A construction engineering construction optimization management method and system

Abstract

The application relates to the technical field of building engineering management, in particular to a building engineering construction optimization management method and system; the method comprises the following steps: constructing a multi-source data acquisition system; performing cleaning, deduplication and standardization processing on the collected data to form a standardized construction database; constructing an initial BIM model based on design drawings, integrating multi-specialty information, connecting real-time construction data to the BIM model, and constructing a construction stage digital twin model; based on the digital twin model and historical construction data, respectively performing progress optimization, resource optimization, cost optimization and safety optimization, generating corresponding optimization schemes, and collecting real-time execution feedback data to form a closed-loop management; the system comprises a construction data acquisition module, a BIM digital twin model construction module and a multi-dimensional dynamic optimization analysis module; through the above mode, the problem that the model is disconnected with the site working condition is avoided, thereby meeting the management requirements of modern building engineering.

Description

Technical Field

[0001] This invention relates to the field of construction project management technology, and in particular to a construction project construction optimization management method and system. Background Technology

[0002] In the field of construction management, the entire construction process involves multiple dimensions of factors such as personnel, equipment, materials, environment, procedures, and costs. These factors are highly interconnected and change frequently, requiring extremely high precision and coordination in management.

[0003] Currently, most construction projects still rely on traditional management models, lacking systematic multi-source data collection and integration capabilities. Data is scattered and stored in different stages and systems, forming information silos and failing to provide comprehensive data support for management decisions. In terms of model building and application, existing BIM technology is mostly applied in the design phase, only able to build an initial 3D model. It is difficult to integrate real-time data from the entire construction process, resulting in a disconnect between the model and the actual construction site conditions. Dynamic updates are not possible, and the model cannot accurately reflect the actual construction status of components, resource distribution, and process progress.

[0004] In summary, existing construction management methods suffer from a disconnect between models and actual on-site conditions, failing to meet the management needs of modern construction projects. Summary of the Invention

[0005] The purpose of this invention is to provide a construction engineering construction optimization management method and system, which aims to solve the technical problem that the existing model is out of touch with the actual working conditions and cannot meet the management needs of modern construction engineering.

[0006] To achieve the above objectives, the present invention employs a construction engineering optimization management method, comprising the following steps: Construct a multi-source data acquisition system to collect personnel data, equipment data, material data, environmental data, process data, and cost data throughout the entire construction process; clean, deduplicate, and standardize the collected data to form a standardized construction database; An initial BIM model is built based on design drawings, integrating information from multiple disciplines; real-time construction data is integrated into the BIM model to build a digital twin model for the construction phase. Based on the digital twin model and historical construction data, schedule optimization, resource optimization, cost optimization and safety optimization are carried out respectively, generating corresponding optimization plans, and collecting execution feedback data in real time to form a closed-loop management.

[0007] Among these steps, the construction of a multi-source data acquisition system involves collecting personnel, equipment, material, environmental, process, and cost data throughout the entire construction process; and cleaning, deduplicating, and standardizing the collected data to form a standardized construction database. Deploy multi-channel data acquisition terminals; The collected raw data is classified and sorted to remove abnormal data caused by sensor malfunctions, duplicate data caused by human operation errors, and data with disordered format. By adopting unified data coding rules and coordinate system standards, data from different sources and in different formats are standardized and converted to ensure that personnel, equipment, and material data are accurately matched with BIM model component information.

[0008] Among the steps in deploying multi-channel data collection terminals: The system collects equipment operating parameters, structural stress state, and environmental parameters at the construction site through IoT sensors, collects personnel attendance, work progress, and quality acceptance results through mobile terminals, and connects to BIM design models, material procurement systems, and cost accounting systems through system interfaces to synchronously obtain corresponding data.

[0009] Among these steps, the standardization and conversion of data from different sources and formats, using unified data coding rules and coordinate system standards, ensures accurate correspondence between personnel, equipment, and material data and BIM model component information: The processed standardized data is imported into a database for categorized storage, thus establishing a standardized construction database.

[0010] Among the steps are: building an initial BIM model based on design drawings, integrating information from multiple disciplines, connecting real-time construction data to the BIM model, and constructing a digital twin model for the construction phase; Use BIM modeling software to build an initial 3D model and input basic information such as component specifications, materials, and construction techniques. Optimize the BIM model data interface and link it with the standardized construction database in real time, so as to synchronously integrate the pre-processed personnel, equipment, materials and process data into the BIM model.

[0011] After optimizing the BIM model data interface and enabling real-time linkage with the standardized construction database, and synchronizing the pre-processed real-time data of personnel, equipment, materials, and processes into the BIM model: Based on the accessed real-time data, the initial BIM model is dynamically iterated and updated to supplement the on-site working conditions information such as the construction status of components, the location of resource distribution, and the progress of process completion, thus constructing a digital twin model that is mapped to the construction site in real time.

[0012] Among them, after dynamically iterating and updating the initial BIM model based on the accessed real-time data, supplementing it with information on the construction status of components, the location of resource distribution, the progress of work processes, and the on-site working conditions, and constructing a digital twin model that is mapped to the construction site in real time: A model update trigger mechanism is set up so that data is updated at a fixed cycle under normal operating conditions; when major process adjustments, quality problems, or resource scheduling changes occur, the model information is updated immediately.

[0013] Among these steps, based on digital twin models and historical construction data, schedule optimization, resource optimization, cost optimization, and safety optimization are performed respectively to generate corresponding optimization plans, and execution feedback data is collected in real time to form a closed-loop management system: Retrieve real-time process data and historical construction data of similar projects from the digital twin model to predict the construction period and potential delay risks of each process, identify process overlap and conflict points, and generate process connection optimization and schedule adjustment plans. By combining resource distribution data and schedule plans in the digital twin model, dynamic planning is carried out on personnel scheduling, equipment dispatching paths, material arrival quantities and stacking locations, and resource supply and demand balance optimization schemes are output. Based on real-time cost consumption data and schedule deviations, the cost of completed work is dynamically calculated, the cost trend of subsequent processes is predicted, the risk points of cost overruns are identified, and cost control optimization measures are proposed.

[0014] The process includes the steps of dynamically calculating the cost of completed work based on real-time cost consumption data and schedule deviations, predicting cost trends for subsequent processes, identifying cost overrun risk points, and proposing cost control optimization measures: Real-time monitoring of construction environment parameters and structural stress status; risk simulation analysis combined with historical safety hazard handling data; identification of safety hazards and issuance of graded early warnings; and push of emergency response and rectification optimization plans.

[0015] This invention also provides a construction engineering optimization management system, including a construction data acquisition module, a BIM digital twin model construction module, and a multi-dimensional dynamic optimization analysis module; wherein: The construction data acquisition module is used to construct a multi-source data acquisition system, collect personnel data, equipment data, material data, environmental data, process data, and cost data throughout the entire construction process; and clean, deduplicate, and standardize the collected data to form a standardized construction database. The BIM digital twin model building module is used to build an initial BIM model based on design drawings, integrate multi-disciplinary information, connect real-time construction data to the BIM model, and build a digital twin model for the construction phase. The multi-dimensional dynamic optimization analysis module is used to optimize progress, resources, costs, and safety based on digital twin models and historical construction data, generate corresponding optimization schemes, and collect execution feedback data in real time to form closed-loop management.

[0016] This invention discloses a construction engineering optimization management method and system, which employs a construction data acquisition module, a BIM digital twin model construction module, and a multi-dimensional dynamic optimization analysis module to perform the following steps: Constructing a multi-source data acquisition system to collect personnel data, equipment data, material data, environmental data, process data, and cost data throughout the entire construction process; cleaning, deduplicating, and standardizing the collected data to form a standardized construction database; constructing an initial BIM model based on design drawings, integrating multi-disciplinary information; integrating real-time construction data into the BIM model to construct a digital twin model for the construction phase; and performing schedule optimization, resource optimization, cost optimization, and safety optimization based on the digital twin model and historical construction data, generating corresponding optimization schemes, and collecting execution feedback data in real time to form closed-loop management. Through the above methods, the problem of model disconnection from on-site conditions is avoided, thereby meeting the management needs of modern construction engineering. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of the steps in the construction engineering optimization management method of the present invention.

[0019] Figure 2 This is a flowchart of steps S100 of the present invention.

[0020] Figure 3 This is a flowchart of steps S200 of the present invention.

[0021] Figure 4 This is a flowchart of steps S300 of the present invention.

[0022] Figure 5 This is a structural principle diagram of the construction engineering optimization management system of the present invention.

[0023] Figure 6 This is a schematic diagram of the electronic device of the present invention.

[0024] 401 - Construction Data Acquisition Module, 402 - BIM Digital Twin Model Construction Module, 403 - Multi-dimensional Dynamic Optimization Analysis Module. Detailed Implementation

[0025] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.

[0026] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0027] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0028] Please see Figures 1-4 This invention provides a method for optimizing the management of construction projects, comprising the following steps: S100: Construct a multi-source data acquisition system to collect personnel data, equipment data, material data, environmental data, process data, and cost data throughout the entire construction process; clean, deduplicate, and standardize the collected data to form a standardized construction database.

[0029] In this embodiment, a multi-source data acquisition system is constructed to collect personnel data, equipment data, material data, environmental data, process data, and cost data throughout the entire construction process. The collected data is then cleaned, deduplicated, and standardized to form a standardized construction database. The specific process is as follows: S101: Deploy multi-channel data acquisition terminals; collect equipment operating parameters, structural stress status and environmental parameters at the construction site through IoT sensors; collect personnel attendance, work progress and quality acceptance results through mobile terminals; and connect to BIM design models, material procurement systems and cost accounting systems through system interfaces to synchronously obtain data in the corresponding dimensions. S102: Classify and sort the collected raw data, and remove abnormal data caused by sensor failure, duplicate data caused by human operation errors, and data with disordered format; S103: Adopting unified data coding rules and coordinate system standards, we standardize and convert data from different sources and in different formats to ensure that personnel, equipment, and material data are accurately matched with BIM model component information; S104: Import the processed standardized data into the database for classification and storage, and build a standardized construction database.

[0030] In the above process, multi-channel data acquisition terminals are deployed to achieve comprehensive data coverage. Specifically, IoT sensors are deployed at key locations on the construction site to collect real-time operating parameters of equipment such as tower cranes and construction elevators, structural stress states of components such as steel bars and formwork, and environmental parameters such as temperature, humidity, wind force, and precipitation. Dedicated data collection portals are configured for construction management personnel and work teams via mobile terminals to collect real-time data on personnel attendance, departure registration, work progress, and quality acceptance results for each process. Standardized system interfaces are used to connect with BIM design model systems, material procurement management systems, and cost accounting systems to simultaneously obtain corresponding data such as component design parameters, material arrival lists, purchase prices, and cost consumption details, ensuring comprehensive and real-time data collection.

[0031] The collected raw data were categorized and sorted, and data preprocessing was carried out. The raw data were split and classified into six categories: personnel, equipment, materials, environment, process, and cost. The validity of each data was verified, and data with abnormal values ​​caused by sensor failure, duplicate reports caused by human operation errors, and data with disordered format and missing fields were removed. The real, complete and valid data were retained to lay the foundation for subsequent standardization processing.

[0032] A unified data coding rule and coordinate system standard are adopted to standardize and convert data from different sources and in different formats. A unified component coding, personnel numbering, equipment numbering, and material coding rule is formulated for the entire project, and the scattered multi-source data is coded and associated. At the same time, a unified data coordinate system is established to ensure that personnel, equipment, and material data are accurately matched with the corresponding component information in the BIM model, eliminating the docking barriers caused by data format differences and achieving deep integration of data and model.

[0033] The processed standardized data is imported into a professional database for categorized storage, creating a structured, standardized construction database. Dedicated storage is allocated according to data type, and data indexes and relationships are established to support real-time updates, rapid queries, and batch access, ensuring the database provides stable and efficient data support for subsequent BIM model building, dynamic optimization analysis, and other processes.

[0034] S200: Based on the design drawings, an initial BIM model is built, integrating information from multiple disciplines, and real-time construction data is connected to the BIM model to construct a digital twin model for the construction phase.

[0035] In this embodiment, an initial BIM model is constructed based on design drawings, integrating information from multiple disciplines, and real-time construction data is incorporated into the BIM model to build a digital twin model for the construction phase. The specific process is as follows: S201: Use BIM modeling software to build an initial 3D model and input basic information such as component specifications, materials, and construction techniques. S202: Optimize the BIM model data interface and link it with the standardized construction database in real time, so as to synchronously connect the pre-processed personnel, equipment, materials and process real-time data into the BIM model. S203: Based on the accessed real-time data, dynamically iterate and update the initial BIM model, supplement the on-site working conditions information such as component construction status, resource distribution location, and process completion progress, and build a digital twin model that is mapped to the construction site in real time; S204: Set a model update trigger mechanism to update data at a fixed cycle under normal operating conditions; when major process adjustments, quality problems, or resource scheduling changes occur, the model information will be updated immediately.

[0036] In the above process, mainstream BIM modeling software (such as Revit and Bentley) is used, relying on design drawings from various disciplines such as architecture, structure, and MEP, to build an initial 3D BIM model that integrates all disciplines. Basic information such as the specifications, dimensions, material types, construction process standards, and installation locations of each component are accurately entered into the model. Simultaneously, design parameters from various disciplines are integrated to eliminate model conflicts between disciplines, achieving collaborative integration and unified management of multi-disciplinary models.

[0037] The BIM model data interface has been optimized, adopting a universal data transmission protocol to achieve real-time linkage with the standardized construction database. The interface supports bidirectional data interaction, automatically retrieving pre-processed personnel attendance status, equipment operation data, material arrival information, and process progress data from the database, and synchronously integrating them into the corresponding components of the BIM model, breaking down information barriers between data and the model.

[0038] Based on the accessed real-time construction data, the initial BIM model is dynamically iterated and updated. According to the data feedback, the actual construction status of components (such as completion of pouring and installation), the real-time distribution of resources (such as material stacking areas and equipment operation points), and the progress of process completion are supplemented with on-site working condition information, so that the model can accurately map the real-time status of the construction site and build a digital twin model that is synchronized with all elements and processes of the construction site in real time.

[0039] A flexible model update trigger mechanism is set up to ensure consistency between the model and on-site operating conditions. Under normal operating conditions, the model data is automatically updated according to a preset fixed cycle (e.g., every 2 hours) to ensure data timeliness. When special circumstances occur, such as major process adjustments, quality problem rectification, or changes in the scheduling of key resources, an immediate update command is triggered to immediately update the corresponding information in the model, ensuring that managers can keep abreast of dynamic changes on site.

[0040] S300: Based on digital twin models and historical construction data, it optimizes schedule, resources, costs and safety respectively, generates corresponding optimization plans, and collects execution feedback data in real time to form closed-loop management.

[0041] In this implementation, based on a digital twin model and historical construction data, schedule optimization, resource optimization, cost optimization, and safety optimization are performed respectively, generating corresponding optimization plans. Execution feedback data is collected in real time to form a closed-loop management system. The specific process is as follows: S301: Retrieve real-time process data and historical construction data of similar projects from the digital twin model, predict the construction period and potential delay risks of each process, identify process intersection conflict points, and generate process connection optimization and schedule adjustment plans. S302: Combining resource distribution data and schedule plans in the digital twin model, dynamically plan personnel scheduling, equipment dispatching paths, material arrival quantities and stacking locations, and output resource supply and demand balance optimization solutions; S303: Based on real-time cost consumption data and schedule deviations, dynamically calculate the cost of completed work, predict the cost trend of subsequent processes, identify cost overrun risk points, and propose cost control optimization measures. S304: Real-time monitoring of construction environment parameters and structural stress state, combined with historical safety hazard handling data to conduct risk simulation analysis, identify safety hazards and issue graded early warnings, and push emergency response and rectification optimization plans.

[0042] In the above process, real-time process data from the digital twin model is retrieved and combined with historical data on construction period and process connection efficiency of similar projects. Through experience analysis and trend prediction, the expected completion period of each process is determined, potential delay risk points are identified, and the locations and time nodes of cross-operation conflicts between different processes are investigated. Based on the risk level and conflict type, a scientific and reasonable process connection optimization plan and schedule adjustment plan are generated, clarifying the work priority and time nodes of each process.

[0043] By combining real-time updated resource distribution data from the digital twin model with the optimized schedule, a comprehensive analysis of the supply and demand balance of personnel, equipment, and materials is conducted. This involves rationally scheduling construction personnel to match the operational needs of each process with personnel skills, avoiding redundancy or shortages; optimizing equipment scheduling routes to reduce equipment idle time and travel time, thereby improving equipment utilization; accurately calculating the amount of materials entering the site, and planning material storage locations based on construction progress and on-site storage capacity to avoid material stockpiling and waste or insufficient supply, ultimately outputting an optimized resource supply and demand balance solution.

[0044] Based on real-time cost consumption data from a standardized construction database and combined with schedule deviations, the actual cost of completed work is dynamically calculated, and the reasons for cost deviations are analyzed by comparing them with budgeted costs. A trend prediction model is used to predict the cost consumption trends of subsequent processes, accurately identifying cost overrun risks in areas such as labor, materials, and equipment. Targeted cost control and optimization measures are proposed for these risk points, such as optimizing material procurement plans and adjusting construction techniques to reduce energy consumption.

[0045] Through IoT sensors linked to a digital twin model, environmental parameters and structural stress states at the construction site are monitored in real time. Combined with historical safety hazard handling cases and hazard occurrence patterns, risk simulation analysis is conducted. The system automatically identifies safety hazards such as falls from heights, collapses, electric shocks, and component instability, issuing red, yellow, and blue warnings based on the severity of the hazard. Simultaneously, it pushes targeted emergency response procedures and rectification optimization plans to guide on-site personnel in quickly addressing the hazards.

[0046] Corresponding to the aforementioned embodiments of the construction project optimization management method, this application also provides embodiments of the construction project optimization management system.

[0047] Figure 5 This is a block diagram illustrating a construction optimization management system for building engineering, according to an exemplary embodiment. (Refer to...) Figure 5 The system may include: a construction data acquisition module 401, a BIM digital twin model construction module 402, and a multi-dimensional dynamic optimization analysis module 403; wherein: The construction data acquisition module 401 is used to construct a multi-source data acquisition system, collect personnel data, equipment data, material data, environmental data, process data, and cost data throughout the entire construction process; and clean, deduplicate, and standardize the collected data to form a standardized construction database. The BIM digital twin model building module 402 is used to build an initial BIM model based on design drawings, integrate multi-disciplinary information, connect real-time construction data to the BIM model, and build a digital twin model for the construction phase. The multi-dimensional dynamic optimization analysis module 403 is used to perform schedule optimization, resource optimization, cost optimization and safety optimization based on the digital twin model and historical construction data, generate corresponding optimization schemes, and collect execution feedback data in real time to form closed-loop management.

[0048] In this embodiment, the construction data acquisition module 401 constructs a multi-source data acquisition system, collecting personnel data, equipment data, material data, environmental data, process data, and cost data throughout the entire construction process. The collected data is cleaned, deduplicated, and standardized to form a standardized construction database. The BIM digital twin model construction module 402 constructs an initial BIM model based on design drawings, integrates multi-disciplinary information, and connects real-time construction data to the BIM model to construct a digital twin model for the construction phase. The multi-dimensional dynamic optimization analysis module 403 performs schedule optimization, resource optimization, cost optimization, and safety optimization based on the digital twin model and historical construction data, generating corresponding optimization schemes and collecting execution feedback data in real time to form a closed-loop management system. Through these methods, the problem of model disconnection from on-site conditions is avoided, thereby meeting the management needs of modern construction projects.

[0049] Regarding the system in the above embodiments, the specific ways in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0050] For the system embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0051] Accordingly, this application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; and when the one or more programs are executed by the one or more processors, causing the one or more processors to implement the construction engineering optimization management method described above. Figure 6 The diagram shown is a hardware structure diagram of any device with data processing capabilities within a construction engineering optimization management system provided in an embodiment of the present invention, except... Figure 6In addition to the processor, memory, and network interface shown, any data processing device in the embodiment may also include other hardware depending on the actual function of the data processing device, which will not be described in detail here.

[0052] Accordingly, this application also provides a computer-readable storage medium storing computer instructions thereon, which, when executed by a processor, implement the construction optimization management method for building engineering described above. The computer-readable storage medium can be an internal storage unit of any data processing device as described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium can also be an external storage device, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc., equipped on the device. Furthermore, the computer-readable storage medium can include both internal storage units of any data processing device and external storage devices. The computer-readable storage medium is used to store the computer program and other programs and data required by the data processing device, and can also be used to temporarily store data that has been output or will be output.

[0053] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0054] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope.

Claims

1. A method for optimizing the management of construction projects, characterized in that, The steps include the following: Construct a multi-source data acquisition system to collect personnel data, equipment data, material data, environmental data, process data, and cost data throughout the entire construction process; clean, deduplicate, and standardize the collected data to form a standardized construction database; An initial BIM model is built based on design drawings, integrating information from multiple disciplines, and real-time construction data is connected to the BIM model to build a digital twin model for the construction phase. Based on the digital twin model and historical construction data, schedule optimization, resource optimization, cost optimization and safety optimization are carried out respectively, generating corresponding optimization plans, and collecting execution feedback data in real time to form a closed-loop management.

2. The construction optimization management method for building engineering as described in claim 1, characterized in that, In the process of constructing a multi-source data acquisition system to collect personnel data, equipment data, material data, environmental data, process data, and cost data throughout the entire construction process; and in the steps of cleaning, deduplicating, and standardizing the collected data to form a standardized construction database: Deploy multi-channel data acquisition terminals; The collected raw data is classified and sorted to remove abnormal data caused by sensor malfunctions, duplicate data caused by human operation errors, and data with disordered format. By adopting unified data coding rules and coordinate system standards, data from different sources and in different formats are standardized and converted to ensure that personnel, equipment, and material data are accurately matched with BIM model component information.

3. The construction optimization management method for building engineering as described in claim 2, characterized in that, In the steps of deploying multi-channel data acquisition terminals: The system collects equipment operating parameters, structural stress state, and environmental parameters at the construction site through IoT sensors, collects personnel attendance, work progress, and quality acceptance results through mobile terminals, and connects to BIM design models, material procurement systems, and cost accounting systems through system interfaces to synchronously obtain corresponding data.

4. The construction optimization management method for building engineering as described in claim 3, characterized in that, In the process of adopting unified data coding rules and coordinate system standards to standardize and convert data from different sources and formats, ensuring accurate correspondence between personnel, equipment, and material data and BIM model component information: The processed standardized data is imported into a database for categorized storage, thus establishing a standardized construction database.

5. The construction optimization management method for building engineering as described in claim 1, characterized in that, In the steps of building an initial BIM model based on design drawings, integrating information from multiple disciplines, and connecting real-time construction data to the BIM model to construct a digital twin model for the construction phase: Use BIM modeling software to build an initial 3D model and input basic information such as component specifications, materials, and construction techniques. Optimize the BIM model data interface and link it with the standardized construction database in real time, so as to synchronously integrate the pre-processed personnel, equipment, materials and process data into the BIM model.

6. The construction optimization management method for building engineering as described in claim 5, characterized in that, After optimizing the BIM model data interface and enabling real-time linkage with the standardized construction database, and synchronizing the pre-processed real-time data on personnel, equipment, materials, and processes into the BIM model: Based on the accessed real-time data, the initial BIM model is dynamically iterated and updated to supplement the on-site working conditions information such as the construction status of components, the location of resource distribution, and the progress of process completion, thus constructing a digital twin model that is mapped to the construction site in real time.

7. The construction optimization management method for building engineering as described in claim 6, characterized in that, After dynamically iterating and updating the initial BIM model based on accessed real-time data, supplementing it with information on component construction status, resource distribution location, and on-site work conditions such as process completion progress, and constructing a digital twin model that is mapped to the construction site in real time: A model update trigger mechanism is set up so that data is updated at a fixed cycle under normal operating conditions; when major process adjustments, quality problems, or resource scheduling changes occur, the model information is updated immediately.

8. The construction optimization management method for building engineering as described in claim 1, characterized in that, In the process of optimizing schedule, resources, costs, and safety based on digital twin models and historical construction data, generating corresponding optimization plans, and collecting execution feedback data in real time to form a closed-loop management system: Retrieve real-time process data and historical construction data of similar projects from the digital twin model to predict the construction period and potential delay risks of each process, identify process overlap and conflict points, and generate process connection optimization and schedule adjustment plans. By combining resource distribution data and schedule plans in the digital twin model, dynamic planning is carried out on personnel scheduling, equipment dispatching paths, material arrival quantities and stacking locations, and resource supply and demand balance optimization schemes are output. Based on real-time cost consumption data and schedule deviations, the cost of completed work is dynamically calculated, the cost trend of subsequent processes is predicted, the risk points of cost overruns are identified, and cost control optimization measures are proposed.

9. The construction optimization management method for building engineering as described in claim 8, characterized in that, After the steps of dynamically calculating the cost of completed work based on real-time cost consumption data and schedule deviations, predicting cost trends for subsequent processes, identifying cost overrun risk points, and proposing cost control optimization measures: Real-time monitoring of construction environment parameters and structural stress status; risk simulation analysis based on historical safety hazard handling data; identification of safety hazards and issuance of graded early warnings; and push of emergency response and rectification optimization plans.

10. A construction project optimization management system, employing the construction project optimization management method as described in claim 1, characterized in that, This includes a construction data acquisition module, a BIM digital twin model construction module, and a multi-dimensional dynamic optimization analysis module; among which: The construction data acquisition module is used to construct a multi-source data acquisition system, collecting personnel data, equipment data, material data, environmental data, process data, and cost data throughout the entire construction process; and to clean, deduplicate, and standardize the collected data to form a standardized construction database. The BIM digital twin model building module is used to build an initial BIM model based on design drawings, integrate multi-disciplinary information, connect real-time construction data to the BIM model, and build a digital twin model for the construction phase. The multi-dimensional dynamic optimization analysis module is used to optimize progress, resources, costs, and safety based on digital twin models and historical construction data, generate corresponding optimization schemes, and collect execution feedback data in real time to form closed-loop management.

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