Indoor space layout optimization system based on data analysis

Abstract

The invention relates to the technical field of indoor space design, and provides an indoor space layout optimization system based on data analysis, and the system comprises an element data importing module which is used for importing indoor space data and indoor decoration object data, and outputting a matching list of indoor objects; the space element construction module is used for performing simulation construction on the data of the indoor decoration objects and converting the data into space elements suitable for layout division; and the space planning module is used for building and simulating indoor space according to indoor space data, dividing the indoor space, setting areas capable of being arranged and areas not capable of being arranged, and classifying the areas capable of being arranged. According to the method, indoor decoration objects are converted into rectangular space elements, a collision volume model is constructed, digital expression of physical constraints is achieved, layout areas are automatically divided, the elements are rapidly arranged, and landing risks such as object collision and channel blockage are avoided.

Description

Technical Field

[0001] This invention relates to the field of interior space design technology, specifically to an interior space layout optimization system based on data analysis. Background Technology

[0002] Interior spaces are generally composed of the main building structure and interior objects. In interior spaces, openness and enclosure are psychological feelings brought about by the definition of environmental boundaries. Open interior spaces have a certain fluidity and interest, and are a reflection of the openness mentality in the environment. Different layouts of interior objects reflect different degrees of openness, and appropriate openness of interior spaces can enhance the user experience.

[0003] Existing technologies have many shortcomings in interior layout, such as low space utilization, unreasonable circulation planning, and poor flooring, making it difficult to meet people's needs for openness, aesthetics, and practicality in interior spaces. Therefore, there is a need for an interior space layout optimization system based on data analysis. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an indoor space layout optimization system based on data analysis, which solves many problems in indoor layout, such as low space utilization, unreasonable circulation planning, and poor practicality, making it difficult to meet people's needs for openness, aesthetics, and practicality of indoor spaces.

[0005] To achieve the above objectives, the present invention provides the following technical solution: An indoor space layout optimization system based on data analysis, comprising: The element data import module is used to import interior space data and interior decoration items. The data is used to generate a list of interior items to match; The spatial element construction module is used to simulate and construct data of interior decoration objects and convert them into spatial elements suitable for layout and division. The space planning module is used to construct a simulated interior space based on indoor space data, divide the space into layoutable and non-layoutable areas, and classify the layoutable areas to arrange the simulated objects constructed from the data of the simulated interior decoration objects output by the space element construction module. The scheme selection module uses the matching list output by the element data import module to generate layout schemes for the spatial elements constructed by the spatial element construction module in the simulated indoor space constructed by the spatial planning module, and selects schemes based on the residential suitability weight allocation.

[0006] Preferably, the feature data import module includes: The data import unit is used to import the floor area, wall area, ceiling area, and load-bearing wall location of the interior space, as well as to store the length, width, height, and volume data of the measured interior decoration objects. The data classification unit is used to classify the data of interior decoration objects, with the object category as the parent number, the purpose as the child number, and the special characteristics as the label number; The matching scheme generation unit is used to match interior decoration items according to the classification number of the data classification unit, and the matching is based on rationality, and the quantity of decoration items with specific numbers is limited. A list generation unit is used to output a list of the numbers and quantities of decorative items. Preferably, the spatial element construction module includes: The data acquisition unit is used to collect the length, width, height, and volume data of interior decoration items, including furniture and building materials. The simulation construction unit is used to import the length, width, height, and volume data of interior decoration objects and simulate and generate simulated objects. The rectangular element generation unit is used to extend the vertical line of the maximum area of ​​simulated objects that are not decorative building materials, construct the object collision space according to the vertical line, and divide the collision space into rectangular aggregate spatial elements.

[0007] Preferably, the spatial planning module includes: The indoor space simulation generation unit is used to generate a two-dimensional or three-dimensional simulated space, including the location of the floor, walls, ceiling and load-bearing walls, based on the imported indoor space data. Interior space partitioning units are used to divide a space into different functional areas based on the location of load-bearing walls, doors, and windows in the simulated space. The area division unit is used to delineate the areas where objects can be placed and the areas where objects are prohibited from being placed within each functional area, based on safety regulations and traffic flow planning principles. The areas where objects can be placed are then classified according to their respective functions.

[0008] Preferably, the scheme screening module includes: The spatial scene layout module is used to automatically arrange and combine the spatial elements generated by the spatial element construction module according to their functional classification and place them into the corresponding layoutable areas divided by the spatial planning module, generating multiple initial layout schemes. The residential element weighting unit is used to pre-store or receive user input of preference weights for different layout elements. The weighted elements include, but are not limited to, circulation smoothness, space utilization, lighting and ventilation, and aesthetic principles. The weighted decision unit is used to calculate the comprehensive residential suitability score of each initial layout scheme according to the weight configuration in the residential element weight unit, and to sort and filter according to the score; The scheme output unit is used to output one or more optimal layout schemes after screening in the form of a two-dimensional plan or a three-dimensional model.

[0009] A data analysis-based method for optimizing indoor space layout includes the following steps: Step 1: Through the element data import module, input the original structural data of the target interior space and the list of decorative items to be arranged, and obtain the item matching list processed by the system. Step 2: Using the spatial element construction module, convert the data of decorative objects into rectangular spatial elements with collision volumes; Step 3: Using the spatial planning module, construct a simulated space based on the original structural data, and divide it into functional zones and areas that can be laid out and those that cannot. Step 4: Through the scheme selection module, spatial elements are automatically filled into the layoutable area of ​​the simulated space to generate a large number of alternative layout schemes. Step 5: Based on the preset residential suitability weighting system, conduct a comprehensive evaluation and scoring of all alternative layout schemes; Step 6: Select the best layout schemes based on the scoring results and output them to the user.

[0010] Preferably, the specific steps for generating the rectangular spatial elements in step two are as follows: S1. Data Acquisition and Simulation: Collect or import the length, width, height, and volume data of interior decoration objects, and generate corresponding three-dimensional simulation objects based on this data; S2. Collision Space Construction: Identify the maximum projection area of ​​the simulated object on the horizontal plane, extend vertical lines from all edge vertices of the area, and construct a three-dimensional collision rectangle space element that can completely enclose the object. S3. Spatial Element Extraction: Extract the projection of the three-dimensional collision space cuboid onto the horizontal plane and define it as a two-dimensional rectangular spatial element of the object. S4. Element Information Association: The dimensions of the rectangular spatial element, the classification number of the object to which it belongs, and the special characteristic mark information are associated and stored for subsequent layout planning.

[0011] Preferably, in the process of constructing the spatial elements in S2, when the object is an irregular object, vertical lines are set at multiple edge points of the maximum area of ​​the simulated object, and the maximum value of the object collision space is constructed according to the vertical lines.

[0012] Preferably, in step four, the layout scheme is generated by using a rule-based algorithm or a genetic algorithm to arrange spatial elements within the layoutable area.

[0013] Preferably, the layout scheme generated in step four will fully consider the mutual occlusion and collision relationships between simulated objects, and reasonably adjust the shape and size of the rectangular set to ensure the rationality and operability of the spatial elements.

[0014] This invention provides an indoor space layout optimization system based on data analysis. It has the following beneficial effects: 1. This invention converts interior decoration objects into rectangular spatial elements and constructs a collision volume model to achieve a digital expression of physical constraints. It also automatically divides the layoutable area and quickly arranges elements, avoiding the risks of object collisions and passage blockages. At the same time, for irregular objects, it uses multi-point vertical line projection to construct the maximum containment rectangle, ensuring the universality and accuracy of spatial element conversion.

[0015] 2. This invention combines user preference weights to automatically evaluate the livability of different layout schemes and generate the optimal layout scheme. During the evaluation process, it fully considers multiple dimensions such as smooth traffic flow, space utilization, lighting and ventilation, feng shui principles, and aesthetic principles to ensure the scientific and rational nature of the layout scheme. In this way, the system can help users quickly realize their ideal interior design, improve user experience and the practicality of space planning, and meet the personalized needs of different users for interior space. Attached Figure Description

[0016] Figure 1 is a schematic diagram of the system of the present invention; Figure 2 is a schematic diagram of the element book data import module system of the present invention; Figure 3 is a schematic diagram of the spatial element construction module system of the present invention; Figure 4 is a schematic diagram of the spatial planning module system of the present invention; Figure 5 is a schematic diagram of the scheme screening module system of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example: Please refer to Figure 1-Appendix Figure 5 This invention provides an indoor space layout optimization system based on data analysis, comprising: The element data import module is used to import interior space data and interior decoration items. The data is used to generate a list of interior items to match, including: The data import unit is used to import the floor area, wall area, ceiling area, and load-bearing wall location of the interior space, as well as to store the length, width, height, and volume data of the measured interior decoration objects. The data classification unit is used to classify the data of interior decoration objects, with the object category as the parent number, the purpose as the child number, and the special characteristics as the label number; The matching scheme generation unit is used to match interior decoration items according to the classification number of the data classification unit, and the matching is based on rationality, and the quantity of decoration items with specific numbers is limited. The matching list generation unit is used to output a list of the numbers and quantities of decorative items; The spatial element construction module is used to simulate and construct data of interior decoration objects and convert them into spatial elements suitable for layout and division, including: The data acquisition unit is used to collect the length, width, height, and volume data of interior decoration items, including furniture and building materials. The simulation construction unit is used to import the length, width, height, and volume data of interior decoration objects and simulate and generate simulated objects. The rectangular element generation unit is used to extend the vertical line of the maximum area of ​​simulated objects that are not decorative building materials, construct the object collision space according to the vertical line, and divide the collision space into rectangular aggregate spatial elements. The space planning module is used to construct a simulated interior space from indoor space data, divide the space, and set up layoutable and non-layoutable areas. Layoutable areas are further categorized to arrange spatial elements. The module constructs a model based on the data of simulated interior decoration objects output by the spatial element construction module. Object-like objects include; The indoor space simulation generation unit is used to generate a two-dimensional or three-dimensional simulated space, including the location of the floor, walls, ceiling and load-bearing walls, based on the imported indoor space data. Interior space partitioning units are used to divide a space into different functional areas based on the location of load-bearing walls, doors, and windows in the simulated space. The area division unit is used to delineate the areas where objects can be placed and the areas where objects are prohibited from being placed within each functional area, based on safety regulations and traffic flow planning principles, and to classify the areas where objects can be placed according to their respective functions. The scheme selection module uses the matching list output by the element data import module to generate layout schemes for the spatial elements constructed by the spatial planning module and the spatial element construction module within the simulated indoor space. It then selects schemes based on a weighted allocation according to livability, including: The spatial scene layout module is used to automatically arrange and combine the spatial elements generated by the spatial element construction module according to their functional classification and place them into the corresponding layoutable areas divided by the spatial planning module, generating multiple initial layout schemes. The residential element weighting unit is used to pre-store or receive user input of preference weights for different layout elements. Weighted elements include, but are not limited to, smooth circulation, space utilization, lighting and ventilation, and aesthetic principles. The weighted decision unit is used to calculate the comprehensive residential suitability score of each initial layout scheme according to the weight configuration in the residential element weight unit, and to sort and filter according to the score; The scheme output unit is used to output one or more of the filtered optimal layout schemes in a two-dimensional format. Output in the form of a 2D diagram or a 3D model.

[0019] Based on the aforementioned data analysis-based indoor space layout optimization system, as another aspect of this application, a data analysis-based indoor space layout optimization method includes the following steps: Step 1: Through the element data import module, input the original structural data of the target interior space and the list of decorative items to be arranged, and obtain the item matching list processed by the system. Step 2: Using the spatial element construction module, convert the decorative object data into rectangular spatial elements with collision volumes. The specific steps for generating the rectangular spatial elements are as follows: S1. Data Acquisition and Simulation: Collect or import the length, width, height, and volume data of interior decoration objects, and generate corresponding three-dimensional simulation objects based on this data; S2. Collision Space Construction: Identify the maximum projection area of ​​the simulated object on the horizontal plane, extend vertical lines from all edge vertices of the area, and construct a three-dimensional collision rectangle space element that can completely enclose the object. During the construction of the space element, when the object is an irregular object, set vertical lines at multiple edge points of the maximum area of ​​the simulated object, and process the maximum value of the object's collision space according to the vertical lines. S3. Spatial Element Extraction: Extract the projection of the three-dimensional collision space cuboid onto the horizontal plane and define it as a two-dimensional rectangular spatial element of the object. S4. Element Information Association: The dimensions of the rectangular spatial element, the classification number of the object to which it belongs, and the special characteristic mark information are associated and stored for subsequent layout planning. Step 3: Using the spatial planning module, construct a simulated space based on the original structural data, and divide it into functional zones and areas that can be laid out and those that cannot. Step 4: Through the scheme selection module, spatial elements are automatically filled into the layoutable area of ​​the simulated space, generating a large number of alternative layout schemes. The layout schemes are generated by using rule-based algorithms or genetic algorithms to arrange spatial elements within the layoutable area. The generation of layout schemes will fully consider the mutual occlusion and collision relationships between simulated objects, and reasonably adjust the shape and size of the rectangular set to ensure the rationality and operability of the spatial elements. Step 5: Based on the preset residential suitability weighting system, conduct a comprehensive evaluation and scoring of all alternative layout schemes; Step 6: Select the best layout schemes based on the scoring results and output them to the user.

[0020] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An indoor space layout optimization system based on data analysis, characterized in that, include: The element data import module is used to import indoor space data and data on indoor decoration items, and output a list of indoor item combinations; The spatial element construction module is used to simulate and construct data of interior decoration objects and convert them into spatial elements suitable for layout and division. The space planning module is used to construct a simulated interior space based on indoor space data, divide the space into layoutable and non-layoutable areas, and classify the layoutable areas to arrange the simulated objects constructed from the data of the simulated interior decoration objects output by the space element construction module. The scheme selection module uses the matching list output by the element data import module to generate layout schemes for the spatial elements constructed by the spatial element construction module in the simulated indoor space constructed by the spatial planning module, and selects schemes based on the residential suitability weight allocation.

2. The indoor space layout optimization system based on data analysis according to claim 1, characterized in that, The feature data import module includes: The data import unit is used to import the floor area, wall area, ceiling area, and load-bearing wall location of the interior space, as well as to store the length, width, height, and volume data of the measured interior decoration objects. The data classification unit is used to classify the data of interior decoration objects, with the object category as the parent number, the purpose as the child number, and the special characteristics as the label number; The scheme generation unit is used to generate interior decoration schemes based on the data classification unit. The items are matched according to their classification numbers, with the matching being based on rationality, and the quantity of decorative items with specific numbers is limited. The matching list generation unit is used to output a list of the numbers and quantities of decorative items.

3. The indoor space layout optimization system based on data analysis according to claim 1, characterized in that, The spatial element construction module includes: The data acquisition unit is used to collect the length, width, height, and volume data of interior decoration items, including furniture and building materials. The simulation construction unit is used to import the length, width, height, and volume data of interior decoration objects and simulate and generate simulated objects. The rectangular element generation unit is used to extend the vertical line of the maximum area of ​​simulated objects that are not decorative building materials, construct the object collision space according to the vertical line, and divide the collision space into rectangular aggregate spatial elements.

4. The indoor space layout optimization system based on data analysis according to claim 1, characterized in that, The spatial planning module includes: The indoor space simulation generation unit is used to generate a two-dimensional or three-dimensional simulated space, including the location of the floor, walls, ceiling and load-bearing walls, based on the imported indoor space data. Interior space partitioning units are used to divide a space into different functional areas based on the location of load-bearing walls, doors, and windows in the simulated space. The area division unit is used to delineate the areas where objects can be placed and the areas where objects are prohibited from being placed within each functional area, based on safety regulations and traffic flow planning principles. The areas where objects can be placed are then classified according to their respective functions.

5. The indoor space layout optimization method based on data analysis as described in claim 1 The chemical system is characterized by, The scheme selection module includes: The spatial scene layout module is used to automatically arrange and combine the spatial elements generated by the spatial element construction module according to their functional classification and place them into the corresponding layoutable areas divided by the spatial planning module, generating multiple initial layout schemes. The residential element weighting unit is used to pre-store or receive user input of preference weights for different layout elements. The weighted elements include, but are not limited to, circulation smoothness, space utilization, lighting and ventilation, and aesthetic principles. The weighted decision unit is used to calculate the comprehensive residential suitability score of each initial layout scheme according to the weight configuration in the residential element weight unit, and to sort and filter according to the score; The scheme output unit is used to output one or more optimal layout schemes after screening in the form of a two-dimensional plan or a three-dimensional model.

6. A data analysis-based method for optimizing indoor space layout, using the data analysis-based indoor space layout optimization system as described in any one of claims 1 to 5, characterized in that, Includes the following steps: Step 1: Through the element data import module, input the original structural data of the target interior space and the list of decorative items to be arranged, and obtain the item matching list processed by the system. Step 2: Using the spatial element construction module, convert the data of decorative objects into rectangular spatial elements with collision volumes; Step 3: Using the spatial planning module, construct a simulated space based on the original structural data, and divide it into functional zones and areas that can be laid out and those that cannot. Step 4: Through the scheme selection module, spatial elements are automatically filled into the layoutable area of ​​the simulated space to generate a large number of alternative layout schemes. Step 5: Based on the preset residential suitability weighting system, conduct a comprehensive evaluation and scoring of all alternative layout schemes; Step 6: Select the best layout schemes based on the scoring results and output them to the user.

7. The indoor space layout optimization method based on data analysis according to claim 6, characterized in that, The specific steps for generating the rectangular spatial elements in step two are as follows: S1. Data Acquisition and Simulation: Collect or import the length, width, height, and volume data of interior decoration objects, and generate corresponding three-dimensional simulation objects based on this data; S2. Collision Space Construction: Identify the maximum projection area of ​​the simulated object on the horizontal plane, extend vertical lines from all edge vertices of the area, and construct a three-dimensional collision rectangle space element that can completely enclose the object. S3. Spatial Element Extraction: Extract the projection of the three-dimensional collision space cuboid onto the horizontal plane and define it as a two-dimensional rectangular spatial element of the object. S4. Element Information Association: The dimensions of the rectangular spatial element, the classification number of the object to which it belongs, and the special characteristic mark information are associated and stored for subsequent layout planning.

8. The indoor space layout optimization method based on data analysis according to claim 6, characterized in that, In the process of constructing the spatial elements in S2, when the object is an irregular object, vertical lines are set at multiple edge points of the maximum area of ​​the simulated object, and the maximum value of the collision space of the object is processed according to the vertical lines.

9. An indoor space layout optimization method based on data analysis as described in claim 6 The method is characterized by, In step four, the layout scheme is generated by using a rule-based algorithm or a genetic algorithm to arrange spatial elements within the layable area.

10. The indoor space layout optimization method based on data analysis according to claim 6, characterized in that, The layout scheme generated in step four will fully consider the mutual occlusion and collision relationships between simulated objects, and reasonably adjust the shape and size of the rectangular set to ensure the rationality and operability of the spatial elements.

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