A method and system for generating a variable space residential design scheme

Abstract

A method and system for generating a design scheme for a variable-space residential building, relating to the field of residential design, includes: obtaining an initial three-dimensional residential model containing fixed and variable functional areas to provide a foundation for subsequent design; generating multiple preselected locations in the fixed functional areas based on preset building codes and structural requirements, and calculating comprehensive performance indicators to determine the optimal location distribution; generating preselected locations in the variable functional areas based on user demand parameters, spatial variability rules, and the location distribution of the fixed functional areas; then optimizing the layout by obtaining parameter values ​​through spatial variability simulation; and finally, placing preselected modules in the corresponding areas to generate a three-dimensional residential design model. The preselected modules are standardized, complete sets of industrial products, ensuring modular production efficiency while meeting the personalized spatial needs of different families at different stages of development. Implementing this method can improve the efficiency of variable-space residential design.

Description

Technical Field

[0001] The present application relates to the field of residential design, and in particular to a method and system for generating a variable space residential design scheme. Background Art

[0002] Currently, the design of adaptable residential spaces primarily utilizes modular design and movable partitions. Designers first determine the locations of fixed-function areas, such as the kitchen and bathroom, and then plan for flexible areas within the remaining space. Within these areas, designers utilize movable partition walls or multifunctional furniture modules, such as foldable beds and retractable dining tables, to achieve multifunctional spatial transformation. This approach adapts the spatial layout through simple mechanical transformations to accommodate diverse living scenarios.

[0003] However, this automatic layout method based on preset templates has certain problems in practical application. If the focus is on the space utilization of residential design, the traffic flow design may be unreasonable. Meeting the traffic flow design may lead to low space utilization. Designers need to spend a lot of time fine-tuning the design, resulting in inefficient variable space residential design. Summary of the Invention

[0004] The present application provides a method and system for generating a variable space residential design solution, which is used to improve the efficiency of variable space residential design.

[0005] In the first aspect, the present application provides a method for generating a variable space residential design scheme, which is applied to a generation system of a variable space residential design scheme, the method comprising: obtaining an initial residential three-dimensional model of a target design residence, wherein the initial residential three-dimensional model includes a fixed function area and a variable function area; within the fixed function area, based on preset building specifications and structural requirements, generating multiple fixed function pre-selected positions, calculating the comprehensive performance index corresponding to each fixed function pre-selected position, and using the fixed function pre-selected position with the highest comprehensive performance index as the fixed function area position distribution, wherein the comprehensive performance index is obtained by weighted calculation of space utilization rate, assembly rate and movement line efficiency ratio; within the variable function area, based on user demand parameters, space The method comprises the following steps: using a computational simulation tool to perform spatial variability simulation on each variable function position based on the initial residential three-dimensional model, and obtaining a spatial variability parameter value corresponding to each variable function position, wherein the spatial variability parameter value is obtained by weighted calculation of spatial conversion efficiency and functional fitness; optimizing the initial layout of the variable function area according to the spatial variability parameter value, and obtaining a position distribution of the variable function area; placing a preset fixed module building in the fixed function area based on the position distribution of the fixed function area, and placing a preset movable module in the variable function area based on the position distribution of the variable function area, and generating a residential design three-dimensional model.

[0006] By adopting the above technical solution, an initial three-dimensional residential model containing fixed and variable functional areas is first obtained, providing a foundation for subsequent design. Based on preset building specifications and structural requirements, multiple pre-selected locations are generated in the fixed functional areas, and comprehensive performance indicators are calculated to determine the optimal location distribution, thereby improving space utilization, assembly rate, and movement efficiency. In the variable functional areas, pre-selected locations are generated based on user demand parameters, spatial variability rules, and the location distribution of fixed functional areas. Spatial variability simulation is then used to obtain parameter values ​​for the optimized layout. Finally, pre-set modules are placed in the corresponding areas to generate a three-dimensional residential design model. The pre-set modules are standardized sets of industrial products. While ensuring modular production efficiency, they meet the personalized spatial needs of different families at different development stages, realizing intelligent residential space design and improving design efficiency.

[0007] In combination with some embodiments of the first aspect, in some embodiments, before the step of obtaining an initial residential three-dimensional model of the target design residence, wherein the initial residential three-dimensional model includes fixed functional areas and variable functional areas, the method further includes: receiving personal information and design requirements input by a user, and constructing a user portrait based on the personal information and the design requirements, wherein the user portrait includes family structure, living habits and space preferences; generating multiple typical life scenes based on the user portrait, wherein each life scene corresponds to a group of functional elements; performing a space demand analysis on each group of the functional elements to determine the minimum space size and form requirements required to realize each of the functional elements; designing multiple space modules based on the minimum space size and the form requirements, wherein the space modules include fixed functional modules and variable functional modules; combining the multiple space modules based on a preset space combination rule library to obtain a module space combination scheme, wherein the preset space combination rule library includes module connection rules, module orientation rules, proximity rules and module variability rules; dividing the fixed functional modules in the module space combination scheme into fixed functional areas, dividing the variable functional modules into variable functional areas, and generating an initial residential three-dimensional model based on the fixed functional areas and the variable functional areas.

[0008] By adopting the above technical solution, before obtaining the initial residential three-dimensional model, user information and needs are received to build a user portrait, life scenes and functional elements are generated based on the user portrait, and space demand analysis is performed to determine the module size and shape requirements, so that the design is more in line with the user's actual life. Fixed and variable functional modules are designed and combined according to the rule library, and fixed and variable functional areas are divided to generate the initial model, ensuring the rationality and scientificity of the area division.

[0009] In combination with some embodiments of the first aspect, in some embodiments, the step of generating multiple fixed function pre-selected positions within the fixed function area based on preset building specifications and structural requirements specifically includes: identifying key function points and equipment positions within the fixed function area; converting the minimum spacing requirements in the preset building specifications into constraints between equipment, and setting the structural requirements as fixed boundaries to determine the movable range of the key function points and the equipment positions; generating multiple fixed function pre-selected positions based on the constraints, fixed boundaries and the movable range.

[0010] By employing this technical solution, key functional points and equipment locations are identified within fixed functional areas. Building code requirements are converted into constraints, and the range of movement is determined. This preselected location better considers the relationships between equipment and space utilization, avoiding illogical layouts. When calculating comprehensive performance indicators, space utilization, assembly rate, and movement efficiency ratio are calculated and weighted, enabling a comprehensive assessment of the pros and cons of each preselected location.

[0011] In combination with some embodiments of the first aspect, in some embodiments, the comprehensive performance index corresponding to each fixed function preselected position is calculated, and the fixed function preselected position with the highest comprehensive performance index is used as the fixed function area position distribution, and the comprehensive performance index is obtained by weighted calculation of the space utilization rate and the assembly rate, specifically including: calculating the space utilization rate and the assembly rate of each fixed function preselected position, the space utilization rate is the ratio of the effective use area to the total area, and the assembly rate is the proportion of standardized modules adopted; based on the preset key movement line path, measuring the actual length of the preset key movement line path in each fixed function preselected position, comparing the actual length of the preset key movement line path with the preset ideal length, and obtaining the movement line efficiency ratio corresponding to each fixed function preselected position; assigning weight coefficients to the space utilization rate, the assembly rate and the movement line efficiency, and calculating the comprehensive performance index based on the weight coefficient, the space utilization rate, the assembly rate and the movement line efficiency; and using the fixed function preselected position with the highest comprehensive performance index as the fixed function area position distribution.

[0012] By adopting the above technical solution, the space utilization rate and assembly rate of each fixed-function pre-selected position are calculated, the degree of space use and module standardization is clarified, and the traffic efficiency ratio is obtained by measuring the preset key traffic path and comparing the actual length with the ideal length. Weight coefficients are assigned to these indicators and the comprehensive performance index is calculated. The position with the highest comprehensive performance index is used as the location distribution of the fixed-function area, ensuring that the fixed-function area reaches the optimal state in terms of space utilization, module assembly and traffic design.

[0013] In combination with some embodiments of the first aspect, in some embodiments, the computational simulation tool is used to perform spatial variability simulation on each variable functional position based on the initial residential three-dimensional model to obtain the spatial variability parameter value corresponding to each variable functional position, specifically including: importing the initial residential three-dimensional model into the computational simulation tool, and for each variable functional position, simulating the spatial change process of the variable functional position under different life scenarios to obtain the operation time and operation complexity required for converting one function to another, and each life scenario corresponds to each functional layout of all the variable functional positions; calculating the spatial conversion efficiency based on the operation time and the operation complexity; evaluating the functional fitness of each variable functional position under each functional layout based on the spatial change process, and the functional fitness is calculated by space utilization and user usage efficiency, the space utilization is obtained by evaluating the spatial changes in the simulation, and the user usage efficiency is obtained by evaluating the time it takes for the user to complete a specific task in the simulation; and obtaining the variability parameter value by weighted calculation based on the spatial conversion efficiency and the functional fitness.

[0014] By adopting the above technical solution, the initial residential three-dimensional model is imported into the computational simulation tool, and the spatial variability of each variable functional position is simulated. The simulation process covers the spatial changes under different life scenarios. The simulation obtains the operation time and operation complexity to calculate the spatial conversion efficiency, and evaluates the functional adaptability, thereby improving the spatial conversion efficiency and functional adaptability of the variable functional area.

[0015] In combination with some embodiments of the first aspect, in some embodiments, the step of optimizing the initial layout of the variable functional area according to the spatial variability parameter value to obtain the position distribution of the variable functional area specifically includes: establishing a spatial layout optimization model according to the spatial variability parameter value of each variable functional position; setting an optimization objective function based on the spatial layout optimization model, and the optimization objective function contains preset constraints, and the preset constraints include the minimum area requirement of the variable functional position and the minimum spacing requirement between functional areas; using the optimization algorithm to iteratively optimize the layout of the variable functional area to obtain a new layout scheme; performing spatial variability simulation on each of the new layout schemes, and calculating the variability parameter value of each of the new layout schemes; and using the layout scheme with a variability parameter value greater than the preset parameter threshold as the position distribution of the variable functional area.

[0016] By adopting the above technical solution, a spatial layout optimization model is established according to the spatial variability parameter value of each variable functional position, and an optimization objective function containing preset constraints is set to ensure that the optimization process meets actual requirements. The layout of the variable functional area is iteratively optimized using an optimization algorithm, and the layout scheme with a variability parameter value greater than the preset parameter threshold is used as the variable functional area position distribution, ultimately achieving the optimization of the variable functional area layout.

[0017] In combination with some embodiments of the first aspect, in some embodiments, after the step of placing a preset fixed module building into the fixed functional area based on the position distribution of the fixed functional area, and placing a preset movable module into the variable functional area based on the position distribution of the variable functional area, and generating a three-dimensional model of the residential design, the method further includes: sending the three-dimensional model of the residential design to a preset client for display.

[0018] By adopting the above technical solution, a three-dimensional model of residential design is generated. The model fully presents the spatial layout and functional settings of the house, intuitively displays the design results, improves the visualization of residential design, and provides users with a clear design solution.

[0019] In a second aspect, an embodiment of the present application provides a system for generating a variable-space residential design scheme, the system comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code comprising computer instructions, the one or more processors calling the computer instructions to enable the system for generating a variable-space residential design scheme to execute the method described in the first aspect and any possible implementation of the first aspect.

[0020] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions. When the above-mentioned computer program product is run on a system for generating a variable-space residential design scheme, the above-mentioned system for generating a variable-space residential design scheme executes the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium comprising instructions. When the above instructions are run on a system for generating a variable-space residential design scheme, the system for generating a variable-space residential design scheme executes the method described in the first aspect and any possible implementation method of the first aspect.

[0022] It is understood that the system for generating a variable-space residential design solution provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the methods provided in the embodiments of this application. Therefore, the beneficial effects achievable by these methods can be referenced to the beneficial effects of the corresponding methods and will not be further elaborated here.

[0023] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0024] 1. This application obtains an initial three-dimensional residential model containing fixed and variable functional areas to provide a basis for subsequent design. Based on preset building specifications and structural requirements, multiple pre-selected locations are generated in the fixed functional area and the optimal location distribution is determined by calculating comprehensive performance indicators, thereby improving space utilization, assembly rate, and movement efficiency. In the variable functional area, pre-selected locations are generated based on user demand parameters, spatial variability rules, and the location distribution of the fixed functional area. Then, through spatial variability simulation, the parameter value optimization layout is obtained. Finally, the preset modules are placed in the corresponding area to generate a three-dimensional residential design model. The preset modules use standardized sets of industrial products. While ensuring modular production efficiency, they meet the personalized space needs of different families at different development stages, realizing the intelligent design of residential space and improving design efficiency.

[0025] 2. This application receives user information and needs before obtaining the initial three-dimensional model of the residence to build a user portrait, generates life scenes and functional elements based on the user portrait, conducts space demand analysis to determine module size and shape requirements, so that the design is more in line with the user's actual life, designs fixed and variable functional modules and combines them according to the rule library, divides the fixed and variable functional areas to generate the initial model, and ensures the rationality and scientificity of the area division.

[0026] 3. This application clarifies the degree of space utilization and module standardization by calculating the space utilization rate and assembly rate of each fixed-function pre-selected position. It measures the preset key traffic line paths and compares the actual length with the ideal length to obtain the traffic line efficiency ratio. It assigns weight coefficients to these indicators and calculates the comprehensive performance index. The position with the highest comprehensive performance index is used as the location distribution of the fixed-function area, ensuring that the fixed-function area reaches the optimal state in terms of space utilization, module assembly and traffic line design. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a flow chart of a method for generating a variable space residential design solution in an embodiment of the present application;

[0028] Figure 2 is another flow chart of the method for generating a variable space residential design solution in an embodiment of the present application;

[0029] Figure 3 This is another flowchart of the method for generating a variable space residential design solution in an embodiment of the present application;

[0030] Figure 4 It is a schematic diagram of the physical device structure of the system for generating a variable space residential design scheme in the embodiment of the present application. DETAILED DESCRIPTION

[0031] The terms used in the following examples of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification of the present application, the singular expressions "a", "an", "above", "the", and "this" are intended to include plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations of one or more of the listed items.

[0032] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of the technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more.

[0033] For ease of understanding, the following describes the process of the method provided by this implementation. Figure 1 , which is a flow chart of a method for generating a variable space residential design scheme in an embodiment of the present application.

[0034] S101. Obtain an initial three-dimensional residential model of a target design residence, wherein the initial three-dimensional residential model includes fixed function areas and variable function areas.

[0035] Among them, the target design residence represents a specific residential project that requires intelligent design, the initial residential three-dimensional model refers to the preliminary three-dimensional digital model of the target design residence, the fixed functional area is used to represent the functional space that cannot be changed in the residence, such as the kitchen, bathroom, etc., and the variable functional area refers to the space area that can be adjusted and changed according to needs, such as the living room, bedroom and other areas that can be flexibly changed in use.

[0036] Specifically, when starting the residential intelligent design process, you first need to obtain a preliminary residential three-dimensional model as the basis for the design. The initial residential three-dimensional model is usually created by an architect or designer based on project requirements and basic layout ideas. The model has divided the approximate range of fixed functional areas and variable functional areas. The initial residential three-dimensional model is obtained by importing CAD files, BIM models or files from other 3D modeling software.

[0037] In some embodiments, the initial residential three-dimensional model can be obtained in a variety of ways: optionally, by using professional 3D modeling software such as Autodesk Revit or SketchUp to create an initial model, draw a floor plan according to project requirements and site conditions, and then stretch the floor plan into a three-dimensional model, divide the model into fixed function areas and variable function areas, and add basic walls, doors, windows and other structural elements, and export the created model to a common 3D file format; optionally, the initial model can be quickly generated using a preset residential template library, and the basic model closest to the target design residence can be selected from the template library. The model can be adjusted according to specific needs, such as modifying the room size, adjusting the wall position, etc., marking the fixed function areas and variable function areas in the adjusted model, and saving the modified model in a format that the system can recognize. It is understandable that other methods can also be used to obtain the initial residential three-dimensional model, such as using 3D scanning technology to scan and model existing buildings, or quickly generating an initial model through AI-assisted design tools, which are not limited here.

[0038] S102. Within the fixed-function area, based on preset building specifications and structural requirements, generate multiple fixed-function pre-selected locations, calculate the comprehensive performance index corresponding to each fixed-function pre-selected location, and use the fixed-function pre-selected location with the highest comprehensive performance index as the fixed-function area location distribution. The comprehensive performance index is obtained by weighted calculation of space utilization rate, assembly rate, and traffic flow efficiency ratio.

[0039] Among them, the preset building specifications represent the standardized building design rules that need to be followed during the design process. Structural requirements refer to the engineering and technical requirements that ensure building safety and stability. Fixed-function preselected locations represent possible layout options within fixed-function areas. Comprehensive performance index is a comprehensive score used to evaluate the advantages and disadvantages of fixed-function layouts. Space utilization rate indicates the efficiency of space use. Assembly rate indicates the degree of use of standardized modules. Movement efficiency ratio refers to the ratio of actual movement routes to ideal movement routes.

[0040] Specifically, after finalizing the initial 3D residential model, detailed design of the fixed-function areas is required. Based on pre-set building codes and structural requirements, the system generates multiple possible layout options within the fixed-function areas, known as pre-selected fixed-function locations. Each pre-selected location is evaluated and its comprehensive performance index is calculated. The comprehensive performance index is based on spatial efficiency, standardization, and ease of use. The option with the highest comprehensive performance index is selected as the final fixed-function area layout.

[0041] In some embodiments, the layout optimization of fixed functional areas can be achieved in a variety of ways: Optionally, a parametric design method can be used to define key parameters of the fixed functional area, such as room size, equipment location, etc., set the parameter variation range and constraints, such as minimum spacing requirements, and use parametric design software to automatically generate multiple layout schemes that meet the conditions. For each scheme, the space utilization rate, assembly rate, and traffic efficiency are calculated, and a weighted comprehensive performance index is calculated. The scheme with the highest comprehensive performance index is selected as the final layout. Optionally, a spatial syntax analysis method can be used to abstract the fixed functional area into a topological graph, with nodes representing functional units and edges representing connection relationships. Spatial syntax indicators such as integration and connectivity are calculated for each node. Based on these indicators, multiple layout schemes are generated, and the space utilization rate, assembly rate, and traffic efficiency of each scheme are calculated. Based on the spatial syntax indicators and performance indicators, a comprehensive score is calculated for each scheme, and the scheme with the highest score is selected as the final layout of the fixed functional area. It is understandable that other methods can also be used, which are not limited here.

[0042] For example, the comprehensive performance index is composed of three sub-indicators: space utilization rate, assembly rate and traffic flow efficiency ratio. Assuming that the weights of these three indicators are w1, w2 and w3 respectively, the calculation formula of the comprehensive performance index is: comprehensive performance index = w1*space utilization rate + w2*assembly rate + w3*traffic flow efficiency ratio, where space utilization rate = effective use area / total area. Effective use area refers to the area that can be actually utilized, excluding the space occupied by walls, pipes, etc. Total area refers to the total area of ​​fixed functional areas. Assembly rate = prefabricated component volume / total building volume. Prefabricated component volume refers to the sum of the volumes of prefabricated modules used (such as integrated bathroom, integrated kitchen, etc.). The total building volume refers to the total volume of fixed functional areas. Traffic flow efficiency ratio = ideal traffic flow length / actual traffic flow length. The ideal traffic flow length is the sum of the straight-line distances between each functional area. The actual traffic flow length is the sum of the actual walking distances between each functional area after considering the actual layout.

[0043] S103 . Generate a plurality of variable function pre-selected positions within the variable function area based on user demand parameters, spatial variability rules, and the position distribution of the fixed function area.

[0044] Variable-function areas represent spaces within a residence that can be flexibly adapted based on demand. User demand parameters are specific indicators that reflect user habits, preferences, and needs. Spatial variability rules represent the constraints and possibilities for spatial change. The fixed-function area location distribution refers to the fixed-function layout determined in the previous step. Variable-function preselected locations represent possible layout options within the variable-function area.

[0045] Specifically, after completing the layout of fixed-function areas, the design of variable-function areas is required. The system analyzes user-provided demand parameters, such as family structure and lifestyle, to understand the user's specific needs for variable space. The system considers predefined spatial variability rules, which define the possibilities and limitations of spatial changes, such as the extent to which walls can be moved and the location of device interfaces. At the same time, the system also needs to consider the established layout of fixed-function areas to ensure that the design of variable-function areas is consistent with the fixed areas. Based on this information, the system generates multiple possible layout plans for variable-function areas, namely, preselected variable-function locations.

[0046] In some embodiments, the generation of variable function pre-selected positions can be achieved in a variety of ways: Optionally, a modular design method can be used to define a series of functional modules according to user demand parameters, such as workspace, rest area, entertainment area, etc., and design variable forms of these modules, such as foldable furniture, sliding partitions, etc. Based on the rules of spatial variability, the combination method and variation possibility between modules are determined, and the location distribution of fixed functional areas is considered. Different module combinations and arrangements are tried in the variable functional areas to generate multiple qualified variable function pre-selected positions; Optionally, a parametric design method can be used to convert user demand parameters, spatial variability rules, and the location distribution of fixed functional areas into quantifiable design parameters, establish a parametric model, define the relationship and constraints between spatial elements, and automatically generate multiple qualified spatial layout plans by adjusting the parameter values. The generated plans are screened and optimized to ensure that each plan meets the basic requirements, and multiple optimized variable function pre-selected positions are output. It is understandable that other methods can also be used to achieve the generation of variable function pre-selected positions, such as using a topology optimization algorithm for spatial layout optimization or using a rule-based expert system for layout generation, which are not limited here.

[0047] S104. Using a computational simulation tool, based on the initial three-dimensional residential model, perform spatial variability simulation on each variable functional position to obtain a spatial variability parameter value corresponding to each variable functional position. The spatial variability parameter value is obtained by weighted calculation of spatial conversion efficiency and functional fitness.

[0048] Computational simulation tools refer to software systems used for digital simulation and analysis. Spatial variability simulation involves digitally simulating spatial change processes. Spatial variability parameters are used to quantitatively assess spatial variability. Spatial conversion efficiency refers to the ease with which a space can be converted from one function to another. Functional adaptability indicates the suitability of a space for a specific function.

[0049] Specifically, after generating multiple variable function pre-selected locations, these options need to be evaluated and compared. The system will import the initial residential three-dimensional model into the computational simulation tool and perform spatial variability simulation on each variable function pre-selected location. This process simulates the changes in space under different functional requirements, including furniture movement, partition adjustment, etc. Through simulation, the system can evaluate the spatial conversion efficiency of each pre-selected location, that is, the difficulty and time required to convert from one functional layout to another. At the same time, the system will also evaluate the functional adaptability of each functional layout, that is, the degree to which the space supports specific functions. The system will perform a weighted calculation of the spatial conversion efficiency and functional adaptability to obtain the spatial variability parameter value of each pre-selected location.

[0050] In some embodiments, spatial variability simulation and parameter calculation can be achieved through various methods: Alternatively, dynamic simulation software can be used for simulation. A 3D model of each preselected variable function location is imported into the software. Different functional scenarios, such as work mode and rest mode, are set. The movement and transformation of spatial elements (such as furniture and partitions) between these scenarios are simulated, and the time and steps required for each transformation are recorded. The spatial transformation efficiency, which can be expressed as the inverse of the average transformation time, is calculated. Simultaneously, space utilization and user comfort are evaluated for each functional layout as indicators of functional adaptability. The spatial transformation efficiency and functional adaptability are weighted averaged according to preset weights to obtain the spatial variability parameter value. Alternatively, a discrete event simulation method can be used to decompose the spatial transformation process into a series of discrete events, such as moving furniture and adjusting partitions. Each event is assigned execution time and resource consumption. An event sequence is constructed to simulate different functional transformation processes. The total time and resource consumption of the entire transformation process is calculated to calculate the spatial transformation efficiency. Simultaneously, spatial performance indicators, such as lighting, ventilation, and privacy, are evaluated for each functional layout to calculate functional adaptability. These indicators are then combined to calculate the spatial variability parameter value. It is understandable that other methods can also be used to achieve spatial variability simulation and parameter value calculation, such as using finite element analysis to evaluate the feasibility of spatial structure changes, or using multi-criteria decision-making methods to comprehensively evaluate spatial performance, which are not limited here.

[0051] S105 : Optimize the initial layout of the variable functional area according to the spatial variability parameter value to obtain a position distribution of the variable functional area.

[0052] The spatial variability parameter value represents a quantitative assessment of the spatial variability. A variable-function area refers to a residential space that can be flexibly adjusted based on demand. The initial layout refers to the initial design of the variable-function area's spatial layout. Optimization refers to improving the design's performance through adjustments and refinements. The variable-function area location distribution represents the optimized variable-function area spatial layout.

[0053] Specifically, after completing the spatial variability simulation and obtaining the spatial variability parameter values ​​for each pre-selected location, the initial layout of the variable functional area needs to be optimized. The system will sort the spatial variability parameter values ​​of all pre-selected locations and identify the best performing solutions. The system will analyze the common characteristics of these high-performance solutions, such as space division methods, furniture layout principles, etc. Based on these analysis results, the system will adjust and improve the initial layout. This process includes adjusting the position of partitions, rearranging the furniture layout, optimizing the location of equipment interfaces, etc. During the adjustment process, the system will continuously evaluate the spatial variability parameter values ​​of the new solution to ensure that each adjustment can improve the overall performance. When the optimization reaches the preset goal or cannot continue to improve significantly, the system will output the final variable functional area location distribution plan. This optimized solution not only retains the basic framework of the initial layout, but also significantly improves the variability performance of the space.

[0054] In some embodiments, the optimization of the layout of the variable functional area can be achieved in a variety of ways: optionally, an iterative optimization method can be used, starting from the initial layout, gradually making small adjustments, evaluating the scheme after each adjustment, calculating its spatial variability parameter value, retaining the scheme with better performance, and continuing to the next round of adjustment. This process is repeated many times, and the layout scheme is continuously improved. When the preset number of iterations or performance requirements are reached, the best scheme is selected as the final variable functional area position distribution; optionally, a template matching and adjustment method can be used to establish a high-performance layout template library containing a variety of excellent variable functional area layout schemes, select the template most similar to the initial layout from the template library, compare the selected template with the initial layout, find out the part that needs to be adjusted, adjust the layout accordingly according to the actual situation, make it closer to the high-performance template, evaluate the adjusted scheme, and adopt it if the performance improvement is obvious, otherwise try other templates or adjustment methods. It is understandable that other methods can also be used for implementation, which are not limited here.

[0055] S106: placing a preset fixed module building into the fixed functional area based on the position distribution of the fixed functional area, and placing a preset movable module into the variable functional area based on the position distribution of the variable functional area, to generate a three-dimensional residential design model.

[0056] The "fixed functional area layout" refers to a space layout with fixed use. A "preset fixed module building" refers to standardized, fixed functional units, such as a kitchen and bathroom. A "variable functional area layout" refers to a space layout with adjustable use. A "preset movable module" refers to a space layout with flexible use, such as movable partitions. A 3D residential design model refers to a digital residential design plan.

[0057] Specifically, this step converts the previously optimized layout into a detailed 3D model. The system then places pre-designed fixed modules, such as kitchen and bathroom units, in the appropriate locations for fixed-function areas. It also places movable modules, such as partitions and adjustable furniture, in the appropriate locations for variable-function areas. The system ensures proper connectivity between modules, including door and window placement and plumbing routing, before generating a complete 3D model that showcases the overall layout and potential spatial variations.

[0058] In some embodiments, the generation of a three-dimensional model can be achieved in a variety of ways: optionally, using a simple module assembly method, preparing a basic three-dimensional model library containing commonly used fixed and movable modules, selecting appropriate modules from the library according to the layout plan, placing these modules in designated locations in the virtual space, adjusting the connections between the modules, ensuring that the overall layout is reasonable, adding basic lighting and materials, and generating a simple but practical three-dimensional model; optionally, using basic parametric design to create a simple residential frame model, setting basic parameters for each spatial unit, such as size and position, setting these parameters according to the layout plan, and the system automatically adjusting the spatial layout according to the parameters to generate a basic three-dimensional model that displays the main spatial structure and functional areas. It is understandable that other methods can also be used to generate three-dimensional models, such as using off-the-shelf architectural design software or using simple computer-aided design tools, which are not limited here.

[0059] In some embodiments, variable-space residential design solutions not only achieve modularity but also meet personalized needs. For example, the system can provide differentiated spatial layouts based on different family types (formation, growth, and maturity), adjust functional settings based on factors such as the number of family members and age, and provide additional options based on standardized modules to meet specific needs. In terms of refined functional space design, dual entryways are supported to enhance privacy, with separate family and guest entrances; bathroom space segmentation is supported to enhance the user experience; embedded design achieves a 5-10% storage space share; and an integrated open kitchen layout is adopted. Furthermore, industrialized production and installation concepts are adopted, using standard designed complete sets of industrial products to ensure quality stability and longevity through industrialized production.

[0060] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the method for generating a variable space residential design scheme in an embodiment of the present application.

[0061] S201. Receive personal information and design requirements input by a user, and build a user portrait based on the personal information and the design requirements. The user portrait includes family structure, living habits, and space preferences.

[0062] Personal information refers to a user's basic information, including age, gender, occupation, and income. Design requirements refer to a user's specific residential requirements, such as the number of rooms, floor space, and preferred style. A user profile is a comprehensive description of a user's characteristics, encompassing family structure (e.g., single, married, or with children), lifestyle habits (e.g., sleep schedule, dietary habits, and leisure activities), and spatial preferences (e.g., open or enclosed spaces, natural light requirements, and storage needs). For example, a young dual-income family may require a flexible workspace, while a family with children may prefer a multifunctional activity area.

[0063] In this step, the system first collects the user's personal information and design requirements through the user interface or questionnaires. Using data analysis algorithms such as cluster analysis or decision trees, the system integrates this information into a complete user profile. This profile includes not only explicit data, such as the number of family members, but also implicit information inferred from the data, such as lifestyle and space usage habits. For example, based on the user's occupation and hobbies, the system can infer the user's needs for workspace and leisure space.

[0064] S202: Generate multiple typical life scenarios based on the user portrait, each of which corresponds to a set of functional elements.

[0065] Typical life scenarios refer to various situations users may encounter in their daily lives, such as work, rest, entertainment, and dining. Functional elements refer to the spatial functions necessary to meet the needs of specific scenarios, such as office areas, rest areas, and dining rooms. For example, for a user who frequently works from home, "working from home" is a typical scenario, and the corresponding functional elements include a workstation, storage space, and lighting.

[0066] In this step, the system first uses scenario generation algorithms based on the information in the user profile to create multiple life scenarios. These algorithms employ rule-based systems or machine learning models to infer possible daily activities based on information such as the user's occupation, hobbies, and family structure. For example, for a family with children, scenarios such as "Family Dinner," "Children Playing," and "Study Tutoring" might be generated. The system then assigns corresponding functional elements to each scenario. This process can be implemented using a predefined scenario-function mapping table or dynamically generated using more complex association rule mining algorithms. Ultimately, the system generates a list of scenarios, each with a corresponding set of functional elements.

[0067] S203: Analyze the space requirements for each group of functional elements to determine the minimum space size and shape requirements required to realize each functional element.

[0068] Space requirements analysis involves quantitatively and qualitatively assessing the space required for each functional element. Minimum space dimensions refer to the minimum area and height required to achieve a given function. Form requirements refer to the geometric characteristics of the space, such as aspect ratio, openness, and connectivity. For example, for a workspace, the minimum space dimensions are 2 square meters, and form requirements include window access and a square layout.

[0069] In this step, the system first creates a space requirement model for each functional element. This model contains the basic space requirements of the functional element, such as minimum area, minimum height, ideal shape, etc. This information can come from architectural design standards, ergonomic data or historical design cases. The system uses spatial analysis algorithms, such as space syntax or space syntax analysis, to evaluate the space requirements of each functional element. These algorithms take into account factors such as the relationship between functions, user activity patterns and accessibility of the space. For example, for an open kitchen, the system must consider not only the minimum space required for cooking, but also the relationship with the adjacent dining area.

[0070] S204 , designing a plurality of space modules according to the minimum space size and the form requirement, wherein the space modules include fixed function modules and variable function modules.

[0071] In this step, the system first reads the minimum spatial dimensions and form requirements for each functional element determined in the previous step. The system then uses parametric design algorithms to generate spatial modules that meet these requirements. These algorithms adjust predefined module templates to meet specific spatial requirements. For example, for a workspace module, the length and width of the module are adjusted based on the minimum area requirements, while also considering form requirements such as window proximity. The spatial modules generated by the system are divided into two categories: fixed-function modules and variable-function modules. Fixed-function modules are used for areas with relatively fixed locations and functions, such as kitchens and bathrooms. The design of these modules takes into account factors such as plumbing layout and equipment installation. Variable-function modules are used for areas that require flexibility, such as living rooms and bedrooms. The design of these modules may include elements such as movable partitions and multifunctional furniture to achieve spatial variability. The system generates multiple different module design options for each functional element, providing more combination possibilities.

[0072] S205. Based on a preset space combination rule library, a plurality of the space modules are combined to obtain a module space combination scheme. The preset space combination rule library includes module connection rules, module orientation rules, proximity rules and module variability rules.

[0073] In this step, the system first loads a preset library of spatial combination rules. This library contains four main rule types: module connection rules, module orientation rules, proximity rules, and module variability rules. Module connection rules define how different modules are physically connected, such as which modules can be directly adjacent and which require transition spaces. Module orientation rules specify the ideal orientation of specific modules, such as bedrooms should avoid western exposure. Proximity rules define the ideal distances and relationships between different functional modules, such as the kitchen should be close to the dining room. Module variability rules define the method and scope of how and to what extent functional modules can be changed. The system uses these rules as constraints to combine spatial modules using a combinatorial optimization algorithm (such as a genetic algorithm or simulated annealing). The algorithm's objective functions include maximizing space utilization and minimizing traffic flow distances. During the combination process, the system continuously checks whether the generated solution meets all rules. If not, it will be adjusted or regenerated. Furthermore, the system considers user preferences and design requirements and adjusts the weighting of certain rules. For example, if a user places particular emphasis on privacy, the system will increase the weighting of separating bedrooms from public areas. Ultimately, the system will generate multiple module space combination solutions that comply with the rules and select the optimal solution based on the comprehensive score.

[0074] S206: Divide the fixed function modules in the module space combination scheme into fixed function areas, divide the variable function modules into variable function areas, and generate an initial residential three-dimensional model based on the fixed function areas and the variable function areas.

[0075] In this step, the system first divides the optimal modular space combination generated in the previous step into zones. The system labels fixed-function modules (such as kitchens and bathrooms) in the plan as fixed-function zones, while variable-function modules (such as living rooms and bedrooms) are labeled as variable-function zones. The system then uses a 3D modeling algorithm to convert these zones into an initial 3D model of the residence. This process involves several steps. First, the system generates corresponding geometry in 3D space based on the dimensions and position of each module. Basic architectural elements such as walls, floors, and ceilings are added to ensure the structural integrity of the model. For fixed-function zones, the system directly places pre-defined fixed fixtures such as kitchen equipment and sanitary ware. For variable-function zones, the system reserves variable space and adds placeholders for movable partitions or multi-functional furniture. The system also considers building codes, such as minimum widths for stairways and hallways, to ensure the model meets basic architectural requirements. The system then performs a preliminary rendering of the model, adding material and lighting information for a more intuitive presentation of the design.

[0076] S207: Obtain an initial three-dimensional residential model of the target design residential building, wherein the initial three-dimensional residential model includes fixed function areas and variable function areas.

[0077] It is understandable that this step is similar to step S101 and will not be described again here.

[0078] S208: Identify key functional points and equipment locations within the fixed functional area.

[0079] In this step, the system first reads the 3D model data of a fixed functional area, including the geometric dimensions and shape of the space. The system then selects appropriate function point identification rules based on predefined function types (such as kitchen, bathroom, etc.). For example, for a kitchen area, the system identifies suitable locations for the sink, stove, and refrigerator; for a bathroom, it identifies potential locations for the toilet, shower area, and sink. The system identifies these key function points by analyzing the geometric characteristics of the space, such as wall continuity, corner locations, and the positions of windows and doors. The system also considers plumbing layouts, such as the location of water pipes and drains, to determine the likely locations of water-consuming appliances. The system also examines the distribution of electrical outlets to identify potential placement points for electrical appliances. Ultimately, the system generates a coordinate list containing each identified key function point and device location. Each point in this list has specific functional attributes and spatial coordinates.

[0080] S208. Convert the minimum spacing requirement in the preset building code into a constraint condition between devices, set the structural requirement as a fixed boundary, and determine the movable range of the key functional point and the device position.

[0081] In this step, the system first extracts specific minimum spacing requirements from the building code database. For example, the minimum distance between the stovetop and sink in the kitchen is set at 600mm, and the minimum distance between the center of the toilet and the side wall is 450mm. The system converts these specific numerical requirements into mathematical relationships in a spatial coordinate system. For example, if the coordinates of the sink are (x1, y1) and the coordinates of the stovetop are (x2, y2), then the system generates the following constraint: √((x2-x1)^2+(y2-y1)^2)≥600. Simultaneously, the system identifies fixed structural elements in the 3D model, such as walls, doors, and windows, and uses their coordinates as fixed boundaries for the layout. For example, if the coordinate range of a wall is x∈[0, 3000] and y∈[0, 4000], then the x and y coordinates of all devices must fall within this range. Based on these specific constraints and boundary restrictions, the system calculates the movable range of each functional point and device. This range is represented as a series of coordinate intervals, for example, the movable range of the sink is x∈[500, 2500], y∈[1000, 3000].

[0082] S209 : Generate a plurality of fixed function pre-selected positions based on the constraint condition, the fixed boundary, and the movable range.

[0083] In this step, a 100mm x 100mm grid is first established. The system samples locations within the movable range of each device, using this grid as the unit. For each sampled point, the system checks whether it satisfies all constraints. For example, for a possible location of a water tank (1500, 2000), the system checks whether it is within the movable range, meets the minimum spacing requirements for other devices, and does not conflict with fixed structures. The system then calculates a score for each location combination that meets these requirements. This score takes into account factors such as the actual distance between devices (the closer to the minimum requirement, the better), the distance from fixed structures (to ensure adequate operating space), and the uniformity of device distribution. The score is calculated using a weighted summation method, for example: Score = w1 * (actual distance / minimum required distance) + w2 * (distance from fixed structures / ideal distance) + w3 * (distribution uniformity index), where w1, w2, and w3 are the weights of the different factors. The system ultimately selects the combinations with the highest scores as preselected solutions, each of which contains the specific coordinates of all devices and function points.

[0084] S210 , calculating the space utilization rate and assembly rate of each fixed function pre-selected position, where the space utilization rate is the ratio of the effective use area to the total area, and the assembly rate is the proportion of standardized modules used.

[0085] In this step, the system first calculates the space utilization rate for each fixed-function preselected location. The system accurately measures the effective usable area in each preselected location plan, which includes the area occupied by all functional areas and equipment, as well as the necessary operating space. For example, in a kitchen layout, the effective usable area includes the area of ​​appliances such as the stove, sink, and refrigerator, as well as the work area around them. The system also calculates the total area, which is the area of ​​the entire fixed-function area. The space utilization rate is calculated by dividing the effective usable area by the total area, and the result is expressed as a percentage. For example, if the effective usable area is 8 square meters and the total area is 10 square meters, the space utilization rate is 80%.

[0086] To calculate the modularity ratio, the system identifies the number of standardized modules used in each preselected location. Standardized modules include prefabricated cabinet units, standard-sized bathroom fixtures, and so on. The system divides the number of standardized modules used by the total number of modules to calculate the modularity ratio. For example, if a kitchen plan has 10 modules, 8 of which are standardized, the modularity ratio is 80%.

[0087] S211. Based on the preset key movement path, measure the actual length of the preset key movement path in each of the fixed function preselected positions, compare the actual length of the preset key movement path with the preset ideal length, and obtain the movement efficiency ratio corresponding to each of the fixed function preselected positions.

[0088] In this step, the system first reads the pre-defined key movement paths. These paths are typically pre-defined based on ergonomics and frequency of use, such as the "work triangle" in a kitchen (refrigerator-sink-stove) or the "washing path" in a bathroom (door-toilet-sink). For each pre-selected fixed functional location, the system simulates these key movement paths in three-dimensional space and calculates their actual lengths. For example, in a kitchen layout, the system calculates the actual walking distance from the refrigerator to the sink and then to the stove.

[0089] When calculating the actual length, the system takes into account obstacles and necessary detours. For example, if there's an island between the refrigerator and sink, the system will calculate the actual path around the island, rather than simply the straight-line distance. The system also considers the direction of door openings to ensure movement isn't obstructed by open doors.

[0090] The system compares the calculated actual length with a preset ideal length. This ideal length is typically an optimal value based on ergonomic research and efficiency analysis. The flow efficiency ratio is calculated as: efficiency ratio = ideal length / actual length. For example, if the ideal length of the kitchen "work triangle" is 4 meters, and the actual length of a pre-selected location is 5 meters, the flow efficiency ratio for this pre-selected location is 0.8, or 80%.

[0091] The system will calculate the efficiency ratio of all preset key traffic lines for each pre-selected location and calculate a weighted average as the overall traffic line efficiency index of the pre-selected location.

[0092] S212 , allocating weight coefficients to the space utilization rate, the assembly rate, and the moving line efficiency, and calculating a comprehensive performance index based on the weight coefficients, the space utilization rate, the assembly rate, and the moving line efficiency.

[0093] In this step, the system first assigns weights to space utilization, assembly ratio, and movement efficiency. These weights reflect the relative importance of each factor in the overall evaluation. Weights are assigned based on the specific project requirements, design philosophy, or user preferences. For example, in projects emphasizing space efficiency, space utilization is given a higher weight, such as 0.5; whereas in projects prioritizing construction efficiency, assembly ratio is given a higher weight, such as 0.4. The weighting of movement efficiency varies across different space types, for example, being higher in kitchen designs and lower in living rooms. Suppose the weights are: space utilization weight w1 = 0.4, assembly ratio weight w2 = 0.3, and movement efficiency weight w3 = 0.3. The system then uses these weights and the various indicators calculated in the previous step to calculate a comprehensive performance index for each fixed-function preselected location. The calculation formula is: Comprehensive performance index = w1 * space utilization + w2 * assembly ratio + w3 * movement efficiency ratio. For example, for a specific preselected location, if the space utilization rate is 85%, the assembly rate is 70%, and the movement efficiency ratio is 90%, then its comprehensive performance index will be: 0.4*85+0.3*70+0.3*90=82. The system calculates this comprehensive performance index for each preselected location and ranks all preselected locations based on this index.

[0094] S213. The fixed function pre-selected position with the highest comprehensive performance index is used as the fixed function area position distribution.

[0095] In this critical step, the system first ranks the comprehensive performance indicators of all previously calculated fixed-function preselected locations. This ranking process is based on the comprehensive performance indicators calculated in the previous step, which already take into account multiple key factors such as space utilization, assembly rate, and traffic flow efficiency. After the ranking is complete, the system selects the preselected location with the highest comprehensive performance indicator as the final fixed-function area location distribution plan. This selection process goes beyond simply selecting the highest score; the system also performs a series of verifications and checks to confirm that the highest-scoring solution meets all design constraints and specifications. For example, it checks whether the spacing between all equipment and functional points meets minimum spacing requirements and whether any equipment or functional points conflict with fixed structures such as walls and columns. Next, the system generates a detailed 3D model of this optimal solution, including the precise location and dimensions of all equipment and functional points within the fixed-function area. This 3D model not only includes the floor plan layout but also takes into account height information to ensure that there are no vertical conflicts. For example, in a kitchen design, the system ensures that there is sufficient operating space between upper and lower cabinets and that the height of wall cabinets is suitable for most users. In addition, the system will generate a visual representation of this optimal solution, including floor plans, elevations and 3D renderings.

[0096] The following is a more detailed description of the process of the method provided by this implementation. Figure 3 , is another flow chart of the method for generating a variable space residential design scheme in an embodiment of the present application.

[0097] S301. Import the initial residential three-dimensional model into the computational simulation tool. For each variable functional position, simulate the spatial change process of the variable functional position under different life scenarios to obtain the operation time and operation complexity required for converting one function to another. Each life scenario corresponds to each functional layout of all the variable functional positions.

[0098] The system first imports the initial 3D model of the residence into a specialized computational simulation tool. This tool simulates the movement, deformation, and interaction of objects in space. For each preselected variable-function location generated in S301, the system simulates its spatial transformation under different living scenarios. These scenarios include daily living, work, leisure, entertainment, sleeping, and dining. During the simulation, the system considers the specific movement paths, rotation angles, and folding processes of furniture and equipment. For example, for a space that can be converted from a living room to a bedroom, the system simulates how the sofa unfolds into a bed, how the coffee table folds and stores, and how the curtains close. During the simulation, the system records the time required for each transformation step, calculated based on preset standard operation times and the dimensions of the space. The system also assesses the complexity of each transformation step, taking into account factors such as the number of items to be moved, the distance to be moved, and whether special tools are required. For example, simply pulling out a folding bed is assigned a lower complexity rating, while large furniture moves requiring the collaboration of multiple people are assigned a higher complexity rating. The system creates a transition matrix for each variable functional position, recording all transition paths from one function to another and their corresponding operation time and complexity.

[0099] S302: Calculate the space conversion efficiency according to the operation time and the operation complexity.

[0100] In this step, the system calculates the spatial conversion efficiency of each variable functional location based on the operation time and complexity data obtained in the previous step. The calculation process uses a comprehensive scoring formula that takes into account multiple factors. The system assigns a base score to each functional conversion, which reflects its importance and frequency in daily life. For example, the conversion from living room to bedroom receives a higher base score because it is a common and important transition. The system adjusts this base score based on operation time. The shorter the operation time, the higher the score. A nonlinear calculation method, such as an exponential decay function, is used to better reflect the impact of time on efficiency. The system further adjusts based on operation complexity. The lower the complexity, the higher the score. The impact of complexity is reflected by a weighting coefficient, with different types of complexity (such as required manpower and tools) having different weights. The system also considers the reliability and stability of the conversion. For example, a conversion mechanism that requires precise adjustment will have a lower score due to the potential risk of failure. Furthermore, the system evaluates the functional integrity of the converted space to ensure that the converted space fully meets its intended function. The system then calculates a comprehensive spatial conversion efficiency score. This score not only reflects the efficiency of a single conversion, but also takes into account the cumulative effect of multiple different conversions within a day or week.

[0101] S303. Based on the spatial change process, the functional fitness of each variable functional position under each functional layout is evaluated. The functional fitness is calculated by space utilization and user efficiency. The space utilization is obtained by evaluating the spatial changes in the simulation, and the user efficiency is obtained by evaluating the time it takes for users to complete specific tasks in the simulation.

[0102] In this step, the system evaluates the functional suitability of each functional layout for each variable functional location. Functional suitability is a metric that measures how well a spatial layout supports a specific function. It consists of two sub-indicators: space utilization and user efficiency. The system analyzes spatial change simulation data to assess space utilization. It calculates the ratio of actual used space to total available space, taking into account three-dimensional space utilization. For example, in a living room-to-office layout, the system assesses whether the placement of office equipment and furniture effectively utilizes available space, including walls, corners, and vertical space. Space utilization is calculated using the following formula: Space utilization = functionally usable area / total available area. Next, the system evaluates user efficiency. It sets standard tasks related to specific functions, such as completing a daily workflow in an office layout. The system uses avatar models to simulate users' movements and actions within the space and calculates the time required to complete these tasks. User efficiency is calculated using the following formula: User efficiency = standard task completion time / actual task completion time. The system combines space utilization and user efficiency to produce a functional suitability score. The calculation formula is: Functional Fitness = w1 * Space Utilization + w2 * User Efficiency, where w1 and w2 are weight coefficients reflecting the relative importance of the two sub-indicators. The system generates a Functional Fitness report for each functional layout at each variable functional location, including an overall score, sub-indicator scores, and specific evaluation data.

[0103] S304: Obtain a variability parameter value by weighted calculation based on the spatial conversion efficiency and the functional fitness.

[0104] In this step, the system combines the previously calculated spatial conversion efficiency and functional adaptability, using a weighted calculation to produce a comprehensive variability parameter. This parameter is a key indicator for measuring the overall performance of a variable functional location. The calculation process first determines the weights for spatial conversion efficiency and functional adaptability. These weights reflect the priority of design objectives and are adjusted based on different user needs or project requirements. For example, spatial conversion efficiency is given a higher weight for users who frequently need to change the use of space, while functional adaptability is given a higher weight for users who prioritize the functional quality of the space. The system uses a flexible weighting mechanism, allowing the relative importance of the two indicators to be adjusted between 0 and 1. The system evaluates all functional layouts for each variable functional location. For each layout, the system calculates its weighted average score, which combines the layout's spatial conversion efficiency (taking into account all possible conversion options) and its functional adaptability. The system then averages these scores to produce the overall variability parameter for the variable functional location.

[0105] It is understandable that steps S301 to S304 may be executed after step S101 or after step S207, which is not limited here.

[0106] S305. Establish a spatial layout optimization model based on the spatial variability parameter values ​​of each variable functional position.

[0107] The system uses the previously calculated spatial variability parameters for each variable program location to construct a comprehensive spatial layout optimization model. The goal of this model is to find the optimal variable program layout for the entire residential space. The system defines an optimization objective function, which is a weighted sum of the variability parameter values ​​for each variable program location, with weights based on each location's area or importance within the overall space. The optimization model also considers a series of constraints, including building structural limitations (such as load-bearing walls and plumbing locations), regulatory requirements (such as minimum aisle widths and emergency evacuation routes), and user-specific needs (such as the need for certain functions to be adjacent or separated). The system employs optimization techniques such as mixed-integer linear programming (MILP) or genetic algorithms to solve this complex optimization problem. During the modeling process, the system treats each variable program location as a decision variable, whose possible values ​​include different program configurations and location options. The model's goal is to find the optimal combination of these variables that maximizes the overall variability parameter value while satisfying all constraints. During the optimization process, the system considers the interactions between different variable program locations; for example, the program choice at one location affects the options available at adjacent locations. The system will also evaluate the performance of different layout options in terms of overall spatial flow, natural lighting, ventilation, etc. These factors will be included in the optimization model as additional evaluation indicators.

[0108] S306: Setting an optimization objective function based on the spatial layout optimization model. The optimization objective function includes preset constraints, which include a minimum area requirement for the variable functional position and a minimum spacing requirement between functional areas.

[0109] In this step, the system sets a comprehensive optimization objective function based on the previously established spatial layout optimization model. The core of this objective function is to maximize the overall spatial variability parameter while satisfying a series of pre-set constraints. The objective function takes the following form: MaxZ = Σ(wi * Vi), where Vi represents the variability parameter of the i-th variable functional location, and wi is the corresponding weight coefficient, reflecting the importance of that location in the overall layout. The weight is determined based on the location's size or frequency of use. The objective function also incorporates key pre-set constraints. The first is a minimum area requirement. For example, a bedroom requires at least 10 square meters, while a living room requires at least 15 square meters. These constraints can be expressed as: Ai ≥ Amin,i, where Ai is the actual area of ​​the i-th functional area and Amin,i is the minimum area requirement for that area. The second is the minimum spacing requirement between functional areas. For example, a distance of at least 1.5 meters must be maintained between the kitchen and the living room to ensure adequate space for movement. This type of constraint can be expressed as: Dij ≥ Dmin,ij, where Dij is the distance between the i-th and j-th functional areas, and Dmin,ij is the required minimum distance between them. In addition, the system considers other constraints, such as building structural limitations (e.g., the location of load-bearing walls) and equipment layout requirements (e.g., the location of piping and electrical wiring).

[0110] S307: Use the optimization algorithm to iteratively optimize the layout of the variable functional area to obtain a new layout solution.

[0111] In this step, the system applies advanced optimization algorithms to iteratively optimize the layout of the variable functional areas to obtain new, more optimal layout solutions. Given the complexity and nonlinear nature of the problem, the system employs heuristic algorithms such as genetic algorithms (GAs) or particle swarm optimization (PSOs). Taking the GA as an example, the system first generates a set of initial layout solutions. Each solution is encoded as a "chromosome," which contains the location, size, and function of each variable functional location. The algorithm then refines these solutions through multiple iterations. In each iteration, the algorithm performs the following operations: selection (selecting the best-performing solution), crossover (combining features from different solutions), and mutation (randomly changing certain features to increase diversity). Each newly generated solution is evaluated for fitness, calculating its variability parameter by optimizing the objective function. During this process, the system strictly adheres to the constraints set in S307 to ensure that all generated solutions are feasible. For example, if a newly generated solution violates the minimum area requirement, the system will adjust it or eliminate it. The iterative process continues until a pre-defined termination condition is reached, such as reaching the maximum number of iterations or failing to achieve significant improvement after multiple iterations. In order to improve optimization efficiency, the system uses parallel computing technology to evaluate multiple solutions simultaneously.

[0112] S308: Perform spatial variability simulation on each of the new layout solutions, and calculate the variability parameter value of each of the new layout solutions.

[0113] In this step, the system performs a detailed spatial variability simulation on each new layout solution generated in S308 to calculate its specific variability parameter value. This process verifies and refines the previous optimization results. For each new layout solution, the system first constructs a detailed 3D model, including the precise geometric information and functional attributes of all variable functional locations. The system then simulates the layout's usage in different life scenarios. For example, the system simulates the transition from daytime work mode to nighttime rest mode, or from daily life mode to family gathering mode. In each transition scenario, the system calculates spatial conversion efficiency, including the time required, operational complexity, and potential interference factors during the transition. The system also evaluates space utilization and user efficiency under each functional mode. Space utilization calculations take into account the ratio of the actual usable area of ​​the functional area to the total available area, as well as the utilization of vertical space. User efficiency uses a virtual character model to simulate the time and difficulty required for users to complete specific tasks in the space. The system integrates these factors and uses a predefined formula to calculate the overall variability parameter value for each layout solution. This parameter reflects the layout solution's overall performance in terms of flexibility, efficiency, and practicality. To ensure the accuracy and comprehensiveness of the evaluation, the system conducts multiple simulations, taking into account different usage scenarios and user behavior patterns. Furthermore, the system performs sensitivity analysis to assess the impact of different factors on the variability parameter values. For each new layout proposal, the system generates a detailed evaluation report, including the overall variability parameter value, scores for each sub-indicator, and specific simulation data and analysis results.

[0114] S309: Using the layout solution with the variability parameter value greater than the preset parameter threshold as the variable functional area position distribution.

[0115] The variability parameter value is a quantitative indicator derived from evaluating the spatial variability capabilities of each candidate layout scheme generated for a variable functional area. This indicator is calculated through digital simulation of different layout schemes, recording the flexibility of spatial transformations, the ease of conversion, and the efficiency of use under various functional layouts. The preset parameter threshold is the minimum acceptable level of spatial variability for a variable functional area and is pre-set by the designer based on actual needs during system initialization. Retaining layout schemes with variability parameter values ​​above this threshold ensures that the resulting positional distribution of the variable functional area meets the basic requirements for flexible transformation. This operation is equivalent to a screening process, eliminating layout schemes with weaker variability capabilities and retaining only layout schemes with variability capabilities that exceed the standard as the final spatial positional distribution of the variable functional area.

[0116] It is understandable that steps S305 to S309 may be executed after step S104 or after step S304, which is not limited here.

[0117] S310: placing a preset fixed module building into the fixed functional area based on the position distribution of the fixed functional area, and placing a preset movable module into the variable functional area based on the position distribution of the variable functional area, to generate a three-dimensional residential design model.

[0118] After obtaining the location distribution of fixed-function areas and variable-function areas, a 3D scene is constructed using standardized functional building modules based on the spatial layout requirements of these two areas. The location distribution of fixed-function areas defines the final layout plan for the area, reflecting the specific arrangement of non-variable spaces. Pre-set fixed-module buildings refer to standardized building components that support fixed functions, such as bathroom and kitchen units. The location distribution of variable-function areas defines the final layout plan for the area, reflecting the specific arrangement of adjustable spaces. Pre-set movable modules refer to flexible building components that support variable functions, such as foldable furniture and movable partitions. This step involves mapping the optimized final layout of the functional areas with the corresponding standardized building modules, performing 3D modeling based on the spatial layout requirements, and ultimately generating a complete 3D residential scene. This process ensures the logical connectivity and rationality of the functional modules, such as the connection of details such as door and window locations and pipeline layouts. The resulting 3D scene intuitively reflects the functional division and layout design of the space.

[0119] S311: Send the residential design three-dimensional model to a preset client for display.

[0120] The preset client refers to the target device or platform designated to receive the generated design results after the 3D model design is completed. The client needs to have the ability to parse and display 3D model files. The purpose of sending the 3D model is to allow designers or users to browse the interactive 3D scene on the client and intuitively inspect and evaluate the design effect. Specifically, the generated 3D model file can be sent to the client in a standardized format (such as FBX), and the client can then load and present the model through the included 3D browser software.

[0121] The following describes the generation system of the variable space residential design scheme in the embodiment of the present invention from the perspective of hardware processing. Figure 4 , which is a schematic diagram of a physical device structure of a system for generating a variable space residential design scheme in an embodiment of the present application.

[0122] It should be noted that Figure 4The structure of the system for generating a variable-space residential design solution shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0123] like Figure 4 As shown, the system for generating a variable-space residential design includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes, such as the methods described in the above embodiments, based on programs stored in a read-only memory (ROM) 402 or programs loaded from a storage unit 408 into a random access memory (RAM) 403. RAM 403 also stores various programs and data required for system operation. CPU 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output (I / O) interface 405 is also connected to bus 404.

[0124] The following components are connected to the I / O interface 405: an input section 306 including an audio input device, push button switches, and the like; an output section 407 including a liquid crystal display (LCD), an audio output device, indicator lights, and the like; a storage section 408 including a hard disk and the like; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. Removable media 411, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 410 as needed, so that computer programs read from the removable media can be installed in the storage section 408 as needed.

[0125] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for executing the methods illustrated in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 409 and / or installed from removable media 411. When executed by central processing unit (CPU) 401, the computer program performs the various functions defined in the present invention.

[0126] It should be noted that specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0127] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings.

[0128] Specifically, the system for generating a variable space residential design scheme in this embodiment includes a processor and a memory, and the memory stores a computer program. When the computer program is executed by the processor, the method for generating a variable space residential design scheme provided in the above embodiment is implemented.

[0129] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the variable-space residential design scheme generation system described in the above embodiments, or may exist independently and not be incorporated into the variable-space residential design scheme generation system. The storage medium carries one or more computer programs, and when the one or more computer programs are executed by a processor of the variable-space residential design scheme generation system, the variable-space residential design scheme generation system implements the variable-space residential design scheme generation method provided in the above embodiments.

[0130] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0131] As used in the above embodiments, the term “when” may be interpreted to mean “if” or “after” or “in response to determining that” or “in response to detecting that”, depending on the context. Similarly, the phrases “upon determining that” or “if (stated condition or event) is detected” may be interpreted to mean “if determining that” or “in response to determining that” or “upon detecting (stated condition or event)” or “in response to detecting (stated condition or event)”, depending on the context.

[0132] Those skilled in the art will appreciate that all or part of the process steps in the above-described method embodiments can be implemented by a computer program instructing the relevant hardware. The program can be stored in a computer-readable storage medium, and when executed, the program can include the process steps in the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for generating a variable space residential design scheme, characterized in that: A system for generating a design scheme for a variable-space residential building, the method comprising: Obtaining an initial three-dimensional residential model of a target design residence, wherein the initial three-dimensional residential model includes fixed function areas and variable function areas; Within the fixed-function area, based on preset building specifications and structural requirements, multiple fixed-function pre-selected locations are generated, a comprehensive performance index corresponding to each fixed-function pre-selected location is calculated, and the fixed-function pre-selected location with the highest comprehensive performance index is used as the fixed-function area location distribution, where the comprehensive performance index is obtained by weighted calculation of space utilization rate, assembly rate, and movement line efficiency ratio; In the variable function area, a plurality of variable function preselected positions are generated based on user demand parameters, spatial variability rules and the position distribution of the fixed function areas; Using a computational simulation tool, based on the initial three-dimensional residential model, a spatial variability simulation is performed on each variable functional position to obtain a spatial variability parameter value corresponding to each variable functional position, wherein the spatial variability parameter value is obtained by weighted calculation of spatial conversion efficiency and functional fitness; Optimizing the initial layout of the variable functional areas according to the spatial variability parameter value to obtain a position distribution of the variable functional areas; Based on the position distribution of the fixed functional areas, the preset fixed module buildings are placed in the fixed functional areas, and based on the position distribution of the variable functional areas, the preset movable modules are placed in the variable functional areas to generate a three-dimensional residential design model.

2. The method according to claim 1, characterized in that Before the step of obtaining an initial three-dimensional residential model of the target design residential house, wherein the initial three-dimensional residential model includes fixed functional areas and variable functional areas, the method further includes: Receive personal information and design requirements input by the user, and build a user profile based on the personal information and the design requirements, the user profile including family structure, living habits and space preferences; Generate multiple typical life scenarios based on the user portrait, each of the life scenarios corresponding to a set of functional elements; Conducting a space requirement analysis for each group of functional elements to determine the minimum space size and form requirements required to realize each functional element; Designing a plurality of space modules according to the minimum space size and the form requirements, wherein the space modules include fixed function modules and variable function modules; Based on a preset spatial combination rule library, a plurality of the spatial modules are combined to obtain a module spatial combination scheme, wherein the preset spatial combination rule library includes module connection rules, module orientation rules, proximity rules, and module variability rules; The fixed function modules in the modular space combination scheme are divided into fixed function areas, and the variable function modules are divided into variable function areas, and an initial residential three-dimensional model is generated based on the fixed function areas and the variable function areas.

3. The method according to claim 1 or 2, characterized in that The step of generating a plurality of fixed function preselected locations within the fixed function area based on preset building specifications and structural requirements specifically includes: Within the fixed functional area, identifying key functional points and equipment locations within the fixed functional area; Based on the minimum spacing requirements in the preset building code, the constraints between the equipment are converted and the structural requirements are set as fixed boundaries to determine the movable range of the key functional points and the equipment positions; A plurality of fixed-function preselected positions are generated based on the constraint conditions, the fixed boundary, and the movable range.

4. The method according to claim 1, wherein The step of calculating the comprehensive performance index corresponding to each fixed function pre-selected position, and taking the fixed function pre-selected position with the highest comprehensive performance index as the fixed function area position distribution, wherein the comprehensive performance index is obtained by weighted calculation of the space utilization rate and the assembly rate, specifically includes: Calculating the space utilization rate and assembly rate of each of the fixed function preselected positions, wherein the space utilization rate is the ratio of the effective use area to the total area, and the assembly rate is the proportion of standardized modules used; Based on a preset key moving path, measuring the actual length of the preset key moving path in each of the fixed function preselected positions, comparing the actual length of the preset key moving path with a preset ideal length, and obtaining a moving path efficiency ratio corresponding to each of the fixed function preselected positions; Assigning weight coefficients to the space utilization rate, the assembly rate, and the moving line efficiency, and calculating a comprehensive performance index based on the weight coefficients, the space utilization rate, the assembly rate, and the moving line efficiency; The fixed function preselected position with the highest comprehensive performance index is used as the fixed function area position distribution.

5. The method according to claim 1, wherein The computational simulation tool is used to perform spatial variability simulation on each variable functional position based on the initial residential three-dimensional model to obtain spatial variability parameter values ​​corresponding to each variable functional position, specifically including: Importing the initial residential three-dimensional model into a computational simulation tool, simulating, for each variable functional location, the spatial change process of the variable functional location under different life scenarios, and obtaining the operation time and operation complexity required to switch from one function to another, wherein each life scenario corresponds to each functional layout of all the variable functional locations; Calculating the spatial conversion efficiency according to the operation time and the operation complexity; evaluating the functional fitness of each variable functional position under each functional layout based on the spatial change process, wherein the functional fitness is calculated by space utilization and user efficiency, wherein the space utilization is obtained by evaluating the spatial change in the simulation, and the user efficiency is obtained by evaluating the time it takes for users to complete specific tasks in the simulation; The variability parameter value is obtained by weighted calculation based on the spatial conversion efficiency and the functional fitness.

6. The method according to claim 1, characterized in that The step of optimizing the initial layout of the variable functional area according to the spatial variability parameter value to obtain the position distribution of the variable functional area specifically includes: According to the spatial variability parameter values ​​of each variable functional location, a spatial layout optimization model is established; An optimization objective function is set based on the spatial layout optimization model, wherein the optimization objective function includes preset constraints, and the preset constraints include a minimum area requirement for the variable functional position and a minimum spacing requirement between functional areas; Use optimization algorithms to iteratively optimize the layout of variable functional areas to obtain a new layout solution; Performing spatial variability simulation on each of the new layout schemes, and calculating a variability parameter value of each of the new layout schemes; The layout scheme with the variability parameter value greater than the preset parameter threshold is used as the variable functional area position distribution.

7. The method according to claim 6, characterized in that After the step of placing the preset fixed module buildings into the fixed functional areas based on the position distribution of the fixed functional areas, and placing the preset movable modules into the variable functional areas based on the position distribution of the variable functional areas, and generating the three-dimensional residential design model, the method further includes: The residential design three-dimensional model is sent to a preset client for display.

8. A system for generating a variable space residential design scheme, characterized in that: The system for generating a variable space residential design solution includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the system for generating a variable space residential design solution to execute the method described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on a system for generating a variable-space residential design solution, the system for generating a variable-space residential design solution executes the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a system for generating a variable-space residential design solution, the system for generating a variable-space residential design solution is enabled to execute the method according to any one of claims 1 to 7.

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