A BIM building model construction method for building engineering design

Abstract

The application relates to the technical field of electric digital data processing, in particular to a BIM building model construction method for building engineering design, which comprises the following steps: determining the newly added building area of each construction stage relative to the previous construction stage based on the change of the BIM building model of the building project at different construction stages; screening out key areas and non-key areas from all the newly added building areas; determining the key degree of the key areas based on the construction complexity of the key areas, and then determining the adaptive LOD level of the key areas; assigning the non-key areas with a set LOD level which is not higher than the adaptive LOD level; and constructing the BIM building model based on the set LOD level assigned to the non-key areas of all the construction stages and the adaptive LOD level of the key areas. The application determines the adaptive LOD level for different key areas, thereby reducing the calculation amount while ensuring the construction quality of the BIM building model.

Description

Technical Field

[0001] This invention relates to the field of electronic digital data processing technology, and more specifically to a BIM building model construction method for architectural engineering design. Background Technology

[0002] Building Information Modeling (BIM) refers to the integration of information from all aspects and fields of a building project into a three-dimensional building model throughout its entire lifecycle. This allows users from different sectors to access the information they need from the model, thereby achieving information integration, exchange, and collaborative work. Utilizing BIM technology can not only reduce design errors, improve architectural design quality, shorten project timelines, and facilitate later operation and maintenance, but also significantly reduce project costs and waste by maintaining information throughout the entire lifecycle of a construction project, thus improving productivity.

[0003] In the process of building BIM architectural models for architectural engineering design, tracking the construction progress is crucial for refining the model. During the architectural design phase, the BIM architectural model is a conceptual model, typically with a Level of Detail (LOD) of 100 to 300. After the initial BIM architectural model is completed (i.e., a basic model with low detail), the architectural design department tracks the construction progress, gradually refining the model based on actual construction conditions to obtain the final model (a high-detail model). For example, unforeseen conditions may arise on the construction site, requiring the design team to adjust the model accordingly and regularly compare the BIM model with the actual construction progress to ensure the model reflects the latest construction status. This allows the architectural design department to ensure the BIM model remains up-to-date and accurate throughout the entire construction process, thereby improving construction efficiency, reducing rework and waste, and ultimately achieving successful project delivery.

[0004] In the process of building a BIM building model, different areas often require different Level of Detail (LOD) levels. When the area division is inaccurate and the LOD level selection for different areas is inaccurate, it is easy to cause non-critical areas to use high-detail models, wasting computing resources, or critical areas to use low-detail models, reducing the model quality. Summary of the Invention

[0005] To address the aforementioned technical challenge of accurately determining the LOD (Level of Detail) of different areas in a BIM building model, thereby ensuring the quality of the BIM building model while conserving computational resources, this invention aims to provide a BIM building model construction method for architectural engineering design. The specific technical solution adopted is as follows:

[0006] In a first aspect, the present invention provides a BIM building model construction method for architectural engineering design, comprising the following steps:

[0007] Based on the changes in the BIM building model of a building project at different construction stages, the newly added building area in each construction stage relative to its previous construction stage is determined.

[0008] Filter out the key and non-key areas from all the newly added building areas;

[0009] Based on the construction complexity of the key areas, the criticality of the key areas is determined;

[0010] Based on the criticality, determine the adaptive LOD level of the critical region;

[0011] A set LOD level is assigned to the non-critical area, and the assigned set LOD level is not higher than the adaptive LOD level;

[0012] Based on the set LOD level of the non-critical areas in all construction stages and the adaptive LOD level of the critical areas, a BIM building model for architectural engineering design is constructed.

[0013] In conjunction with the first aspect above, in some possible implementations, the process of determining the construction complexity of the key area includes:

[0014] Based on the changes in the number of each type of construction worker at different sampling times in each construction phase of the key area, the personnel activity variation factor for each type of construction worker is determined.

[0015] The construction complexity of the key areas is determined based on the personnel activity variation factors and importance of different types of construction workers.

[0016] In conjunction with the first aspect above, among some possible implementation methods, the personnel activity variation factors for each type of construction worker are determined, including:

[0017] Based on the number of each type of construction worker at different sampling times in each construction stage of the key area, a time series sequence of the number of each type of construction worker is constructed.

[0018] Based on the changes in the time series of the number of people, each construction stage is divided into several positive and negative time periods. The time series of the number of people shows an upward trend in the positive time periods and a downward trend in the negative time periods.

[0019] Based on the difference in the number of people at the two endpoints in adjacent positive and negative time periods, and in combination with the number of people in the positive and negative time periods, the personnel activity variation factor for each type of construction worker is determined.

[0020] In conjunction with the first aspect above, in some possible implementations, the criticality of the critical area is determined based on the construction complexity of the critical area, including:

[0021] Based on the distribution of construction personnel types at different sampling times in each construction phase of the key area, the diversity of construction personnel in the key area is determined.

[0022] The criticality of the critical areas is determined based on the construction complexity, the diversity of construction personnel, and the factors of concern in the critical areas.

[0023] In conjunction with the first aspect above, in some possible implementations, the adaptive LOD level of the key region is determined based on the criticality, including:

[0024] The reference LOD level of the key region is obtained by multiplying the key region's criticality by the highest LOD level.

[0025] Determine the absolute value of the difference between the reference LOD level and each set LOD level;

[0026] Determine the minimum value among all the absolute values ​​of the differences, and use the set LOD level corresponding to the minimum value as the adaptive LOD level of the key region.

[0027] In conjunction with the first aspect above, in some possible implementations, the process of determining each type of construction worker corresponding to different sampling times in each construction stage of the key area includes:

[0028] Acquire images from each monitoring camera within the key area at different sampling times during each construction phase;

[0029] The safety helmets in the image are identified, and the colors of the identified safety helmets are statistically analyzed to determine the type of construction worker corresponding to different sampling times in each construction stage of the key area.

[0030] In conjunction with the first aspect above, among some possible implementations, key and non-key areas are selected from all the newly added building areas, including:

[0031] In each newly added building area, target data points in the BIM building model for each set time period of each construction phase are determined at any latitude and longitude.

[0032] Based on the number of all target data points at each construction stage and the difference in height values ​​of all target data points for any given latitude and longitude, the building density corresponding to any given latitude and longitude is determined.

[0033] Based on the changes in the number of target data points at each set time period during each construction phase at any given latitude and longitude, the construction activity corresponding to any given latitude and longitude is determined.

[0034] Based on the building density and construction activity, and combined with the building data point density at any latitude and longitude location, the building complexity index corresponding to any latitude and longitude is determined.

[0035] Based on the building complexity index corresponding to all latitude and longitude in each of the newly added building areas, key and non-key areas are selected from all the newly added building areas.

[0036] In conjunction with the first aspect mentioned above, among some possible implementation methods, determining the construction activity corresponding to any given latitude and longitude includes:

[0037] Based on the change in the number of target data points at each set time period of any latitude and longitude in each construction stage, each construction stage is divided into several construction progress stages and construction stagnation stages.

[0038] Determine the total duration of all construction progress phases and the time percentage of each construction phase;

[0039] Determine the first quantity difference of the target data points between the last set time period in each construction progress phase and the last set time period in the previous construction stagnation phase;

[0040] Determine the second quantitative difference of target data points between adjacent set time periods in each construction progress phase;

[0041] Based on the time proportions and combined with the first and second quantity differences across all construction progress stages, the construction activity corresponding to any latitude and longitude is determined.

[0042] In conjunction with the first aspect mentioned above, among some possible implementation methods, the building complexity index corresponding to any latitude and longitude is determined, including:

[0043] The ratio of the number of target data points corresponding to any latitude and longitude in the last set time period of each construction stage to the building volume at that latitude and longitude location is determined as the data point density.

[0044] Based on the data point density, the building density, and the construction activity, the building complexity index corresponding to any latitude and longitude is determined.

[0045] In conjunction with the first aspect above, in some possible implementations, based on the building complexity index corresponding to all latitude and longitude coordinates in each newly added building area, key and non-key areas are selected from all the newly added building areas, including:

[0046] In each newly added building area, the latitude and longitude of the building complexity index that are greater than the set complexity index threshold are determined as reference points;

[0047] Based on the number of all reference points and the building complexity index, and combined with the distance between adjacent reference points, the attention factor corresponding to each newly added building area is determined;

[0048] Newly added building areas whose attention factor is greater than a set attention factor threshold are identified as key areas, and the remaining newly added building areas outside the key areas are identified as non-key areas.

[0049] Secondly, the present invention also provides a BIM building model building device for architectural engineering design, the device comprising:

[0050] A new building area determination module has been added, which is used to determine the new building area of ​​each construction stage relative to the previous construction stage based on the changes in the BIM building model of the building project at different construction stages.

[0051] The area filtering module is used to filter out key and non-key areas from all the newly added building areas;

[0052] The criticality determination module is used to determine the criticality of the critical area based on the construction complexity of the critical area;

[0053] The first-level determination module is used to determine the adaptive LOD level of the key region based on the criticality.

[0054] The second-level determination module is used to assign a set LOD level to the non-critical area, wherein the assigned set LOD level is not higher than the adaptive LOD level;

[0055] The model building module constructs a BIM building model for architectural engineering design based on the set LOD level of the non-critical areas in all construction stages and the adaptive LOD level of the critical areas.

[0056] Thirdly, the present invention also provides a BIM building model construction system for architectural engineering design, including a memory and a processor. The memory is used to store executable computer program code, and the processor is used to call and run the executable computer program code from the memory, causing the system to execute a BIM building model construction method for architectural engineering design according to the first aspect or any possible implementation thereof.

[0057] Fourthly, the present invention also provides a computer program product comprising: computer program code, which, when run on a computer, causes the computer to execute a BIM building model construction method for architectural engineering design, as described in the first aspect or any possible implementation thereof.

[0058] Fifthly, the present invention also provides a computer-readable storage medium storing computer program code that, when executed on a computer, causes the computer to perform a BIM building model construction method for architectural engineering design, as described in the first aspect or any possible implementation thereof.

[0059] This invention offers the following advantages: By determining the newly added building areas in the BIM building model for each construction stage relative to the previous stage, and filtering out key and non-key areas from all newly added building areas; based on the construction complexity of each key area, the criticality of each key area is determined, and thus the adaptive LOD level of each key area is determined. The criticality reflects the importance and required attention of the corresponding key area. Key areas with higher attention have higher adaptive LOD levels to more accurately reflect the position, size, and details of each component, thereby providing clearer visual information. Key and non-key areas with lower attention, since they do not require high-detail rendering, are assigned lower LOD levels, thus saving computational resources and avoiding wasting resources in unimportant areas. By determining the adaptive LOD levels of different key areas and assigning lower LOD levels to non-key areas, this invention effectively reduces the amount of computation and saves computational resources while ensuring the quality of BIM building model construction. Attached Figure Description

[0060] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0061] Figure 1 This is a flowchart illustrating the steps of a BIM building model construction method for architectural engineering design according to an embodiment of the present invention.

[0062] Figure 2 This is a flowchart illustrating the screening process for key and non-key regions in an embodiment of the present invention.

[0063] Figure 3This is a flowchart illustrating the process of determining the criticality of key regions in an embodiment of the present invention.

[0064] Figure 4 This is a schematic diagram of a BIM building model building device for architectural engineering design according to an embodiment of the present invention;

[0065] Figure 5 This is a schematic diagram of a BIM building model construction system for architectural engineering design, according to an embodiment of the present invention. Detailed Implementation

[0066] To clearly illustrate the technical features of this solution, the invention will be described in detail below through specific embodiments and in conjunction with the accompanying drawings.

[0067] Embodiments of the present invention will now be described in more detail with reference to the accompanying drawings. While some embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the invention. It should be understood that the accompanying drawings and embodiments are for illustrative purposes only and are not intended to limit the scope of protection of the invention.

[0068] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0069] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0070] It should be noted that the concepts of "first" and "second" mentioned in this invention are only used to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0071] Although operations or steps are described in a specific order in the accompanying drawings in the embodiments of the present invention, this should not be construed as requiring these operations or steps to be performed in the specific order or serial order shown, or requiring all of the shown operations or steps to be performed to obtain the desired result. In the embodiments of the present invention, these operations or steps may be performed serially; they may be performed in parallel; or a portion of these operations or steps may be performed.

[0072] Furthermore, it is understood that the data involved in the technical solutions of this invention (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions. Unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains, and all parameters or indicators in the formulas involved in this invention are normalized values ​​that have eliminated the influence of dimensions.

[0073] To address the technical challenge of accurately determining the Level of Detail (LOD) of different areas in a BIM building model, thereby ensuring the quality of the BIM building model while conserving computational resources, this invention provides a BIM building model construction method for architectural engineering design. This method identifies key and non-key areas within the newly added building areas of each construction stage relative to its predecessor. Based on the construction complexity of different key areas, it determines the criticality of each key area, thereby determining an adaptive LOD level for each key area. A lower LOD level is assigned to non-key areas. This allows for the use of a low LOD level in areas where high detail is not required, reducing rendering burden and improving system performance. Conversely, different levels of high LOD levels are used in different key areas to more accurately reflect the position, size, and details of each component, thus reducing computational load while maintaining the quality of the BIM building model.

[0074] The following will describe in detail, with reference to the accompanying drawings, a BIM building model construction method for architectural engineering design provided by an embodiment of the present invention.

[0075] Figure 1 This diagram illustrates the basic flow of a BIM building model construction method for architectural engineering design, as provided in an embodiment of the present invention. Figure 1 As shown, the method specifically includes the following steps:

[0076] Step S100: Based on the changes in the BIM building model of the building project at different construction stages, determine the newly added building area of ​​each construction stage relative to its previous construction stage.

[0077] Step S200: Filter out the key areas and non-key areas from all the newly added building areas;

[0078] Step S300: Determine the criticality of the critical area based on the construction complexity of the critical area;

[0079] Step S400: Based on the criticality, determine the adaptive LOD level of the critical region;

[0080] Step S500: Assign a set LOD level to the non-critical area, wherein the set LOD level is not higher than the adaptive LOD level;

[0081] Step S600: Based on the non-critical areas of all construction stages, set the LOD level and the adaptive LOD level of the critical areas to construct the BIM building model of the architectural engineering design.

[0082] In the BIM building model construction method for architectural engineering design provided in the above embodiments of the present invention, firstly, key and non-key areas are identified in the newly added building areas of each construction stage relative to its previous construction stage; secondly, based on the construction complexity of different key areas, the criticality of different key areas is determined, with higher criticality corresponding to key areas with higher construction complexity; furthermore, based on this criticality, the adaptive LOD level of different key areas is determined, and a lower set LOD level is assigned to non-key areas, thereby enabling the use of a low LOD level in areas that do not require high detail to reduce rendering burden and improve system performance, and using different levels of high LOD levels in different key areas to more accurately reflect the position, size, and details of each component; finally, based on the set LOD levels assigned to non-key areas of all construction stages and the adaptive LOD levels of each key area, the BIM building model for architectural engineering design is constructed. Thus, by reasonably allocating the LOD levels of different building areas, while avoiding wasting resources in unimportant areas, better rendering effects and clearer visual information can be ensured, ultimately guaranteeing the construction quality of the BIM building model.

[0083] The following is a detailed description of each step in a BIM building model construction method for architectural engineering design provided by an embodiment of the present invention.

[0084] Step S100: Based on the changes in the BIM building model of the building project at different construction stages, determine the newly added building area for each construction stage relative to its previous construction stage.

[0085] In architectural engineering design, during the process of building a BIM building model, it is necessary to assign different levels of modeling detail to the model according to the needs of different areas and stages. This hierarchical level of modeling detail is usually defined by the LOD level. The LOD level describes the process of BIM building model component units developing from the lowest level of approximate conceptualization to the highest level of demonstration-level precision.

[0086] Because building construction is a complex and multi-stage process, design changes, on-site problems, or updates to technical requirements are common during architectural design and construction. By acquiring BIM building models at each construction stage, real-time monitoring and tracking of project progress can be achieved. In the process of building BIM building models for architectural engineering design, the model needs to be gradually improved during construction to obtain a final model that accurately reflects the actual building conditions. This approach is known as "incremental model improvement" or "construction-stage model iteration."

[0087] In a specific example, firstly, for any given construction project, each construction phase is pre-defined to last one month. During each phase, multiple cameras are deployed in the construction area to capture real-time views of the site and obtain geometric data of the project. This helps managers monitor construction progress, worker safety behavior, and promptly identify potential safety hazards. Each camera captures a video image corresponding to a specific construction area. Simultaneously, the construction site utilizes a video surveillance system equipped with AI intelligent recognition technology to ensure workers wear safety helmets and reflective vests, thus guaranteeing worker safety.

[0088] Secondly, the preset acquisition frequency is 1 time per minute. Based on the video images captured by each camera, point cloud data (which reflects the three-dimensional spatial structure of the construction site) is generated using computer vision technology. Then, a 3D reconstruction algorithm (such as Poisson Surface Reconstruction) is used to connect the discrete point clouds into a continuous surface, forming a 3D model. This yields the 3D model corresponding to the daily construction progress within each construction phase. The horizontal, vertical, and elongation axes of the 3D model represent longitude, latitude, and altitude, respectively.

[0089] Next, the geometric data of the building project is imported into a BIM platform (such as Revit, ArchiCAD, etc.) to obtain the BIM building model for each construction stage, and simplified to LOD 100 level. That is, the details in the model will be simplified to simple geometry, such as the approximate shape and volume of walls, floors, roofs, etc., without involving complex components and decorations.

[0090] The BIM building model construction used in architectural engineering design is a complex and systematic process involving the entire lifecycle management from design and construction to operation and maintenance. Different LOD levels are used at different application stages, as shown in Table 1 below:

[0091] Table 1

[0092]

[0093] Finally, utilize the built-in tracking and management tools in BIM software, such as Revit's "Site to BIM" feature, to track construction progress.

[0094] In architectural engineering design, BIM models are typically updated and adjusted according to different project phases and actual needs. Each construction phase introduces new details and complexities with the design and construction of new building areas. Therefore, it is necessary to determine the Level of Detail (LOD) for each new building area based on the different construction phases. This helps ensure that the model meets the relevant design, construction, coordination, and management requirements at different stages.

[0095] Architectural projects often encompass various types of areas, including existing buildings, expansion areas, and ancillary facilities. Because the function and complexity of each area may differ, different design strategies are required. This invention first determines the newly added building areas for each construction stage relative to its predecessor, based on the changes in the BIM building model of the project at different construction phases.

[0096] In a specific example, firstly, the BIM building model of each construction phase is compared with the BIM building model of the previous construction phase to identify newly added data points in the BIM building model of each construction phase (i.e., the subsequent BIM building model). These newly added data points typically represent newly added building areas. Secondly, adjacent newly added data points are grouped into a new area, thus obtaining several new building areas in the BIM building model of each construction phase (i.e., the subsequent BIM building model).

[0097] Step S200: Filter out the key areas and non-key areas from all the newly added building areas.

[0098] For each construction phase, several newly added building areas in the BIM building model are screened to determine critical and non-critical areas. Critical areas refer to important building areas with complex or concentrated architectural features (such as important building projects, core facilities, public spaces, etc.), while non-critical areas refer to peripheral or less developed, less important areas.

[0099] Furthermore, such as Figure 2 As shown, step S200 above filters out key and non-key areas from all the newly added building areas, including:

[0100] Step S201: In each newly added building area, determine the target data point in the BIM building model for each set time period of each construction phase at any given latitude and longitude.

[0101] For each newly added building area relative to the previous construction phase, target data points in the BIM building model for any given latitude and longitude within each defined time period of that construction phase can be determined. In a specific example, the defined time period is one day. For instance, for the e-th newly added building area, multiple data points corresponding to any given latitude and longitude (X, Y) in the BIM building model for each day are selected and recorded as target data points. These target data points have the same latitude and longitude in their 3D coordinates, but different altitudes. Therefore, the altitude value Z in the 3D coordinates of the target data points will exhibit different variations.

[0102] Step S202: Based on the number of all target data points and the maximum height of all target data points at each construction stage for any latitude and longitude, determine the building density corresponding to any latitude and longitude.

[0103] For each new building area in each construction phase relative to the previous phase, the number of target data points at any given latitude and longitude in each phase not only represents the density of the data but also reflects its spatial distribution. If the target data points are highly concentrated in space, it indicates that the building characteristics of that area are complex or concentrated, potentially representing an important building area. Conversely, if the target data points are scattered, it may indicate that the area is on the periphery or less developed. Furthermore, differences in the height of the target data points can reflect the number of floors, structural complexity, or topographical variations in a building project. In architectural design, significant height differences in target data points within a region may indicate complex building types such as multi-story buildings, high-rise structures, and underground facilities; areas with smaller height differences may indicate simpler single-story structures or low-rise buildings. Therefore, from the perspective of complexity and construction cost, data points with larger height differences require more attention.

[0104] In a specific example, based on the number of all target data points at each construction stage and the maximum height value of all target data points for any given latitude and longitude (X,Y), the building density corresponding to any given latitude and longitude (X,Y) is determined. Where A represents the number of target data points corresponding to any given latitude and longitude (X,Y); This represents the maximum altitude value among the target data points corresponding to any latitude and longitude (X,Y); This represents the minimum altitude value among the target data points corresponding to any latitude and longitude (X,Y); This represents the maximum height difference of the target data points corresponding to any given latitude and longitude (X, Y). It reflects the space occupied by the building in the vertical direction. The smaller the space occupied, the more likely the location is to have only a single-story building, a relatively simple structure, and a low building density. This represents the standard normalization function, used to normalize numerical values. Normalize to the range (0, 1).

[0105] Step S203: Based on the changes in the number of target data points at each set time period in each construction phase for any latitude and longitude, determine the construction activity corresponding to any latitude and longitude.

[0106] Analyze the changes in the number of target data points at any given latitude and longitude during each construction phase and time period. When the number of target data points changes significantly, it indicates that the building height at the corresponding latitude and longitude is increasing faster, the construction activity is higher, and more attention is needed.

[0107] Furthermore, step S203 above, determining the construction activity corresponding to any latitude and longitude, includes: dividing each construction stage into several construction progress stages and construction stagnation stages based on the change in the number of target data points in each set time period of each construction stage for any latitude and longitude; determining the proportion of the total duration of all construction progress stages in each construction stage; determining the first difference in the number of target data points between the last set time period in each construction progress stage and the last set time period in the previous construction stagnation stage; determining the second difference in the number of target data points between adjacent set time periods in each construction progress stage; and determining the construction activity corresponding to any latitude and longitude based on the time proportion and in combination with the first and second differences in the number of target data points in all construction progress stages.

[0108] In a specific example, firstly, the number of target data points for any given latitude and longitude (X,Y) is counted daily in chronological order to obtain a quantity sequence. This quantity sequence represents the construction progress trend of the newly added building area for any given latitude and longitude (X,Y) at different time points.

[0109] Secondly, the number of target data points on day d-1 and the number of target data points on day d For example, calculate the difference in the number of target data points between every two adjacent days in the quantity sequence. ; This represents the standard normalization function, used to normalize numerical values. Normalize to the range (0, 1). A preset threshold of 0.2 is set; when the difference... A difference greater than or equal to 0.2 indicates that construction activity on day d is progressing rapidly, leading to a significant increase in the number of target data points in a short period; when the difference is... A difference of less than 0.2 indicates that the number of floors and structure of the building project did not change significantly on day d, and construction was at a standstill. The difference between consecutive adjacent values ​​is then considered. A period of 0.2 days or more constitutes a construction progress phase, with consecutive adjacent phases... A period of less than 0.2 days constitutes a construction standstill phase. Therefore, each construction phase can be divided into several construction progress phases and construction standstill phases.

[0110] Finally, based on all identified construction progress and stagnation phases, the construction activity corresponding to any given latitude and longitude (X, Y) is determined. ;in, This represents the total duration of all construction progress stages within each construction phase, i.e., the total number of days for all construction progress stages. E represents the total duration of a construction phase, which is 30 days; E represents the number of all construction progress phases within each construction phase. This represents the mean of the second quantity differences of the target data points between each set time period and its previous set time period in the e-th construction progress stage, i.e., the difference of all days in the e-th construction progress stage. The mean; This represents the first difference in the number of target data points between the last set time period in the e-th construction progress stage and the last set time period in the previous construction stagnation stage for any latitude and longitude (X,Y) location. In other words, it is the difference between the number of target data points on the last day of the e-th construction progress stage and the number of target data points on the last day of the adjacent previous construction stagnation stage.

[0111] Step S204: Based on the building density and the construction activity, and combined with the building data point density at any latitude and longitude location, determine the building complexity index corresponding to any latitude and longitude.

[0112] The density of building data points at any latitude and longitude location in each construction stage reflects the details and complexity of the building at that latitude and longitude location. The more details and the higher the complexity, the higher the LOD level is needed to more accurately reflect the location, size and details of each component.

[0113] Based on the building density and construction activity at any given latitude and longitude during each construction phase, and combined with the building data point density at that latitude and longitude location, a building complexity index is determined for that given latitude and longitude. The higher the building density and construction activity at that given latitude and longitude location during the corresponding construction phase, and the higher the building data point density, the higher the complexity of the buildings at that location.

[0114] Furthermore, step S204 above, which determines the building complexity index corresponding to any latitude and longitude, includes: determining the ratio of the number of target data points at the last set time period of each construction stage to the building volume at the location of any latitude and longitude as the data point density; and determining the building complexity index corresponding to any latitude and longitude based on the data point density, the building density, and the construction activity.

[0115] In a specific example, based on the building density at any latitude and longitude (X,Y) location. and construction activity By combining the building data point density at that latitude and longitude (X,Y) location, the building complexity index corresponding to that arbitrary latitude and longitude (X,Y) is determined. ;in, This represents the number of target data points for any given latitude and longitude (X,Y) location in the last set time period, i.e., the last day, during the current construction phase. This represents the volume of a building project at any given latitude and longitude (X,Y). This represents the density of building data points at any latitude and longitude (X,Y), i.e., the density of target data points per unit volume. This represents the standard normalization function, used to normalize numerical values. Normalize to the range (0, 1).

[0116] Step S205: Based on the building complexity index corresponding to all latitude and longitude in each of the newly added building areas, select the key areas and non-key areas among all the newly added building areas.

[0117] In a newly added building area, if there are many latitude and longitude coordinates with high building complexity indices, it indicates that the area may be a core area of ​​the building project. The more important the area, the more likely it is to be a key area that needs special attention.

[0118] Furthermore, step S205 above, based on the building complexity index corresponding to all latitudes and longitudes in each of the newly added building areas, filters out key and non-key areas among all the newly added building areas, including: in each of the newly added building areas, determining the latitudes and longitudes with a building complexity index greater than a set complexity index threshold as reference points; based on the number of all reference points and the building complexity index, and combined with the distance between adjacent reference points, determining the attention factor corresponding to each of the newly added building areas; determining the newly added building areas with an attention factor greater than a set attention factor threshold as key areas, and determining the remaining newly added building areas outside the key areas as non-key areas.

[0119] In a specific example, firstly, for any newly added building area, taking the e-th newly added building area as an example, a complexity index threshold is preset, such as setting the value of the complexity index threshold to 0.7, and then the building complexity index is set... Latitude and longitude (X, Y) greater than or equal to 0.7 are denoted as reference points.

[0120] Secondly, based on the number of all reference points and the building complexity index, and combined with the distance between adjacent reference points, the attention factor for the e-th newly added building area is calculated. ;in, This represents the number of reference points in the e-th newly added building area; This represents the number of all data points in the e-th newly added building area; This represents the sum of the building complexity indices of all reference points in the e-th newly added building region; This represents the average distance between all adjacent reference points in the e-th newly added building area. The smaller the average value, the higher the building density.

[0121] Finally, preset the threshold for the focus factor, for example, setting the threshold value to 0.5, and then setting the focus factor... New building areas with a value greater than or equal to 0.5 are designated as key areas, and their attention factor is set accordingly. New building areas with a value less than 0.5 are designated as non-critical areas. Therefore, it is possible to filter out critical and non-critical areas from all new building areas.

[0122] Step S300: Determine the criticality of the critical area based on the construction complexity of the critical area.

[0123] Some new building areas may involve high construction complexity, such as requiring complex structural designs, special materials, or processes (e.g., suspended structures, special glass curtain walls). Increasing the LOD (Level of Detail) level for these areas can help the construction team better understand and execute the design, thereby reducing errors and risks during construction. Conversely, if the design of new building areas is relatively simple (e.g., open-plan office areas), their construction complexity is lower and may not require excessive detail. Therefore, based on the construction complexity of each critical area, its corresponding criticality is determined, allowing for the adaptive determination of the optimal LOD level for each critical area.

[0124] Furthermore, such as Figure 3 As shown, the process of determining the construction complexity of the key area in step S300 above includes:

[0125] Step S301: Based on the changes in the number of each type of construction worker at different sampling times in each construction stage of the key area, determine the personnel activity change factor for each type of construction worker.

[0126] Different types of construction workers may exist in different key areas, such as ordinary construction workers, technicians or engineers, safety officers or site managers, etc. For each type of construction worker, when the number of workers varies greatly at different sampling times in each construction phase, it indicates that the more frequent the activity of that type of construction worker, the greater the factor of personnel activity variation.

[0127] Furthermore, step S301 above determines the personnel activity variation factor for each type of construction worker, including: constructing a time series sequence of the number of each type of construction worker based on the number of each type of construction worker at different sampling times in each construction stage of the key area; dividing each construction stage into several positive and negative time periods based on the changes in the time series sequence of the number of workers, wherein the time series sequence of the number of workers shows an upward trend in the positive time period and a downward trend in the negative time period; and determining the personnel activity variation factor for each type of construction worker based on the difference in the number of workers at the two endpoints in adjacent positive and negative time periods, and in combination with the number of positive and negative time periods.

[0128] The process of determining each type of construction worker corresponding to different sampling times in each construction stage of the key area includes: acquiring images captured by each monitoring camera in the key area at different sampling times in each construction stage; identifying the safety helmets in the images and statistically analyzing the colors of the identified safety helmets to determine each type of construction worker corresponding to different sampling times in each construction stage of the key area.

[0129] In a specific example, firstly, construction sites are often narrow and have many obstacles. When workers move or work, their heads are prone to colliding with protruding components (such as steel bar ends or scaffold crossbars), posing many safety hazards. Therefore, workers must wear safety helmets during construction to reduce head injuries.

[0130] The color of safety helmets worn by workers typically reflects their roles and responsibilities. For example, yellow helmets are suitable for ordinary construction workers; blue helmets are usually for technicians or engineers; red helmets are for safety officers or site managers; white helmets are often used by project managers or senior managers; and green helmets are for quality inspectors or environmental protection personnel. Therefore, by identifying the color of safety helmets in images captured by each monitoring camera in a key area at different sampling times during each construction phase, it is possible to determine the various types of construction workers at different times during each construction phase. In this case, one helmet color corresponds to one type of construction worker.

[0131] Secondly, considering a construction area with multiple cameras, taking the g-th critical area as an example, the multiple cameras corresponding to the construction area where the critical area is located are designated as the cameras for the g-th critical area. Taking the image captured by the c-th camera as an example, for the image captured by the c-th camera at each sampling time, contour detection and morphological operations are used to identify the safety helmet region within the g-th critical area. Then, region labeling and thresholding techniques are used to count the types of safety helmet colors and the corresponding quantity for each type.

[0132] In the g-th critical region, with the first Taking a safety helmet of a certain color as an example for analysis, the sampling time at all sampling moments within each construction stage will be analyzed. The number of safety helmets of different colors constitutes a time sequence of the number of people. };in, as well as They represent the first The number of safety helmets of each color at the first sampling time, the second sampling time, and the i-th sampling time. In the time series of people { In}, calculation ,when When the difference is positive, the first time step is recorded as a positive time step; otherwise, it is recorded as a negative time step. Following this method, several positive and negative times can be determined. When the i-th sampling time step is positive, it indicates that the i-th sampling time step is being worn. The number of construction workers wearing safety helmets of different colors increases at the i-th sampling time, and more people enter the g-th critical area. This may be due to the advancement of the process, requiring more personnel to support or perform specific tasks. By forming a positive time period from consecutive adjacent positive times, we can obtain several positive time periods in each construction stage; similarly, we can also obtain several negative time periods in each construction stage.

[0133] Next, in the g-th key region, for the time series sequence of the number of people { In the context of two adjacent positive and negative time periods, the last sampling time of the previous time period will be used as the reference. Corresponding to the last data collection time in the next time period The absolute value of the difference is denoted as the change in the number of people between the two adjacent time periods. .

[0134] Finally, in the g-th critical region, based on the... The change in the number of people corresponding to each adjacent positive and negative time period for each type of safety helmet color, and the total number of people in both positive and negative time periods, are used to calculate the number of people in the first time period. The color of the safety helmet is the first Personnel activity variation factors corresponding to different types of construction workers ;in, Represents the time series sequence of the number of people { The magnitude of population changes for all adjacent positive and negative time periods in} The mean; Represents the time series sequence of the number of people { The total number of all positive and negative time periods in the data indicates that the greater the number of personnel changes, the more frequent the personnel activities, and the greater the factor of personnel activity variation.

[0135] Step S302: Determine the construction complexity of the key area based on the personnel activity variation factors and importance of different types of construction personnel.

[0136] In critical areas, for each type of construction worker, frequent activity (e.g., frequent entry and exit, cross-operation) usually indicates that the construction task in that area is more complex, meaning that multiple processes are carried out simultaneously, requiring coordination among various parties, which increases the complexity of the construction environment.

[0137] Meanwhile, because different types of construction workers have different functions, the impact of their activities on the construction environment also varies. For example, the red safety helmet corresponds to site management personnel, who are responsible for overall coordination and decision-making. If their activity change factor is high, it may mean adjustments to the construction plan or handling of unexpected problems, indicating that the construction complexity of the area is higher and requires more attention.

[0138] In a specific example, firstly, based on existing experience, different label values ​​are assigned to different types of construction workers according to their perceived importance. For example, the label value for construction workers wearing red safety helmets is set to 5, the label value for those wearing white safety helmets is set to 4, the label value for those wearing yellow safety helmets is set to 3, the label value for those wearing blue safety helmets is set to 2, and the label value for those wearing blue helmets is set to 1.

[0139] Secondly, in the g-th critical area, the construction complexity of the g-th critical area is calculated based on the personnel activity variation factors of different types of construction workers and the sticky notes corresponding to their importance. ;in, This represents the number of types of construction workers in the g-th critical area, i.e., the number of different colors of safety helmets. Indicates the first The label value corresponding to the importance of each type of construction worker, i.e., the first... The label value corresponding to each color of safety helmet.

[0140] Furthermore, such as Figure 3As shown, step S300 above determines the criticality of the critical area based on the construction complexity of the critical area, including:

[0141] Step S303: Based on the distribution of construction personnel types at different sampling times in each construction stage of the key area, determine the diversity of construction personnel in the key area.

[0142] If multiple types of construction workers are present in a critical area, i.e., multiple colors of safety helmets are present (such as yellow, blue, red, and white), it indicates that there are multiple types of personnel involved in basic construction, technical operations, and management coordination in that area. This may involve multiple overlapping work processes (such as mechanical and electrical installation and structural construction in parallel), and therefore requires closer attention.

[0143] In a specific example, also for the c-th camera, taking the g-th critical region as an example, the average number of different helmet colors in the g-th critical region across all sampling times, which is also the average number of different types of construction workers corresponding to the sampling times, is denoted as the construction worker diversity in the g-th critical region. .

[0144] Step S304: Determine the criticality of the critical area based on the construction complexity, the diversity of construction personnel, and the factors of concern.

[0145] The criticality of a critical area is determined based on its construction complexity, the diversity of construction personnel, and key factors. Higher personnel diversity and construction complexity indicate the presence of various personnel involved in foundation construction, technical operations, and management coordination, making the construction tasks in this area more complex and requiring close attention to ensure the smooth progress of the construction project. Conversely, when considering key factors, the more likely the area is to be a core part of the construction project, the higher its importance and criticality.

[0146] In a specific example, the construction complexity is based on the g-th key area corresponding to the c-th camera. Diversity of construction personnel and attention factors Calculate the criticality of the g-th key region corresponding to the c-th camera. ;in, This represents the standard normalization function, used to... The value of is normalized to the range (0,1).

[0147] Furthermore, since there are multiple cameras within a construction area, the criticality of the g-th critical area corresponding to all cameras is determined. The mean value is denoted as the criticality of the g-th critical region. Therefore, the criticality of each critical region can be obtained.

[0148] Step S400: Based on the criticality, determine the adaptive LOD level of the critical region.

[0149] The above step S300 obtains the criticality of each key area in each BIM building model construction process. Based on the criticality of each key area, key areas with high criticality are converted into high-detail LOD versions, and key areas with low criticality are converted into low-detail LOD versions, thereby completing the selection of different levels of detail for different areas of the model.

[0150] Furthermore, step S400 above, based on the criticality, determines the adaptive LOD level of the critical region, including: determining the product of the criticality of the critical region and the highest LOD level to obtain the reference LOD level of the critical region; determining the absolute value of the difference between the reference LOD level and each set LOD level; determining the minimum value among all the absolute values ​​of the difference, and taking the set LOD level corresponding to the minimum value as the adaptive LOD level of the critical region.

[0151] In a specific example, firstly, a maximum LOD level is preset. The highest LOD level The specific value can be set according to the actual situation; there are no hard and fast requirements here. For example, setting this as the highest LOD level... .

[0152] Secondly, based on this highest LOD level And the criticality of the g-th critical region in the BIM building model for each construction phase. Determine the reference LOD level of the g-th critical region. Specifically, the LOD level of the model is adaptively determined based on the criticality of each key region, so as to more accurately reflect the position, size and details of each component.

[0153] Finally, the reference LOD level of the g-th critical area in the BIM building model for each construction stage is calculated. The absolute value of the difference between the LOD level and each set LOD level, namely LOD100, LOD200, LOD300, LOD350, LOD400, and LOD500, is used as the set LOD level corresponding to the smallest absolute value of the difference. This is the optimal LOD level, i.e., the adaptive LOD level, in the g-th critical area of ​​the BIM building model for each construction stage.

[0154] Step S500: Assign a set LOD level to the non-critical area, wherein the assigned set LOD level is not higher than the adaptive LOD level.

[0155] Assign a low-detail LOD level to non-critical areas in the BIM building model for each construction phase. In a specific example, all non-critical areas are assigned a LOD level of LOD100. At this level, the general shapes of walls, floors, roofs, etc., are sufficient for on-site construction needs; excessive detail would hinder construction progress. This process allows for the selection of different LOD levels for different areas in the BIM building model for each construction phase.

[0156] Step S600: Based on the set LOD level of the non-critical areas in all construction stages and the adaptive LOD level of the critical areas, construct the BIM building model of the architectural engineering design.

[0157] Based on the assigned Level of Detail (LOD) levels for all non-critical areas and the adaptive LOD levels for critical areas in the BIM building model for each construction phase, different areas are rendered to complete the construction of the BIM building model for architectural engineering design. Since this specific construction process is existing technology, it will not be elaborated upon here.

[0158] Based on the same inventive concept, embodiments of the present invention also provide a BIM building model building device for architectural engineering design, such as... Figure 4 As shown, the device includes:

[0159] A new building area determination module has been added, which is used to determine the new building area of ​​each construction stage relative to the previous construction stage based on the changes in the BIM building model of the building project at different construction stages.

[0160] The area filtering module is used to filter out key and non-key areas from all the newly added building areas;

[0161] The criticality determination module is used to determine the criticality of the critical area based on the construction complexity of the critical area;

[0162] The first-level determination module is used to determine the adaptive LOD level of the key region based on the criticality.

[0163] The second-level determination module is used to assign a set LOD level to the non-critical area, wherein the assigned set LOD level is not higher than the adaptive LOD level;

[0164] The model building module constructs a BIM building model for architectural engineering design based on the set LOD level of the non-critical areas in all construction stages and the adaptive LOD level of the critical areas.

[0165] It should be noted that the device provided in the above embodiments is only an example of the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device can be divided into different functional modules to complete all or part of the functions described above.

[0166] Based on the same inventive concept, embodiments of the present invention also provide a BIM building model construction system for architectural engineering design, such as... Figure 5 As shown, the system includes: a memory 501, a processor 502, and computer program code 503 stored in the memory 501 and running on the processor 502, wherein when the processor 502 executes the computer program code 503, the system can execute any of the BIM building model construction methods for architectural engineering design described above.

[0167] In this embodiment of the invention, the system can be divided into functional modules according to the above method example. For example, each module can correspond to a separate functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0168] Based on the same inventive concept, embodiments of the present invention also provide a computer program product, which includes: computer program code, which, when run on a computer, causes the computer to execute any of the BIM building model construction methods for architectural engineering design described above.

[0169] Based on the same inventive concept, embodiments of the present invention also provide a computer-readable storage medium storing computer program code, which, when run on a computer, causes the computer to execute any of the aforementioned BIM building model construction methods for architectural engineering design.

[0170] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for constructing BIM building models for architectural engineering design, characterized in that, Includes the following steps: Based on the changes in the BIM building model of a building project at different construction stages, the newly added building area in each construction stage relative to its previous construction stage is determined. Filter out the key and non-key areas from all the newly added building areas; Based on the construction complexity of the key areas, the criticality of the key areas is determined; Based on the criticality, determine the adaptive LOD level of the critical region; A set LOD level is assigned to the non-critical area, and the assigned set LOD level is not higher than the adaptive LOD level; Based on the set LOD level of the non-critical areas in all construction stages and the adaptive LOD level of the critical areas, a BIM building model for architectural engineering design is constructed. The process of determining the construction complexity of the key areas includes: Based on the changes in the number of each type of construction worker at different sampling times in each construction phase of the key area, the personnel activity variation factor for each type of construction worker is determined. Based on the personnel activity variation factors and importance of different types of construction workers, the construction complexity of the key areas is determined. In the g-th key area, the construction complexity of the g-th key area is calculated. ;in, This represents the number of different types of construction workers in the g-th critical area; Indicates the first The label values ​​corresponding to the importance of each type of construction worker Indicates the first Factors affecting the changes in personnel activities corresponding to different types of construction workers; Determine the factors affecting the variation of personnel activities for each type of construction worker, including: Based on the number of each type of construction worker at different sampling times in each construction stage of the key area, a time series sequence of the number of each type of construction worker is constructed. Based on the changes in the time series of the number of people, each construction stage is divided into several positive and negative time periods. The time series of the number of people shows an upward trend in the positive time periods and a downward trend in the negative time periods. Based on the difference in the number of people at the two endpoints of adjacent positive and negative time periods, and combined with the number of people in the positive and negative time periods, the personnel activity variation factor for each type of construction worker is determined. In the g-th key area, the th... Personnel activity variation factors corresponding to different types of construction workers ;in, Represents the time series sequence of the number of people { The magnitude of population changes for all adjacent positive and negative time periods in} The average value is the value corresponding to the last sampling time of the previous period. Corresponding to the last data collection time in the next time period The absolute value of the difference is denoted as the change in the number of people between the two adjacent time periods. ; Represents the time series sequence of the number of people { The total number of all positive and negative time periods in}; Based on the construction complexity of the key areas, the criticality of the key areas is determined, including: Based on the distribution of construction worker types at different sampling times in each construction phase of the key area, the diversity of construction workers in the key area is determined. In the g-th key area, the average number of construction worker types in the g-th key area at all sampling times is recorded as the diversity of construction workers in the g-th key area. ; Based on the construction complexity, diversity of construction personnel, and attention factors of the key areas, the criticality of the key areas is determined, and the construction complexity of the g-th key area corresponding to the c-th camera is also considered. Diversity of construction personnel and attention factors Calculate the criticality of the g-th key region corresponding to the c-th camera. ;in, This represents the standard normalization function, used to... The values ​​of are normalized to the range (0,1); Based on the criticality, the adaptive LOD level of the critical region is determined, including: The reference LOD level of the key region is obtained by multiplying the key region's criticality by the highest LOD level. Determine the absolute value of the difference between the reference LOD level and each set LOD level; Determine the minimum value among all the absolute values ​​of the differences, and use the set LOD level corresponding to the minimum value as the adaptive LOD level of the key region.

2. The BIM building model construction method for architectural engineering design according to claim 1, characterized in that, The process for determining the type of construction worker corresponding to different sampling times in each construction phase of the key area includes: Acquire images from each monitoring camera within the key area at different sampling times during each construction phase; The safety helmets in the image are identified, and the colors of the identified safety helmets are statistically analyzed to determine the type of construction worker corresponding to different sampling times in each construction stage of the key area.

3. The BIM building model construction method for architectural engineering design according to claim 1, characterized in that, Filter out the key and non-key areas from all the newly added building areas, including: In each newly added building area, target data points in the BIM building model for each set time period of each construction phase are determined at any latitude and longitude. Based on the number of all target data points at each construction stage and the difference in height values ​​of all target data points for any given latitude and longitude, the building density corresponding to any given latitude and longitude is determined. Based on the changes in the number of target data points at each set time period during each construction phase at any given latitude and longitude, the construction activity corresponding to any given latitude and longitude is determined. Based on the building density and construction activity, and combined with the building data point density at any latitude and longitude location, the building complexity index corresponding to any latitude and longitude is determined. Based on the building complexity index corresponding to all latitude and longitude in each of the newly added building areas, key and non-key areas are selected from all the newly added building areas. Determine the construction activity corresponding to any given latitude and longitude, including: Based on the change in the number of target data points at each set time period of any latitude and longitude in each construction stage, each construction stage is divided into several construction progress stages and construction stagnation stages. Determine the total duration of all construction progress phases and the time percentage of each construction phase; Determine the first quantity difference of the target data points between the last set time period in each construction progress phase and the last set time period in the previous construction stagnation phase; Determine the second quantitative difference of target data points between adjacent set time periods in each construction progress phase; Based on the aforementioned time proportions, and combined with the first and second quantity differences across all construction progress stages, the construction activity corresponding to any given latitude and longitude is determined. Based on the determined construction progress stages and construction stagnation stages, the construction activity corresponding to any given latitude and longitude (X, Y) is then determined. ;in, This indicates the total duration of all construction progress stages within each construction phase; E represents the total duration of a construction phase; E represents the number of all construction progress phases within each construction phase. This represents the mean of the second quantity difference of the target data points between each set time period and its previous set time period in the e-th construction progress stage; This represents the first difference in the number of target data points between any latitude and longitude (X,Y) location in the last set time period of the e-th construction progress stage and the last set time period of the previous construction stagnation stage; Determine the building complexity index corresponding to any given latitude and longitude, including: The ratio of the number of target data points corresponding to any latitude and longitude in the last set time period of each construction stage to the building volume at that latitude and longitude location is determined as the data point density. Based on the data point density, the building density, and the construction activity, a building complexity index is determined for any given latitude and longitude. The building density at any given latitude and longitude (X, Y) location is then used to determine the overall building complexity index. and construction activity By combining the building data point density at that latitude and longitude (X,Y) location, the building complexity index corresponding to that arbitrary latitude and longitude (X,Y) is determined. ;in, This represents the number of target data points for any given latitude and longitude (X,Y) location in the last set time period, i.e., the last day, during the current construction phase. This represents the volume of a building project at any given latitude and longitude (X,Y). This represents the density of building data points at any latitude and longitude (X,Y), i.e., the density of target data points per unit volume. This represents the standard normalization function, used to normalize numerical values. Normalize to the range (0, 1).

4. The BIM building model construction method for architectural engineering design according to claim 3, characterized in that, Based on the building complexity index corresponding to all latitude and longitude coordinates in each of the newly added building areas, key and non-key areas are selected from all the newly added building areas, including: In each newly added building area, the latitude and longitude of the building complexity index that are greater than the set complexity index threshold are determined as reference points; Based on the number of all reference points and the building complexity index, and combined with the distance between adjacent reference points, the attention factor corresponding to each newly added building area is determined; Newly added building areas whose attention factor is greater than a set attention factor threshold are identified as key areas, and the remaining newly added building areas outside the key areas are identified as non-key areas.

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