Real estate project design scheme generation method, device and equipment and storage medium

Abstract

This disclosure relates to the field of digital design technology, and provides a method, apparatus, equipment, and storage medium for generating design schemes for real estate projects. The method includes: initializing and associating preset project design benchmark data based on project requirement data and a preset scheme design toolset to obtain compliant design data; processing scheme model creation based on the compliant design data and the preset scheme design toolset to obtain 3D model data; performing index analysis processing on the 3D model data to obtain spatial index data; associating and integrating the 3D model data and spatial index data to obtain target scheme data; and visualizing the target scheme data to obtain the target design scheme. This improves the efficiency and standardization of design scheme generation, enhances the collaborative efficiency between supplier input and scheme design, strengthens the intuitiveness and accuracy of scheme decision-making, and reduces internal and external communication costs and the losses from repeated modifications.

Description

Technical Field

[0001] This disclosure relates to the field of digital design technology, and in particular to a method, apparatus, equipment and storage medium for generating design schemes for real estate projects. Background Technology

[0002] In traditional real estate development and design management, the design process typically relies on manual drawing of two-dimensional drawings and fragmented data storage, resulting in a lack of unified standards for internal and external collaboration, low communication efficiency, and repeated revisions of plans. The design cycle is long, with no standardized module reuse mechanism; the data is unstructured, making it difficult to quickly retrieve and correlate; information is not intuitive during decision-making, and the separation of indicator data from models makes the decision-making process slow and inaccurate. To address the design efficiency problem, the conventional approach is to introduce Building Information Modeling (BIM) technology to improve design visualization and collaboration, but the lack of unified application standards leads to chaotic data formats and difficulties in collaboration.

[0003] It is evident that existing technologies suffer from problems such as a lack of unified standards for internal and external collaboration in the design process, the absence of standardized module reuse mechanisms, and the separation of data and models. These issues result in long design solution generation cycles, low generation efficiency and poor accuracy, as well as high difficulty and insufficient precision in data retrieval and association. Summary of the Invention

[0004] In view of this, the present disclosure provides a method, apparatus, electronic device and readable storage medium for generating real estate project design schemes, in order to solve the problems in the prior art that the lack of unified standards for internal and external collaboration in the design process, the absence of standardized module reuse mechanisms, and the separation of data and models lead to long design scheme generation cycles, low generation efficiency and poor accuracy, and high difficulty and insufficient precision in data retrieval and association.

[0005] A first aspect of this disclosure provides a method for generating a design scheme for a real estate project, comprising: initializing and associating preset project design benchmark data based on project demand data and a preset scheme design toolset to obtain compliant design data; performing scheme model creation processing based on the compliant design data and the preset scheme design toolset to obtain three-dimensional model data; performing index analysis processing on the three-dimensional model data to obtain spatial index data; associating and integrating the three-dimensional model data and the spatial index data to obtain target scheme data; and performing visualization processing on the target scheme data to obtain a target design scheme.

[0006] In some embodiments, the three-dimensional model data is subjected to index parsing processing to obtain spatial index data, including: performing spatial attribute extraction processing on the three-dimensional model data to obtain initial spatial parameters; performing index calculation processing on the initial spatial parameters to obtain calculated index data; and performing structured encapsulation processing on the calculated index data to obtain spatial index data.

[0007] In some embodiments, the process of creating a scheme model based on compliant design data and a preset scheme design toolset to obtain three-dimensional model data includes: parsing the compliant design data for design parameters to obtain a model generation instruction; calling the preset scheme design toolset based on the model generation instruction to perform three-dimensional modeling to generate a scheme building information model; and performing data structuring transformation on the scheme building information model to obtain three-dimensional model data.

[0008] In some embodiments, the three-dimensional model data and spatial indicator data are associated and integrated to obtain target scheme data, including: classifying and indexing the three-dimensional model data to obtain structured model data; associating and mapping the structured model data and spatial indicator data to obtain indicator attribute model data; and encapsulating and storing the indicator attribute model data to obtain target scheme data.

[0009] In some embodiments, visualizing the target scheme data to obtain the target design scheme includes: constructing a general map model from the target scheme data to obtain a three-dimensional general map model; performing digital-model linkage processing on the three-dimensional general map model to obtain a digital-model linkage model; and performing synchronous rendering processing on the digital-model linkage model to obtain the target design scheme.

[0010] In some embodiments, the preset project design benchmark data is initialized and associated based on project requirement data and a preset scheme design toolset to obtain compliant design data, including: filtering and calling the preset project design benchmark data based on project requirement data to obtain target project specification data; associating and mapping the target project specification data and the preset scheme design toolset to obtain initial design content; and performing compliance verification on the initial design content to obtain compliant design data.

[0011] In some embodiments, the initial spatial parameters are processed to obtain the calculated index data, including: performing spatial boundary identification processing on the initial spatial parameters to obtain spatial boundary data; performing area calculation processing on the spatial boundary data to obtain unit area data; performing volume index calculation processing on the unit area data to obtain volume ratio index data; and encapsulating the volume ratio index data and the unit area data to obtain the calculated index data.

[0012] A second aspect of this disclosure provides a real estate project design scheme generation device, comprising: a first processing module for initializing and associating preset project design benchmark data based on project demand data and a preset scheme design toolset to obtain compliant design data; a second processing module for creating scheme models based on the compliant design data and the preset scheme design toolset to obtain three-dimensional model data; a third processing module for analyzing the three-dimensional model data to obtain spatial indicator data; a fourth processing module for associating and integrating the three-dimensional model data and spatial indicator data to obtain target scheme data; and a fifth processing module for visualizing the target scheme data to obtain a target design scheme.

[0013] A third aspect of this disclosure provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described above.

[0014] A fourth aspect of this disclosure provides a readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method.

[0015] The beneficial effects of this disclosed embodiment compared with the prior art are as follows: By initializing and associating preset project design benchmark data based on project requirement data and a preset scheme design toolset, compliant design data is obtained; based on the compliant design data and the preset scheme design toolset, scheme model creation processing is performed to obtain 3D model data; index analysis processing is performed on the 3D model data to obtain spatial index data; the 3D model data and spatial index data are correlated and integrated to obtain target scheme data; and the target scheme data is visualized to obtain the target design scheme. This improves the efficiency and standardization of design scheme generation, enhances the structure and reusability of design data, improves the collaborative efficiency between supplier information provision and scheme design, strengthens the intuitiveness and accuracy of scheme decision-making, and reduces internal and external communication costs and the losses from repeated modifications. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram illustrating an application scenario of an embodiment of this disclosure; Figure 2 This is a flowchart illustrating a method for generating a real estate project design scheme according to an embodiment of this disclosure; Figure 3 This is a flowchart illustrating another method for generating a real estate project design scheme provided in this embodiment of the disclosure; Figure 4 This is a schematic diagram of the structure of a real estate project design scheme generation device provided in an embodiment of this disclosure; Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0018] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, so as to provide a thorough understanding of the embodiments of this disclosure. However, those skilled in the art will understand that this disclosure may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this disclosure with unnecessary detail.

[0019] It should be noted that the user information (including but not limited to terminal device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties.

[0020] The following will describe in detail, with reference to the accompanying drawings, a method and apparatus for generating a real estate project design scheme according to an embodiment of the present disclosure.

[0021] Figure 1 This is a schematic diagram illustrating an application scenario of an embodiment of this disclosure. The application scenario may include terminal devices 1, 2, and 3, server 4, and network 5.

[0022] Terminal devices 1, 2, and 3 can be hardware or software. When terminal devices 1, 2, and 3 are hardware, they can be various electronic devices with displays and supporting communication with server 4, including but not limited to smartphones, tablets, laptops, and desktop computers. When terminal devices 1, 2, and 3 are software, they can be installed in the aforementioned electronic devices. Terminal devices 1, 2, and 3 can be implemented as multiple software programs or software modules, or as a single software program or software module; this disclosure does not limit this. Furthermore, various applications can be installed on terminal devices 1, 2, and 3, such as data processing applications, instant messaging tools, social platform software, search applications, shopping applications, etc.

[0023] Server 4 can be a server that provides various services, such as a backend server that receives requests sent by terminal devices with which it has established communication connections. This backend server can receive and analyze the requests sent by the terminal devices and generate processing results. Server 4 can be a single server, a server cluster consisting of several servers, or a cloud computing service center. This disclosure embodiment does not limit this.

[0024] It should be noted that server 4 can be either hardware or software. When server 4 is hardware, it can be various electronic devices that provide various services to terminal devices 1, 2, and 3. When server 4 is software, it can be multiple software programs or software modules that provide various services to terminal devices 1, 2, and 3, or it can be a single software program or software module that provides various services to terminal devices 1, 2, and 3. This disclosure does not limit the scope of the embodiments.

[0025] Network 5 can be a wired network using coaxial cable, twisted pair, and fiber optic connection, or it can be a wireless network that enables interconnection of various communication devices without wiring, such as Bluetooth, Near Field Communication (NFC), and Infrared. This disclosure does not limit the scope of the network.

[0026] Users can establish a communication connection with server 4 via network 5 through terminal devices 1, 2, and 3 to receive or send information. Specifically, server 4 can obtain project requirement data through terminal devices 1, 2, and 3; perform initial correlation processing on preset project design benchmark data based on project requirement data and preset scheme design toolsets to obtain compliant design data; perform scheme model creation processing based on compliant design data and preset scheme design toolsets to obtain 3D model data; perform index analysis processing on 3D model data to obtain spatial index data; perform correlation and integration processing on 3D model data and spatial index data to obtain target scheme data; and perform visualization processing on target scheme data to obtain the target design scheme.

[0027] It should be noted that the specific types, quantities, and combinations of terminal devices 1, 2, and 3, server 4, and network 5 can be adjusted according to the actual needs of the application scenario, and this disclosure embodiment does not impose any restrictions on this.

[0028] Figure 2 This is a flowchart illustrating a method for generating a real estate project design scheme according to an embodiment of this disclosure. Figure 2 The method for generating real estate project design schemes can be derived from Figure 1 The server executes this. For example... Figure 2 As shown, the method for generating the design scheme for this real estate project includes: S201, based on project requirement data and a pre-set design toolset, initializes and associates the pre-set project design baseline data to obtain compliant design data.

[0029] Specifically, project requirement data can be a set of information representing the specific goals, constraints, and functional requirements of a real estate development project. This project requirement data can be the original requirements data proposed by the project initiator or manager regarding project positioning, scale, cost, time, and technical standards. This can provide clear input basis and directional guidance for the entire design scheme generation process, ensuring that subsequent design activities are aligned with project goals. This project requirement data can be obtained through preliminary project surveys, task book preparation, or requirements analysis meetings, and can be used to represent the core demands and decision boundaries of the project.

[0030] Pre-defined project design baseline data can be a predefined set of design starting point data that conforms to industry or enterprise standards. The form of the pre-defined project design baseline data can be a collective term for standardized design rules, product parameters, process templates and / or historical experience data stored in the system. This can provide a standardized foundation that can be called or referenced for new project designs, ensuring the basic compliance and consistency of design output. The pre-defined project design baseline data can come from long-term project practice accumulation, industry standard transformation and the accumulation of internal enterprise knowledge base, such as BIM application specifications, standard product library parameters and R&D process node definitions, which can be used to represent a mature and reliable design input framework.

[0031] A pre-defined solution design toolset can be a collection of software functional components or modules integrated into a system to assist in design, verification, and analysis. The pre-defined solution design toolset can take the form of a program unit that encapsulates specific design, processing, or verification logic. By providing standardized functional interfaces, it can automate or semi-automatically perform tasks such as design correlation and compliance checks, thereby improving processing efficiency and accuracy. This pre-defined solution design toolset can be pre-built during system development based on common requirements of the design process. For example, it may include a standard matching engine, a data correlator, and a preliminary verification unit, which can be used to support the automated correlation and preliminary processing of pre-defined project baseline data and project requirement data.

[0032] Furthermore, the initialization association processing can be a data processing procedure that matches, binds, and adaptively adjusts project requirement data with preset project design benchmark data based on established rules. This can be used to translate abstract project requirements into concrete and operable design specifications and resources, laying a structured and compliant data foundation for subsequent detailed design. This initialization association processing can be driven by a preset scheme design toolset, which can map project requirement data and retrieved benchmark data through logic within the preset scheme design toolset. The compliant design data can be intermediate design data output through the initialization association processing that has initially met the basic project requirements and preset specifications. The compliant design data can be a structured data result that integrates specific project requirements and standardized design benchmarks. This provides standardized and unambiguous input for subsequent steps such as scheme model creation and indicator calculation, ensuring the compliance and consistency of the design process starting point. This compliant design data can be obtained by filtering, assigning values, and applying association rules to the project design benchmark data based on project requirement data, and can be used to carry the standardized information required to initiate the detailed design of the scheme.

[0033] Furthermore, the standard matching engine in the preset design toolset can parse project requirement data and identify key design elements such as building type, cost range, or technical standard level.

[0034] Furthermore, this standard matching engine can search and match within preset project design benchmark data. For example, based on the "residential project" and "cost-control type" tags in the requirements, it can associate the corresponding BIM modeling accuracy level (LOD) standard, recommended structural system standard product parameters, and applicable design submission process templates. It can also bind successfully matched benchmark data entries to project requirement data through a data association tool, and assign values ​​to variable parameters in the preset project benchmark data based on specific parameters (such as building area and plot ratio) in the project requirement data, generating a preliminary design specification list for the project. The preliminary verification unit can perform logical checks on this list to ensure there are no contradictions between the project requirement data and the associated preset project benchmark data. For example, it can check whether specified product specifications meet cost constraints, obtaining conflict-free compliant design data.

[0035] For example, when a real estate development company launches a new residential community project, the project management department can input project requirements data into the system. This data can include the project's positioning as high-end improved housing, building area requirements, maximum plot ratio, cost budget range, green building star rating target, and planned development cycle. The system can also access a pre-set design toolset. This toolset can retrieve and associate the corresponding BIM implementation standard from pre-set project design benchmark data based on the "high-end improved housing" positioning tag. This BIM implementation standard specifies the modeling depth and information attribute requirements for components such as doors, windows, and walls in the model. Furthermore, the toolset can filter standardized product parameters such as exterior wall insulation systems and door / window models that meet the cost range and energy-saving and environmental protection indicators from a standard product library based on the cost budget range and green building targets. Additionally, the toolset can match a research and development process management template suitable for residential projects of this scale based on the project development cycle. After completing the retrieval and association, the data association tool can fill in the specific building area and plot ratio values ​​into the associated design specifications and product parameters, forming quantitative preliminary requirements, i.e., compliant design data.

[0036] This application embodiment initializes and associates project requirement data and preset project design benchmark data based on a preset design toolset. A standard matching engine parses key design elements in the project requirement data and retrieves and matches them within the preset project design benchmark data. A data association tool binds successfully matched benchmark data entries to the project requirement data and assigns values ​​to variable parameters in the benchmark data according to specific parameters in the project requirements. A preliminary verification unit performs logical checks on the generated list to obtain compliant design data. This enhances the accuracy and automation of matching project requirements and design benchmarks, improves compliance and consistency assurance during the design initiation phase, and increases the efficiency and reliability of preliminary design data generation.

[0037] S202, based on compliant design data and a pre-set design toolset, performs scheme modeling and processing to obtain 3D model data.

[0038] Specifically, the creation of the schematic model can involve calling a preset schematic design toolset, importing compliant design data into the interface provided by the toolset, and then using the 3D modeling tools and parametric design plugins within the toolset to create, edit, and assemble 3D geometry based on the compliant design data. This gradually builds a 3D model that expresses the design scheme. During the modeling process, the component attribute information is mounted or associated according to the built-in BIM standards to obtain 3D schematic model data. This 3D schematic model data can be a digital design deliverable file or dataset integrating 3D geometric information and associated attribute information, which can be used to fully represent the spatial form, component composition, and technical parameters of the design scheme. This 3D schematic model data can be the data output obtained based on compliant design data through modeling and drawing operations using the preset schematic design toolset, and can be used to represent the design scheme of a real estate project.

[0039] For example, during the design phase of a residential development project, compliant design data can be a data package from the supplier that has passed system compliance verification. This data may include confirmed unit type module library index numbers, standardized floor elevations, standard wall thicknesses and material codes, and building setback outlines required in the planning guidelines. A pre-configured design toolset configured for the project can be loaded, which integrates specific BIM modeling software and enterprise-defined parametric component library plugins. A new project file can be opened within the pre-configured design toolset interface, importing the land setback outlines from the compliant design data as a base. The data can then be used to design the building based on the unit type index numbers within the pre-configured design toolset. The toolkit can retrieve the corresponding parametric 3D apartment model from the component library embedded in the design toolset. Based on the floor elevation information in the compliant design data, it can copy and stitch floors in 3D space to form standard floors. The toolkit can also use the wall tool in the preset design toolset to perform in-depth modeling of the building's exterior walls and partition walls based on the thickness and materials specified in the compliant design data, and can assign corresponding material properties to the walls. The preset design toolset can also generate floor plans, main elevations, and sections based on the 3D model and maintain a dynamic relationship with the 3D model. It can integrate all 3D geometry, associated 2D views, and attribute information mounted on components to package them into a 3D model data file.

[0040] This application embodiment processes scheme model creation based on compliant design data and a preset scheme design toolset. It utilizes 3D modeling tools and parametric design plugins provided by the preset scheme design toolset to create, edit, and assemble 3D geometry. During the modeling process, it loads or associates component attribute information according to the built-in BIM standard to obtain 3D model data. This improves the success rate and efficiency of model creation, shortens the cycle from design conception to 3D output, and enhances the structured potential of the 3D model data.

[0041] S203 performs index analysis on the 3D model data to obtain spatial index data.

[0042] Specifically, index parsing processing can be a data processing process that uses predetermined rules and algorithms to analyze, calculate, and transform the input 3D model data in order to extract the quantitative information contained therein. This index parsing processing can be used to transform non-quantitative geometric and attribute information into structured index data that can be calculated and evaluated.

[0043] Furthermore, it can read the 3D model data of a specific project stored in a structured database. This 3D model data may include the geometric components of the building, spatial division, component attribute label information, etc., without limitation here. Based on the built-in parsing rules, it can identify the key geometric parameters and attribute labels in the 3D model data. For example, it can identify wall and floor components to calculate the building area, identify room boundaries to calculate the usable area, and identify door and window components to calculate the window-to-floor ratio.

[0044] Furthermore, calculation logic can be executed on the extracted geometric and attribute information based on predefined accounting standards in the R&D process management mechanism, such as the "Code for Calculation of Building Area of ​​Construction Projects" or project-specific indicator calculation templates. This calculation logic can include area accumulation, volume calculation, and ratio calculation, thereby generating spatial indicator data such as total building area, plot ratio, building density, area ratio of each functional space, and usable floor area ratio. The generated structured spatial indicator data can be associated with the source 3D model data for easy retrieval and retrieval later.

[0045] Spatial index data can be structured numerical values ​​or datasets generated by parsing and calculating three-dimensional model data, which can be used to quantitatively characterize the spatial composition, scale, performance or economy of a design scheme. This spatial index data can provide objective and quantitative data support for the visualization and decision-making evaluation of design schemes.

[0046] This application embodiment processes 3D model data through index analysis. The index analysis unit identifies key geometric parameters and attribute labels in the 3D model data based on built-in analysis rules, and performs calculation logic on the extracted geometric and attribute information according to predefined calculation standards to obtain spatial index data. In this way, unstructured design results are transformed into standardized and quantifiable spatial index data, enhancing the automation of quantitative representation of design schemes; improving the accuracy and efficiency of spatial index calculation; and improving the quality of the data foundation for subsequent decision evaluation.

[0047] S204 involves linking and integrating the 3D model data and spatial index data to obtain the target scheme data.

[0048] Specifically, the correlation and integration processing can be a data processing process that establishes a one-to-one mapping relationship between 3D model data and spatial indicator data through specific data processing logic and technical means, and can bind and merge the two, thereby realizing the linkage between data and models, and combining abstract spatial indicator data with intuitive model visualization.

[0049] Furthermore, the association and integration processing can specifically include matching the unique identifiers of each component in the 3D model data with the identifiers of the components or spatial ranges corresponding to each indicator in the spatial indicator data. After a successful match, the spatial indicator data can be mounted as attribute information or associated data onto the corresponding 3D model component nodes. This results in a structured data package containing a complete geometric model, attribute information, and associated indicator data, i.e., the target scheme data. The target scheme data can be a complete design scheme dataset generated through association and integration processing, integrating a 3D geometric model, attribute information, and corresponding spatial indicator data. The target scheme data can be in the form of structured data results used for scheme decision presentation. This can serve as a data source for rendering the overall model and displaying the digital model in conjunction with the design.

[0050] Furthermore, the mapping relationships established by the association integration process can exist in the target solution data in the form of data tables, key-value pairs, or application programming interfaces, thereby ensuring the stability and programmable accessibility of the data association. The target solution data can be encapsulated in structured data formats such as JavaScript Object Notation (JSON) and Extensible Markup Language (XML), or encapsulated in a scene file format supported by a specific 3D engine, which can contain both the geometric and texture information of the model and indicator data embedded in the form of attributes.

[0051] For example, during the preparation phase of a residential development project's scheme decision-making meeting, all professional 3D model data from the completed scheme design phase can be retrieved from a structured database. Spatial indicator data such as calculated building area, unit internal area, shared area, and plot ratio can be obtained from the indicator analysis unit. Association and integration processing can be performed, linking each area indicator to the corresponding 3D model components based on the unique codes of building units, floors, and unit types. For instance, the internal area indicator data of unit type A can be linked to the set of all walls, slabs, columns, and other components representing unit type A in the 3D model; thus, the target scheme data can be obtained.

[0052] This application embodiment integrates and processes 3D model data and spatial indicator data, and matches them based on unique identifiers. The spatial indicator data is then attached as attribute information to the corresponding 3D model component nodes to obtain the target scheme data. This enhances the integration capability of digital model linkage and the stability of data association; improves the collaborative efficiency of design scheme visualization and quantitative analysis; and enhances the data integrity and programmable accessibility for subsequent decision presentation.

[0053] S205, Visualize the target scheme data to obtain the target design scheme.

[0054] Specifically, visualization processing can be a data processing process that transforms abstract data into graphical or image forms. Visualization processing can render and display target solution data in relation to other data. In this way, structured graphical and indicator data can be transformed into visual forms that are easy to understand and review, so as to support solution decision-making.

[0055] Furthermore, the visualization process can specifically retrieve graphical model data from the target solution data in a structured database, and construct the overall project structure based on this graphical model data. Figure 3 The model is rendered to generate a visual model view; spatial indicator data associated with the model data can be retrieved from a structured database, and the spatial indicator data can be compared with the total... Figure 3 The dimensional model is dynamically associated and bound, so that when a user interacts with a specific component or area in the model, the corresponding spatial indicator data can be displayed in real time, thereby completing the structured presentation of the indicator data and obtaining the target design scheme.

[0056] The target design scheme can be the output obtained by visualizing the target scheme data. The target design scheme can be a complete design scheme presentation after intuitive and related processing, specifically including a comprehensive display of the visualized master map model and related indicator data; this can serve as the review basis for the scheme decision meeting.

[0057] For example, in a real estate development project, the model rendering unit can retrieve the graphic model data of a candidate scheme from the database according to instructions, construct a 3D model of the overall building of the scheme, and perform lighting and material rendering to generate a visual model; the digital-model linkage unit can associate and retrieve the spatial indicator data corresponding to the scheme; the 3D model can be displayed through an interactive interface, and decision-makers can rotate and zoom the model to examine the building form and spatial layout from different angles; when the decision-maker clicks on a specific unit type in the model, the digital-model linkage mechanism can be triggered, and a structured indicator data panel associated with the unit type can pop up on the interface, displaying its internal area, usable floor area ratio, and other key information.

[0058] This application embodiment visualizes the target scheme data and constructs a total model rendering unit. Figure 3 The model is then rendered, and spatial index data is linked with the total data through the digital-model linkage unit. Figure 3 The model is dynamically associated and bound to obtain the target design scheme, thereby enhancing the visualization and interactive experience of the design scheme; improving the intuitiveness and efficiency of the linkage between the model and indicator data in the decision-making process; and enhancing the data support capability for scheme review and decision-making.

[0059] According to the technical solution provided in this disclosure, project requirement data and preset project design benchmark data are initialized and associated using a preset scheme design toolset. A standard matching engine parses project requirements and retrieves matching benchmark data. After data association and binding assignment by a data association device and logical checks by a preliminary verification unit, compliant design data is output. Scheme model creation is performed based on the compliant design data and the preset scheme design toolset. Geometry is created and attribute information is attached using a 3D modeling tool to generate 3D model data. The 3D model data undergoes index analysis processing. Geometric parameters and attribute labels are identified based on built-in rules, and calculations are performed according to accounting standards to obtain spatial index data. The 3D model data and spatial index data are then associated and integrated. Index data is matched and attached to corresponding component nodes based on unique identifiers to obtain target scheme data. The target scheme data is then visualized, and a final model is constructed through model rendering. Figure 3 The system utilizes a 3D model and dynamically links spatial indicator data with the model through digital-model linkage to obtain the target design scheme. This enhances the accuracy and automation level of matching project requirements with design benchmarks; improves compliance and consistency assurance capabilities during the design initiation phase; increases the success rate and efficiency of drawing and model production; improves the collaborative efficiency of design scheme visualization and quantitative analysis; enhances the generation efficiency and standardization of design schemes; strengthens the structuring and reusability of design data; improves the collaborative efficiency of supplier information provision and scheme design; enhances the intuitiveness and accuracy of scheme decision-making; and reduces internal and external communication costs and the losses from repeated modifications.

[0060] In some embodiments, the three-dimensional model data is subjected to index parsing processing to obtain spatial index data, including: performing spatial attribute extraction processing on the three-dimensional model data to obtain initial spatial parameters; performing index calculation processing on the initial spatial parameters to obtain calculated index data; and performing structured encapsulation processing on the calculated index data to obtain spatial index data.

[0061] Specifically, spatial attribute extraction processing can include calling the built-in geometric analysis engine to traverse various component objects in the 3D model data, identify and calculate the basic geometric dimensions of the components such as length, width, height, area, and volume, and extract their functional attributes, such as room type and wall material information, based on component type labels. The extracted geometric values ​​can be associated and bound with attribute labels to form a set of initial spatial parameters. The initial spatial parameters can be a data set obtained by performing geometric information calculation and attribute identification on the 3D model data. The initial spatial parameters can be the basic geometric measurements and type identifiers representing spatial objects. This can provide basic geometric and attribute information for subsequent index calculations.

[0062] Furthermore, the indicator calculation process can construct specific calculation logic based on the R&D indicator requirements established during the project initialization phase. For example, the initial spatial parameters of the areas of multiple components belonging to the same functional space can be accumulated to calculate the total area of ​​the functional space; key indicators such as building area, usable area, and floor area ratio can be calculated based on rules such as wall thickness and common area ratio; or planning indicators such as daylighting spacing and plot ratio can be verified according to regulatory requirements. Among these, the calculated indicator data can be the result data generated after calculating the initial spatial parameters based on preset calculation rules and algorithms. The calculated indicator data can be a quantitative result used to characterize space utilization efficiency, design compliance, or economy. In this way, basic geometric parameters can be transformed into evaluation indicators with business significance, providing a quantitative basis for design evaluation and decision-making.

[0063] Furthermore, structured encapsulation can map scattered accounting indicator data with different calculation dimensions to a unified data structure template according to their business attributes and data relationships. For example, area indicators, plot ratio indicators, and economic indicators can be classified and encapsulated separately, and corresponding spatial identifiers, project identifiers, and timestamps can be added to each indicator data.

[0064] For example, in the construction of 3D model data for a standard floor of a residential building, spatial attribute extraction processing can be performed on the 3D model data to identify components such as walls, floors, doors, and windows in the model, calculate the net dimensions of each room, identify functional labels such as bedroom and living room, and generate an initial set of spatial parameters containing information such as room area, perimeter, and type. Index calculation processing can be performed, calculating the usable area, building area, and internal building area of ​​each unit type based on preset residential design standards and initial spatial parameters. The shared area can also be calculated according to the wall centerline rules, thereby calculating the usable floor area ratio and forming accounting index data. Structured encapsulation processing can be performed, encapsulating the calculated usable area, building area, usable floor area ratio, and other accounting index data into a JSON format data package, i.e., spatial index data, based on the hierarchical structure of project-building-unit-unit type and the classification of area and efficiency indicators.

[0065] According to the technical solution provided in this disclosure, spatial attributes are extracted from 3D model data. A geometric analysis engine is invoked to traverse component objects, identify and calculate basic geometric dimensions, and associate functional attribute tags to obtain initial spatial parameters. These initial spatial parameters are then processed for index calculation. Calculation logic is constructed based on preset R&D index requirements to calculate parameters and generate business-meaning quantitative results, resulting in calculated index data. This data is then structured and encapsulated, mapped to a unified data structure template based on business attributes and data relationships, and identifiers are added to obtain spatial index data. This enhances the automated extraction capability from 3D models to basic geometric parameters, improves the accuracy and configurability of business index calculation, and enhances the structured level of spatial index data storage and exchange.

[0066] In some embodiments, the process of creating a scheme model based on compliant design data and a preset scheme design toolset to obtain three-dimensional model data includes: parsing the compliant design data for design parameters to obtain a model generation instruction; calling the preset scheme design toolset based on the model generation instruction to perform three-dimensional modeling to generate a scheme building information model; and performing data structuring transformation on the scheme building information model to obtain three-dimensional model data.

[0067] Specifically, design parameter parsing can be a data processing process that identifies, extracts, and transforms the instructions required for modeling from the above-mentioned formatted data. This process can transform abstract, compliant data into specific commands that can be executed by the modeling tool, namely, model generation instructions. Among them, model generation instructions can be a sequence of formatted commands obtained from design parameter parsing that can be recognized and executed by the modeling tool, thereby guiding the 3D modeling tool to perform specific model building operations.

[0068] Furthermore, 3D modeling processing can be a data processing process that automatically or semi-automatically constructs a 3D geometric model and its attribute information based on the instruction sequence generated from the drawing model in a preset scheme design toolset, thereby realizing the transformation from design instructions to 3D models; the scheme building information model can be a digital 3D model that carries complete building geometry, attributes and related information, which can serve as the core digital result of scheme design and provide a foundation for subsequent indicator calculation, visualization and data association; the scheme building information model can be generated by 3D modeling processing.

[0069] Furthermore, data structuring transformation can be a data processing procedure that converts the building information model of a scheme from a specific software format into a standard, open, easily searchable and associative general data format, thereby achieving the standardization and usability of model data. This data structuring transformation process can reorganize and encode information such as components, spaces, and attributes in the model based on preset classification and association rules to form a data structure with a unified identifier, namely, three-dimensional model data.

[0070] For example, in the design phase of a residential community project, compliant design data can include land boundary lines, plot ratio, building density, unit type module library numbers, and combination rules. This compliant design data can be parsed to identify the locations of the building blocks to be generated, the selected standard unit type modules, and their assembly logic, forming a set of drawing and model generation instructions containing parameters such as coordinates, module codes, and rotation angles. Based on these drawing and model generation instructions, a preset design toolset can be invoked to retrieve corresponding family files of walls, floors, doors, and windows from the standard component library. These files are then assembled in three-dimensional space based on the instruction parameters to generate a scheme building information model containing building geometry, room divisions, and component attributes. This scheme building information model can then undergo data structuring conversion, exporting it from its native software format to a Building Information Model Data Exchange Standard (IFC) format file containing geometric information, component type codes, spatial area lists, and interrelationships. This file is then 3D drawing and model data that can be stored in a structured database and supports rapid retrieval and correlation analysis.

[0071] According to the technical solution provided in this disclosure, by parsing and processing the compliant design data for design parameters, identifying, extracting, and converting it into a drawing model generation instruction that can be executed by the modeling tool, and calling a preset scheme design toolset based on the drawing model generation instruction to perform three-dimensional modeling processing, constructing a three-dimensional geometric model and attribute information, generating a scheme building information model, and performing data structure conversion processing on the scheme building information model to convert it from a specific software format to a standard, open data format, forming three-dimensional drawing model data with a unified identifier. In this way, the automated conversion capability from design data to modeling instructions is enhanced; the accuracy and efficiency of three-dimensional model generation are improved; and the standardization level and cross-platform exchangeability of model data are improved.

[0072] In some embodiments, the three-dimensional model data and spatial indicator data are associated and integrated to obtain target scheme data, including: classifying and indexing the three-dimensional model data to obtain structured model data; associating and mapping the structured model data and spatial indicator data to obtain indicator attribute model data; and encapsulating and storing the indicator attribute model data to obtain target scheme data.

[0073] Specifically, classification and indexing processing refers to the data processing of adding searchable tags and establishing index relationships to 3D model data based on preset data classification standards, such as the professional type, component category, or spatial function of 3D model data (this is not limited here). This can transform scattered, unstructured 3D model data into structured data. This classification and indexing processing can call standard product libraries and combine them with supplier-provided information to generate data. The preset data classification standards can come from the BIM implementation standards established during the project initialization phase. These BIM implementation standards can specify the naming, classification, and attribute information rules that model components should follow. According to these BIM implementation standards, imported model files can be parsed to identify component objects and assign corresponding classification codes and descriptive tags to them based on component type, system, or spatial location. This can generate a unique index identifier pointing to the model file or a specific component within it. Structured model data can be 3D model data that has undergone classification and indexing processing.

[0074] Furthermore, the association mapping process can be a data processing procedure that establishes a one-to-one or one-to-many correspondence between specific classification components or spatial units in structured graphical model data and specific indicator items in spatial indicator data. This enables deep integration of graphical models and quantitative data, ensuring that each relevant element in the model carries its corresponding key indicator attributes. This association mapping process can be implemented through methods such as data table association, attribute field binding, or external reference links. For example, based on a common classification code or index identifier, spatial indicator data records stored in a database table can be associated with the attribute information of corresponding components or spaces in the structured graphical model data. For instance, the interior area of ​​standard layer A can be mapped to a custom attribute set representing the model component of standard layer A, resulting in indicator attribute graphical model data. The indicator attribute graphical model data can be a data set in which the 3D graphical model and its corresponding spatial indicator data have formed an intrinsic binding relationship after the association mapping process is completed. This can constitute a composite data object that simultaneously carries geometric information and indicator information.

[0075] Furthermore, the encapsulation and storage processing can be a data processing procedure that packages the indicator attribute model data associated with spatial indicator data according to a predetermined data encapsulation format and stores it in a persistent storage system; this can generate a design scheme data package, i.e., target scheme data; the encapsulation format of this encapsulation and storage processing can be a self-describing file format or a database record format, which can not only contain model geometric data and texture resources, but also embed associated structured indicator data tables, mapping relationship definitions, and necessary metadata information. The encapsulation process can include steps such as data compression, encryption, and integrity verification.

[0076] For example, during the design phase of a residential development project, components such as walls, floors, doors, and windows in the 3D model data can be categorized and labeled according to the building component classification table defined in the project's BIM standard. For instance, all exterior walls can be labeled as A-Exterior Wall-Concrete, and an index can be created to form structured model data. Various economic and technical indicators for each scheme can be calculated, such as the internal area, shared area, total building area, and window-to-floor ratio of each unit type, generating spatial indicator data. Association mapping processing can be performed, mapping the indicator data Unit Type A-Internal Area: 95 square meters to the attributes of all related wall and floor components of Unit Type A through the unit type number, forming indicator attribute model data. All model files, associated indicator data tables, material textures, and project information metadata for this scheme can be packaged into an encrypted file, encapsulated, and stored in the project database as the target scheme data.

[0077] According to the technical solution provided in this disclosure, by classifying and indexing 3D model data, adding searchable tags to model components and establishing an index based on a preset data classification standard, structured model data is obtained. The structured model data is then associated and mapped with spatial indicator data. A correspondence between components and indicator items is established through a common classification code or index identifier. The indicator data is bound to the attributes of the model components to obtain indicator attribute model data. The indicator attribute model data is then encapsulated and stored, packaged according to a predetermined format, and stored in a persistent system to obtain the target solution data. This enhances the structured association depth between the 3D model and the indicator data; improves the accuracy of model data retrieval and indicator mapping; and enhances the integrity and standardization of the design solution data package encapsulation.

[0078] In some embodiments, visualizing the target scheme data to obtain the target design scheme includes: constructing a general map model from the target scheme data to obtain a three-dimensional general map model; performing digital-model linkage processing on the three-dimensional general map model to obtain a digital-model linkage model; and performing synchronous rendering processing on the digital-model linkage model to obtain the target design scheme.

[0079] Specifically, the site plan model construction process involves generating a 3D model in a 3D coordinate system based on structured graphic data. This model represents the overall layout of the project, the form of individual buildings, and their relationship with the surrounding environment. This process integrates and transforms non-intuitive, discrete graphic data into a unified, visual 3D digital model, laying the foundation for subsequent interactive displays and data association. The site plan model construction process reads geometric data, material properties, and spatial location information from the target scheme data, drives the graphics engine to instantiate corresponding 3D objects, and performs preliminary lighting and material calculations based on a pre-defined rendering pipeline, thereby generating a site plan model with basic 3D morphology and visual characteristics. The 3D site plan model, obtained through this process, serves as the core carrier of the design scheme in virtual space, providing users with an intuitive and three-dimensional perception of spatial layout and architectural form.

[0080] Furthermore, the digital-model linkage processing can be a data processing procedure for establishing dynamic relationships between geometric entities and structured indicator data in a 3D site plan model. This enables bidirectional binding and synchronous updates between the model view and business data, allowing the model's visualization status to represent changes in underlying data in real time, and interactive operations on the model to trigger updates and displays of relevant data. This digital-model linkage processing can be executed by the digital-model linkage unit in the decision presentation module. By defining unique identifiers for specific components or spatial regions in the 3D site plan model, and associating and mapping these identifiers with corresponding spatial indicator data in the target scheme data, a link relationship between geometric objects and data records can be constructed. The digital-model linkage model can be an enhanced 3D model that integrates geometric information and business data after digital-model linkage processing. The form of the digital-model linkage model can be a composite information model that achieves deep integration and interaction between the 3D model and structured data. This can serve as a unified interactive object for information query, analysis, and simulation in the scheme decision-making stage.

[0081] Furthermore, synchronous rendering processing can be used to integrate and visualize the index data associated with the digital-model linkage model in real time within the graphics rendering pipeline. This allows the associated index data to be overlaid and rendered as graphical elements on the corresponding positions in the view while displaying the 3D model. This synchronous rendering processing can be completed collaboratively by the model rendering unit and the digital-model linkage unit. The model rendering unit can draw the geometric parts of the digital-model linkage model in real time, while the digital-model linkage unit can calculate and generate the corresponding index data visualization elements based on the current view perspective and user interaction focus before each frame is rendered, and submit them to the model rendering unit for composite drawing.

[0082] According to the technical solution provided in this disclosure, by processing the target scheme data into a general layout model, by reading geometric data, material properties, and spatial location information, the graphics engine is driven to instantiate three-dimensional objects and calculate basic visual features to generate a three-dimensional general layout model. The three-dimensional general layout model is then processed through a digital-model linkage. By defining unique identifiers for components or spaces and establishing association mappings with spatial indicator data, a link between geometric objects and data records is constructed, generating a digital-model linkage model integrating geometric information and business data. The digital-model linkage model is then synchronously rendered, with the model rendering unit drawing the geometric parts in real time. Simultaneously, before rendering each frame, the digital-model linkage unit calculates and synthesizes the indicator data visualization elements based on the viewpoint and interactive focus to obtain the target design scheme. This enhances the automation and visual integrity of the three-dimensional model construction; improves the depth and stability of the bidirectional association between geometric entities and business data; and enhances the real-time visualization integration capability and interactive experience of indicator data in the three-dimensional view.

[0083] In some embodiments, the preset project design benchmark data is initialized and associated based on project requirement data and a preset scheme design toolset to obtain compliant design data, including: filtering and calling the preset project design benchmark data based on project requirement data to obtain target project specification data; associating and mapping the target project specification data and the preset scheme design toolset to obtain initial design content; and performing compliance verification on the initial design content to obtain compliant design data.

[0084] Specifically, the filtering and retrieval process can be based on key information in the project requirement data, such as project type, location, and cost level, to match and extract applicable design specifications, standard product parameters, and related process templates from the preset project design benchmark data. This filtering and retrieval process can be implemented through a data indexing unit, which matches the tags set in the project requirement data with the data tags stored in the preset project design benchmark data to locate and retrieve relevant data entries. In this way, the benchmark data can be converged into specific design guidelines that are highly relevant to the current project, i.e., target project specification data. The target project specification data can be the data obtained through the filtering and retrieval process, which can be specific design guidelines that are highly relevant to the current project.

[0085] Furthermore, the association mapping process can establish logical connections between specific parameter requirements in the target project specification data and corresponding modules in the preset design toolkit. For example, if the target project specification data requires the exterior wall material to be Class A fire-retardant real stone paint, this prerequisite can be bound to the facade in the module library that meets the requirement. If the specification requires the main unit type to be three bedrooms and two living rooms with an area range of 90-110 square meters, then standard unit type computer-aided design (CAD) blocks that meet the area range and functional layout can be associated. This association mapping process can be implemented through a preset rule engine or configuration table to ensure that the specification requirements can drive the invocation and parameter initialization of the corresponding design tools. The initial design content can be a preliminary scheme formed by invoking the specification and combining relevant design tool modules. The form of this initial design content can be a digital model or drawing set that includes preliminary building blocks, standard unit layouts, and basic landscape elements.

[0086] Furthermore, compliance verification can be performed by automating or semi-automating the checking and comparison of the generated initial design content based on the mandatory clauses and R&D indicators in the target project specification data. This compliance verification can be executed by the indicator verification unit, thereby enabling the timely detection of deviations between the initial scheme and the established specifications in the early stages of design. The verification content may include, but is not limited to, whether the building setback meets local planning requirements, whether the sunlight simulation results comply with the specifications, whether the unit area is controlled within the target range, and whether the selected standard product model is within the cost limit. The verification process can involve comparing the spatial dimensions, material properties, component quantities, and other data obtained from the parsing of the initial design content with the corresponding limit or enumerated values ​​in the target project specification data one by one, and generating a verification report, i.e., compliant design data.

[0087] For example, in a residential development project, the project requirements data could include the project being positioned as an improved housing type, with a plot ratio of 2.0, a building height limit of 80 meters, a green space ratio of no less than 35%, and the main unit type being a 110-square-meter three-bedroom apartment. The pre-set project design baseline data could store the city's latest "Urban Planning Management Technical Regulations," the company's "Residential Project BIM Design Standard V3.0," exterior wall systems, door and window models, interior decoration packages, and typical site layout templates from similar past projects in the standard product library. Based on the improved housing type and the city area label, the system could filter and retrieve corresponding urban planning provisions, the company's BIM standards for modeling accuracy and information delivery requirements for this type of housing, and cost-appropriate exterior wall and door / window product model parameters from the pre-set project design baseline data to form the target project specification data. Furthermore, the system could be linked to the plot ratio of 2.0 and the building height limit of 80 meters in the target project specification data. The design toolkit uses standard building blocks that meet the strength and height controls. Based on the 110-square-meter three-bedroom apartment requirement, it calls up multiple standardized CAD block options corresponding to the preset design toolkit. It also calls up basic landscape greening modules based on a green space ratio of no less than 35%. These modules are initially combined and arranged to generate initial design content including building outlines, apartment units, and green areas. The indicator verification unit can verify the compliance of this initial design content, calculating whether the ratio of total building area to land area is 2.0, checking whether the building outline meets the setback distance, simulating whether its shadow affects the surrounding existing buildings' compliance with sunlight standards, and verifying whether the associated exterior wall product model is within cost control limits. For issues found during verification that do not meet the preliminary estimated green space ratio, it can prompt adjustments to the configuration or layout of the landscape modules. After adjustments and passing all verifications, the resulting data is the compliant design data.

[0088] According to the technical solution provided in this disclosure, preset project design benchmark data is filtered and processed based on project requirement data. A data indexing unit matches and extracts applicable design specifications, standard parameters, and process templates according to requirement tags to obtain target project specification data. This target project specification data is then associated and mapped with a preset design toolset. A rule engine establishes a logical connection between specification parameters and design tool modules, driving tool module calls and parameter initialization to generate initial design content. The initial design content undergoes compliance verification. An indicator verification unit compares the parsed data with the target project specification data item by item, checks for deviations, and generates a verification report, resulting in compliant design data. This enhances the accurate matching capability between project requirements and design benchmarks; improves the efficiency of converting specification requirements into design tool-driven processes; and enhances the automation level and accuracy of early-stage design compliance verification.

[0089] In some embodiments, the initial spatial parameters are processed to obtain the calculated index data, including: performing spatial boundary identification processing on the initial spatial parameters to obtain spatial boundary data; performing area calculation processing on the spatial boundary data to obtain unit area data; performing volume index calculation processing on the unit area data to obtain volume ratio index data; and encapsulating the volume ratio index data and the unit area data to obtain the calculated index data.

[0090] Specifically, spatial boundary recognition processing can be a data processing process that identifies and extracts the closed contours of each functional unit defined by initial spatial parameters through algorithms. Spatial boundary recognition processing can transform abstract geometric descriptions into a set of boundary lines or boundary polygons that can be calculated, providing a geometric basis for subsequent area calculation. This spatial boundary recognition processing can distinguish boundaries of different properties, such as wall centerlines and room outlines, based on primitive layers, geometric topological relationships, or preset spatial type rules, thereby generating structured spatial boundary data. Spatial boundary data can be intermediate data generated by applying recognition algorithms to initial spatial parameters.

[0091] Furthermore, area calculation processing can be a data processing procedure that calculates the area of ​​the region enclosed by each closed boundary based on spatial boundary data using numerical integration or geometric formulas. Area calculation processing can quantify the actual occupied area of ​​each independent functional unit, serving as the core basic data for calculating building planning indicators. This area calculation processing can adopt different calculation strategies for different types of spatial boundaries. For example, for complex polygonal boundaries composed of polylines, Green's formula can be used for area calculation to ensure the accuracy and consistency of unit area data. Unit area data can be the result data obtained by performing area calculation algorithms on spatial boundary data.

[0092] Furthermore, the floor area ratio (FAR) calculation and processing can be a data processing process that combines unit area data with parameters such as total land area, number of building floors, and functional correction coefficients based on building planning codes to calculate key planning indicators such as floor area ratio and building density. The FAR calculation and processing can transform basic geometric area data into planning control indicators with legal significance and decision-making value. This FAR calculation and processing can incorporate calculation formulas from various local planning codes and can be linked to land boundary data set during the project initialization phase to achieve one-click and standardized calculation of indicators such as floor area ratio. The floor area ratio indicator data can be derived data generated by substituting unit area data into a preset floor area ratio calculation formula.

[0093] Encapsulation processing is a data processing procedure that integrates and packages indicator data from different sources and of different types based on a predefined structure format. Encapsulation processing can integrate the unit area results calculated separately with core indicators such as the floor area ratio obtained from comprehensive calculation into a structured data package, which is convenient for subsequent storage, retrieval, and association with the model for display. This encapsulation processing can follow a unified data exchange format, such as JSON or XML, and can bind various indicator data with their corresponding spatial unit identifiers to form structured accounting indicator data with good readability and parsability.

[0094] According to the technical solution provided in this disclosure, spatial boundary identification processing is performed on the initial spatial parameters, and the closed contours of each functional unit are identified and extracted through algorithms to generate spatial boundary data. Area calculation processing is performed on the spatial boundary data, and the area of ​​the region enclosed by each closed boundary is calculated using numerical integration or geometric formulas to obtain unit area data. Volume ratio calculation processing is performed on the unit area data, and planning indicators are calculated according to standard formulas based on parameters such as land area and number of building floors to obtain volume ratio index data. The volume ratio index data and unit area data are encapsulated, integrated based on a predefined format, and bound to spatial unit identifiers to obtain the calculated index data. This enhances the automation and accuracy of the vectorization of spatial geometric information into indexes; improves the standardization and consistency of area calculation and volume ratio calculation; and enhances the structured level and exchangeability of the index data encapsulation.

[0095] All of the above-mentioned optional technical solutions can be combined in any way to form optional embodiments of this disclosure, and will not be described in detail here.

[0096] Figure 3 This is a schematic diagram of another method for generating real estate project design schemes provided in this embodiment of the disclosure. Figure 3 As shown, the method for generating the design scheme for this real estate project includes: Project initialization - clear requirements: Develop BIM implementation standards and determine the BIM application specifications and data format requirements for design schemes; complete the selection of standard products and clarify the parameters and specifications of the standardized products required in the design (preset project design benchmark data); establish a research and development process management mechanism to standardize the process nodes and responsibility boundaries of subsequent information submission, design, and delivery.

[0097] Supplier-provided resources - helping to improve efficiency: The pre-packaged solution CAD module is invoked to generate preliminary information based on project requirements; the information is then verified for compliance according to R&D indicators to ensure it meets project design standards.

[0098] Solution Design - Deliverables: Based on the CAD module and the information provided by the supplier (project requirement data), the scheme model is completed; the completed model (3D model data) is stored in a structured database to realize the classification and association storage of model data; the spatial index data corresponding to the model is analyzed and calculated to generate structured index results.

[0099] Solution Decision Meeting - Advanced Presentation: Retrieve stored map data, construct a master map model and visualize it; achieve data-model linkage, associate structured indicator data with the master map model for display, and complete the structured presentation of indicator data.

[0100] This method comprises five core functional modules that work together to rapidly present design solutions: Project initialization module Function: Output the basic specifications and process framework for project design, specifically including the formulation of BIM implementation standards, the selection of standard products, and the configuration of R&D processes; Components: Standard Library (stores BIM specifications and standard product parameters), Process Configuration Unit (defines process nodes and responsible parties).

[0101] Supplier-provided auxiliary modules Function: Improve the efficiency and compliance of supplier submissions, specifically by providing CAD encapsulation module calling interfaces and verifying submission content based on R&D indicators; Components: Module library (stores pre-packaged CAD design modules), indicator verification unit (automatically verifies content to match R&D indicators).

[0102] Solution Design Processing Module Function: Completes the creation of graphic models and data structuring, specifically including graphic model drawing, structured storage, and spatial index analysis; Components: Drawing and model creation unit (tool component supporting CAD operations), structured storage unit (database for classifying and associating drawing and model data), and indicator analysis unit (spatial indicator calculation component).

[0103] Decision Presentation Module Function: To achieve an intuitive and interconnected presentation of the solution, specifically including site plan model rendering and digital model linkage display; Components: Model rendering unit (overall model visualization component), numerical model linkage unit (indicator data and model association display component).

[0104] Data storage module Functions: Stores full-process data and supports fast retrieval, including BIM standards, CAD modules, drawing and model data, spatial indicators, etc. Components: Distributed database (compatible with structured / unstructured data), data indexing unit (enabling accurate and fast data retrieval).

[0105] According to the technical solutions provided in this disclosure, by unifying BIM standards, product selection, and process management, information discrepancies in scheme communication are reduced, and repeated back-and-forth is avoided; the reuse of pre-packaged CAD modules improves the efficiency of supplier information provision and scheme design, and reduces the time spent in the scheme stage; the structured storage of drawings and indicator data facilitates subsequent retrieval, reuse, and cross-stage data association; the generation efficiency and standardization of design schemes are improved, the structure and reusability of design data are enhanced, the collaborative efficiency of supplier information provision and scheme design is improved, the intuitiveness and accuracy of scheme decisions are strengthened, and the costs of internal and external communication and repeated modifications are reduced.

[0106] The following are embodiments of the apparatus disclosed herein, which can be used to execute embodiments of the method disclosed herein. For details not disclosed in the apparatus embodiments of this disclosure, please refer to the embodiments of the method disclosed herein.

[0107] Figure 4 This is a schematic diagram of a real estate project design scheme generation device provided in an embodiment of this disclosure. Figure 4 As shown, the device for generating design schemes for real estate projects includes: The first processing module 401 is used to perform initial association processing on the preset project design benchmark data based on the project requirement data and the preset scheme design toolset to obtain compliant design data. The second processing module 402 is used to process the scheme model based on the compliant design data and the preset scheme design toolset to obtain three-dimensional model data. The third processing module 403 is used to perform index analysis processing on the three-dimensional model data to obtain spatial index data. The fourth processing module 404 is used to correlate and integrate the 3D model data and spatial index data to obtain the target scheme data; The fifth processing module 405 is used to visualize the target scheme data to obtain the target design scheme.

[0108] According to the technical solution provided in this disclosure, project requirement data and preset project design benchmark data are initialized and associated using a preset scheme design toolset. A standard matching engine parses project requirements and retrieves matching benchmark data. After data association and binding assignment by a data association device and logical checks by a preliminary verification unit, compliant design data is output. Scheme model creation is performed based on the compliant design data and the preset scheme design toolset. Geometry is created and attribute information is attached using a 3D modeling tool to generate 3D model data. The 3D model data undergoes index analysis processing. Geometric parameters and attribute labels are identified based on built-in rules, and calculations are performed according to accounting standards to obtain spatial index data. The 3D model data and spatial index data are then associated and integrated. Index data is matched and attached to corresponding component nodes based on unique identifiers to obtain target scheme data. The target scheme data is then visualized, and a final model is constructed through model rendering. Figure 3 The system utilizes a 3D model and dynamically links spatial indicator data with the model through digital-model linkage to obtain the target design scheme. This enhances the accuracy and automation level of matching project requirements with design benchmarks; improves compliance and consistency assurance capabilities during the design initiation phase; increases the success rate and efficiency of drawing and model production; improves the collaborative efficiency of design scheme visualization and quantitative analysis; enhances the generation efficiency and standardization of design schemes; strengthens the structuring and reusability of design data; improves the collaborative efficiency of supplier information provision and scheme design; enhances the intuitiveness and accuracy of scheme decision-making; and reduces internal and external communication costs and the losses from repeated modifications.

[0109] In some embodiments, the third processing module 403 is specifically used to: extract spatial attributes from the three-dimensional model data to obtain initial spatial parameters; perform index calculation on the initial spatial parameters to obtain calculated index data; and perform structured encapsulation on the calculated index data to obtain spatial index data.

[0110] In some embodiments, the second processing module 402 is specifically used to: perform design parameter parsing processing on the compliant design data to obtain a drawing model generation instruction; call a preset scheme design toolset based on the drawing model generation instruction to perform three-dimensional modeling processing to generate a scheme building information model; and perform data structuring conversion processing on the scheme building information model to obtain three-dimensional drawing model data.

[0111] In some embodiments, the fourth processing module 404 is specifically used to: perform classification and indexing processing on the three-dimensional model data to obtain structured model data; perform association mapping processing on the structured model data and spatial indicator data to obtain indicator attribute model data; and perform encapsulation and storage processing on the indicator attribute model data to obtain target scheme data.

[0112] In some embodiments, the fifth processing module 405 is specifically used to: perform site map model construction processing on the target scheme data to obtain a three-dimensional site map model; perform digital-model linkage processing on the three-dimensional site map model to obtain a digital-model linkage model; and perform synchronous rendering processing on the digital-model linkage model to obtain the target design scheme.

[0113] In some embodiments, the first processing module 401 is specifically used to: filter and call preset project design benchmark data based on project requirement data to obtain target project specification data; perform association mapping processing on the target project specification data and preset scheme design toolset to obtain initial design content; and perform compliance verification processing on the initial design content to obtain compliant design data.

[0114] In some embodiments, the initial spatial parameters are processed to obtain index data. Specifically, the initial spatial parameters are processed to identify spatial boundaries to obtain spatial boundary data; the spatial boundary data is processed to calculate area to obtain unit area data; the unit area data is processed to calculate volume index to obtain volume ratio index data; and the volume ratio index data and unit area data are encapsulated to obtain the index data.

[0115] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this disclosure.

[0116] Figure 5 This is a schematic diagram of the electronic device 5 provided in an embodiment of this disclosure. Figure 5 As shown, the electronic device 5 of this embodiment includes: a processor 501, a memory 502, and a computer program 503 stored in the memory 502 and executable on the processor 501. When the processor 501 executes the computer program 503, it implements the steps in the various method embodiments described above. Alternatively, when the processor 501 executes the computer program 503, it implements the functions of each module / unit in the various device embodiments described above.

[0117] Electronic device 5 can be a desktop computer, laptop, handheld computer, cloud server, or other electronic device. Electronic device 5 may include, but is not limited to, processor 501 and memory 502. Those skilled in the art will understand that... Figure 5 This is merely an example of electronic device 5 and does not constitute a limitation on electronic device 5. It may include more or fewer components than shown, or different components.

[0118] The processor 501 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0119] The memory 502 can be an internal storage unit of the electronic device 5, such as a hard disk or RAM of the electronic device 5. The memory 502 can also be an external storage device of the electronic device 5, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc., equipped on the electronic device 5. The memory 502 can also include both internal and external storage units of the electronic device 5. The memory 502 is used to store computer programs and other programs and data required by the electronic device.

[0120] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0121] If integrated modules / units are implemented as software functional units and sold or used as independent products, they can be stored in a readable storage medium (e.g., a computer-readable storage medium). Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program may include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. A computer-readable storage medium may include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0122] The above embodiments are only used to illustrate the technical solutions of this disclosure, and are not intended to limit it. Although this disclosure 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 spirit and scope of the technical solutions of the embodiments of this disclosure, and should all be included within the protection scope of this disclosure.

Claims

1. A method for generating a design scheme for a real estate project, characterized in that, include: Based on project requirement data and a pre-set design toolset, the pre-set project design baseline data is initialized and associated to obtain compliant design data. Based on the compliant design data and the preset scheme design toolset, the scheme model is processed to obtain three-dimensional model data; The three-dimensional model data is subjected to index analysis processing to obtain spatial index data; The three-dimensional model data and the spatial index data are correlated and integrated to obtain the target scheme data; The target scheme data is visualized to obtain the target design scheme.

2. The method for generating real estate project design schemes according to claim 1, characterized in that, The step of performing index analysis processing on the three-dimensional model data to obtain spatial index data includes: Spatial attribute extraction processing is performed on the three-dimensional model data to obtain initial spatial parameters; The initial spatial parameters are processed to obtain the calculated index data; The calculated index data is structured and encapsulated to obtain the spatial index data.

3. The method for generating a real estate project design scheme according to claim 1, characterized in that, The process of creating 3D model data based on the compliant design data and the preset design toolset includes: The compliant design data is processed by parsing design parameters to obtain drawing generation instructions; Based on the drawing model generation command, the preset scheme design toolset is invoked to perform three-dimensional modeling processing and generate a scheme building information model; The building information model of the proposed scheme is subjected to data structuring transformation to obtain three-dimensional model data.

4. The method for generating a real estate project design scheme according to claim 1, characterized in that, The step of associating and integrating the 3D model data and the spatial index data to obtain the target scheme data includes: The three-dimensional model data is classified and indexed to obtain structured model data; The structured graph data and the spatial index data are correlated and mapped to obtain index attribute graph data; The indicator attribute graph data is encapsulated and stored to obtain the target scheme data.

5. The method for generating a real estate project design scheme according to claim 1, characterized in that, The visualization processing of the target scheme data to obtain the target design scheme includes: The target scheme data is processed to construct a general map model, resulting in a three-dimensional general map model; The three-dimensional site plan model is subjected to digital-model linkage processing to obtain a digital-model linkage model; The digital-analog linkage model is synchronously rendered to obtain the target design scheme.

6. The method for generating a real estate project design scheme according to claim 1, characterized in that, The process of initializing and associating preset project design benchmark data based on project requirement data and preset scheme design toolsets yields compliant design data, including: Based on the project requirement data, the preset project design benchmark data is filtered and processed to obtain the target project specification data; The target project specification data and the preset scheme design toolset are associated and mapped to obtain the initial design content; The initial design content is subjected to compliance verification to obtain the compliant design data.

7. The method for generating a real estate project design scheme according to claim 2, characterized in that, The step of performing index calculation processing on the initial spatial parameters to obtain calculated index data includes: The initial spatial parameters are subjected to spatial boundary identification processing to obtain spatial boundary data; The spatial boundary data is processed by area calculation to obtain unit area data; The unit area data is processed by volume index calculation to obtain the volume ratio index data; The plot ratio data and the unit area data are encapsulated to obtain the accounting index data.

8. A device for generating design schemes for real estate projects, characterized in that, include: The first processing module is used to initialize and associate the preset project design benchmark data based on the project requirement data and the preset scheme design toolset to obtain compliant design data. The second processing module is used to process the scheme model based on the compliant design data and the preset scheme design toolset to obtain three-dimensional model data. The third processing module is used to perform index parsing processing on the three-dimensional model data to obtain spatial index data; The fourth processing module is used to correlate and integrate the three-dimensional model data and the spatial index data to obtain the target scheme data; The fifth processing module is used to perform visualization processing on the target scheme data to obtain the target design scheme.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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