AIGC technology-based indigenous building space design generation method

Abstract

The invention discloses an AIGC technology-based indigenous building space design generation method, and relates to the field of indigenous buildings, the method comprises S1 and S2, the S1 comprises data acquisition, data cleaning and processing, feature extraction and selection, design scheme, design suggestion generation, design scheme optimization, cooperative work and feedback, and design output; s2, space design generation preprocessing, target building module generation, target building floor height determination, space scene generation, scheme building windowing position analysis and windowing area determination are included; the AIGC technology is used for conducting intelligent design, effective data are provided for local buildings, the design accuracy and efficiency can be improved, human errors can be reduced, the design quality and sustainability can be improved, and the situation that due to the fact that the building distance is unqualified or the planning layout design is unreasonable, the construction cost is lowered can be avoided. And the problems of disassembly, rework and the like after a project is built are solved.

Description

Technical Field

[0001] The present invention mainly relates to the technical field of vernacular architecture, and specifically to a vernacular architectural space design generative method based on AIGC technology. Background Art

[0003] With the development of my country's economy and the improvement of people's living standards, the intelligentization of rural architecture has become the future development direction of the rural architecture industry. Construction projects are digitalized and intelligentized. However, in the design stage of existing rural architecture, the proposal of the scheme often relies on the design experience of engineers. Once the engineers lack available experience, it is bound to cause defects in the scheme. Therefore, in order to improve the quality of rural architectural space, enhance safety, comfort and other functions, reduce the experience defects in the space design stage, and effectively promote the development of digitalization and intelligence in the field of rural architecture, so as to better meet the future development needs of rural architecture. Summary of the invention

[0004] Based on this, the purpose of the present invention is to provide a generative method for vernacular architectural space design based on AIGC technology to solve the technical problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A vernacular architectural space design generative method based on AIGC technology, comprising S1 and S2, wherein S1 comprises the following steps:

[0007] (1) Data collection: Conduct historical, cultural, and geographical surveys and research on vernacular architecture, and collect relevant spatial design data and documents, including data collection on native rural settlements and vernacular architecture, and data collection on new vernacular architecture of representative and demonstrative projects;

[0008] (2) Data cleaning and processing: Clean and process the collected data, remove useless information and duplicate records, and unify the data format into a machine-readable format;

[0009] (3) Feature extraction and selection: According to the characteristics and design requirements of vernacular architecture, useful features such as building shape, cladding texture, color, material and window position are selected and extracted;

[0010] (4) Design solutions: Use deep learning algorithms to predict the popularity of specific design elements and improve design efficiency and quality;

[0011] (5) Design suggestion generation: Select useful information features and input them into the model to generate corresponding space design suggestions;

[0012] (6) Design optimization: Optimize the generated design to adapt to the surrounding environment and consider practicality and safety factors;

[0013] (7) Collaborative work and feedback: During the design generation process, architects and other relevant personnel collaborate and provide feedback to improve the design plan and adjust the design plan in a timely manner;

[0014] (8) Design output: Output the final vernacular architectural space design drawing plan;

[0015] The S2 comprises the following steps:

[0016] (1) Spatial design generation preprocessing: collecting the building design information scheme of the user in S1, identifying and analyzing the building design information content, and triggering data preprocessing operations according to the analysis results;

[0017] (2) Generation of target building module: Establishing the model of the target building, dividing the monomers of the target building, setting the storey height value of the target building, and taking the storey height value of the target building as a variable condition;

[0018] (3) Determine the storey height of the target building: Determine the storey height and corresponding location conditions of the target building according to the variable conditions, wherein the location conditions include the orientation of the building, the distances in front, behind, left, and right directions, and the relative location information with respect to other buildings;

[0019] (4) Generation of spatial scenes: Generate corresponding spatial scenes based on parametric modeling, assign component parameter shapes and colors, form a spatial distribution matrix based on component position parameters and preset space, match it with component information in the standard component library, place standard components in each spatial distribution matrix grid, and generate corresponding spatial scenes through the automatic modeling tool conversion module of AIGC technology;

[0020] (5) Analysis of window positions in planned buildings: Based on the building outline information and spatial scene information of the building plan, the window size is determined by calculating the building layout, window positions, and indoor lighting range, and the window area is used as a variable condition;

[0021] (6) Determine the window area: According to the window variable conditions, room height, and lighting range, the automatic calculation tool based on AIGC technology is used to determine the window size of the target building.

[0022] Specifically, the calculation formula for the window area in the southern region is as follows:

[0023] The formula for indoor lighting area in the southern region is: Q = A×H×0.4+B×H×0.4, where Q is the indoor lighting area in square meters; A and B are the size parameters of the window openings in centimeters; and H is the height of the room in meters.

[0024] Specifically, the calculation formula for the window area in the northern region is as follows:

[0025] The formula for indoor lighting area in northern China is: Q = K × H × 0.2

[0026] Among them, Q is the indoor lighting area, in square meters; K is the window size parameter, generally taking a value of 0.2 to 0.3 square meters per square meter; H is the height of the room, in meters.

[0027] Specifically, the technical solution also includes the following calculation formula for the occlusion between the storey heights of the target buildings according to the geometric shape, size and relative position of the rural civil engineering in S2:

[0028] dmin=dmax-((b1a1+b2a2+mm / sqrt(a1^2+a2^2))-(c1b2-c2b1+mm / sqrt(a1^2+a2^2)))

[0029] Among them, dmax and dmin represent the maximum and minimum spacing respectively, a1, a2, b1 and b2 represent the side lengths of adjacent buildings respectively, mm represents the height difference between adjacent buildings, c1, c2 and m represent the diagonal lengths from adjacent buildings to the intersecting line segment respectively, and the minimum spacing between any two buildings is calculated.

[0030] Specifically, the southern region is north of 23° north latitude, and the northern region is south of 23° north latitude.

[0031] Specifically, the S1 also includes data integration and association, definition of design rules and constraints, and continuous learning and optimization. The data integration and association are used to integrate and associate data from different sources to form a complete spatial design data set to facilitate subsequent feature extraction and model training; the definition of design rules and constraints is used to define appropriate design rules and constraints based on the protection, regional and cultural characteristics of vernacular architecture to ensure the feasibility and sustainability of the design solution; the continuous learning and optimization is used to continuously obtain feedback and data from actual projects, clean and process them, and revise and improve models and algorithms.

[0032] Specifically, the technical solution described in S2 also includes user feedback and testing, and the user feedback and testing are used to optimize and improve the design generation method through user feedback and testing after each design solution is completed.

[0033] In summary, the present invention mainly has the following beneficial effects:

[0034] This application uses AIGC technology for intelligent design, investigates and studies the local history, culture, and geography of vernacular architecture, collects relevant spatial design data and documents, and selects and extracts useful features, architectural forms, colors, materials, and window positions according to the characteristics and design requirements of vernacular architecture, providing effective data for vernacular architecture, which can not only improve the accuracy and efficiency of design, but also reduce human errors and improve the quality and sustainability of design;

[0035] This method can also avoid errors in the size of window openings in later buildings due to unqualified building spacing or unreasonable planning and layout design, leading to problems with building lighting when living in, and demolition and rework after the project is completed. It effectively reduces the phenomenon of unreasonable planning and design, and thus avoids unqualified building spacing and unreasonable building layout after the project is completed, providing scientific and accurate design report results for vernacular architecture. This method is of great significance to promoting the protection and development of traditional vernacular architecture in my country. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a flowchart of step S1 of the present invention;

[0037] Figure 2 It is a flowchart of step S2 of the present invention;

[0038] Figure 3 It is a flow chart of calculating indoor lighting area of ​​the present invention;

[0039] Figure 4 The present invention is a flow chart for calculating the minimum distance between any two buildings. DETAILED DESCRIPTION

[0040] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0041] The following describes an embodiment of the present invention based on its overall structure.

[0042] Example

[0043] Please see attached Figure 1-4 , a vernacular architectural space design generative method based on AIGC technology, including S1 and S2, S1 includes the following steps:

[0044] (1) Data collection: Conduct historical, cultural, and geographical surveys and research on vernacular architecture, and collect relevant spatial design data and documents, including data collection on native rural settlements and vernacular architecture, and data collection on new vernacular architecture of representative and demonstrative projects;

[0045] (2) Data cleaning and processing: Clean and process the collected data, remove useless information and duplicate records, and unify the data format into a machine-readable format;

[0046] (3) Feature extraction and selection: According to the characteristics and design requirements of vernacular architecture, useful features such as building shape, cladding texture, color, material and window position are selected and extracted;

[0047] (4) Design solutions: Use deep learning algorithms to predict the popularity of specific design elements and improve design efficiency and quality;

[0048] (5) Design suggestion generation: Select useful information features and input them into the model to generate corresponding space design suggestions;

[0049] (6) Design optimization: Optimize the generated design to adapt to the surrounding environment and consider practicality and safety factors;

[0050] (7) Collaborative work and feedback: During the design generation process, architects and other relevant personnel collaborate and provide feedback to improve the design plan and adjust the design plan in a timely manner;

[0051] (8) Design output: Output the final vernacular architectural space design drawing plan;

[0052] S2 includes the following steps:

[0053] (1) Spatial design generation preprocessing: Collect the building design information scheme of the user in S1, identify and analyze the building design information content, and trigger data preprocessing operations based on the analysis results;

[0054] (2) Generation of target building module: Establishing the model of the target building, dividing the monomers of the target building, setting the storey height value of the target building, and taking the storey height value of the target building as a variable condition;

[0055] (3) Determine the height of the target building: Determine the height of the target building and the corresponding location conditions based on the variable conditions. The location conditions include the building's orientation, front, back, left, and right distances, and relative location information with other buildings.

[0056] (4) Generation of spatial scenes: Generate corresponding spatial scenes based on parametric modeling, assign component parameter shapes and colors, form a spatial distribution matrix based on component position parameters and preset space, match it with component information in the standard component library, place standard components in each spatial distribution matrix grid, and generate corresponding spatial scenes through the automatic modeling tool conversion module of AIGC technology;

[0057] (5) Analysis of window positions in planned buildings: Based on the building outline information and spatial scene information of the building plan, the window size is determined by calculating the building layout, window positions, and indoor lighting range, and the window area is used as a variable condition;

[0058] (6) Determine the window area: According to the window variable conditions, room height, and lighting range, the automatic calculation tool based on AIGC technology is used to determine the window size of the target building.

[0059] It also includes the following calculation formula for the occlusion between the target building storeys based on the geometric shape, size and relative position of the rural buildings in S2:

[0060] dmin=dmax-((b1a1+b2a2+mm / sqrt(a1^2+a2^2))-(c1b2-c2b1+mm / sqrt(a1^2+a2^2)))

[0061] Among them, dmax and dmin represent the maximum and minimum spacing respectively, a1, a2, b1 and b2 represent the side lengths of adjacent buildings respectively, mm represents the height difference of adjacent buildings, c1, c2 and m represent the diagonal lengths from adjacent buildings to the intersecting line segment respectively, and the minimum spacing between any two buildings is calculated; S1 also includes data integration and association, definition of design rules and constraints, and continuous learning and optimization. Data integration and association are used to integrate and associate data from different sources to form a complete spatial design data set for subsequent feature extraction and model training; the definition of design rules and constraints is used to define appropriate design rules and constraints according to the protection, regional and cultural characteristics of vernacular architecture to ensure the feasibility and sustainability of the design scheme; continuous learning and optimization is used to continuously obtain feedback and data from actual projects, clean and process them, and revise and improve models and algorithms; S2 also includes user feedback and testing. User feedback and testing are used to optimize and improve the design generation method through user feedback and testing after completing each design scheme.

[0062] It should be noted that in this embodiment, through the application of AIGC technology deep learning algorithm in S1, various design elements can be quickly predicted and generated, thereby improving design efficiency and quality; through AIGC technology, the local building site, building appearance, building structure, building equipment, building space, building performance and intangible design element data are deeply considered, and AIGC technology can greatly reduce the cost and time of manual creation, and can quickly respond to user needs and feedback, and can generate a large number of alternative plans in a short time, and can be adjusted and improved in real time according to user needs. Through automated feature extraction and selection, human intervention can be reduced, thereby improving work efficiency and reducing human errors; by considering the surrounding environment and practicality, safety and other factors, the design plan can be closer to actual needs, and the feasibility of the design can also be guaranteed; through collaborative work and feedback, the design plan can be adjusted in time to meet customer needs and actual conditions; by generating corresponding space design suggestions, the design plan can be intuitively displayed, which helps architects and other relevant personnel to better understand and communicate; so as to facilitate the modification and update of the design plan to adapt to changing needs;

[0063] Furthermore, in S2, the AIGC technology system can quickly respond to and process information input by users, and use artificial intelligence technology to generate space design, thereby improving design efficiency and reducing labor costs; the system can generate personalized space design plans based on the specific needs and preferences input by users to meet users' needs for personalized customization; the system can generate visual space scenes to help users better understand and evaluate the effects of different design plans; the system takes into account the sustainability of the building environment, and can consider environmental factors in the design process to reduce the impact on the environment; the system supports modification and updating of design plans at any time to adapt to changing needs and market environment.

[0064] Please see attached Figure 3 , calculate the indoor lighting area, according to the indoor lighting area formula in the southern region: Q = A × H × 0.4 + B × H × 0.4, where Q is the indoor lighting area, in square meters; A and B are the size parameters of the window opening, in centimeters; H is the height of the room, in meters;

[0065] The formula for indoor lighting area in northern China is: Q = K × H × 0.2

[0066] Among them, Q is the indoor lighting area, in square meters; K is the window size parameter, generally taking a value of 0.2 to 0.3 square meters per square meter; H is the height of the room, in meters.

[0067] The southern region is north of 23° north latitude, and the northern region is south of 23° north latitude.

[0068] Example

[0069] According to the formula Q = A × H × 0.4 + B × H × 0.4, we can calculate the indoor lighting area Q, where A and B are the size parameters of the window opening, representing the width and length of the window. Assuming that the height of the room is H, the width and length of the window opening are A and B respectively, the calculation process of Q is as follows:

[0070] Q=A×H×0.4+B×H×0.4

[0071] Substituting specific values ​​into the above formula, for example, the room height H is 3 meters, the width and length A and B of the window opening are 1 meter and 2 meters respectively, then Q is calculated as follows:

[0072] Q = 1 × 3 × 0.4 + 2 × 3 × 0.4

[0073] Q=1.2+2.4

[0074] Q=3.6(square meters)

[0075] Therefore, the indoor lighting area of ​​the room is 3.6 square meters;

[0076] The indoor lighting area is 3.6 square meters. The height H of the room is 3 meters. The window is located in the center. According to the formula Q = A × H × 0.4 + B × H × 0.4, the width A and length B of the window can be set to x and y respectively, so that xy = 3.6 square meters.

[0077] Solving for x and y:

[0078] Since the window is in the center, we have x / y = h / w, where h is the height of the room and w is the width of the room. Based on this equation, we can set w to hx / y and then substitute it into the above equation to get:

[0079] xy=3.6 m2

[0080] x(hx / y)=3.6 square meters

[0081] x 2 *h=3.6㎡*y

[0082] x 2 =3.6 m2 / y

[0083] x=±√(3.6 m2 / y)

[0084] From this, we can see that the value of x is the width of the window.

[0085] According to Chinese building codes and standards, there are many common window opening sizes, such as 90mmx60mm, 80mmx60mm, 70mmx50mm, etc.

[0086] Here we take 90 mm x 60 mm as an example to calculate the opening area of ​​the window, that is, length multiplied by width. For a 90 mm x 60 mm window, its area is 90 mm x 60 mm = 5400 square millimeters. Convert the opening area of ​​the window into square meters. Since 1 square meter is equal to 10,000 square millimeters, 5400 square millimeters is equal to 0.54 square meters.

[0087] Finally, the window opening area needs to be calculated based on the room height and the window opening coefficient. Here we take the window opening coefficient of 0.2 as an example. The window opening coefficient value range is generally between 0.1 and 0.3. The larger the value, the higher the window opening area ratio and the better the house lighting effect. 0.2 is equivalent to the window opening area accounting for 20% of the total room area.

[0088] Calculate the window opening area according to the window size, convert the window opening area into square meters, and calculate the window opening area according to the room height and window opening coefficient.

[0089] Using AIGC technology for intelligent design, we investigate and study the local history, culture, and geography of vernacular architecture, collect relevant spatial design data and documents, and select and extract useful features, architectural forms, colors, materials, and window positions based on the characteristics and design requirements of vernacular architecture to provide effective data for vernacular architecture. This can not only improve the accuracy and efficiency of design, but also reduce human errors, improve the quality and sustainability of design, and avoid errors in the size of later building windows due to unqualified building spacing or unreasonable planning and layout design, which can lead to problems with building lighting when living.

[0090] The working principle of the present invention is:

[0091] Including S1 and S2, S1 includes the following steps: data collection, data cleaning and processing, feature extraction and selection, design plan, design suggestion generation, design plan optimization, collaborative work and feedback and design output; S2 includes the following steps: spatial design generation preprocessing, target building module generation, determination of target building floor height, generation of spatial scenes, analysis of window positions of plan buildings, and determination of window areas; This application uses AIGC technology for intelligent design, investigates and studies the local history, culture, and geography of vernacular architecture, collects relevant spatial design data and documents, and selects and extracts useful features, architectural forms, colors, etc. according to the characteristics and design requirements of vernacular architecture. The method can provide effective data for vernacular architecture by analyzing the color, material and window position, which can not only improve the accuracy and efficiency of design, but also reduce human errors and improve the quality and sustainability of design. The method can also avoid errors in the size of window openings in later buildings due to unqualified building spacing or unreasonable planning and layout design, resulting in problems with building lighting when living in the building, as well as demolition and rework after the project is completed. It effectively reduces the phenomenon of unreasonable planning and design, and thus avoids the situation of unqualified building spacing and unreasonable building layout after the project is completed, providing scientific and accurate design report results for vernacular architecture. This method is of great significance to promoting the protection and development of traditional vernacular architecture in my country.

[0092] Although an embodiment of the present invention has been shown and described, this specific embodiment is merely an explanation of the present invention and is not a limitation of the invention. The specific features, structures, materials or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. After reading this specification, those skilled in the art may make modifications, substitutions and variations to the embodiments without creative contributions as needed without departing from the principles and purpose of the present invention. However, as long as they are within the scope of the claims of the present invention, they are protected by patent law.

Claims

1. A generative method for vernacular architectural space design based on AIGC technology, characterized by , including S1 and S2, wherein S1 includes the following steps: (1) Data collection: Conduct historical, cultural, and geographical surveys and research on vernacular architecture, and collect relevant spatial design data and documents, including data collection on native rural settlements and vernacular architecture, and data collection on new vernacular architecture of representative and demonstrative projects; (2) Data cleaning and processing: Clean and process the collected data, remove useless information and duplicate records, and unify the data format into a machine-readable format; (3) Feature extraction and selection: According to the characteristics and design requirements of vernacular architecture, useful features such as building shape, cladding texture, color, material and window position are selected and extracted; (4) Design solutions: Use deep learning algorithms to predict the popularity of specific design elements and improve design efficiency and quality; (5) Design suggestion generation: Select useful information features and input them into the model to generate corresponding space design suggestions; (6) Design optimization: Optimize the generated design to adapt to the surrounding environment and consider practicality and safety factors; (7) Collaborative work and feedback: During the design generation process, architects and other relevant personnel collaborate and provide feedback to improve the design plan and adjust the design plan in a timely manner; (8) Design output: Output the final vernacular architectural space design drawing plan; The S2 comprises the following steps: (1) Spatial design generation preprocessing: collecting the building design information scheme of the user in S1, identifying and analyzing the building design information content, and triggering data preprocessing operations according to the analysis results; (2) Generation of target building module: Establishing the model of the target building, dividing the monomers of the target building, setting the storey height value of the target building, and taking the storey height value of the target building as a variable condition; (3) Determine the storey height of the target building: Determine the storey height and corresponding location conditions of the target building according to the variable conditions, wherein the location conditions include the orientation of the building, the distances in front, behind, left, and right directions, and the relative location information with respect to other buildings; (4) Generation of spatial scenes: Generate corresponding spatial scenes based on parametric modeling, assign component parameter shapes and colors, form a spatial distribution matrix based on component position parameters and preset space, match it with component information in the standard component library, place standard components in each spatial distribution matrix grid, and generate corresponding spatial scenes through the automatic modeling tool conversion module of AIGC technology; (5) Analysis of window positions in planned buildings: Based on the building outline information and spatial scene information of the building plan, the window size is determined by calculating the building layout, window positions, and indoor lighting range, and the window area is used as a variable condition; (6) Determine the window area: According to the window variable conditions, room height, and lighting range, the automatic calculation tool based on AIGC technology is used to determine the window size of the target building.

2. According to the method of generating vernacular architectural space design based on AIGC technology described in claim 1, it is characterized by ,The calculation formula for the window area in the southern region is as follows: The formula for indoor lighting area in the southern region is: Q = A×H×0.4+B×H×0.4, where Q is the indoor lighting area in square meters; A and B are the size parameters of the window openings in centimeters; and H is the height of the room in meters.

3. According to the method of generating vernacular architectural space design based on AIGC technology described in claim 1, it is characterized in that ,The calculation formula for the window area in the northern region is as follows: The formula for indoor lighting area in northern China is: Q = K × H × 0.2 Among them, Q is the indoor lighting area, in square meters; K is the window size parameter, generally taking a value of 0.2 to 0.3 square meters per square meter; H is the height of the room, in meters.

4. According to the method of generating vernacular architectural space design based on AIGC technology described in claim 1, it is characterized in that , and also includes the following calculation formula for the occlusion between the target building storey heights based on the geometric shape, size and relative position of the rural civil engineering in S2: dmin=dmax-((b1a1+b2a2+mm / sqrt(a1^2+a2^2))-(c1b2-c2b1+mm / sqrt(a1^2+a2^2))) Among them, dmax and dmin represent the maximum and minimum spacing respectively, a1, a2, b1 and b2 represent the side lengths of adjacent buildings respectively, mm represents the height difference between adjacent buildings, c1, c2 and m represent the diagonal lengths from adjacent buildings to the intersecting line segment respectively, and the minimum spacing between any two buildings is calculated.

5. According to the method of generating vernacular architectural space design based on AIGC technology described in claim 2, it is characterized in that The southern region is north of 23° north latitude, and the northern region is south of 23° north latitude.

6. According to the method of generating vernacular architectural space design based on AIGC technology described in claim 1, it is characterized by ,S1 also includes data integration and association, definition of design rules and constraints, and continuous learning and optimization. The data integration and association are used to integrate and associate data from different sources to form a complete spatial design data set for subsequent feature extraction and model training; the definition of design rules and constraints is used to define appropriate design rules and constraints according to the protection, regional and cultural characteristics of vernacular architecture to ensure the feasibility and sustainability of the design scheme; the continuous learning and optimization is used to continuously obtain feedback and data from actual projects, clean and process them, and revise and improve models and algorithms.

7. According to the method of generating vernacular architectural space design based on AIGC technology described in claim 1, it is characterized in that ,S2 also includes user feedback and testing, which are used to optimize and improve the design generation method through user feedback and testing after completing each design solution.

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