness-enhanced monitoring image and mark all regional obstacle nodes; Perform precise traffic flow visual analysis on the globally brightness-enhanced monitoring image and extract all traffic flow lines; Based on the regional terrain features, the spatial area parameters, all regional obstacle nodes, and all traffic flow lines, perform the evolution of the spatial structure of the building area to generate the spatial structure data of the building area.

[0025] In this embodiment, initial panoramic monitoring images are collected, ensuring good quality and covering the required building area. Select a suitable image format (such as JPEG or PNG) to ensure the retention of image details. Perform image preprocessing, such as denoising, to reduce the impact of random noise in the image. This step can use methods such as median filtering or Gaussian filtering. Apply global brightness enhancement algorithms, such as histogram equalization or contrast-limited adaptive histogram equalization (CLAHE), to improve the overall brightness and contrast of the image. These algorithms can improve the visual effect of the image and make details more obvious. When applying the algorithms, set parameters to avoid over-enhancement, such as limiting the enhancement amplitude, to ensure that the naturalness of the image is not damaged. Record the brightness histograms before and after enhancement for subsequent analysis. Conduct a visual inspection of the enhanced image to ensure that details in all areas are clearly visible. It can be compared with the original image to verify the effect of brightness enhancement. Save the enhanced image in a new file format and record the relevant processing parameters (such as algorithm type, parameter settings) for reference in subsequent steps. Use the enhanced monitoring image as input and utilize computer vision technology for regional terrain recognition. Select an appropriate image segmentation method, such as K-means clustering or edge detection algorithms (such as Canny edge detection), to identify different regions of the terrain. Apply a deep learning model (such as a convolutional neural network) for the recognition of regional terrain features. These models are trained to recognize different features in the terrain, such as slopes, flat areas, and obstacles. During the recognition process, ensure the accuracy and robustness of the model, and regularly evaluate and adjust it. Use the validation set to evaluate the performance of the model. Organize the recognized terrain feature data into a structured format, such as a table or database, and record the feature information of each region (such as elevation, area, type, etc.). Generate a visualization image of the terrain features to intuitively display the terrain features of different regions and provide support for subsequent analysis. Using the enhanced image, first perform image preprocessing to more clearly identify the outlines of surrounding buildings. This step includes further noise filtering and contrast adjustment. Apply object detection algorithms (such as YOLO or Faster R-CNN) to identify and mark the surrounding buildings. These algorithms can quickly and accurately identify the buildings in the image and give their bounding boxes. During the marking process, ensure the accuracy of the model, and evaluate the accuracy rate and recall rate through cross-validation. Conduct a manual review of the recognition results to ensure the accuracy of the markings. Organize the marked building area and location data into a report, including the attribute information of each building (such as height, area, usage function, etc.). Generate a visualization diagram indicating the specific locations and markings of each building. Save the marked image and enter the building information into the database for subsequent analysis. Using the marked building data, select an appropriate geometric calculation method to calculate the spatial area of each building. Usually, the bounding box data of the building can be used for a preliminary estimate.For each marked building, extract its boundary coordinates and calculate the actual spatial area using geometric formulas (such as the polygon area calculation formula). For buildings with complex shapes, numerical integration or Monte Carlo methods can be used for area estimation. Record the calculation parameters and results of each building to ensure the accuracy and consistency of the data. Organize the calculated building spatial area parameters into a table form, including information such as building name, spatial area, and relative position. Save the calculation results and provide the necessary support for subsequent analysis. Use the enhanced monitoring images and apply image segmentation techniques (such as threshold segmentation or region growing) to identify potential obstacles in the images. Ensure that the contrast in the images is obvious to improve the recognition accuracy. Adopt a deep learning model (such as Mask R-CNN) to detect and mark the obstacles in the area. This model can effectively identify obstacles in complex environments and mark their positions. During the detection process, regularly evaluate the performance of the model to ensure its robustness and accuracy under different environmental conditions. Organize the detected obstacle node information into structured data, including the type, position, size, etc. of the obstacles, and generate an obstacle marking map. Save the obstacle analysis results and enter the data into the database for subsequent use. Use the enhanced images and apply motion detection techniques to analyze the traffic flow lines. Select a suitable algorithm, such as the background subtraction method, to extract the dynamic traffic flow information. Adopt the optical flow method or clustering analysis techniques to analyze the traffic flow in the images and extract the traffic flow lines. For static images, edge detection and path analysis can be used to identify the main direction of the traffic flow. During the analysis process, ensure that the traffic flow changes at different times can be identified, and record the peak flow time periods and the flow line directions. Organize the extracted traffic flow line data into a table, including information such as the position, flow rate, and flow direction of the flow lines, and generate a visualization image of the traffic flow lines. Save the analysis results and provide support for subsequent traffic management and planning. Integrate the previously extracted regional terrain features, spatial area parameters, obstacle nodes, and traffic flow line information to construct a spatial structure evolution model of the building area. Select a suitable modeling tool (such as GIS software or 3D modeling software) for integration. Simulate the evolution process of the spatial structure of the building area and analyze the influence of different factors (terrain, buildings, obstacles, traffic flow lines) on the spatial structure. Use spatial analysis techniques to identify possible evolution paths and future development directions. During the simulation process, record the influence of different parameters on the spatial structure evolution to ensure the accuracy and integrity of the data. Organize the generated spatial structure data of the building area into a report, including detailed analysis results, visualization charts, evolution models, and future planning suggestions.

[0026] In this embodiment, refer to Figure 3 , which is a schematic diagram of the detailed implementation steps of step S2. In this embodiment, the detailed implementation steps of the said step S2 include: Step S21: Identify the information of prefabricated building components based on the initial BIM model of the construction design; Step S22: Calculate the external dimensions of the prefabricated building component information to generate external dimension parameters; Step S23: Conduct three-dimensional form analysis based on the external dimension parameters to generate the three-dimensional form characteristics of each building component; Step S24: Extract the installation surface of the component according to the prefabricated building component information and conduct connection method analysis to generate the connection method of the building component; Step S25: Conduct assembly conflict analysis between components based on the connection method of the building component and the three-dimensional form characteristics of each building component to generate geometric space conflict data for component assembly; Step S26: Mine the pre-dependence relationship of the installation sequence based on the initial BIM model of the construction design to obtain the dependence rule of the component installation sequence; Step S27: Evolve the geometric space conflict data of component assembly and the dependence rule of component installation sequence to generate the assembly requirement characteristics of building components.

[0027] In this embodiment, obtain the initial BIM model of the construction design from the design team to ensure that the model contains information on all prefabricated building components. Import the model using BIM software (such as Revit or Navisworks). Check the imported model to ensure its integrity and accuracy, paying particular attention to the information tags, attributes, and their relationships of the components. Verify whether the model contains all important component types, such as walls, beams, columns, floors, etc. In the BIM software, use the component classification and attribute filtering functions to extract the component information of the prefabricated building. Create a structured data table to record the type, material, size, quantity, and other relevant attributes of each component. Use parametric design tools to ensure that the extracted data can be updated flexibly to reflect the latest component information in a timely manner when the construction design changes. Define the external dimension parameters based on the identified prefabricated building component information. The external dimensions include basic indicators such as length, width, height, and volume, and these parameters will be used for subsequent component form analysis and assembly analysis. Use the measurement tools in the BIM software to calculate the dimensions of each component. Select an appropriate view (such as a 3D view or a sectional view) to ensure accurate measurement. For components with complex shapes, apply geometric calculation methods (such as polygon area and volume calculation formulas) to obtain accurate external dimension parameters. Ensure that the specific dimensions and calculation methods of each component are recorded. Organize the calculated external dimension parameters into a table, including the type of each component and its corresponding dimension data. Ensure that the table format is clear for subsequent analysis and reference. Save the external dimension parameter data and provide a basis for subsequent 3D form analysis. Use the external dimension parameters as input and select an appropriate 3D modeling software (such as SketchUp, 3ds Max, or Fusion 360) for 3D form analysis. Ensure that the software can handle the complex geometries of prefabricated building components. Based on the external dimension parameters, establish 3D models for each prefabricated building component. Apply parametric design methods to ensure the flexibility and adjustability of the models to adapt to subsequent design changes. During the modeling process, ensure that the shape, proportion, and details of each component are consistent with the design requirements, and use appropriate materials and textures to enhance the realism of the models. Organize the 3D form feature data of each component into a structured format, recording the geometric information of each component (such as vertex coordinates, bounding box dimensions, etc.). Save the 3D model files and associate the form feature data with the BIM model for subsequent analysis and simulation use. Based on the information of the prefabricated building components, determine the installation surface of each component. The installation surface refers to the surface where components are connected, and it usually needs to be located on a specific plane or boundary. In the BIM software, extract the installation surface using the geometric information of the components and the connecting parts. Ensure that the connection methods of different types of components are identified (such as bolt connection, welding, plug-in connection, etc.). Combine the material properties of the components to analyze the impact of different connection methods on the structural performance. For example, evaluate the load-bearing capacity and fatigue performance of bolt connections.Collect data on the connection methods and three-dimensional morphological characteristics of building components for assembly conflict analysis. Ensure the data is complete and covers all relevant component information. Use conflict detection tools (such as Navisworks) in BIM software to perform geometric space conflict analysis on the components. Set appropriate conflict detection parameters to capture all possible spatial conflicts. Run the conflict detection program, and the system will automatically identify and mark all spatial conflicts between components and generate a conflict report. Organize the detected geometric space conflict data into a report, including information such as the names of conflicting components, conflict types, locations, and solution suggestions. Save the conflict analysis results for subsequent use in the evolution of assembly requirements and the adjustment of construction plans. Analyze the installation sequence and dependencies of each component in the initial BIM model of the construction design. Dependencies mean that the installation of some components must be completed before others. Use construction scheduling software (such as Primavera P6 or Microsoft Project) to perform pre-dependency analysis on the components. By inputting the installation information and construction requirements of the components, establish a logical relationship diagram of the installation sequence. Ensure that all key factors are considered, such as the supporting role and interconnection relationship of the components, to accurately identify dependencies. Organize the analysis results into a dependency table, recording the installation sequence and pre-dependency relationship of each component. Ensure that the data format is clear for subsequent scheduling and construction plan formulation. Collect the geometric space conflict data of component assembly and the dependency rules of component installation sequence for assembly requirement evolution analysis. Combine the conflict data and dependency rules to conduct assembly requirement evolution analysis. Use decision trees or optimization algorithms to identify how to reduce conflicts and optimize assembly requirements under different assembly sequences. During the analysis process, consider construction safety, efficiency, and material utilization rate to ensure that the generated assembly requirement characteristics meet the actual construction conditions. Organize the evolution analysis results into a building component assembly requirement characteristics table, recording the specific requirements of the assembly, the recommended assembly sequence, and possible conflict solutions. Save the assembly requirement characteristic data for subsequent use in the formulation of construction plans and strategies.

[0028] In this embodiment, refer to Figure 4 , which is a schematic diagram of the detailed implementation steps of step S3. In this embodiment, the detailed implementation steps of step S3 include: Step S31: Based on the assembly requirement characteristics of building components, perform a full-process digital assembly simulation on the three-dimensional construction scene diagram and the initial BIM model of the construction design to construct a virtual building construction model; Step S32: Perform a time-series analysis of all construction links on the virtual building construction model to generate a full-cycle construction link sequence; Step S33: Perform a construction space logic analysis on the full-cycle construction link sequence to generate construction space logic data; Step S34: Based on the construction space logic data, identify spatial interference conflict points and mark the conflict links; Step S35: Speculate on construction bottlenecks for the construction space logic data to generate construction bottleneck speculation data; Step S36: Optimize the dynamic construction sequence based on the conflict links and the construction bottleneck speculation data to construct a dynamically optimized construction sequence.

[0029] In this embodiment, the assembly requirement characteristics of building components, 3D construction scene diagrams, and the initial BIM model of the construction design are collected. These data will be used to construct a virtual building construction model. Ensure that all data formats are compatible and can be integrated in the same modeling software. Import the initial model into the BIM software and combine the assembly requirement characteristics with the 3D construction scene diagrams to ensure that the connection methods and assembly sequences of the components are accurately reflected. Use the simulation function of the BIM software to perform digital assembly simulations on the building components. According to the assembly requirement characteristics, gradually construct the virtual construction model according to the preset assembly sequence and connection method. During the assembly process, monitor the connection conditions between the components in real time to ensure compliance with the design requirements. Use parametric modeling tools so that when the model is adjusted, all related components can be automatically updated. After completing the virtual building construction model, verify the model to ensure that the dimensions, positions, and connection methods of all components meet the design standards. Identify potential design defects by comparing with the actual construction conditions. Make necessary adjustments according to the verification results to ensure the accuracy and feasibility of the model, and save the final model in a format that can be used for subsequent analysis. In the virtual building construction model, define each construction link, including foundation, structure, mechanical and electrical installation, and decoration, etc. Each link should clearly define its start and end times, the components and processes involved. Use construction scheduling software (such as Primavera P6 or Microsoft Project) to perform a full-link time sequence analysis on the virtual model. This process involves inputting the construction period, resource requirements, and dependencies of each link to establish a logical model of the construction cycle. Through the functions of the software, generate a full-cycle construction link sequence, recording the time arrangement, resource allocation, and construction responsibilities of each link. Collect the full-cycle construction link sequence data and prepare for the spatial logic analysis of the construction. Ensure the integrity and accuracy of the data for subsequent analysis. Use logical analysis tools (such as graph theory analysis or Petri net models) to perform spatial logic analysis on the construction links. By establishing the relationships between nodes and edges, identify the logical relationships and dependencies between each construction link. During the analysis process, consider the limitations of the construction space and the availability of resources to ensure that the generated spatial logic data reflects the real construction environment. Organize the analysis results into a construction spatial logic data table, recording the spatial relationships, dependency sequences, and potential conflict points of each link. Ensure that the data format is clear for easy subsequent reference. Save the logical data and provide support for the subsequent identification of spatial interference conflict points. Collect the construction spatial logic data and prepare for the identification of spatial interference conflict points. Clearly define the logical relationships and spatial occupancy situations between the construction links for easy analysis. Apply conflict detection tools (such as Navisworks or Space Syntax) to perform spatial interference analysis on the construction links. By setting the detection parameters, the system will automatically identify the spatial conflicts between the construction links. During the analysis process, record the specific locations of each conflict point, the construction links involved, and the conflict types to ensure the integrity of the detailed information.Organize the identified conflict links into a report, including descriptions of conflicts, impact analysis, and suggestions for solutions. Ensure that the report is well-structured and easy for the construction team to understand and implement. Save the conflict identification results for subsequent adjustment and optimization of the construction plan. Collect construction space logic data to prepare for speculation analysis of construction bottlenecks. Clearly define the resource requirements, time arrangements, and space occupancy of each link for in-depth analysis. Use bottleneck analysis tools (such as linear programming or simulation software) to analyze the construction space logic data and identify possible construction bottlenecks, which include factors such as resource limitations, time delays, and space conflicts. During the speculation process, monitor the resource utilization rate and time arrangements of each link to ensure the accuracy and feasibility of the speculation results. Organize the speculated construction bottleneck information into a report, recording the specific situation, impact degree, and possible solutions of each bottleneck. Ensure that the information is clear and easy to understand. Save the bottleneck speculation results for subsequent dynamic construction sequence optimization. Collect conflict link and construction bottleneck speculation data to prepare for dynamic construction sequence optimization. Clearly define the time arrangements, resource requirements, and space occupancy of each link for optimization analysis. Use optimization algorithms (such as genetic algorithms or simulated annealing) to optimize the construction sequence. By inputting conflict information and bottleneck data, the system will automatically generate the optimal construction sequence to minimize the impact of conflicts and bottlenecks. During the optimization process, monitor the construction period and resource allocation of each link in real time to ensure that the generated construction sequence can improve construction efficiency and safety. Organize the optimized construction sequence into a document, recording the time arrangements, responsibility assignments, and resource requirements of each link. Ensure that the information is clear and convenient for the construction team to implement. Save the dynamic optimized construction sequence data for subsequent construction management and plan adjustment.

[0030] In this embodiment, step S4 includes the following steps: Step S41: Monitor the material transportation process of the virtual building construction model to identify material transportation process data; Step S42: Analyze the available material transportation paths of the three-dimensional construction scene diagram and extract all available transportation paths; Step S43: Mark the nearest stacking point and the destination construction point of each material according to the material transportation process data; Step S44: Calculate the material transfer distance based on the nearest stacking point and the destination construction point to generate the material transfer distance; Step S45: Plan the optimal transfer path for each material for all available transportation paths according to the material transfer distance, thereby generating the optimal transfer path for each material.

[0031] In this embodiment, in the virtual building construction model, monitoring points are set to track the transportation process of materials. The monitoring points should cover the main transportation routes and key construction areas to ensure that the dynamics of material transportation can be comprehensively captured. Determine the key parameters for monitoring, including material types, transportation time, transportation tools, transportation routes, and transportation volume. These parameters will be used for subsequent data analysis. Start the material transportation monitoring system to record the transportation process of materials in real time. Use sensors and monitoring technologies (such as RFID tags, GPS positioning) to track the movement of materials to ensure the accuracy and timeliness of data. During the monitoring process, record information such as the starting point, ending point, time taken, and transportation tools used for each material transportation. In the three-dimensional construction scene diagram, clarify the layout of the construction site, including buildings, roads, stacking areas, and construction areas. Ensure that all key elements are accurately represented in the model for path analysis. Use path analysis tools (such as the shortest path algorithm or Dijkstra algorithm) to analyze the three-dimensional scene diagram to identify all available material transportation paths. Consider the spatial limitations and safety requirements of the construction site to ensure the rationality of the paths. During the analysis process, record the length, traffic capacity, and potential obstacles of each available path for subsequent evaluation and optimization. Organize the extracted available transportation paths into a report, including detailed information about each path (such as starting point, ending point, length, traffic conditions, etc.). Ensure that the information is clear for the understanding and application of the construction team. Save the path analysis results for subsequent calculation of material transfer distances and optimal path planning. According to the material transportation process data, analyze the stacking points and construction points of each material. The stacking point refers to the temporary storage location of materials at the construction site, while the construction point is the location where the materials are finally used. Associate the material transportation process data with the layout information of the construction site to mark the nearest stacking point and the destination construction point of each material. The use of geographic information system (GIS) technology can help accurately locate these points in the model. During the marking process, ensure that the material types, expected transportation routes, and construction priorities are considered to ensure the accuracy and practicality of the marking. Organize the marked stacking point and construction point information into a data table, recording the nearest stacking point of each material and its corresponding destination construction point, ensuring that the information is complete and clear. Collect the information of the nearest stacking point and the destination construction point to prepare for the calculation of material transfer distances. Ensure that the coordinates and distance measurement units of all points are consistent for subsequent calculations. Use the Euclidean distance formula or Manhattan distance formula to calculate the transfer distance for each pair of stacking points and construction points. Select a calculation method suitable for the construction site layout to ensure the accuracy of the results. During the calculation process, consider the actual transportation conditions, such as road layout, obstacles, and traffic restrictions, to more accurately reflect the actual transportation distance. Organize the calculated material transfer distances into a data table, including the nearest stacking point, destination construction point, and their corresponding transfer distances for each material, ensuring that the information is clear and easy to understand.Collect data on the running distance of materials and available transportation routes for optimal running route planning. Ensure the integrity of all data for effective analysis. Use route planning algorithms (such as the A* algorithm or genetic algorithm) to plan the optimal running route for each material. Generate the shortest and most efficient transportation route based on the nearest stacking point, destination construction point, and available transportation routes of the material. Consider the characteristics of the transportation vehicle, load capacity, and actual situation of the construction site during the planning process to ensure the feasibility and safety of the route. Organize the optimal running route of each material into a data table, recording information such as the starting point, ending point, passed route, and total running distance of the route, ensuring the content is complete and easy to reference. Save the optimal running route data to provide a basis for subsequent material transportation plans and ensure the efficiency and smoothness of the construction process.

[0032] In this embodiment, step S5 includes the following steps: Step S51: Make an intelligent construction design plan decision based on the dynamically optimized construction sequence and the optimal running route of each material, and construct an intelligent construction decision plan; Step S52: Execute on-site building construction operations based on the intelligent construction decision plan and collect real-time building construction monitoring videos; Step S53: Perform stereo vision positioning of the assembled components on the real-time building construction monitoring video and extract the positioning coordinates of the assembled components; Step S54: Detect the position deviation of the components on the virtual building construction model based on the positioning coordinates of the assembled components and mark the component nodes with position deviations; Step S55: Perform instant synchronization processing on the virtual building construction model according to the component nodes with position deviations to generate an instant synchronization twin construction model.

[0033] In this embodiment, data on the dynamically optimized construction sequence and the optimal operation path of each material are collected. These data will serve as the basis for the intelligent construction decision-making plan to ensure the integrity and accuracy of all information. Integrate these data in project management software to create a comprehensive database that records the time schedule, resource requirements, and material transportation paths for each construction link. Use a decision support system (DSS) and artificial intelligence algorithms (such as machine learning, genetic algorithms) to construct an intelligent construction design plan. Set the input variables of the decision model, including the construction sequence, material requirements, transportation paths, and on-site resources. Evaluate the feasibility and efficiency of different construction plans through a multi-dimensional analysis model to ensure that optimal decision-making suggestions can be provided to the construction team. Generate an intelligent construction decision-making plan and transform it into a specific construction plan, including the responsible person, resource allocation, and time nodes for each link. Ensure the implementability and rationality of the plan. Conduct simulation verification on the generated plan to evaluate its performance in actual construction and ensure that the expected goals are achieved in terms of resource utilization, time management, and safety. Make preparations at the construction site according to the intelligent construction decision-making plan to ensure that all necessary resources (such as manpower, materials, and equipment) are in place. Communicate the construction plan to the construction team to ensure that the responsibilities for each link are clear. Develop a detailed construction schedule to arrange the time and sequence of various construction activities to ensure the efficiency of the construction process. Deploy a video monitoring system, select high-definition camera equipment suitable for the construction site to ensure that the construction process can be monitored comprehensively. Set the video acquisition frequency to obtain real-time construction data. Ensure that the camera equipment is well connected to the monitoring system and can transmit video data to the central monitoring platform in real time for subsequent analysis and recording. During the construction process, collect real-time construction monitoring videos and record the progress of each construction link. Ensure the integrity and clarity of the video files for subsequent analysis. Regularly check the monitoring equipment to ensure its normal operation and promptly handle possible failures to ensure the continuity and reliability of the video data. Import the collected real-time monitoring videos into visual analysis software for preprocessing. This includes denoising, enhancing contrast, and adjusting colors to improve the effect of subsequent analysis. Set the analysis parameters to ensure that the software can accurately identify the assembled components in the video. Apply stereo vision positioning algorithms (such as structured light, stereo matching, or deep learning models) to analyze the video. Through computer vision technology, identify the positions of each assembled component and extract their three-dimensional coordinates. During the analysis process, record the recognition accuracy and positioning error of each component to ensure the accuracy of the data. Organize the extracted positioning coordinates of the assembled components into a data table, including the ID, position coordinates, and status information of each component during the construction process. Ensure the structuring of the data for easy subsequent analysis and use. Save the positioning coordinate data for subsequent deviation detection and synchronization processing. Collect the component position data in the virtual building construction model and the real-time extracted positioning coordinates of the assembled components to prepare for position deviation detection. Ensure that the formats of all data are consistent for effective comparison.Use the geometric error analysis method to compare the positions of components in the virtual model with the actual positioning coordinates, and identify the position deviations. Set an error threshold to determine which components have deviations exceeding the allowable range. During the detection process, record the specific positions, deviation values, and their impact degrees of each deviated component to ensure the accuracy and integrity of the data. Organize the detected position deviation component nodes into a report, including the deviation information, position coordinates, and recommended adjustment plans for each component. Ensure that the report content is clear and easy to understand. Mark the deviated component nodes in the virtual building construction model for subsequent real-time synchronization processing and adjustment. Collect the information of the position deviation component nodes for preparing the synchronization processing of the virtual building construction model. Ensure the integrity and accuracy of all deviation data for effective adjustment. Adopt virtual reality (VR) technology or augmented reality (AR) technology to perform real-time synchronization processing on the virtual building construction model. According to the information of the deviated component nodes, update the positions of the components in the model in real time. During the synchronization process, ensure that the updated model is consistent with the actual construction site for subsequent management and decision-making. Save the processed virtual building construction model as a real-time synchronized twin construction model, recording the latest status and position of each component. Ensure the accuracy and real-time nature of the model to support the monitoring and management of the construction process. Save the synchronized model and associate it with the actual situation of the construction site for subsequent analysis and decision-making support.

[0034] In this embodiment, step S6 includes the following steps: Step S61: Perform component error compensation calculation on the position deviation component nodes to obtain the component error compensation value; Step S62: Adjust the construction parameters based on the component error compensation value to generate the component construction compensation adjustment parameters; Step S63: Perform iterative simulation compensation based on the component construction compensation adjustment parameters to generate multiple component construction compensation results; Step S64: Extract the optimal compensation result based on the multiple component construction compensation results; Step S65: Perform on-site construction deviation elimination compensation processing based on the optimal compensation result, and perform cloud data collaborative management synchronization to construct a real-time construction optimization management engine.

[0035] In this embodiment, information on the nodes of the position deviation components is collected, including the current positioning coordinates and design coordinates of each component. Ensure that all data formats are consistent for effective comparison. Determine the calculation model for error compensation, including the deviation type (such as linear, angular, etc.) and the compensation method (such as linear interpolation or curve fitting). Using the error calculation formula, calculate the error value for each component. The formula is generally: Compensation value = Design coordinate - Actual coordinate. Ensure that the compensation value is calculated separately for each direction (X, Y, Z). During the calculation process, record the error compensation values for each component, including positive and negative deviations, for subsequent analysis and adjustment. Organize the calculated component error compensation values into a data table, including the ID, error value, compensation value, and calculation method of each component. Ensure the structuring of the data for subsequent analysis and use. Save the results of the error compensation calculation to provide a basis for adjusting construction parameters. Collect the component error compensation values and relevant construction parameter information, including construction technology, material properties, and construction equipment, etc. These information will be used to determine the specific adjustment parameters. According to the error compensation values, formulate a construction parameter adjustment plan. The parameters that may be involved include the installation angle, position, applied force, and possible construction sequence of the components. Use optimization algorithms (such as linear programming or genetic algorithms) to determine the optimal parameter adjustment plan to ensure that the construction effect after compensation meets the design requirements. Organize the generated component construction compensation adjustment parameters into a data table, recording the adjustment parameters of each component and their calculation basis. Ensure that the information is complete and clear for the construction team to understand and implement. Save the adjustment parameter data to provide a basis for subsequent iterative simulation compensation. Collect the component construction compensation adjustment parameters and prepare for iterative simulation compensation. Ensure the accuracy and consistency of all parameters for effective simulation. Use simulation software (such as Revit, Navisworks, etc.) to perform iterative simulation of construction compensation. According to the adjustment parameters, gradually adjust the position of the components and observe its impact on the overall construction effect. Set reasonable iteration times and convergence conditions to ensure the stability and reliability of the simulation results. After each iteration, record the displacement, angle, and other relevant information of the components. Organize the construction compensation results of the components obtained from multiple iterative simulations into a data table, including the specific parameters and effect evaluation of each result. Ensure that the information is clear and easy to understand. Collect all the construction compensation results of the components obtained from iterative simulations and prepare for the extraction of the best compensation result. Ensure the integrity of the result data for comparative analysis. Use statistical analysis methods (such as variance analysis, mean comparison, etc.) to compare multiple compensation results and determine the advantages and disadvantages of each result. The evaluation criteria can include construction accuracy, material utilization rate, and construction time, etc. During the comparison process, record the key parameters and performance indicators of each result to support the extraction of the best result. Organize the extracted best compensation result into a report, including a detailed description of the best result, key parameters, and effect evaluation. Ensure that the information is complete and clear for the construction team to implement.Save the best compensation result data to provide a basis for subsequent on-site construction deviation elimination and compensation processing. Collect information on the best compensation results and prepare for deviation elimination and compensation processing at the construction site. Ensure that all relevant personnel understand the compensation plan and implementation steps. Based on the best compensation results, implement on-site construction deviation elimination and compensation processing. This includes adjusting the position, angle of components or applying additional forces to ensure that the components meet the design requirements. During the implementation process, monitor the adjustment effect in real time to ensure the timeliness and effectiveness of deviation elimination. Upload the data during the on-site construction process to the cloud in real time to ensure that all adjustment and compensation information is recorded and archived. Use a data management platform for information collaboration and sharing to ensure that all relevant parties can obtain the latest data in real time.

[0036] In this embodiment, a BIM-based prefabricated building design and construction optimization management system is provided for executing the BIM-based prefabricated building design and construction optimization management method as described above, including: A construction scenario module for obtaining panoramic monitoring images of the building area and the initial BIM model of the construction design; performing regional space structure evolution and three-dimensional simulation of the construction scenario on the panoramic monitoring images of the building area to construct a three-dimensional construction scenario map; An assembly requirement module for identifying prefabricated building component information according to the initial BIM model of the construction design and performing component assembly requirement evolution to generate building component assembly requirement characteristics; A construction sequence optimization module for dynamically simulating and optimizing the construction sequence of the three-dimensional construction scenario map and the initial BIM model of the construction design based on the building component assembly requirement characteristics to construct a dynamically optimized construction sequence; An operation path planning module for analyzing the available material transportation paths of the three-dimensional construction scenario map and planning the optimal operation paths for each material one by one to generate the optimal operation path for each material; An error identification module for making intelligent construction design plan decisions according to the dynamically optimized construction sequence and the optimal operation path of each material and synchronizing the detection of component position deviation to generate an instant synchronous twin construction model; A construction deviation compensation module for performing on-site construction deviation elimination and compensation processing based on the instant synchronous twin construction model and synchronizing cloud data collaborative management to construct an instant construction optimization management engine.

[0037] By obtaining panoramic monitoring images of the construction area, the present invention can comprehensively and real-time understand the environmental characteristics and surrounding conditions of the construction site, which provides accurate site data for construction design and ensures the rationality of the construction plan. Using image analysis technology and BIM technology for regional space structure evolution can deeply analyze the spatial constraints, obstacles, etc. at the construction site, predict in advance the spatial limiting factors during the construction process, and thus provide optimization suggestions for subsequent construction. Based on the integration of panoramic images and BIM models, a three-dimensional construction scene diagram is constructed, which can truly restore the spatial layout and construction process of the construction site, helping the project team to intuitively understand how each link unfolds and identify potential conflicts and risks. By accurately identifying the information of all prefabricated building components through the BIM model, such as the type, specification, material, weight, etc. of the components, in this way, the construction team can clearly understand the specific requirements and characteristics of each component at the design stage. According to the actual situation of the construction site and the project progress, the assembly requirements of the components are updated in real time to avoid resource waste caused by changes during the design or construction process. The assembly sequence of the components can be flexibly adjusted to ensure the efficiency of construction. Through the evolutionary analysis of the assembly requirements of the components, the material procurement, transportation, assembly plan, etc. can be dynamically adjusted, effectively reducing surplus or insufficient resources and improving the utilization rate of construction resources. Through dynamic construction sequence simulation, bottlenecks in the construction process can be identified and eliminated. For example, avoid the interference caused by multiple tasks being carried out simultaneously, and optimize the workflow and working procedures. Using the three-dimensional construction scene diagram and BIM model for all-round conflict detection and risk warning can detect possible spatial conflicts, time conflicts or resource conflicts before construction and propose optimization solutions to ensure the smooth progress of construction. By optimizing the construction sequence, unnecessary waiting time and repetitive labor are reduced, making the construction process more efficient and smooth, and ensuring the completion of the construction task in the shortest time. By analyzing the transportation routes and material requirements at the construction site, the shortest and most effective transportation route can be planned for each type of material, reducing the time loss and traffic bottlenecks during transportation. Through reasonable material transportation route planning, the stacking and moving times of materials on site can be reduced, reducing waste and time delays, and thus ensuring that each construction work can be carried out on time. Route planning can reasonably allocate transportation resources, avoid multiple materials crossing on the same route at the same time, and improve the fluidity of on-site materials and construction efficiency. By deploying sensors and monitoring devices, the system can real-time detect the position and installation accuracy of components at the construction site. The instant identification and feedback of component position deviation can avoid the accumulation of errors and rework in the later stage. Through the combination of BIM and real-time data, the error identification module can provide intelligent decision support, helping the construction team to make timely adjustments when problems occur and avoiding delays in the construction progress. By real-time synchronizing the twin model, the actual construction progress on site can be docked with the virtual design model in real time, ensuring a high degree of consistency between design and construction and effectively eliminating non-compliance phenomena during the construction process.Through the instant synchronous twin construction model, the system can identify various errors in on-site construction in real time (such as geometric deviations and position deviations of components), calculate compensation values, and make dynamic adjustments to ensure that the construction accuracy meets the expected standards. The deviation compensation module can directly feedback the compensation plan to the construction team and guide the on-site staff to make precise adjustments, avoiding excessive manual intervention and delays, and improving construction efficiency. All construction data, error information, optimization strategies, etc. are managed in real-time collaboration through the cloud to ensure efficient communication and resource sharing among project teams. At the same time, the optimization management engine can provide precise support for project decision-making based on real-time data and historical data analysis, realizing global construction optimization.

[0038] Therefore, in any regard, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Accordingly, all changes falling within the meaning and scope of the equivalent elements of the application documents are intended to be embraced within the present invention.

[0039] As described above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features invented herein.

Claims

1. A BIM-based optimization management method for prefabricated building design and construction, characterized in that, It includes the following steps: Step S1: Obtain the panoramic monitoring image of the construction area and the initial BIM model of the construction design; Perform regional spatial structure evolution and three-dimensional simulation of the construction scene on the panoramic monitoring image of the construction area to construct a three-dimensional construction scene diagram; Step S2: Identify the information of prefabricated building components according to the initial BIM model of the construction design, and perform the evolution of component assembly requirements, so as to generate the assembly requirement characteristics of building components; Step S3: Based on the assembly requirement characteristics of building components, perform dynamic construction sequence simulation optimization on the three-dimensional construction scene diagram and the initial BIM model of the construction design to construct a dynamically optimized construction sequence; Step S4: Analyze the transport path of available materials for the three-dimensional construction scene diagram, and plan the optimal operation path for each material one by one, so as to generate the optimal operation path for each material; Step S5: Make a decision on the intelligent construction design plan according to the dynamically optimized construction sequence and the optimal operation path of each material, and synchronize the detection of component position deviation to generate an instantaneously synchronized twin construction model; Step S6: Perform on-site construction deviation elimination and compensation processing based on the instantaneously synchronized twin construction model, and perform cloud data collaborative management synchronization to construct an instant construction optimization management engine.

2. The BIM-based prefabricated building design and construction optimization management method according to claim 1, wherein The specific steps of Step S1 are as follows: Step S11: Obtain the panoramic monitoring image of the construction area and the initial BIM model of the construction design; Step S12: Perform regional spatial structure evolution on the panoramic monitoring image of the construction area to generate construction area spatial structure data; Step S13: Calculate the floor area of the building to be constructed according to the initial BIM model of the construction design, and extract the floor area; Step S14: Analyze the spatial boundary conditions of the initial BIM model of the construction design to generate the spatial boundary conditions of the building construction; Step S15: Identify the construction space limitations based on the floor area of the building and the spatial boundary conditions of the building construction to generate construction space limitation characteristics; Step S16: Perform three-dimensional simulation of the construction scene on the construction area spatial structure data and the construction space limitation characteristics to construct a three-dimensional construction scene diagram.

3. The optimized management method for prefabricated building design and construction based on BIM according to claim 2, wherein, The specific steps of Step S12 are as follows: Perform global brightness enhancement processing on the panoramic monitoring image of the construction area to obtain a globally brightness-enhanced monitoring image; Perform regional terrain visual recognition on the globally brightness-enhanced monitoring image to generate regional terrain characteristics; Mark the surrounding buildings according to the globally brightness-enhanced monitoring image; Calculate the spatial area parameters of the surrounding buildings; Perform regional obstacle analysis on the globally brightness-enhanced monitoring image and mark all regional obstacle nodes; Perform precise visual analysis of traffic flow lines on the globally brightness-enhanced monitoring image and extract all traffic flow lines; Perform regional spatial structure evolution based on the regional terrain characteristics, the spatial area parameters, all regional obstacle nodes and all traffic flow lines to generate construction area spatial structure data.

4. The BIM-based prefabricated building design and construction optimization management method according to claim 1, characterized in that, The specific steps of Step S2 are as follows: Step S21: Identify the information of prefabricated building components according to the initial BIM model of the construction design; Step S22: Calculate the external dimensions of the prefabricated building component information to generate external dimension parameters; Step S23: Conduct three-dimensional morphological analysis based on the external dimension parameters to generate the three-dimensional morphological characteristics of each building component; Step S24: Extract the installation surface of the building components according to the prefabricated building component information and analyze the connection method to generate the connection method of the building components; Step S25: Conduct assembly conflict analysis between components based on the connection method of the building components and the three-dimensional morphological characteristics of each building component to generate geometric space conflict data for component assembly; Step S26: Mine the pre-dependence relationship of the installation sequence based on the initial BIM model of the construction design to obtain the dependence law of the component installation sequence; Step S27: Evolve the geometric space conflict data of component assembly and the dependence law of component installation sequence to generate the assembly requirement characteristics of building components.

5. The optimized management method for the design and construction of prefabricated buildings based on BIM according to claim 1, characterized in that, The specific steps of Step S3 are as follows: Step S31: Conduct a full-process digital assembly simulation on the three-dimensional construction scene diagram and the initial BIM model of the construction design based on the assembly requirement characteristics of the building components to construct a virtual building construction model; Step S32: Conduct a time-sequence analysis of all construction links of the virtual building construction model to generate a full-cycle construction link sequence; Step S33: Conduct a construction space logic analysis on the full-cycle construction link sequence to generate construction space logic data; Step S34: Identify the spatial interference conflict points based on the construction space logic data and mark the conflict links; Step S35: Speculate on the construction bottlenecks based on the construction space logic data to generate construction bottleneck speculation data; Step S36: Optimize the dynamic construction sequence based on the conflict links and the construction bottleneck speculation data to construct a dynamically optimized construction sequence.

6. The optimized management method for the design and construction of prefabricated buildings based on BIM according to claim 1, wherein The specific steps of Step S4 are as follows: Step S41: Monitor the material transportation process of the virtual building construction model to identify the material transportation process data; Step S42: Analyze the available material transportation paths of the three-dimensional construction scene diagram and extract all available transportation paths; Step S43: Mark the nearest stacking point and the destination construction point of each material according to the material transportation process data; Step S44: Calculate the material transfer distance based on the nearest stacking point and the destination construction point to generate the material transfer distance; Step S45: Plan the optimal transfer path for each material for all available transportation paths according to the material transfer distance to generate the optimal transfer path for each material.

7. The BIM-based prefabricated building design and construction optimization management method according to claim 1, characterized in that The specific steps of Step S5 are as follows: Step S51: Make a decision on the intelligent construction design plan according to the dynamically optimized construction sequence and the optimal transfer path of each material to construct an intelligent construction decision-making plan; Step S52: Execute the on-site building construction operation based on the intelligent construction decision-making plan and collect the real-time building construction monitoring video; Step S53: Conduct three-dimensional visual positioning of the assembled components on the real-time building construction monitoring video and extract the positioning coordinates of the assembled components; Step S54: Detect the position deviation of the components on the virtual building construction model based on the positioning coordinates of the assembled components and mark the component nodes with position deviation; Step S55: Conduct immediate synchronization processing on the virtual building construction model according to the component nodes with position deviation to generate an immediate synchronization twin construction model.

8. The BIM-based prefabricated building design and construction optimization management method according to claim 1, characterized in that The specific steps of Step S6 are as follows: Step S61: Calculate the component error compensation for the component node with position deviation to obtain the component error compensation value; Step S62: Adjust the construction parameters based on the component error compensation value to generate the component construction compensation adjustment parameters; Step S63: Perform iterative simulation compensation based on the component construction compensation adjustment parameters to generate multiple component construction compensation results; Step S64: Extract the optimal compensation result based on multiple component construction compensation results; Step S65: Perform on-site construction deviation elimination compensation processing based on the optimal compensation result, and perform cloud data collaborative management synchronization to construct an instant construction optimization management engine.

9. An optimized management system for the design and construction of prefabricated buildings based on BIM, characterized in that, Used to execute the BIM-based prefabricated building design and construction optimization management method as described in claim 1, including: A construction scenario module, used to obtain the panoramic monitoring image of the building area and the initial BIM model of the construction design; perform regional space structure evolution and three-dimensional simulation of the construction scenario on the panoramic monitoring image of the building area to construct a three-dimensional construction scenario map; An assembly requirement module, used to identify the prefabricated building component information according to the initial BIM model of the construction design, and perform the evolution of the component assembly requirements, so as to generate the assembly requirement characteristics of the building components; A construction sequence optimization module, used to dynamically simulate and optimize the three-dimensional construction scenario map and the initial BIM model of the construction design based on the assembly requirement characteristics of the building components to construct a dynamically optimized construction sequence; A running path planning module, used to analyze the available material transportation path of the three-dimensional construction scenario map, and perform the optimal running path planning for each material, so as to generate the optimal running path for each material; An error identification module, used to make an intelligent construction design plan decision according to the dynamically optimized construction sequence and the optimal running path of each material, and perform synchronous detection of the component position deviation to generate an instant synchronous twin construction model; A construction deviation compensation module, used to perform on-site construction deviation elimination compensation processing based on the instant synchronous twin construction model, and perform cloud data collaborative management synchronization to construct an instant construction optimization management engine.

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