Digital management methods and systems for construction processes combined with BIM

Abstract

This invention provides a method and system for digital management of the construction process combined with BIM. First, it collects a real-time 3D model data set from the construction site, including the geometric attributes and spatial topological relationships of construction components. Next, it analyzes the logical execution relationships between different construction components to generate a set of schedule scheduling rules. By dynamically matching the actual construction progress data with this set, it derives anomaly detection strategies and resource allocation optimization strategies. Subsequently, it adjusts the component parameter configurations of the real-time 3D model data set according to the anomaly detection strategies, generating updated 3D model verification data. Finally, it generates construction progress adjustment instructions based on the resource allocation optimization strategies and the updated 3D model verification data, and synchronizes them to the construction management terminal. This achieves digital and intelligent management of the construction process, effectively improving construction efficiency and project management level.

Description

Technical Field

[0001] This invention relates to the field of building information modeling (BIM) technology, and more specifically, to a digital management method and system for construction processes that incorporates BIM. Background Technology

[0002] In the field of construction engineering, construction process management has always been a crucial link in ensuring projects are completed on time, to the required quality, and within budget. Traditional construction process management methods mainly rely on manual records, paper documents, and simple progress tracking tools. These methods suffer from problems such as untimely information updates, poor data accuracy, and difficulty in achieving multi-dimensional collaboration. With the rise of Building Information Modeling (BIM) technology, construction management is gradually developing towards digitalization and intelligence. However, existing BIM technology applications are mostly concentrated in the design phase, with insufficient support for real-time monitoring and dynamic management of the construction process. Especially when facing complex and ever-changing construction site environments, how to effectively utilize BIM technology to achieve precise scheduling of construction processes, anomaly detection, and optimized resource allocation has become a pressing technical challenge in the field of construction management. Summary of the Invention

[0003] In view of the aforementioned problems, and in conjunction with the first aspect of the present invention, embodiments of the present invention provide a method for digital management of construction processes incorporating BIM, the method comprising:

[0004] Collect a real-time 3D model data set of the construction site, wherein the real-time 3D model data set contains geometric attribute information and spatial topology association information of multiple construction components;

[0005] The logical execution relationships between different construction components in the real-time 3D model data set are analyzed to generate a set of progress scheduling rules corresponding to the current construction stage.

[0006] The actual construction progress data is dynamically matched with the set of progress scheduling rules to obtain the construction process anomaly detection strategy and resource allocation optimization strategy.

[0007] Based on the construction process anomaly detection strategy, the component parameter configuration of the real-time 3D model data set is adjusted to generate updated 3D model verification data;

[0008] Based on the resource allocation optimization strategy and the updated 3D model verification data, a construction progress adjustment instruction is generated and synchronized to the construction management terminal.

[0009] In another aspect, embodiments of the present invention also provide a digital management system for construction processes integrated with BIM, including a processor and a machine-readable storage medium connected to the processor. The machine-readable storage medium is used to store programs, instructions, or code, and the processor is used to execute the programs, instructions, or code in the machine-readable storage medium to implement the above-described method.

[0010] Based on the above, this invention, by collecting real-time 3D model data sets from the construction site and deeply analyzing the logical execution relationships between different construction components, achieves precise control and dynamic scheduling of construction progress. It dynamically matches actual construction progress data with the generated set of progress scheduling rules, enabling timely detection of anomalies in the construction process and proposing targeted resource allocation optimization strategies. This effectively avoids resource waste and project delays. Furthermore, based on the construction process anomaly detection strategy, the component parameter configurations of the real-time 3D model data set are adjusted to generate updated 3D model verification data. Finally, based on the resource allocation optimization strategy and the updated 3D model verification data, a construction progress adjustment instruction is generated and synchronized to the construction management terminal. This achieves digitalization, intelligence, and collaboration in construction management, significantly improving construction efficiency and project management level. Attached Figure Description

[0011] Figure 1 This is a schematic diagram of the execution flow of the digital management method for construction process combined with BIM provided in the embodiments of the present invention.

[0012] Figure 2 This is a schematic diagram of exemplary hardware and software components of a BIM-integrated digital management system for construction processes provided in an embodiment of the present invention. Detailed Implementation

[0013] The present invention will now be described in detail with reference to the accompanying drawings. Figure 1 This is a flowchart illustrating a BIM-integrated digital management method for construction processes, as provided in one embodiment of the present invention. The following is a detailed description of this BIM-integrated digital management method for construction processes.

[0014] Step S110: Collect a real-time 3D model data set of the construction site. The real-time 3D model data set includes geometric attribute information and spatial topology association information of multiple construction components.

[0015] Step S111: Deploy laser scanning equipment and image acquisition equipment to obtain multi-angle point cloud data and texture image data of the construction site.

[0016] To comprehensively acquire information about the construction site, it is necessary to rationally deploy laser scanning equipment and image acquisition equipment. Laser scanning equipment utilizes the principle of laser ranging to emit laser beams towards surrounding objects. By measuring the time it takes for the laser beam to travel from emission to reflection back to the equipment, the distance from each point on the object's surface to the equipment is calculated, thus obtaining the three-dimensional coordinate information of the object's surface and forming point cloud data. Image acquisition equipment is responsible for capturing images of the construction site from different angles, recording visual information such as the color and texture of the object's surface.

[0017] When deploying equipment, multiple laser scanning and image acquisition devices should be set up at different locations and heights according to the layout and scale of the construction site to ensure coverage of the entire construction site from multiple angles. For example, in a large building construction site, laser scanning and image acquisition devices can be set up at the four corners, the top, and key internal areas of the building. The laser scanning devices scan at a set scanning frequency and angle range to acquire point cloud data A1, A2, A3...An from multiple angles, where n represents the number of point cloud data sets from different angles. The image acquisition devices simultaneously capture texture image data B1, B2, B3...Bm from different angles, where m represents the number of texture image data sets from different angles.

[0018] Step S112: Perform denoising and registration processing on the multi-angle point cloud data to generate a high-precision three-dimensional point cloud model.

[0019] The acquired multi-angle point cloud data may contain noisy points, which may be caused by environmental interference, equipment errors, or other factors. The purpose of denoising is to remove these noisy points and improve the quality of the point cloud data. Statistical filtering methods can be used to calculate the distance statistics between each point and its neighboring points, and points whose distance exceeds a set threshold are considered noise points and removed.

[0020] Registration is the process of aligning point cloud data from different angles to the same coordinate system to form a complete 3D point cloud model. The Iterative Closest Point (ICP) algorithm can be used, which iteratively finds the optimal transformation matrix between two point cloud datasets, making them as overlapping as possible. The specific process is as follows: First, select one point cloud dataset as the reference and another as the dataset to be registered. Then, find the closest point to each point in the reference point cloud within the dataset to be registered, and calculate the transformation matrix between these two sets of corresponding points. The transformation matrix is ​​iteratively updated until convergence is met. After denoising and registration, all point cloud data are merged to generate a high-precision 3D point cloud model C.

[0021] Step S113: Map the texture image data onto the corresponding surface of the high-precision 3D point cloud model to generate an initial 3D model with material properties.

[0022] After obtaining a high-precision 3D point cloud model, it is necessary to map the texture image data onto the corresponding surface of the model to assign material properties to the model. First, it is necessary to establish the correspondence between the texture image data and the 3D point cloud model. This can be achieved by extracting feature points, such as corner points and edge points, from both the texture image and the 3D point cloud model using feature matching. Then, by matching these feature points, the corresponding position of each pixel in the texture image in the 3D point cloud model can be determined.

[0023] Next, based on the correspondence, the color and texture information of the texture image are mapped onto the surface of the 3D point cloud model. For each point cloud point, its corresponding pixel in the texture image is found, and the color value of that pixel is assigned to that point cloud point. In this way, an initial 3D model D with material properties is generated.

[0024] Step S114: Identify the geometric deviation areas of components in the initial 3D model that do not match the design drawings, manually annotate them to generate a corrected 3D model, and synchronously update the manual annotation results to the version update record of the real-time 3D model data set.

[0025] The initial 3D model is compared with the design drawings to identify areas of geometric deviation where components do not match the design drawings. Geometric feature matching can be used to extract geometric features of components from the initial 3D model and design drawings, such as shape and size, and then comparative analysis is performed. Areas with deviations exceeding a set threshold are marked as geometric deviation areas.

[0026] These geometric deviation areas are manually labeled, recording information such as the type and magnitude of the deviation. Based on the labeling results, the initial 3D model is corrected to generate a corrected 3D model E. Simultaneously, the manual labeling results are updated to the version update record of the real-time 3D model dataset for subsequent querying and traceability.

[0027] Step S115: Associate the corrected 3D model with the progress milestone nodes in the construction plan to form a version update record of the real-time 3D model data set.

[0028] Schedule milestones in a construction plan are key time points and important stages in the construction process. Associating the calibrated 3D model with these milestones clearly reflects the correspondence between construction progress and model status. For example, at a certain schedule milestone, the corresponding calibrated 3D model should have reached a specific state.

[0029] By associating the calibrated 3D model with project milestones, a version update record of the real-time 3D model dataset is created. Each time the construction progress reaches a new milestone, the corresponding calibrated 3D model is updated, and the update information is recorded in the version update record. In this way, changes in construction progress and model status can be monitored at any time through the version update record.

[0030] Step S116: Extract the color distribution features from the texture image data and convert them into LAB color space parameters. At the same time, extract the surface roughness features and combine the LAB color space parameters and surface roughness features into a material feature vector of the same dimension, and match it with standard material parameters with the same dimension definition in the material database.

[0031] After generating an initial 3D model with material properties, feature extraction of the texture image data is required to further analyze and verify the material information of the construction components in the initial 3D model. First, the color distribution features in the texture image data are extracted, which can describe the types, proportions, and distribution of colors in the image.

[0032] The extracted color distribution features are converted into LAB color space parameters. LAB color space is a device-independent color space that can more accurately represent the brightness, chroma, and saturation information of colors. Simultaneously, the surface roughness features of the construction components are extracted from the texture image data. Surface roughness features reflect the microscopic unevenness of the component surface.

[0033] The LAB color space parameters and surface roughness features are combined into a material feature vector F with a unified dimension. Then, standard material parameters with the same dimension definition are searched in the material database, and the material feature vector F is matched with the standard material parameters to determine whether the material of the construction component meets the design requirements.

[0034] Step S117: When the difference between the color distribution feature and the standard material parameter exceeds a preset threshold, the construction component corresponding to the texture image data is marked as an object to be reviewed.

[0035] During the matching process between the material feature vector and the standard material parameters, the difference between the color distribution characteristics and the standard material parameters is calculated. Methods such as Euclidean distance can be used to measure this difference. When the difference between the color distribution characteristics and the standard material parameters exceeds a preset threshold, it indicates that there may be a problem with the material of the construction component, and the construction component corresponding to the texture image data is marked as an object to be reviewed.

[0036] Step S118: Obtain the purchase order and quality inspection report of the object to be reviewed, and verify whether the material specifications of the object to be reviewed meet the design requirements.

[0037] For construction components marked as requiring review, their purchase invoices and quality inspection reports need to be obtained to verify whether their material specifications meet design requirements. Purchase invoices record the procurement information for the construction components, such as the supplier, material type, and specifications. Quality inspection reports contain the quality inspection results for the construction components.

[0038] By comparing the information in the purchase orders and quality inspection reports with the design requirements, it can be determined whether the material specifications of the object to be reviewed meet the requirements. If the material specifications meet the requirements, it indicates that the difference in color distribution characteristics may be caused by other factors, such as lighting conditions or surface contamination. If the material specifications do not meet the requirements, it indicates that there is a problem with the material of the construction component.

[0039] Step S119: If the material specifications are verified, then based on the light reflection characteristics of the actual texture image, adjust the diffuse reflection coefficient, specular reflection coefficient and ambient light occlusion coefficient in the standard material parameters in a coordinated manner to adapt to the actual scene lighting model.

[0040] If the material specifications of the object to be reviewed pass the verification, it indicates that the difference in color distribution characteristics may be due to factors such as lighting conditions. In order to make the model more accurately reflect the actual scene, it is necessary to adjust the diffuse reflection coefficient, specular reflection coefficient, and ambient light occlusion coefficient in the standard material parameters based on the lighting reflection characteristics of the actual texture image.

[0041] The diffuse reflection coefficient describes the ability of an object's surface to diffusely reflect light, the specular reflection coefficient describes the ability of an object's surface to specularly reflect light, and the ambient occlusion coefficient describes the degree to which an object's surface is affected by ambient light. By adjusting these coefficients, the materials in the model can present a visual effect similar to the actual scene under different lighting conditions, thus adapting to the lighting model of the real scene.

[0042] Step S1110: If the material specification verification fails, mark the material abnormality warning in the initial 3D model and trigger the supplier quality traceability process.

[0043] If the material specifications verification of the object to be reviewed fails, it indicates a problem with the material of that construction component. A material anomaly warning is marked in the initial 3D model to alert construction personnel to the component's quality issue. Simultaneously, the supplier quality traceability process is triggered to investigate the cause of the problem, hold the supplier accountable, and take appropriate measures, such as replacing materials or requiring supplier compensation.

[0044] Step S120: Analyze the logical execution relationships between different construction components in the real-time 3D model data set, and generate a set of progress scheduling rules corresponding to the current construction stage.

[0045] After acquiring the real-time 3D model data set, it is necessary to analyze the logical execution relationships between different construction components in order to formulate reasonable schedule rules. Various logical relationships exist between different construction components, such as sequential order and parallel relationships. For example, in building construction, the main structure can only be constructed after the foundation is completed, while the main structure construction of different floors can be carried out in parallel.

[0046] By analyzing the real-time 3D model data set, the logical execution relationship of each construction component is determined. Then, based on the characteristics and requirements of the current construction phase, a set of schedule scheduling rules corresponding to the current construction phase is generated. These rules will guide the schedule arrangement and resource allocation during the construction process.

[0047] Step S121: Traverse each construction component in the real-time 3D model data set and extract the material property constraints and process dependency constraints of the construction component.

[0048] In real-world construction management scenarios, real-time 3D model datasets encompass detailed information on numerous construction components. To accurately analyze the logical execution relationships between these components, it is necessary to traverse each construction component in the dataset. Construction components possess diverse attributes and dependencies, among which material property constraints and process dependency constraints are key factors.

[0049] Material property constraints involve various characteristic requirements of the materials used in construction components. For example, for a column component used in a load-bearing structure, material property constraints might include requirements for material strength grades to ensure the column can withstand the design loads; there might also be requirements for material durability, such as corrosion resistance, to adapt to different construction environments. By extracting relevant information from the real-time 3D model data set, the specific material limitations for each construction component can be clearly defined. Based on the identification information of the construction component, the corresponding material property data can be found in the model data and organized into a set of material property constraints, Ma.

[0050] Process dependency constraints describe the sequential construction order of construction components. In building construction, the construction of many components needs to follow specific processes. For example, bricklaying must be completed before plastering; door and window installation must be done after the wall is basically formed. When extracting process dependency constraints, it is necessary to analyze the logical relationships between construction components. By examining the construction sequence markers and association information in the model data, it can be determined which other components each construction component depends on in terms of process, thereby constructing a set of process dependency constraints Pa.

[0051] Step S122: Identify the set of adjacent components contained in the spatial topology association information of the construction component, and establish the process connection rules between the construction component and the set of adjacent components.

[0052] The spatial topological association information of construction components reflects their position and interconnections in three-dimensional space. Using coordinate information and connectivity details from a real-time 3D model dataset, the set of adjacent components for each construction component can be identified. For example, a floor slab component might have adjacent components including the supporting columns and connected walls.

[0053] After determining the sets of adjacent components, it is necessary to establish process connection rules between the construction components and the sets of adjacent components. These process connection rules are formulated based on construction techniques and quality requirements, and are used to standardize the connection methods and requirements between components during construction. For the connection between floor slabs and columns, the process connection rules may stipulate that the top of the column must be treated before pouring the floor slab concrete to ensure good adhesion between the two. For the installation of walls and doors / windows, the rules may require that the size of the doors / windows match the pre-reserved openings in the wall, and that sealing performance be ensured during installation.

[0054] When establishing process connection rules, the material properties, construction sequence, and spatial relationships of the components must be comprehensively considered. Construction specifications and past construction experience can be referenced, along with detailed information from the real-time 3D model dataset, to develop a specific set of process connection rules Ra for each construction component and its adjacent component sets.

[0055] Step S123: Generate initial schedule scheduling rules based on the material property constraints, the process dependency constraints, and the process connection rules.

[0056] The generation of initial schedule rules is a process that comprehensively considers material property constraints, process dependency constraints, and process connection rules. Material property constraints determine the preconditions for component construction, process dependency constraints clarify the order of construction, and process connection rules regulate the construction connection methods between components. These three factors jointly affect the arrangement of the construction schedule.

[0057] First, based on the process dependency constraints, determine the approximate construction sequence of the construction components. Taking the construction of a multi-story building as an example, foundation construction must precede the main structure construction, and the main structure construction must precede the decoration and finishing construction. Then, considering material property constraints, factors such as material supply time and processing time, further refine the construction sequence. For example, if certain special materials need to be pre-ordered and processed, the construction time of the relevant components will be postponed accordingly.

[0058] Finally, based on the process connection rules, the construction intervals and connection times between adjacent components are reasonably arranged. For example, in the construction of walls and floor slabs, the setting time of concrete must be considered to ensure that the walls reach the set strength before the floor slabs are constructed, thus guaranteeing the stability of the structure. By comprehensively analyzing these three aspects, an initial schedule scheduling rule set Sa is generated.

[0059] Step S124: Obtain the time consumption benchmark data corresponding to the current construction stage from the historical construction log data, perform time sequence alignment processing between the time consumption benchmark data and the initial progress scheduling rules, and generate the progress scheduling rule set.

[0060] Historical construction logs record detailed information about similar past projects at each construction stage, including benchmark data on time consumption corresponding to the current construction stage. This benchmark data is based on practical construction experience and reflects the time required to complete each construction task under normal construction conditions.

[0061] When acquiring historical construction log data, a data query system can be used to filter project logs from the database that are similar to the current construction project in terms of type, scale, and construction environment. Then, a benchmark data set Ta corresponding to the time consumption of the current construction phase can be extracted.

[0062] The time consumption benchmark data set Ta is time-aligned with the initial schedule scheduling rule set Sa. The purpose of time alignment is to make the initial schedule scheduling rules more consistent with the actual construction situation. Specifically, the time consumption information of each construction task in the benchmark data is matched with the corresponding construction task in the initial schedule scheduling rules. If the benchmark data shows that a certain construction task usually takes longer to complete, then the time allocation for that task is extended accordingly in the initial schedule scheduling rules; conversely, if the benchmark data shows that a certain task can be completed faster, then its time allocation is shortened.

[0063] Through this timing alignment process, the initial schedule scheduling rules are adjusted and optimized, ultimately generating a schedule scheduling rule set R.

[0064] Step S125: Convert the set of progress scheduling rules into an executable sequence of task nodes, and map the sequence of task nodes to the spatial topology association information of the real-time 3D model data set.

[0065] The schedule rule set R describes the construction schedule in a relatively abstract way. To facilitate execution by construction personnel, it needs to be converted into an executable sequence of task nodes. A sequence of task nodes is a collection of task nodes with clearly defined start times, finish times, and task contents.

[0066] During the transformation process, the schedule scheduling rule set R is parsed, and each construction task is broken down into specific task nodes. Each task node corresponds to a specific construction operation or stage, such as "column reinforcement binding" or "wall formwork installation". At the same time, a clear start time and finish time are determined for each task node, forming a task node sequence T.

[0067] The task node sequence T is mapped to the spatial topological association information of the real-time 3D model dataset. This means associating each task node with a specific construction component in 3D space. The location of the construction component corresponding to each task node is determined using the coordinate information and component identifiers in the real-time 3D model dataset. For example, the "column rebar tying" task node can be associated with a specific column component in the model, allowing construction workers to intuitively understand the specific location of this task node in 3D space by viewing the model.

[0068] This mapping allows construction workers to clearly see the construction location and time schedule of each task node based on the 3D model, thus enabling them to carry out construction operations more efficiently.

[0069] Step S130: Dynamically match the actual construction progress data with the set of progress scheduling rules to obtain the construction process anomaly detection strategy and resource allocation optimization strategy.

[0070] During construction, it is necessary to acquire real-time construction progress data and dynamically match it with a set of progress scheduling rules to detect any anomalies in the construction process and optimize resource allocation. The actual construction progress data reflects the actual progress of construction components, including the acceptance timestamps of completed components and the estimated time for incomplete components.

[0071] By comparing and analyzing actual construction progress data with a set of schedule scheduling rules, issues such as time deviations and unreasonable resource allocation in the construction process can be identified. Based on the analysis results, strategies for detecting construction process anomalies and optimizing resource allocation are developed to ensure the smooth progress of construction and the rational utilization of resources.

[0072] Step S131: Receive the actual construction progress data uploaded by the construction terminal. The actual construction progress data includes the acceptance timestamps of completed construction components and the estimated time for uncompleted construction components.

[0073] In a construction management system, the construction terminal is a crucial tool for construction workers to record and upload actual construction progress data. After completing each construction component, workers will operate on the construction terminal to record the acceptance timestamp for that component. This process is typically achieved through a dedicated application on the construction terminal. Workers open the application, select the corresponding construction component identifier, and then click the "Complete Acceptance" button. The system will automatically record the current time as the acceptance timestamp.

[0074] For unfinished construction components, construction workers will estimate the estimated time based on the current construction progress and experience. The construction terminal application has a dedicated input box for workers to enter the estimated time. Workers can combine factors such as the remaining workload of the construction component and current construction efficiency to make a comprehensive judgment and enter a reasonable estimated time value.

[0075] The construction terminal periodically uploads the acceptance timestamps of completed construction components and the estimated time for incomplete construction components to the construction management system. After receiving this data, the construction management system organizes it into an actual construction progress data set P, where the set of acceptance timestamps of completed construction components is Ta, and the set of estimated time for incomplete construction components is Te.

[0076] Step S132: Compare the acceptance timestamp with the task node sequence in the progress scheduling rule set on the time axis to identify abnormal task nodes with time deviations.

[0077] The task node sequence in the schedule scheduling rule set specifies the planned start and finish times for each construction task. To identify the difference between the actual construction progress and the planned progress, it is necessary to compare the acceptance timestamp set Ta in the actual construction progress data set P with the task node sequence on the timeline.

[0078] First, locate the task node corresponding to the completed construction component in the task node sequence. Each task node has a unique identifier that corresponds to the identifier of the construction component, enabling accurate matching.

[0079] Then, the acceptance timestamp of each completed construction component is compared with the planned completion time of the corresponding task node. The time difference between the two is calculated. If the time difference exceeds the preset allowable deviation range, the task node is considered to have a time deviation and is identified as an abnormal task node.

[0080] For example, for a wall construction task node, the planned completion time is Tp, and the actual acceptance time is Ta1. The time difference ΔT = Ta1 - Tp is calculated. If |ΔT| is greater than the preset allowable deviation threshold Tth, then the wall construction task node is an abnormal task node. In this way, the acceptance timestamps of all completed construction components are compared to identify all abnormal task nodes with time deviations, forming an abnormal task node set E.

[0081] Step S133: Extract the geometric attribute information and spatial topology association information of the construction component corresponding to the abnormal task node, and determine the influence radiation range of the construction component in three-dimensional space.

[0082] For the identified set E of abnormal task nodes, further analysis of the relevant information of their corresponding construction components is needed. Geometric attribute information and spatial topological association information of the construction components corresponding to these abnormal task nodes should be extracted from the real-time 3D model data set.

[0083] Geometric attribute information includes parameters such as the length, width, height, and shape of the construction components. This information can be obtained from the geometric data module in the real-time 3D model dataset. Spatial topology association information describes the relative positions and connections of the construction components in 3D space, such as adjacency relationships and support relationships between components. This information can be obtained from the topology module in the model data.

[0084] Based on the extracted geometric attribute information and spatial topological association information, the influence radiation range of the construction component in three-dimensional space is determined. The influence radiation range refers to the area where abnormal construction progress of this component may affect surrounding components.

[0085] Taking a large beam component as an example, its geometric properties indicate a long length and large span, while its spatial topology information shows it is connected to multiple floor slabs and columns. Therefore, its influence range may include the floor slabs and columns directly connected to it, as well as other components within a defined range around these floor slabs and columns. The influence range can be determined by analyzing factors such as the mechanical transmission relationships between components and construction process requirements, combined with geometric properties and spatial topology information. The influence range of the construction component corresponding to each abnormal task node is then compiled into an influence range set Ir.

[0086] Step S134: Identify the dependencies of the abnormal task nodes in the construction process network based on the critical path method, calculate the probability of schedule delay risk by combining the process buffer time of adjacent component sets, and generate the construction process anomaly detection strategy containing abnormal construction components.

[0087] The Critical Path Method (CPM) is an important method for analyzing project schedule. It identifies critical tasks that affect the overall project duration by determining the critical path in the project. For a set of abnormal task nodes E, the CPM is used to identify their dependencies in the construction sequence network.

[0088] A construction process network is a network diagram consisting of various construction task nodes and the logical relationships between them. By analyzing this network diagram, it is possible to determine which other task nodes each abnormal task node depends on, and which task nodes depend on the abnormal task node.

[0089] The process buffer time of an adjacent component set refers to the maximum time a task can be delayed without affecting the start time of subsequent tasks. For each abnormal task node, the probability of schedule delay is calculated by combining its dependencies in the construction process network and the process buffer time of the adjacent component set.

[0090] When calculating the probability of project delay risk, multiple factors are considered. If an abnormal task node is on the critical path and its delay exceeds the process buffer time of adjacent component sets, the risk of project delay is high; conversely, if the task node is not on the critical path and has sufficient process buffer time, the risk of project delay is relatively low. A risk assessment model can be established, using these factors as input, to calculate the probability of project delay risk for each abnormal task node.

[0091] Based on the calculated probability of project delay risk, an anomaly detection strategy for the construction process, including abnormal construction components, is generated. This strategy includes suggestions for handling abnormal construction components, such as whether additional resources are needed to accelerate construction progress or whether the construction sequence needs to be adjusted; and suggestions for adjusting the construction plan of affected components, such as whether certain tasks need to be scheduled in advance or whether the time for certain tasks needs to be extended. These suggestions are then compiled into a set of construction process anomaly detection strategies, Sd.

[0092] Step S135: Based on the resource consumption rate per unit time in the historical construction log, convert the time difference between the estimated time consumption and the time consumption benchmark data into the corresponding labor demand gap and material demand gap, and generate the resource allocation optimization strategy that includes material replenishment priority and manpower scheduling scheme in combination with the project delay risk probability.

[0093] Historical construction logs record the resource consumption rate per unit time for each construction phase of previous projects, including labor consumption rate and material consumption rate. Labor consumption rate can be expressed as the amount of labor required for each construction task per unit time, while material consumption rate can be expressed as the amount of materials required for each construction task per unit time.

[0094] For the estimated time set Te of incomplete construction components, it is compared with the time consumption benchmark data set Ta, and the time difference value is calculated. The time difference value reflects the deviation between the actual estimated time and the benchmark data, which may lead to changes in resource requirements.

[0095] Based on the resource consumption rate per unit time in historical construction logs, the time difference values ​​are converted into corresponding labor demand gaps and material demand gaps. For example, if the estimated time is longer than the benchmark time consumption data, it indicates that more labor and materials may be needed to complete the construction of this component. In specific calculations, the time difference value is multiplied by the resource consumption rate per unit time to obtain the labor demand gap set Lg and the material demand gap set Mg.

[0096] Based on the probability of project delay risk, determine the priority for material replenishment and the manpower allocation plan. For task nodes with a high probability of project delay risk, prioritize the replenishment of materials and the allocation of manpower. The material replenishment priority can be determined based on the material demand gap and the probability of project delay risk; materials for task nodes with large material demand gaps and high project delay risk will be replenished first. The manpower allocation plan is arranged based on the labor demand gap and the probability of project delay risk, prioritizing the allocation of labor to task nodes with large labor demand gaps and high project delay risk.

[0097] In this way, a set of resource allocation optimization strategies Sr, which includes material replenishment priorities and manpower scheduling plans, is generated.

[0098] Step S140: Adjust the component parameter configuration of the real-time 3D model data set based on the construction process anomaly detection strategy to generate updated 3D model verification data.

[0099] The construction process anomaly detection strategy clearly identifies abnormal construction components and corresponding handling suggestions. Based on this information, the component parameter configurations of the real-time 3D model dataset are adjusted. Because the presence of abnormal construction components may affect the safety and progress of the entire construction process, their parameters need to be reset to ensure the smooth progress of subsequent construction. During the adjustment process, the spatial topology associations and process connection rules between components must be fully considered to avoid new problems arising from parameter adjustments.

[0100] Step S141: Locate the abnormal construction components marked in the construction process anomaly detection strategy, and obtain the current geometric parameters and design geometric parameters of the abnormal construction components.

[0101] The construction process anomaly detection strategy clearly identifies abnormal construction components. When locating these abnormal components in the real-time 3D model dataset, the component's unique identifier is used. Each construction component has a specific code in the model dataset, similar to an ID number, which allows for rapid identification of the corresponding abnormal component within the component information module of the dataset.

[0102] For any abnormal construction component located, its current geometric parameters are obtained. These current geometric parameters are the component's dimensions, shape, and other relevant parameters at the actual construction site. This can be obtained using on-site measuring equipment, such as a high-precision laser rangefinder for measuring length and width, and a 3D scanner for acquiring the component's overall shape data. These measured data are then compiled into a current geometric parameter set Cp.

[0103] Design geometric parameters are the ideal dimensions and shape parameters that the component should possess, determined during the construction design phase. The design geometric parameter set Dp is extracted from the construction design document database by searching the corresponding design document based on the component's identification information. For example, for a column component designed as a cuboid, the design geometric parameters might specify the exact values ​​of its length, width, and height, while the current geometric parameters reflect the actual length, width, and height of the column after construction.

[0104] Step S142: Calculate the spatial deformation difference between the current geometric parameters and the design geometric parameters, and generate a structural stability score by combining the material strength properties and design load requirements of the abnormal construction components through a finite element analysis model.

[0105] Calculate the spatial deformation difference between the current set of geometric parameters Cp and the design set of geometric parameters Dp. For each dimension of the parameter, such as length, width, and height, calculate the difference separately. For example, for the length parameter, calculate the difference between the current length and the design length; for the angle parameter, calculate the deviation between the current angle and the design angle. Summarize these differences into a spatial deformation difference set Spd.

[0106] The material strength properties of components with abnormal construction can be obtained from the material testing reports provided by the material suppliers. These reports will record in detail the compressive strength, tensile strength, and other indicators of the materials, forming a set of material strength properties, Ms. Design load requirements are determined during the design phase based on the building's function and safety standards. These requirements include the static and dynamic loads that the components need to withstand, forming a set of design load requirements, Dl.

[0107] The finite element method (FEM) is a numerical analysis tool that divides abnormally constructed components into numerous tiny elements. During the analysis, the set of spatial deformation differences (Spd), the set of material strength properties (Ms), and the set of design load requirements (Dl) are used as input parameters. The FEM simulates the mechanical response of the component under design loads, calculating the stress distribution, strain, and other mechanical properties within the component.

[0108] Structural stability scores are generated based on these mechanical indicators. A series of scoring criteria can be pre-defined; for example, a lower score is given when the stress value inside the component exceeds a set proportion of the material strength, and a higher score is given when the stress distribution is relatively uniform and does not exceed the safety range. In this way, the calculation results of the finite element analysis model are transformed into an intuitive structural stability score Ss.

[0109] Step S143: Adjust the material property constraints of the abnormal construction components according to the structural stability score, and generate an alternative component parameter configuration scheme.

[0110] The structural stability score Ss reflects the degree of structural stability of the component under abnormal construction conditions. A low score indicates poor structural stability of the component, which may not meet design load requirements and necessitates adjustments to its material property constraints.

[0111] Material property constraints include requirements for material type, strength grade, and specifications. The direction and extent of adjustments are determined based on the specific structural stability score (Ss). For example, if the score is extremely low, it may be necessary to replace it with a higher-strength material; if the score is slightly low, the amount of material used can be increased or the material specifications can be changed.

[0112] By adjusting material property constraints, alternative component parameter configuration schemes are generated. These schemes include new material property parameters, such as the changed material type, adjusted strength grade, and corresponding dimensional parameters. For example, for a column component, the original design used ordinary concrete, but after adjustment, it might be replaced with high-strength concrete, and the column's cross-sectional dimensions might be increased. These new parameters are then compiled into a set of alternative component parameter configuration schemes, Acp.

[0113] Step S144: Replace the original parameters of the abnormal construction component in the real-time three-dimensional model data set, and simulate the influence path of the alternative component parameter configuration scheme on the spatial topological association information of adjacent component sets.

[0114] In the real-time 3D model dataset, locate the record corresponding to the abnormal construction component and replace its original parameters with new parameters from the alternative component parameter configuration scheme set Acp. This replacement process must ensure the accuracy and completeness of the data to avoid errors or omissions.

[0115] This study investigates the impact of simulated alternative component parameter configuration schemes on the spatial topological relationships of adjacent component sets. Spatial topological relationships describe the relative positions and connectivity of components in three-dimensional space. Using computer simulation techniques and based on a real-time three-dimensional model dataset, the interaction between abnormal construction components and adjacent components is analyzed according to the new parameter configuration.

[0116] For example, when the size of an abnormally constructed component increases, it may affect the installation space of adjacent components, requiring repositioning or dimensional modifications. During the simulation, factors such as the mechanical transmission relationships between components and construction process requirements are considered to predict the impact path of the new parameter configuration on adjacent components. Simulations can be performed by establishing mechanical models, motion models, etc., and the simulation-derived impact path information is compiled into an impact path set Ip.

[0117] Step S145: If the influence path does not exceed the preset process connection rule threshold, then mark the three-dimensional model data set after parameter replacement as the updated three-dimensional model verification data.

[0118] The preset process connection rule thresholds are a range set according to construction technology and safety requirements, used to measure whether the impact of component parameter changes on adjacent components is within acceptable limits. The process connection rule threshold set Tr includes the allowable ranges for various influencing factors, such as position offset and angle deviation.

[0119] The set of influencing paths (Ip) is compared with the set of process connection rule thresholds (Tr). For each influencing factor in the set of influencing paths, it is checked whether it falls within the corresponding process connection rule threshold range. For example, it is checked whether the positional offset of adjacent components exceeds the maximum allowable offset, and whether the angular deviation is within the allowable angular range.

[0120] If all influencing factors in the path set Ip do not exceed the preset threshold set Tr for process connection rules, it indicates that the alternative component parameter configuration scheme will not have a serious negative impact on the entire construction process. In this case, the 3D model data set after parameter replacement is marked as the updated 3D model verification data. This data set will serve as an important basis for subsequent construction schedule adjustments and resource allocation, and includes the updated parameters of abnormal construction components and assessment information on their impact on adjacent components.

[0121] Step S150: Generate a construction progress adjustment instruction based on the resource allocation optimization strategy and the updated 3D model verification data, and synchronize the construction progress adjustment instruction to the construction management terminal.

[0122] The resource allocation optimization strategy determined the priority of material replenishment and manpower scheduling plan, and the updated 3D model verification data reflected the latest status and parameter configuration of construction components. Combining these two aspects of information, construction schedule adjustment instructions were generated. These instructions guide construction personnel on how to adjust the construction schedule and rationally allocate resources to ensure that construction proceeds smoothly according to plan. After generation, the instructions are synchronized to the construction management terminal, enabling construction personnel to obtain the latest construction arrangements in a timely manner.

[0123] Step S151: Extract the material replenishment priority and manpower scheduling plan from the resource allocation optimization strategy, and match them with the real-time inventory data and personnel attendance data in the supplier database.

[0124] Resource allocation optimization strategies include key information such as material replenishment priorities and manpower scheduling plans. To implement these strategies, it's necessary to first accurately extract material replenishment priorities and manpower scheduling plans from them. Material replenishment priorities clarify the order in which different materials should be replenished; for example, certain critical building materials such as steel bars and cement may have higher replenishment priorities. Manpower scheduling plans specify the direction of personnel deployment and task allocation, such as assigning experienced workers to key construction phases.

[0125] The supplier database stores real-time inventory data for each supplier, reflecting the types and quantities of materials currently available. Personnel attendance data records the attendance status of construction workers, including on-duty status and leave status. By matching materials in the replenishment priority list with the real-time inventory data in the supplier database, it determines which materials can be obtained from which suppliers, as well as the quantity and estimated time of acquisition. Simultaneously, based on personnel identification information, it matches the personnel needs in the manpower dispatch plan with personnel attendance data to understand which personnel can participate in the corresponding work tasks.

[0126] Step S152: Determine the material allocation route and estimated arrival time based on the real-time inventory data, and generate a phased manpower deployment plan in conjunction with the personnel attendance data.

[0127] Based on the real-time inventory data obtained through matching, the material allocation route and estimated arrival time are determined. Determining the material allocation route requires comprehensive consideration of multiple factors, such as the supplier's geographical location, transportation mode, transportation cost, and transportation time. For suppliers close to the construction site, road transportation can be chosen to reduce transportation time and costs; for suppliers located far away and with large quantities of materials, rail or waterway transportation may need to be considered. By analyzing these factors, the optimal material allocation route is planned.

[0128] The estimated delivery time is determined based on the transportation speed and route of the materials. Considering various potential issues during transportation, such as traffic congestion and weather changes, a buffer period needs to be allowed. For example, based on historical transportation data and real-time traffic information, it is estimated how long it will take for a certain material to arrive at the construction site from the supplier via a specific transportation route.

[0129] A phased manpower deployment plan is generated by combining personnel attendance data. The construction process can typically be divided into different phases, each with different tasks and personnel requirements. Based on personnel attendance data and the characteristics of the construction tasks, manpower is rationally allocated to each phase. For example, in the foundation construction phase, more manual laborers are needed for earthwork excavation and foundation pouring; in the main structure construction phase, more skilled workers are needed for rebar tying and formwork installation. Through a phased manpower deployment plan, it is ensured that sufficient and suitable personnel are involved in the work at each construction phase.

[0130] Step S153: Map the material allocation path and the phased manpower deployment plan to the spatial topology association information of the updated three-dimensional model verification data to generate a three-dimensional visualization scheduling map.

[0131] The updated 3D model verification data includes the latest status and parameter configurations of the construction components, and its spatial topology association information describes the location and interrelationships of each component in 3D space. Mapping the material allocation routes and phased manpower deployment plans to this spatial topology association information is to determine the specific distribution of material transportation routes and personnel work positions in 3D space.

[0132] For material allocation routes, based on their origin (supplier location) and destination (material storage point at the construction site) in real space, the corresponding coordinates are located in the 3D model, and the transportation route is drawn in the model. Simultaneously, key nodes that may be passed through during transportation, such as transfer points and transportation hubs, are marked. For phased manpower deployment plans, each person's work tasks are mapped to specific construction component locations in the 3D model, and the personnel's work areas and movement routes are marked.

[0133] This mapping generates a 3D visual scheduling map. Based on a 3D model, the map intuitively displays information such as material transportation routes, personnel work locations, and construction progress. Construction workers can clearly understand their work tasks and locations, as well as the supply status of materials, by viewing this map.

[0134] Step S154: Based on real-time construction equipment positioning data and personnel activity trajectories, a dynamic path planning algorithm is used to analyze the construction movement conflict areas in the three-dimensional visualization scheduling map, and optimize the material allocation path and the phased manpower deployment plan.

[0135] Real-time construction equipment location data is acquired through positioning devices installed on the equipment, reflecting the equipment's location on the construction site in real time. Personnel movement trajectories are recorded through positioning tags worn by personnel or by monitoring equipment at the construction site, showing the movement paths of personnel.

[0136] A dynamic path planning algorithm is used to analyze the 3D visualized scheduling map and identify conflict areas in construction movement routes. These conflict areas refer to regions where the movement routes of construction equipment and personnel may clash, such as intersections and narrow passages. The dynamic path planning algorithm considers real-time equipment location data and personnel movement trajectories to predict potential conflicts. For example, when a piece of construction equipment travels along a predetermined material allocation route, the algorithm analyzes whether it will intersect with the movement trajectory of personnel. If an intersection is likely, the area is marked as a conflict area.

[0137] Based on the analysis results, the material allocation routes and phased manpower deployment plans were optimized. For material allocation routes, if a route was found to pass through an area conflicting with construction movement, the route could be adjusted to select an alternative suitable route. For phased manpower deployment plans, the work areas and movement routes of personnel could be rearranged to avoid encounters between personnel and construction equipment in conflict areas. This optimization improved construction safety and efficiency.

[0138] Step S155: Convert the optimized scheduling scheme into the construction progress adjustment instruction containing time nodes and responsible entities, and bind the triggering conditions of the construction progress adjustment instruction to the updated 3D model verification data.

[0139] The optimized material allocation routes and phased manpower deployment plans were converted into construction schedule adjustment instructions. These instructions included timeframes and responsible parties for each task. Timeframes clearly defined the start and end times for each task, such as the estimated arrival time of materials and the start and end times of personnel work. The responsible parties specified the personnel or departments responsible for executing the task, ensuring that each task had a clearly defined person in charge.

[0140] The trigger conditions for construction schedule adjustment commands are linked to the updated 3D model verification data through event binding. Trigger conditions can be specific construction states reached by a component in the updated 3D model verification data, such as a wall component completing a certain percentage of construction or a piece of equipment being installed. When these trigger conditions are met, the corresponding construction schedule adjustment command will automatically take effect. This event binding ensures that construction schedule adjustment commands are executed promptly based on the actual construction progress.

[0141] Step S156: Decompose the construction progress adjustment instruction into multiple instruction sub-units, and associate each instruction sub-unit with the three-dimensional spatial coordinates of a construction component and the task execution time window.

[0142] To facilitate the execution of construction schedule adjustment instructions by construction personnel, they are broken down into multiple instruction sub-units. Each instruction sub-unit corresponds to a specific construction task and is associated with the three-dimensional spatial coordinates of a construction component and the task execution time window.

[0143] The three-dimensional spatial coordinates of the construction components clearly define the specific location of the construction task, and the updated three-dimensional model verifies that the data can be accurately obtained. The task execution time window specifies the execution time period of the task, that is, the range from the start time to the end time. For example, an instruction sub-unit may instruct to complete the painting task of a wall component at a specific three-dimensional spatial coordinate position (such as x, y, z coordinates) within a certain time period (such as from t1 to t2).

[0144] By breaking down construction schedule adjustment instructions into sub-instruction units, construction personnel can more clearly understand the requirements and execution time of each specific task, thereby improving the accuracy and efficiency of construction.

[0145] Step S157: Highlight the construction component corresponding to the instruction subunit in the three-dimensional interface of the construction management terminal, and overlay the task execution time window and resource requirement label.

[0146] The construction management terminal's 3D interface displays updated 3D model verification data, allowing construction personnel to intuitively view the construction site situation. Within this 3D interface, the construction components corresponding to the instruction sub-units are highlighted. Different colors, brightness levels, or flashing effects can be used for highlighting to enable construction personnel to quickly locate the components requiring tasks.

[0147] Simultaneously, the task execution time window and resource requirement label are overlaid. The task execution time window intuitively displays the task's execution period, which can be shown in a timeline format, allowing construction personnel to clearly understand the task's start and end times. The resource requirement label displays information such as the materials and manpower required to complete the task, such as the quantity of a certain material and the number of workers needed. In this way, construction personnel can clearly understand the specific requirements, execution time, and required resources for each task on a 3D interface.

[0148] Step S158: Receive the instruction confirmation signal fed back by the construction management terminal. When the instruction confirmation signal covers all instruction sub-units, activate the execution state of the construction progress adjustment instruction.

[0149] After reviewing the construction progress adjustment instructions, construction personnel send a confirmation signal through the construction management terminal. The terminal interface has a dedicated confirmation button or operation option; by clicking the corresponding button or completing a specific operation, construction personnel indicate that they have understood and agreed to execute the instruction sub-unit.

[0150] The system continuously receives instruction confirmation signals from the construction management terminal and performs statistical analysis on these signals. When the confirmation signals cover all instruction sub-units, it indicates that the construction personnel have understood and agreed to execute all tasks, at which point the execution status of the construction schedule adjustment instruction is activated. The construction schedule adjustment instruction becomes effective, and the construction personnel begin executing the tasks according to the instructions.

[0151] Step S159: Monitor the completion progress of each instruction subunit in the execution state in real time. When a lag in progress or a lack of resources is detected, trigger the dynamic update operation of the three-dimensional visualization scheduling map.

[0152] During construction, the progress of each instruction sub-unit is monitored in real time. This monitoring can be achieved in various ways, such as construction personnel manually updating the task progress on the construction management terminal, or using sensors and other equipment to monitor the status of construction components in real time. For example, for a concrete pouring task, the progress can be determined by monitoring the height of the poured concrete.

[0153] When a delay or resource shortage is detected in a specific instruction subunit, it indicates a problem has occurred during construction and requires immediate adjustment. The delay may be due to increased construction difficulty, insufficient personnel, or other reasons; the resource shortage may be caused by untimely material supply, equipment malfunction, or other reasons.

[0154] Once a delay or resource shortage is detected, the 3D visualization scheduling map is dynamically updated. Based on the latest construction progress and resource status, material allocation routes and manpower deployment plans are re-planned, and relevant information in the map is updated. For example, if a shortage of a certain material is found, the material allocation route needs to be readjusted, alternative suppliers need to be found, or transportation speed needs to be accelerated; if a shortage of personnel is found in a certain area, personnel need to be transferred from other areas.

[0155] Step S1510: Push the dynamically updated 3D visualization scheduling map to the relevant construction terminals and regenerate the construction progress adjustment instructions adapted to the current construction stage.

[0156] The dynamically updated 3D visualization scheduling map is pushed to relevant construction terminals, including handheld terminals used by construction workers and monitoring terminals at the construction site. Through wireless communication technology, the updated map data is sent to each terminal device, ensuring that construction workers can obtain the latest construction arrangements in a timely manner.

[0157] Based on the dynamically updated information, a new construction schedule adjustment instruction adapted to the current construction phase will be generated. This new instruction will take into account issues such as schedule delays or resource shortages, adjusting task timelines, responsible parties, and resource requirements. For example, if a task is behind schedule, its execution window may need to be extended; if a resource is missing, the instruction must specify the timing and method for replenishing that resource.

[0158] By regenerating construction schedule adjustment instructions, construction can proceed smoothly according to the new plan, improving both efficiency and quality.

[0159] Furthermore, the method may further include:

[0160] Step S160: Collect environmental monitoring data of the construction site within a preset time interval. The environmental monitoring data includes temperature fluctuation values, humidity change curves, and dust concentration indicators.

[0161] Environmental conditions at the construction site significantly impact the construction process, necessitating the collection of environmental monitoring data at predetermined time intervals. Environmental monitoring equipment, such as temperature sensors, humidity sensors, and dust concentration sensors, can be deployed at various locations within the construction site. These devices monitor parameters like temperature, humidity, and dust concentration in real time, recording temperature fluctuations, humidity change curves, and dust concentration indices. For example, temperature fluctuations reflect the range of temperature variation over a period, humidity change curves illustrate how humidity changes over time, and dust concentration indices represent the amount of dust in the air at the construction site.

[0162] Step S161: Analyze the influence weight of the environmental monitoring data on the construction components in the updated three-dimensional model verification data, and generate environmentally adaptive construction parameter correction quantities.

[0163] The collected environmental monitoring data was analyzed to determine its influence weight on the construction components in the updated 3D model validation data. Different environmental factors may have varying degrees of impact on different construction components; for example, high temperatures may affect the setting speed of concrete, and high humidity may cause wood to warp due to moisture. By analyzing the environmental monitoring data and the characteristics of the construction components, the influence weight of each environmental factor on the construction components was calculated. Then, environmentally adaptive construction parameter corrections were generated based on the influence weights. These corrections are adjustments to the original parameters of the construction components to adapt to different environmental conditions.

[0164] Step S162: Add the environmentally adaptive construction parameter correction to the resource allocation optimization strategy, and recalculate the material replenishment priority and manpower scheduling plan.

[0165] The generated environmentally adaptive construction parameter corrections are then overlaid into the resource allocation optimization strategy. Since changes in environmental conditions may affect construction progress and resource requirements, the resource allocation optimization strategy needs adjustment. Based on the overlaid parameters, the material replenishment priority and manpower scheduling plan are recalculated. For example, if the ambient temperature is too high, it may be necessary to increase the replenishment priority of concrete cooling materials and adjust the manpower scheduling plan to assign more personnel to concrete curing.

[0166] Step S163: Update the task execution time window and resource requirement label in the construction progress adjustment instruction according to the recalculated scheduling scheme.

[0167] Based on the recalculated material replenishment priority and manpower allocation plan, update the task execution time window and resource requirement tag in the construction schedule adjustment instruction. The task execution time window may be extended or shortened due to environmental factors, and the resource requirement tag also needs to be adjusted according to the new resource allocation plan. For example, if it is necessary to increase the replenishment quantity of a certain material, the corresponding material quantity in the resource requirement tag also needs to be updated.

[0168] Step S164: The updated 3D visualization scheduling map is synchronized in the construction management terminal, and the construction component areas affected by environmental factors are highlighted.

[0169] The updated 3D visualization scheduling map is synchronized to the construction management terminal, allowing construction personnel to see the latest construction arrangements. Simultaneously, areas of construction components affected by environmental factors are highlighted in the map. These areas can be highlighted using different colors and markers to remind construction personnel to pay attention to the impact of environmental factors on these components and to take appropriate measures to ensure construction quality and safety. For example, areas where concrete pouring is affected by high temperatures can be marked in red to remind construction personnel to strengthen concrete curing procedures.

[0170] Figure 2 The illustration shows exemplary hardware and software components of a BIM-integrated construction process digital management system 100 that can implement the ideas of this application, according to some embodiments of this application. For example, a processor 120 can be used on the BIM-integrated construction process digital management system 100 and to perform the functions described in this application.

[0171] The BIM-integrated construction process digital management system 100 can be a general-purpose server or a special-purpose server; both can be used to implement the BIM-integrated construction process digital management method of this application. Although only one server is shown in this application, for convenience, the functions described in this application can be implemented in a distributed manner on multiple similar platforms to balance the load.

[0172] For example, a BIM-integrated construction process digital management system 100 may include a network port 110 connected to a network, one or more processors 120 for executing program instructions, a communication bus 130, and various forms of storage media 140, such as a disk, ROM, or RAM, or any combination thereof. Exemplarily, the BIM-integrated construction process digital management system 100 may also include program instructions stored in ROM, RAM, or other types of non-transitory storage media, or any combination thereof. The methods of this application can be implemented according to these program instructions. The BIM-integrated construction process digital management system 100 also includes an I / O interface 150 between the computer and other input / output devices.

[0173] For ease of explanation, only one processor is described in the BIM-integrated construction process digital management system 100. However, it should be noted that the BIM-integrated construction process digital management system 100 of this application may also include multiple processors, and therefore the steps performed by one processor described in this application may also be performed jointly by multiple processors or individually. For example, if the processor of the BIM-integrated construction process digital management system 100 performs steps A and B, it should be understood that steps A and B may also be performed jointly by two different processors or individually by one processor. For example, the first processor performs step A, the second processor performs step B, or the first processor and the second processor jointly perform steps A and B.

[0174] Furthermore, this embodiment of the invention also provides a readable storage medium, which has computer-executable instructions pre-set in it. When the processor executes the computer-executable instructions, the above-mentioned digital management method for construction process combined with BIM is realized.

[0175] It should be noted that, in order to simplify the description of the present invention and thus help to understand one or more embodiments of the invention, multiple features may sometimes be grouped into one embodiment, drawing or description thereof in the foregoing description of the embodiments of the present invention.

Claims

1. A digital management method for construction process combining BIM, characterized in that, The method includes: Collect a real-time 3D model data set of the construction site, wherein the real-time 3D model data set contains geometric attribute information and spatial topology association information of multiple construction components; The logical execution relationships between different construction components in the real-time 3D model data set are analyzed to generate a set of progress scheduling rules corresponding to the current construction stage. The actual construction progress data is dynamically matched with the set of progress scheduling rules to obtain the construction process anomaly detection strategy and resource allocation optimization strategy. Based on the construction process anomaly detection strategy, the component parameter configuration of the real-time 3D model data set is adjusted to generate updated 3D model verification data; Based on the resource allocation optimization strategy and the updated 3D model verification data, a construction progress adjustment instruction is generated and synchronized to the construction management terminal. The step of parsing the logical execution relationships between different construction components in the real-time 3D model data set to generate a set of progress scheduling rules corresponding to the current construction stage includes: Traverse each construction component in the real-time 3D model data set and extract the material property constraints and process dependency constraints of the construction component; Identify the set of adjacent components contained in the spatial topology association information of the construction component, and establish process connection rules between the construction component and the set of adjacent components; An initial schedule scheduling rule is generated based on the material property constraints, the process dependency constraints, and the process connection rules. Obtain the time consumption benchmark data corresponding to the current construction stage from the historical construction log data, and perform time-series alignment processing between the time consumption benchmark data and the initial progress scheduling rules to generate the progress scheduling rule set; The set of schedule rules is converted into an executable sequence of task nodes, and the sequence of task nodes is mapped to the spatial topology association information of the real-time 3D model data set.

2. The digital management method for construction process combined with BIM according to claim 1, characterized in that, The collection of real-time 3D model data of the construction site includes: Deploy laser scanning and image acquisition equipment to obtain multi-angle point cloud data and texture image data of the construction site; The multi-angle point cloud data is denoised and registered to generate a high-precision three-dimensional point cloud model. The texture image data is mapped onto the corresponding surface of the high-precision 3D point cloud model to generate an initial 3D model with material properties. Identify the geometric deviation areas of components in the initial 3D model that do not match the design drawings, manually annotate them to generate a corrected 3D model, and synchronously update the manual annotation results to the version update record of the real-time 3D model data set; The corrected 3D model is associated with the progress milestone nodes in the construction plan to form a version update record of the real-time 3D model data set.

3. The digital management method for construction process combined with BIM according to claim 2, characterized in that, After mapping the texture image data onto the corresponding surface of the high-precision 3D point cloud model to generate an initial 3D model with material properties, the method further includes: The color distribution features in the texture image data are extracted and converted into LAB color space parameters. At the same time, the surface roughness features are extracted. The LAB color space parameters and surface roughness features are combined into a material feature vector of the same dimension, which is matched with standard material parameters with the same dimension definition in the material database. When the difference between the color distribution feature and the standard material parameter exceeds a preset threshold, the construction component corresponding to the texture image data is marked as an object to be reviewed. Obtain the purchase orders and quality inspection reports of the object to be reviewed, and verify whether the material specifications of the object to be reviewed meet the design requirements; If the material specifications are verified, the diffuse reflection coefficient, specular reflection coefficient, and ambient light occlusion coefficient in the standard material parameters will be adjusted in a coordinated manner based on the light reflection characteristics of the actual texture image to adapt to the actual scene lighting model. If the material specification verification fails, a material anomaly warning will be marked in the initial 3D model, and the supplier quality traceability process will be triggered.

4. The digital management method for construction process combined with BIM according to claim 1, characterized in that, The step of dynamically matching the actual construction progress data with the set of progress scheduling rules to obtain the construction process anomaly detection strategy and resource allocation optimization strategy includes: Receive the actual construction progress data uploaded by the construction terminal, wherein the actual construction progress data includes the acceptance timestamps of completed construction components and the estimated time for uncompleted construction components; The acceptance timestamp is compared with the task node sequence in the progress scheduling rule set on a time axis to identify abnormal task nodes with time deviations. Extract the geometric attribute information and spatial topology association information of the construction components corresponding to the abnormal task nodes, and determine the influence radiation range of the construction components in three-dimensional space; Based on the critical path method, the dependencies of the abnormal task nodes in the construction process network are identified. Combined with the process buffer time of adjacent component sets, the probability of schedule delay risk is calculated, and the abnormal detection strategy of the construction process containing abnormal construction components is generated. Based on the resource consumption rate per unit time in the historical construction logs, the time difference between the estimated time consumption and the benchmark data is converted into the corresponding labor demand gap and material demand gap. Combined with the probability of project delay risk, a resource allocation optimization strategy including material replenishment priority and manpower scheduling scheme is generated.

5. The digital management method for construction process incorporating BIM according to claim 1, characterized in that, The step of adjusting the component parameter configuration of the real-time 3D model data set based on the construction process anomaly detection strategy to generate updated 3D model verification data includes: Locate the abnormal construction components marked in the construction process anomaly detection strategy, and obtain the current geometric parameters and design geometric parameters of the abnormal construction components; Calculate the spatial deformation difference between the current geometric parameters and the design geometric parameters, and generate a structural stability score by combining the material strength properties and design load requirements of the abnormal construction components through a finite element analysis model. Based on the structural stability score, adjust the material property constraints of the abnormal construction components to generate alternative component parameter configuration schemes; Replace the original parameters of the abnormal construction component in the real-time three-dimensional model data set, and simulate the influence path of the alternative component parameter configuration scheme on the spatial topological association information of adjacent component sets; If the influence path does not exceed the preset process connection rule threshold, the 3D model data set after parameter replacement is marked as the updated 3D model verification data.

6. The digital management method for construction process incorporating BIM according to claim 1, characterized in that, The step of generating construction schedule adjustment instructions based on the resource allocation optimization strategy and the updated 3D model verification data includes: Extract the material replenishment priority and manpower scheduling plan from the resource allocation optimization strategy, and match them with real-time inventory data and personnel attendance data in the supplier database; Based on the real-time inventory data, determine the material allocation route and estimated arrival time, and generate a phased manpower deployment plan by combining the personnel attendance data; The material allocation path and the phased manpower deployment plan are mapped to the spatial topological association information of the updated three-dimensional model verification data to generate a three-dimensional visual scheduling map; Based on real-time construction equipment positioning data and personnel activity trajectories, a dynamic path planning algorithm is used to analyze the construction movement conflict areas in the three-dimensional visualization scheduling map, and optimize the material allocation path and the phased manpower deployment plan. The optimized scheduling scheme is converted into a construction progress adjustment instruction that includes time nodes and responsible parties, and the triggering conditions of the construction progress adjustment instruction are event-bound to the updated 3D model verification data.

7. The digital management method for construction process incorporating BIM according to claim 6, characterized in that, The step of synchronizing the construction progress adjustment instruction to the construction management terminal includes: The construction progress adjustment instruction is decomposed into multiple instruction sub-units, and each instruction sub-unit is associated with the three-dimensional spatial coordinates of a construction component and the task execution time window; The construction components corresponding to the instruction subunit are highlighted in the three-dimensional interface of the construction management terminal, and the task execution time window and resource requirement label are overlaid. The system receives an instruction confirmation signal from the construction management terminal. When the instruction confirmation signal covers all instruction sub-units, the system activates the execution state of the construction progress adjustment instruction. The system monitors the completion progress of each instruction subunit in the execution state in real time. When a delay or resource deficiency is detected, the system triggers a dynamic update operation of the three-dimensional visualization scheduling map. The dynamically updated 3D visualization scheduling map is pushed to the relevant construction terminals, and the construction progress adjustment instructions adapted to the current construction stage are regenerated.

8. The digital management method for construction process combined with BIM according to claim 1, characterized in that, After generating the construction schedule adjustment instruction based on the resource allocation optimization strategy and the updated 3D model verification data, the method further includes: Environmental monitoring data of the construction site is collected within a preset time interval. The environmental monitoring data includes temperature fluctuation values, humidity change curves and dust concentration indicators. Analyze the influence weights of the environmental monitoring data on the construction components in the updated 3D model verification data, and generate environmentally adaptive construction parameter correction quantities; The environmentally adaptive construction parameter corrections are superimposed on the resource allocation optimization strategy to recalculate the material replenishment priority and manpower scheduling plan. Update the task execution time window and resource requirement label in the construction progress adjustment instruction according to the recalculated scheduling scheme; The three-dimensional visualization scheduling map is updated synchronously in the construction management terminal, highlighting the construction component areas affected by environmental factors.

9. A digital management system for construction process integrating BIM, characterized in that, The system includes a processor and a memory, the memory being connected to the processor. The memory is used to store programs, instructions, or code, and the processor is used to execute the programs, instructions, or code in the memory to implement the digital management method for construction process combined with BIM as described in any one of claims 1-8.

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