An AI-generated intelligent building form parameterized design method

Abstract

The application discloses an AI generation-based intelligent building form parameterized design method, and relates to the technical field of building design. The application discloses an AI generation-based intelligent building form parameterized design method, and relates to the technical field of building design. The application discloses an AI generation-based intelligent building form parameterized design method, and relates to the technical field of building design. The application discloses an AI generation-based intelligent building form parameterized design method, and relates to the technical field of building design. The application discloses an AI generation-based intelligent building form parameterized design method, and relates to the technical field of building design. The application discloses an AI generation-based intelligent building form parameterized design method, and relates to the technical field of building design. The application discloses an AI generation-based intelligent building form parameterized design method, and relates to the technical field of building design. The application discloses an AI generation-based intelligent building form parameterized design method, and relates to the technical field of building design. The application discloses an AI generation-based intelligent building form parameterized design method, and relates to the technical field of building design. The application discloses an AI generation-based intelligent building form parameterized design method, and relates to the technical field of building design. The application discloses an AI generation-based intelligent building form parameterized

Description

Technical Field

[0001] This invention relates to the field of architectural design technology, specifically to a parametric design method for intelligent building forms based on AI generation. Background Technology

[0002] Smart buildings refer to buildings that optimize the combination of structure, systems, services, and management according to user needs, thereby providing users with an efficient, comfortable, and convenient humanized building environment. Autonomous identification for security and fire protection is paramount in smart buildings, relying on image recognition from surveillance cameras. However, this requires comprehensive monitoring without blind spots. Since smart buildings often have multiple walls, these obstruct the field of view. While increasing the number of cameras can achieve comprehensive monitoring, it increases equipment costs. Optimizing the building's internal structure involves complexities that current technologies fail to adequately address, making it difficult to achieve comprehensive monitoring and ensure structural safety. Summary of the Invention

[0003] To address the aforementioned technical issues, this paper provides a parametric design method for smart building forms based on AI generation. This technical solution resolves the problems mentioned in the background section.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A parametric design method for smart building form based on AI generation includes: Obtain the design requirements and spatial volume of the smart building; based on the design requirements, analyze and obtain at least one compartment of the smart building; based on the spatial volume, form the allocated volume of the compartment. Based on design requirements, the compartments are divided into layers and categories to form at least one compartment category; The spatial layout of the compartments in the compartment classification is designed to obtain a preliminary design configuration; The shapes of the compartments arranged in the preliminary design configuration are set to obtain the intermediate design configuration; Based on monitoring costs, the upper limit of the number of monitoring devices is determined, and at least one monitoring setup scheme is formed for each compartment category; Based on the monitoring setup scheme, the demolition area of ​​the partition space wall is analyzed, the remaining wall of the partition space is analyzed, and it is determined whether the supporting capacity of the remaining wall can support the upper building. If so, the monitoring setup scheme is used as the feature setup scheme, in which tempered glass doors are installed in the demolition area. The number of monitoring devices set in the feature setting scheme is used as the feature value of the feature setting scheme, and the feature setting scheme with the smallest feature value in the compartment classification is used as the target setting scheme for the compartment classification. According to the wall demolition area in the target setting scheme, the intermediate design configuration is demolished to obtain the advanced design configuration. The advanced design configurations of at least one compartment are summarized to obtain the overall design configuration of the smart building.

[0005] Preferably, obtaining the design requirements and spatial volume of a smart building includes the following steps: The design requirements for a smart building include its floor area, number of floors, floor height, and at least one building module. The building module can be an elevator, HVAC control equipment, water, electricity, gas and energy management equipment, office area, corridor, restroom, stairwell or integrated management module. The volume of a smart building is obtained by multiplying its floor area, number of floors, and floor height.

[0006] Preferably, the analysis to obtain at least one compartment of the smart building includes the following steps: The smart building is divided into layers, resulting in at least one floor, which is then numbered from bottom to top. On each floor, a partition is formed for building modules that serve as elevators, HVAC control equipment, water, electricity and gas energy management equipment, corridors, stairwells or integrated management modules; Based on historical data, identify at least one historical company that has moved into a historical smart building, and take the average number of offices of the historical companies to obtain the preset number. The preset number is obtained by multiplying it by the expected number of companies to occupy the office area; On each floor, at least one cubicle is formed for the building module that serves as the office area, and the number of cubicles is equal to a preset value.

[0007] Preferably, the distribution volume for forming the compartment includes the following steps: The cubicles located in the office area are designated as the first cubicle, and the cubicles not located in the office area are designated as the second cubicle; The average proportion of the volume of the second compartment in the historical smart building is obtained by taking the average proportion of the second compartment. The average proportion of the space volume to the second compartment is obtained by calculating the allocated volume of the second compartment. Subtract the allocated volumes of all the second compartments from the total space volume to obtain the remaining volume; In historical data, companies with the number of offices equal to the preset number of historical smart buildings are used as sample companies. The attributes of the first compartment where the sample company is located are obtained, and the average volume ratio of the first compartment with the same attributes is taken to obtain the feature ratio of the first compartment. Multiply the characteristic proportion of the first compartment by the remaining volume to obtain the allocated volume of the first compartment.

[0008] Preferably, the step of classifying the compartments into at least one compartment category includes the following steps: Group the cubicles located on the same floor into cubicle categories and assign the floor number to the cubicle category.

[0009] Preferably, the spatial arrangement design of the compartments in the compartment classification to obtain the preliminary design configuration includes the following steps: The partitions that serve as corridors are designated as main partitions, the partitions that serve as restrooms are designated as secondary partitions, the partitions that house residents of the same company are designated as related partitions, the partitions that serve as elevators are designated as secondary partitions, and the remaining partitions are designated as auxiliary partitions. The main compartment is randomly arranged with the secondary compartments, associated compartments, and auxiliary compartments surrounding it. Each arrangement is recorded as the first row. The first row of consecutive adjacent related compartments is taken as the second row. In the second row, the sum of the distances from the related compartments to the secondary compartments and the next secondary compartments is taken as the first distance, and the sum of the distances from the secondary compartments to the secondary compartments and the next secondary compartments is taken as the second distance. The third distance is obtained by summing all the first and second distances in the second row; The arrangement of the compartments in the second row with the smallest third distance is taken as the preliminary design configuration.

[0010] Preferably, the step of setting the shape of the compartments arranged in the preliminary design configuration to obtain the intermediate design configuration includes the following steps: Divide the allocated volume by the floor height of the smart building to obtain the allocated area. Use the circle whose area is equal to the allocated area of ​​the main compartment as the feature circle and use the feature circle as the top-view projection shape of the main compartment. The areas of the partitions in the preliminary design are summed to obtain the total area, and the circle with an area equal to the total area is taken as the target circle. Set the target circle and the feature circle to have the same center, and take the part of the target circle that extends beyond the feature circle as the target part; According to the arrangement order of the main compartment, related compartment, secondary compartment and auxiliary compartment in the preliminary design configuration, the target part is divided using the radius of the target circle to obtain at least one compartment shape. The area of ​​the divided compartment shape is equal to the allocated area of ​​the main compartment, related compartment, secondary compartment or auxiliary compartment in the preliminary design configuration. Walls are generated at the edges of the partition shape to obtain the partition space. The wall height is equal to the floor height of the smart building. At least one partition space is combined to obtain the intermediate design configuration.

[0011] Preferably, the analysis to obtain the upper limit of the number of monitoring devices and to form at least one monitoring setup scheme for compartment classification includes the following steps: Within the funding for smart buildings, the amount allocated for purchasing monitoring equipment is taken as the monitoring cost. The average price is obtained by taking the average price of the monitoring equipment used in historical smart buildings. The monitoring cost is then divided by the average price to obtain the upper limit for the number of monitoring equipment. At least one sampling point is uniformly taken from the top of the compartment space in the intermediate design configuration of the compartment classification, and sampling points are randomly selected to form a preliminary setting plan. The number of sampling points in the preliminary setting plan shall not exceed the upper limit of the number of monitoring devices. Set any direction as the initial direction, and take at least one test point evenly between 0 and 360 degrees. The direction that makes an angle with the initial direction clockwise equal to the test point is taken as the test direction. Randomly and repeatedly assign test directions to sampling points in the initial setup to form an intermediate setup. When implementing the intermediate setup scheme, at the sampling points in the intermediate setup scheme, set the monitoring direction of the monitoring equipment according to the test direction assigned to the sampling points; The intermediate area is obtained by taking the union of the field of view of the monitoring devices set in the intermediate setting scheme. If the intermediate area includes all the compartment spaces in the intermediate design configuration that generates the compartment classification of the intermediate setting scheme, then the intermediate setting scheme is taken as the monitoring setting scheme of the compartment classification.

[0012] Preferably, the analysis of the demolished wall area of ​​the partition space and the analysis of the remaining wall surface of the partition space include the following steps: The wall of the partition space is evenly divided into at least one local block. If both sides of the local block are monitored by the monitoring equipment in the monitoring setup scheme, the local block is regarded as the target local block; otherwise, the local block is regarded as a non-target local block. The connection between the non-target local block and the monitoring device in the monitoring setup scheme is taken as the feature line segment. The feature line segments of the non-target local block are summarized to obtain the feature line segment set of the non-target local block. The feature line segment that passes through the least local block in the set of feature line segments of the non-target local block is taken as the designated line segment of the non-target local block, and the local blocks that the designated line segment passes through, other than the non-target local block, are taken as the local blocks to be smashed. The sections of the wall in the partition space that need to be demolished are collected to obtain the demolition area of ​​the wall in the partition space. The remaining wall of the partition space is the part of the wall excluding the demolition area.

[0013] Preferably, determining whether the supporting force of the remaining wall surface can support the upper structure includes the following steps: The wall thicknesses constructed in smart buildings are obtained in advance as feature thicknesses, and walls with a height equal to the floor height of the smart building, a thickness equal to the feature thickness, and a volume equal to the unit volume are used as sample walls. The maximum supporting force of the sample wall is obtained in advance and used as the characteristic force; The remaining wall areas of the partition spaces in the intermediate design configuration of the partition category are superimposed to obtain the total remaining area of ​​the partition category. The total supporting force of the partition category is calculated using the supporting force formula. The wall areas of all the partition spaces in the intermediate design configuration of the smart building are superimposed to obtain the total area. The total area is then multiplied by the characteristic thickness to obtain the first volume. Multiply the floor slab thickness, the floor area, and the number of floors of the smart building to obtain the second volume. Add the first and second volumes to obtain the third volume. Multiply the third volume by the average density of the building materials used in the smart building to obtain the total mass of the smart building. Multiply the total mass of the smart building by the gravitational acceleration to obtain the total weight of the smart building. Divide the compartment classification number by the floor height of the smart building to get the first proportion, and subtract the first proportion from 1 to get the second proportion; The total weight of the smart building is multiplied by the second proportion to obtain the reference weight. If the total support force of the partition classification is not less than the reference weight, the support force of the remaining walls can support the upper building; otherwise, the support force of the remaining walls cannot support the upper building. The formula for supporting force is as follows: , Where A is the total supporting force of the compartment classification, B is the total remaining area of ​​the compartment classification, C is the feature thickness, D is the unit volume, and E is the feature force.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: By developing intermediate design configurations, creating monitoring setup schemes, and analyzing and filtering these schemes, it is possible to generate partitions based on the construction requirements of smart buildings, plan the shapes of the partitions, analyze all monitoring situations within the cost range, demolish walls based on the locations of the monitoring equipment, and assess the load-bearing capacity of the remaining walls. This ensures that, within cost constraints, there are no blind spots in monitoring while also guaranteeing the structural safety of the building. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating the AI-generated intelligent building form parametric design method of the present invention. Figure 2 This is a schematic diagram illustrating the process of obtaining the design requirements and spatial volume of a smart building according to the present invention. Figure 3 This is a schematic diagram illustrating the process of obtaining at least one compartment of a smart building through analysis according to the present invention. Figure 4 This is a schematic diagram illustrating the process of forming the compartmentalized volume according to the present invention; Figure 5 This is a flowchart illustrating the spatial arrangement design of the compartments in the compartment classification of the present invention, resulting in a preliminary design configuration. Figure 6 This is a flowchart illustrating the process of setting the shape of the compartments arranged in the preliminary design configuration to obtain the intermediate design configuration according to the present invention. Figure 7 This is a flowchart illustrating the process of obtaining the upper limit of the number of monitoring devices and forming at least one monitoring setup scheme for compartment classification in accordance with the analysis of the present invention. Figure 8 This is a flowchart illustrating the process of analyzing and determining the wall demolition area of ​​the partition space and the remaining wall surface of the partition space in accordance with the present invention. Figure 9 This is a schematic diagram illustrating the process of determining whether the remaining wall surface has sufficient support to support the superstructure according to the present invention. Detailed Implementation

[0016] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0017] Reference Figure 1 As shown, a parametric design method for smart building form based on AI generation includes: Obtain the design requirements and spatial volume of the smart building; based on the design requirements, analyze and obtain at least one compartment of the smart building; based on the spatial volume, form the allocated volume of the compartment. Based on design requirements, the compartments are divided into layers and categories to form at least one compartment category; The spatial layout of the compartments in the compartment classification is designed to obtain a preliminary design configuration; The shapes of the compartments arranged in the preliminary design configuration are set to obtain the intermediate design configuration; Based on monitoring costs, the upper limit of the number of monitoring devices is determined, and at least one monitoring setup scheme is formed for each compartment category; Based on the monitoring setup scheme, the demolition area of ​​the partition space wall is analyzed, the remaining wall of the partition space is analyzed, and it is determined whether the supporting capacity of the remaining wall can support the upper building. If so, the monitoring setup scheme is used as the feature setup scheme, in which tempered glass doors are installed in the demolition area. The number of monitoring devices set in the feature setting scheme is used as the feature value of the feature setting scheme, and the feature setting scheme with the smallest feature value in the compartment classification is used as the target setting scheme for the compartment classification. According to the wall demolition area in the target setting scheme, the intermediate design configuration is demolished to obtain the advanced design configuration. The advanced design configurations of at least one compartment are summarized to obtain the overall design configuration of the smart building.

[0018] This solution primarily optimizes the internal structure of smart buildings. By adjusting the shape of the internal structure and removing walls, it achieves comprehensive monitoring of the building's interior without blind spots, within the constraints of monitoring costs and by adjusting the viewing angle of the monitoring equipment. It also minimizes the number of monitoring points while ensuring that the load-bearing capacity of the removed walls is sufficient to support the upper floors. This optimization of the building's internal structure allows for real-time decision-making based on monitoring data, enabling intelligent control. Subsequent steps will then be implemented to complete the design of the smart building's internal structure.

[0019] Reference Figure 2 As shown, obtaining the design requirements and spatial volume of a smart building includes the following steps: The design requirements for a smart building include its floor area, number of floors, floor height, and at least one building module. The building module can be an elevator, HVAC control equipment, water, electricity, gas and energy management equipment, office area, corridor, restroom, stairwell or integrated management module. The volume of a smart building is obtained by multiplying its floor area, number of floors, and floor height.

[0020] Different modules in a smart building need to be separated by different walls; otherwise, they may interfere with each other during use. For example, if the office area and the corridor are not separated, people can enter the corridor at will, the office area has no privacy, and if someone who is not a member of the company enters, there is a risk of company data leakage.

[0021] Reference Figure 3 As shown, the analysis of at least one compartment in a smart building includes the following steps: The smart building is divided into layers, resulting in at least one floor, which is then numbered from bottom to top. On each floor, a partition is formed for building modules that serve as elevators, HVAC control equipment, water, electricity and gas energy management equipment, corridors, stairwells or integrated management modules; Based on historical data, identify at least one historical company that has moved into a historical smart building, and take the average number of offices of the historical companies to obtain the preset number. The preset number is obtained by multiplying it by the expected number of companies to occupy the office area; On each floor, at least one cubicle is formed for the building module that serves as the office area, and the number of cubicles is equal to a preset value.

[0022] When forming partitions, different partitions need to be formed depending on the building modules. However, here, only partitions are formed, and the area and shape of the partitions are not limited for the time being. The office area needs to be considered separately because the office area is rented out to external parties and will not be rented to the same company. Therefore, the building modules that serve as office areas need to be partitioned according to the number and size of the companies expected to move in.

[0023] Reference Figure 4 As shown, the process of forming the partition volume includes the following steps: The cubicles located in the office area are designated as the first cubicle, and the cubicles not located in the office area are designated as the second cubicle; The average proportion of the volume of the second compartment in the historical smart building is obtained by taking the average proportion of the second compartment. The average proportion of the space volume to the second compartment is obtained by calculating the allocated volume of the second compartment. Subtract the allocated volumes of all the second compartments from the total space volume to obtain the remaining volume; In historical data, companies with the number of offices equal to the preset number of historical smart buildings are used as sample companies. The attributes of the first compartment where the sample company is located are obtained, and the average volume ratio of the first compartment with the same attributes is taken to obtain the feature ratio of the first compartment. Multiply the characteristic proportion of the first compartment by the remaining volume to obtain the allocated volume of the first compartment.

[0024] Based on the historical data of the second compartment, its volume ratio can be obtained. Therefore, by considering this ratio and the overall spatial volume of the smart building, the allocated volume of the second compartment can be determined. For the first compartment, since it is the company's office, its volume cannot be obtained by simply dividing it equally. Each first compartment has different attributes; it might be a meeting room, an access room used for receptions and job interviews, or an employee workspace. Therefore, it is necessary to determine its usage ratio based on its attributes, and then allocate the remaining volume accordingly to obtain the allocated volume of the first compartment.

[0025] To classify and categorize the compartments into at least one category, the following steps are included: Group the cubicles located on the same floor into cubicle categories and assign the floor number to the cubicle category.

[0026] When setting the layout and shape of the cubicles, there is no interference between the cubicles on different floors. Therefore, they are classified according to the floors, and the parameters of each cubicle category are set separately.

[0027] Reference Figure 5 As shown, the spatial layout design of the compartments in the compartment classification to obtain the preliminary design configuration includes the following steps: The partitions that serve as corridors are designated as main partitions, the partitions that serve as restrooms are designated as secondary partitions, the partitions that house residents of the same company are designated as related partitions, the partitions that serve as elevators are designated as secondary partitions, and the remaining partitions are designated as auxiliary partitions. The main compartment is randomly arranged with the secondary compartments, associated compartments, and auxiliary compartments surrounding it. Each arrangement is recorded as the first row. The first row of consecutive adjacent related compartments is taken as the second row. In the second row, the sum of the distances from the related compartments to the secondary compartments and the next secondary compartments is taken as the first distance, and the sum of the distances from the secondary compartments to the secondary compartments and the next secondary compartments is taken as the second distance. The third distance is obtained by summing all the first and second distances in the second row; The arrangement of the compartments in the second row with the smallest third distance is taken as the preliminary design configuration.

[0028] Since the most frequently used routes in smart buildings are those from the company to the restrooms and from the company to the elevators, it is more reasonable to design them with the shortest total path length. This way, employees will expend less physical energy during daily use. When designing, the corridor is placed in the center, and the rest are arranged around it, so that they can all be connected through the central corridor. At the same time, when arranging them, it is important to note that related cubicles should be arranged continuously, because the overall area is an office area, so they should be arranged adjacent to each other.

[0029] Reference Figure 6 As shown, the process of setting the shape of the compartments arranged in the preliminary design configuration to obtain the intermediate design configuration includes the following steps: Divide the allocated volume by the floor height of the smart building to obtain the allocated area. Use the circle whose area is equal to the allocated area of ​​the main compartment as the feature circle and use the feature circle as the top-view projection shape of the main compartment. The areas of the partitions in the preliminary design are summed to obtain the total area, and the circle with an area equal to the total area is taken as the target circle. Set the target circle and the feature circle to have the same center, and take the part of the target circle that extends beyond the feature circle as the target part; According to the arrangement order of the main compartment, related compartment, secondary compartment and auxiliary compartment in the preliminary design configuration, the target part is divided using the radius of the target circle to obtain at least one compartment shape. The area of ​​the divided compartment shape is equal to the allocated area of ​​the main compartment, related compartment, secondary compartment or auxiliary compartment in the preliminary design configuration. Walls are generated at the edges of the partition shape to obtain the partition space. The wall height is equal to the floor height of the smart building. At least one partition space is combined to obtain the intermediate design configuration.

[0030] Since the main compartment is located in the center and the other compartments are arranged around it, the top-view projection of the main compartment is set as a circle, and the overall top-view projection of the main compartment and the other compartments is also set as a circle. Based on the volume and floor height, the top-view area can be calculated, and the radii of the two circles can be obtained. The annulus formed by the two circles is then divided, with each division corresponding to the area allocated to the secondary compartment, related compartment, or auxiliary compartment in the initial design configuration. This generates compartmentalized spaces. Initially, the compartmentalized spaces are completely sealed, but the walls will be removed later. Because the goal is to minimize the number of monitoring devices, compartmentalized spaces with monitoring devices will not be completely sealed; otherwise, the monitoring range of the devices would be significantly obstructed. Similarly, compartmentalized spaces without monitoring devices must have their walls removed to be monitored; otherwise, the monitoring devices cannot monitor their interiors. Therefore, in the subsequent selection of schemes aimed at minimizing the number of monitoring devices, the walls of the compartmentalized spaces will inevitably be removed. Glass doors can then be installed in these areas for entry and exit.

[0031] Reference Figure 7 As shown, the analysis yields the upper limit for the number of monitoring devices, and the formation of at least one monitoring setup scheme based on compartment classification includes the following steps: Within the funding for smart buildings, the amount allocated for purchasing monitoring equipment is taken as the monitoring cost. The average price is obtained by taking the average price of the monitoring equipment used in historical smart buildings. The monitoring cost is then divided by the average price to obtain the upper limit for the number of monitoring equipment. At least one sampling point is uniformly taken from the top of the compartment space in the intermediate design configuration of the compartment classification, and sampling points are randomly selected to form a preliminary setting plan. The number of sampling points in the preliminary setting plan shall not exceed the upper limit of the number of monitoring devices. Set any direction as the initial direction, and take at least one test point evenly between 0 and 360 degrees. The direction that makes an angle with the initial direction clockwise equal to the test point is taken as the test direction. Randomly and repeatedly assign test directions to sampling points in the initial setup to form an intermediate setup. When implementing the intermediate setup scheme, at the sampling points in the intermediate setup scheme, set the monitoring direction of the monitoring equipment according to the test direction assigned to the sampling points; The intermediate area is obtained by taking the union of the field of view of the monitoring devices set in the intermediate setting scheme. If the intermediate area includes all the compartment spaces in the intermediate design configuration that generates the compartment classification of the intermediate setting scheme, then the intermediate setting scheme is taken as the monitoring setting scheme of the compartment classification.

[0032] The angle between the initial direction and the test direction here is the angle by which the initial direction is rotated clockwise and first coincides with the test direction; The monitoring field of view varies depending on the orientation of the monitoring equipment at the sampling points. Therefore, it is necessary to exhaustively list all possible orientations of the monitoring equipment at the sampling points in the initial setup plan, and then select a plan that can cover all the partition spaces in the intermediate design configuration of the partition classification. Here, the walls are considered invisible when determining whether to cover.

[0033] Reference Figure 8 As shown, the analysis of the demolition area of ​​the partition space wall and the analysis of the remaining wall surface of the partition space include the following steps: The wall of the partition space is evenly divided into at least one local block. If both sides of the local block are monitored by the monitoring equipment in the monitoring setup scheme, the local block is regarded as the target local block; otherwise, the local block is regarded as a non-target local block. The connection between the non-target local block and the monitoring device in the monitoring setup scheme is taken as the feature line segment. The feature line segments of the non-target local block are summarized to obtain the feature line segment set of the non-target local block. The feature line segment that passes through the least local block in the set of feature line segments of the non-target local block is taken as the designated line segment of the non-target local block, and the local blocks that the designated line segment passes through, other than the non-target local block, are taken as the local blocks to be smashed. The sections of the wall in the partition space that need to be demolished are collected to obtain the demolition area of ​​the wall in the partition space. The remaining wall of the partition space is the part of the wall excluding the demolition area.

[0034] Because of the obstruction of walls, the field of view of the monitoring equipment is blocked. Therefore, it is necessary to remove part of the walls to make the interior of the floor fully monitorable. It's easy to see that if each local block can be monitored by a monitoring device in the monitoring setup, there will be no blind spots. Since blind spots are generally in corners, non-target local blocks are formed. These non-target local blocks are unmonitorable parts, meaning they are blocked from each monitoring device by other local blocks. These blocking local blocks need to be removed. During removal, as little wall surface as possible should be removed, as removing too much may result in insufficient support for the upper structure. Therefore, the local blocks to be demolished are those with the least amount of wall surface removed. After all the local blocks to be demolished are removed, all non-target local blocks can be monitored, meaning every wall surface can be monitored, thus eliminating blind spots.

[0035] Reference Figure 9 As shown, determining whether the remaining wall surface has sufficient support to support the superstructure includes the following steps: The wall thicknesses constructed in smart buildings are obtained in advance as feature thicknesses, and walls with a height equal to the floor height of the smart building, a thickness equal to the feature thickness, and a volume equal to the unit volume are used as sample walls. The maximum supporting force of the sample wall is obtained in advance and used as the characteristic force; The remaining wall areas of the partition spaces in the intermediate design configuration of the partition category are superimposed to obtain the total remaining area of ​​the partition category. The total supporting force of the partition category is calculated using the supporting force formula. The wall areas of all the partition spaces in the intermediate design configuration of the smart building are superimposed to obtain the total area. The total area is then multiplied by the characteristic thickness to obtain the first volume. Multiply the floor slab thickness, the floor area, and the number of floors of the smart building to obtain the second volume. Add the first and second volumes to obtain the third volume. Multiply the third volume by the average density of the building materials used in the smart building to obtain the total mass of the smart building. Multiply the total mass of the smart building by the gravitational acceleration to obtain the total weight of the smart building. Divide the compartment classification number by the floor height of the smart building to get the first proportion, and subtract the first proportion from 1 to get the second proportion; The total weight of the smart building is multiplied by the second proportion to obtain the reference weight. If the total support force of the partition classification is not less than the reference weight, the support force of the remaining walls can support the upper building; otherwise, the support force of the remaining walls cannot support the upper building. The formula for supporting force is as follows: , Where A is the total supporting force of the compartment classification, B is the total remaining area of ​​the compartment classification, C is the feature thickness, D is the unit volume, and E is the feature force.

[0036] Here, it is necessary to calculate whether the monitoring setup generated by the compartment classification can support the upper building. Since there are various possibilities for the demolition of the upper building's walls, for ease of calculation, we will calculate based on the case where the walls are not demolished. If it can support the upper building under this case, it means that it can safely support the upper building under any demolition situation. Therefore, we calculate the proportion of the building above the floor where the compartment classification is located, i.e., the second proportion. Thus, the reference weight obtained is the weight of the building above the floor where the compartment classification is located. By comparing it with the total support force of the compartment classification, we can determine whether it can support the upper building.

[0037] Furthermore, this solution also proposes a storage medium on which a computer-readable program is stored. When the computer-readable program is invoked, the aforementioned AI-generated intelligent building form parametric design method is executed.

[0038] It is understandable that the storage medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid-state drive (SSD).

[0039] In summary, the advantages of this invention are as follows: by forming an intermediate design configuration, developing a monitoring setup scheme, and analyzing and filtering the monitoring setup scheme, it is possible to generate partitions according to the construction requirements of smart buildings, plan the shape of the partitions, analyze all monitoring situations within the cost range, and thus demolish walls according to the locations of the monitoring equipment, and assess the load-bearing capacity of the remaining demolished walls. Therefore, within the cost limit, it ensures both comprehensive monitoring and structural safety of the building.

[0040] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A parametric design method for intelligent building form based on AI generation, characterized in that, include: Obtain the design requirements and spatial volume of the smart building; based on the design requirements, analyze and obtain at least one compartment of the smart building; based on the spatial volume, form the allocated volume of the compartment. Based on design requirements, the compartments are divided into layers and categories to form at least one compartment category; The spatial layout of the compartments in the compartment classification is designed to obtain a preliminary design configuration; The shapes of the compartments arranged in the preliminary design configuration are set to obtain the intermediate design configuration; Based on monitoring costs, the upper limit of the number of monitoring devices is determined, and at least one monitoring setup scheme is formed for each compartment category; Based on the monitoring setup scheme, the demolition area of ​​the partition space wall is analyzed, the remaining wall of the partition space is analyzed, and it is determined whether the supporting capacity of the remaining wall can support the upper building. If so, the monitoring setup scheme is used as the feature setup scheme, in which tempered glass doors are installed in the demolition area. The number of monitoring devices set in the feature setting scheme is used as the feature value of the feature setting scheme, and the feature setting scheme with the smallest feature value in the compartment classification is used as the target setting scheme for the compartment classification. According to the wall demolition area in the target setting scheme, the intermediate design configuration is demolished to obtain the advanced design configuration. The advanced design configurations of at least one compartment are summarized to obtain the overall design configuration of the smart building.

2. The AI-generated intelligent building form parametric design method according to claim 1, characterized in that, The process of obtaining the design requirements and spatial volume of smart buildings includes the following steps: The design requirements for a smart building include its floor area, number of floors, floor height, and at least one building module. The building module can be an elevator, HVAC control equipment, water, electricity, gas and energy management equipment, office area, corridor, restroom, stairwell or integrated management module. The volume of a smart building is obtained by multiplying its floor area, number of floors, and floor height.

3. The AI-generated intelligent building form parametric design method according to claim 2, characterized in that, The analysis to obtain at least one compartment of the smart building includes the following steps: The smart building is divided into layers, resulting in at least one floor, which is then numbered from bottom to top. On each floor, a partition is formed for building modules that serve as elevators, HVAC control equipment, water, electricity and gas energy management equipment, corridors, stairwells or integrated management modules; Based on historical data, identify at least one historical company that has moved into a historical smart building, and take the average number of offices of the historical companies to obtain the preset number. The preset number is obtained by multiplying it by the expected number of companies to occupy the office area; On each floor, at least one cubicle is formed for the building module that serves as the office area, and the number of cubicles is equal to a preset value.

4. The AI-generated intelligent building form parametric design method according to claim 3, characterized in that, The process of forming the compartmentalized volume includes the following steps: The cubicles located in the office area are designated as the first cubicle, and the cubicles not located in the office area are designated as the second cubicle; The average proportion of the volume of the second compartment in the historical smart building is obtained by taking the average proportion of the second compartment. The average proportion of the space volume to the second compartment is obtained to obtain the allocated volume of the second compartment. Subtract the allocated volumes of all the second compartments from the total space volume to obtain the remaining volume; In historical data, companies with the number of offices equal to the preset number of historical smart buildings are used as sample companies. The attributes of the first compartment where the sample company is located are obtained, and the average volume ratio of the first compartment with the same attributes is taken to obtain the feature ratio of the first compartment. Multiply the characteristic proportion of the first compartment by the remaining volume to obtain the allocated volume of the first compartment.

5. The AI-generated intelligent building form parametric design method according to claim 4, characterized in that, The step of classifying the compartments into at least one compartment category includes the following steps: Group the cubicles located on the same floor into cubicle categories and assign the floor number to the cubicle category.

6. The AI-generated intelligent building form parametric design method according to claim 5, characterized in that, The process of spatially arranging the compartments in the compartment classification to obtain a preliminary design configuration includes the following steps: The partitions that serve as corridors are designated as main partitions, the partitions that serve as restrooms are designated as secondary partitions, the partitions that house residents of the same company are designated as related partitions, the partitions that serve as elevators are designated as secondary partitions, and the remaining partitions are designated as auxiliary partitions. The main compartment is randomly arranged with the secondary compartments, associated compartments, and auxiliary compartments surrounding it. Each arrangement is recorded as the first row. The first row of consecutive adjacent related compartments is taken as the second row. In the second row, the sum of the distances from the related compartments to the secondary compartments and the next secondary compartments is taken as the first distance, and the sum of the distances from the secondary compartments to the secondary compartments and the next secondary compartments is taken as the second distance. The third distance is obtained by summing all the first and second distances in the second row; The arrangement of the compartments in the second row with the smallest third distance is taken as the preliminary design configuration.

7. The AI-generated intelligent building form parametric design method according to claim 6, characterized in that, The process of shaping the compartments arranged in the preliminary design configuration to obtain the intermediate design configuration includes the following steps: Divide the allocated volume by the floor height of the smart building to obtain the allocated area. Use the circle whose area is equal to the allocated area of ​​the main compartment as the feature circle and use the feature circle as the top-view projection shape of the main compartment. The areas of the partitions in the preliminary design are summed to obtain the total area, and the circle with an area equal to the total area is taken as the target circle. Set the target circle and the feature circle to have the same center, and take the part of the target circle that extends beyond the feature circle as the target part; According to the arrangement order of the main compartment, related compartment, secondary compartment and auxiliary compartment in the preliminary design configuration, the target part is divided using the radius of the target circle to obtain at least one compartment shape. The area of ​​the divided compartment shape is equal to the allocated area of ​​the main compartment, related compartment, secondary compartment or auxiliary compartment in the preliminary design configuration. Walls are generated at the edges of the partition shape to obtain the partition space. The wall height is equal to the floor height of the smart building. At least one partition space is combined to obtain the intermediate design configuration.

8. The AI-generated intelligent building form parametric design method according to claim 7, characterized in that, The analysis, which determines the upper limit of the number of monitoring devices and forms at least one monitoring setup scheme for compartment classification, includes the following steps: Within the funding for smart buildings, the amount allocated for purchasing monitoring equipment is taken as the monitoring cost. The average price is obtained by taking the average price of the monitoring equipment used in historical smart buildings. The monitoring cost is then divided by the average price to obtain the upper limit for the number of monitoring equipment. At least one sampling point is uniformly taken from the top of the compartment space in the intermediate design configuration of the compartment classification, and sampling points are randomly selected to form a preliminary setting plan. The number of sampling points in the preliminary setting plan shall not exceed the upper limit of the number of monitoring devices. Set any direction as the initial direction, and take at least one test point evenly between 0 and 360 degrees. The direction that makes an angle with the initial direction clockwise equal to the test point is taken as the test direction. Randomly and repeatedly assign test directions to sampling points in the initial setup to form an intermediate setup. When implementing the intermediate setup scheme, at the sampling points in the intermediate setup scheme, set the monitoring direction of the monitoring equipment according to the test direction assigned to the sampling points; The intermediate area is obtained by taking the union of the field of view of the monitoring devices set in the intermediate setting scheme. If the intermediate area includes all the compartment spaces in the intermediate design configuration that generates the compartment classification of the intermediate setting scheme, then the intermediate setting scheme is taken as the monitoring setting scheme of the compartment classification.

9. The AI-generated intelligent building form parametric design method according to claim 8, characterized in that, The analysis identifies the demolition area of ​​the partition space's walls, and the analysis of the remaining walls of the partition space includes the following steps: The wall of the partition space is evenly divided into at least one local block. If both sides of the local block are monitored by the monitoring equipment in the monitoring setup scheme, the local block is regarded as the target local block; otherwise, the local block is regarded as a non-target local block. The connection between the non-target local block and the monitoring device in the monitoring setup scheme is taken as the feature line segment. The feature line segments of the non-target local block are summarized to obtain the feature line segment set of the non-target local block. The feature line segment that passes through the least local block in the set of feature line segments of the non-target local block is taken as the designated line segment of the non-target local block, and the local blocks that the designated line segment passes through, other than the non-target local block, are taken as the local blocks to be smashed. The sections of the wall in the partition space that need to be demolished are collected to obtain the demolition area of ​​the wall in the partition space. The remaining wall of the partition space is the part of the wall excluding the demolition area.

10. The AI-generated intelligent building form parametric design method according to claim 9, characterized in that, The process of determining whether the remaining wall surface has sufficient support to support the superstructure includes the following steps: The wall thicknesses constructed in smart buildings are obtained in advance as feature thicknesses, and walls with a height equal to the floor height of the smart building, a thickness equal to the feature thickness, and a volume equal to the unit volume are used as sample walls. The maximum supporting force of the sample wall is obtained in advance and used as the characteristic force; The remaining wall areas of the partition spaces in the intermediate design configuration of the partition category are superimposed to obtain the total remaining area of ​​the partition category. The total supporting force of the partition category is calculated using the supporting force formula. The wall areas of all the partition spaces in the intermediate design configuration of the smart building are superimposed to obtain the total area. The total area is then multiplied by the characteristic thickness to obtain the first volume. Multiply the floor slab thickness, the floor area, and the number of floors of the smart building to obtain the second volume. Add the first and second volumes to obtain the third volume. Multiply the third volume by the average density of the building materials used in the smart building to obtain the total mass of the smart building. Multiply the total mass of the smart building by the gravitational acceleration to obtain the total weight of the smart building. Divide the compartment classification number by the floor height of the smart building to get the first proportion, and subtract the first proportion from 1 to get the second proportion; The total weight of the smart building is multiplied by the second proportion to obtain the reference weight. If the total support force of the partition classification is not less than the reference weight, the support force of the remaining walls can support the upper building; otherwise, the support force of the remaining walls cannot support the upper building. The formula for supporting force is as follows: ， Where A is the total supporting force of the compartment classification, B is the total remaining area of ​​the compartment classification, C is the feature thickness, D is the unit volume, and E is the feature force.

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