An indoor design method and system based on image processing technology

Abstract

The present invention provides an interior design method and system based on image processing technology, which relates to the technical field of interior design; by deeply integrating the personalized needs and physical conditions of the elderly, the present invention realizes a highly customized design scheme. Through in-depth analysis of the physical conditions and behavior habits of the elderly and combining historical monitoring data, it not only significantly improves the safety of the indoor space, effectively prevents and reduces potential safety hazards brought by household appliances and the environment, and creates a safe living environment for the elderly. At the same time, based on the dual concerns of safety and comfort, the furniture layout in each area of the indoor space is optimized, providing a more high-quality, safe and comfortable living environment for the elderly.

Description

Technical Field

[0001] The present invention relates to the technical field of interior design, and particularly to an interior design method and system based on image processing technology. Background Art

[0002] With the accelerating aging process of society, the living environment problems of the elderly population have become increasingly prominent. Traditional interior design methods often ignore the special needs and physical conditions of the elderly, resulting in many inconveniences and safety hazards for the elderly at home. Specifically, due to physical limitations such as decreased vision, mobility difficulties, and weakened hearing, the elderly may have difficulty adapting to the conventional furniture layout and home environment in their daily lives. At the same time, with the popularization and complexity of household appliances, the elderly also face problems such as inconvenient operation and increased safety hazards during use.

[0003] First of all, the movement routes and ranges of the elderly at home are unique. Traditional designs often fail to fully consider their daily behavior habits, resulting in unreasonable furniture layouts and increasing the risk of accidents such as falls and collisions. For example, design defects such as narrow passages between furniture and lack of handrails at corners can all become obstacles to the movement of the elderly.

[0004] Secondly, when using household appliances, due to poor eyesight, memory loss, etc., the elderly often make misoperations or forget to turn off the power, which not only affects the service life of household appliances, but also may cause safety hazards such as fires and electric shocks. In addition, the layout positions of some household appliances are unreasonable, such as too high or too low socket positions, inconvenient switch positions, etc., which also bring many inconveniences to the elderly.

[0005] Therefore, it is necessary to provide an interior design method and system based on image processing technology to solve the above technical problems. Summary of the Invention

[0006] To solve the above technical problems, the present invention provides an interior design method and system based on image processing technology to solve the problems of unreasonable furniture layout and safety hazards in the home space.

[0007] The interior design method and system based on image processing technology provided by the present invention, the design method includes the following steps:

[0008] Collect the layout image and three-dimensional space data of the indoor space, and preprocess the layout image to obtain the preprocessed layout image;

[0009] Identify the movement routes and ranges of the elderly according to the monitoring data, divide multiple activity areas, and identify the specific equipment and environment in the activity areas;

[0010] Identify potential safety hazards of household appliances and the environment in each activity area, and assign a comprehensive hazard weight to each activity area respectively;

[0011] Dynamically adjust the furniture layout weight based on the physical conditions and behavior habits of the elderly;

[0012] Integrate the hazard weights and furniture layout weights of each activity area to generate corresponding layout suggestion plans;

[0013] Use the layout suggestion plan as input to generate a 3D model of the indoor space through 3D modeling technology.

[0014] Preferably, the specific steps of collecting the layout image and 3D spatial data of the indoor space and preprocessing the layout image are as follows:

[0015] Take multi-directional photos of the indoor space through a camera device to collect and obtain the layout image, and scan and obtain the 3D point cloud data of the indoor space through a scanning device;

[0016] Preprocess the collected layout image, specifically including denoising, enhancing contrast, and correcting colors;

[0017] Normalize the size of the preprocessed layout image and store it.

[0018] Preferably, the specific steps of identifying the activity routes and scopes of the elderly according to the monitoring data, dividing them into multiple activity areas, and identifying the specific equipment and environment in the activity areas are as follows:

[0019] Collect the daily activity data of the elderly, use a data analysis tool to statistically analyze the collected activity data to obtain statistical results, where the daily activity data specifically includes walking trajectories and staying times;

[0020] Divide the indoor space into different activity areas according to the statistical results;

[0021] In each activity area, identify the specific equipment and environment information, specifically including furniture layout data, safety facility data, lighting data, and floor data.

[0022] Preferably, the specific steps of identifying the potential safety hazards of household appliances and the environment in each activity area and assigning a comprehensive hazard weight to each activity area respectively are as follows:

[0023] Collect the specific equipment and environment information identified in each activity area, and judge the safety hazard level of each activity area through a preset safety parameter threshold section, specifically including judging the equipment safety hazard level and environment information of each activity area respectively;

[0024] Based on the results of judging the safety hazard levels of each activity area, a comprehensive hazard weight is calculated for each activity area in a multiplicative manner.

[0025] Preferably, the specific steps for dynamically adjusting the furniture layout weight based on the physical conditions and behavior habits of the elderly are as follows:

[0026] Obtain the physical condition data and behavior habit data of the elderly. Among them, the physical condition data is specifically the mobility and vision conditions, and the behavior habit data is specifically the wake-up time and dining habits;

[0027] Based on the physical condition data and behavior habit data of the elderly, set the furniture layout weights in different scenarios of each activity area;

[0028] Monitor and identify the changes in the physical conditions and behavior habits of the elderly, and regularly evaluate and adjust the furniture layout weights.

[0029] Preferably, the specific steps for generating the corresponding layout suggestion plan by integrating the hazard weights and furniture layout weights of each activity area are as follows:

[0030] Standardize the hazard weights and furniture layout weights of each activity area to obtain the integrated weight data;

[0031] Input the integrated weight data into a preset genetic algorithm to output multiple candidate layout plans;

[0032] Set evaluation criteria to evaluate and screen the multiple candidate layout plans to obtain the screened layout suggestion plan.

[0033] Preferably, the specific steps for generating a three-dimensional model of the indoor space with the layout suggestion plan as the input through three-dimensional modeling technology are as follows:

[0034] Use the layout suggestion plan as the input and utilize three-dimensional modeling software to construct a three-dimensional model of the indoor space;

[0035] Preview the effect of the three-dimensional model and verify the three-dimensional model. After verification, obtain the final three-dimensional model.

[0036] An indoor design system based on image processing technology, the design system includes:

[0037] An acquisition and processing module, used for acquiring the layout images and three-dimensional space data of the indoor space, and preprocessing the layout images to obtain the preprocessed layout images;

[0038] An identification module, used for identifying the activity routes and ranges of the elderly according to the monitoring data, dividing multiple activity areas, and identifying the specific equipment and environment within the activity areas;

[0039] A weight distribution module, which is used to identify potential safety hazards of household appliances and the environment in each activity area, and assign a comprehensive hazard weight to each activity area respectively;

[0040] A dynamic adjustment module, which is used to dynamically adjust the furniture layout weight based on the physical conditions and behavior habits of the elderly;

[0041] A suggestion generation module, which is used to generate corresponding layout suggestion plans by integrating the hazard weights and furniture layout weights of each activity area;

[0042] A 3D modeling module, which is used to generate a 3D model of the indoor space by taking the layout suggestion plan as input through 3D modeling technology.

[0043] Compared with the related technologies, an indoor design method and system based on image processing technology provided by the present invention has the following beneficial effects:

[0044] By deeply integrating the personalized needs of the elderly with their physical conditions, the present invention realizes a highly customized design plan. Through in-depth analysis of the physical conditions and behavior habits of the elderly and combining historical monitoring data, it not only significantly improves the safety of the indoor space, effectively prevents and reduces potential safety hazards brought by household appliances and the environment, and creates a safe living environment for the elderly. At the same time, based on the dual concerns of safety and comfort, it optimizes the furniture layout in each area of the indoor space and provides a better, safer and more comfortable living environment for the elderly. Brief Description of the Drawings

[0045] Figure 1 It is a flowchart of an indoor design method based on image processing technology of the present invention;

[0046] Figure 2 It is a system block diagram of an indoor design system based on image processing technology of the present invention. Detailed Embodiments

[0047] The present invention will be further described below in conjunction with the drawings and embodiments.

[0048] Embodiment 1

[0049] As Figure 1 shown, an indoor design method based on image processing technology includes the following steps:

[0050] S100. Collect the layout images and 3D space data of the indoor space, and preprocess the layout images to obtain the preprocessed layout images;

[0051] In the specific implementation process, the specific steps of step S100 are:

[0052] S101. Take multi-directional photos of the indoor space through a camera device to collect and obtain layout images, and scan through a scanning device to obtain three-dimensional point cloud data of the indoor space;

[0053] Specifically, take photos of the indoor space through a high-definition camera device, covering all corners and key areas to ensure that complete and detailed indoor layout information can be obtained during subsequent analysis. After collecting the captured layout images, use a three-dimensional laser scanner to scan the indoor space and simultaneously obtain three-dimensional point cloud data of the indoor space.

[0054] S102. Preprocess the collected layout images, specifically including denoising, enhancing contrast, and correcting colors;

[0055] Specifically, eliminate noise in the layout images through Photoshop, and enhance the contrast of the layout images to improve the visual effect of the images and the accuracy of subsequent analysis. And eliminate these deviations through color correction to eliminate the color deviations of the layout images due to factors such as light and color temperature.

[0056] S103. Standardize the size of the preprocessed layout images and store them;

[0057] Specifically, perform size standardization processing on the preprocessed layout images, specifically including setting parameters such as unified resolution, image size, or scaling ratio, etc. Exemplarily, set the resolution of all bedroom layout images to 1920x1080 pixels, or uniformly adjust the width of all images to 1000 pixels.

[0058] S200. Identify the activity routes of the elderly and divide multiple activity areas according to the monitoring data, and identify the specific equipment and environment within the activity areas;

[0059] In the specific implementation process, the specific steps of step S200 are as follows:

[0060] S201. Collect the daily activity data of the elderly, use a data analysis tool to statistically analyze the collected activity data, and obtain statistical results. Among them, the daily activity data specifically includes walking trajectories and staying times;

[0061] Specifically, collect the daily activity data of the elderly through sensors installed indoors, specifically infrared sensors, pressure sensors, and cameras. Import the collected activity data into a data analysis tool, specifically Python, for cleaning, sorting, and analysis, and analyze through cluster analysis in statistical methods to extract key information, such as the areas where the elderly are most active, the average staying time in each area, and the changing trend of activity patterns, etc.

[0062] Exemplarily, the analysis of the extracted key information shows that the elderly spend the longest time in the living room, mainly concentrated in the sofa and TV areas; the nighttime activities in the bedroom are mainly concentrated in the periods of going to bed and getting up.

[0063] S202. Divide the indoor space into different activity areas according to the statistical results;

[0064] Specifically, according to the statistical results and the actual situation of the indoor space, divide the indoor space into different activity areas. The activity areas divided in this embodiment are: rest area, entertainment area, dining area, and bathroom, etc.

[0065] S203. Identify the specific equipment and environmental information in each activity area, specifically including furniture layout data, safety facility data, lighting data, and floor data;

[0066] Specifically, in each activity area, detail the layout and size information of the furniture, specifically including the type, location, orientation, and distance between furniture, etc.; evaluate and identify the safety facilities in each activity area, specifically including emergency call buttons, handrails, and anti-slip floors, etc.; check and record the lighting conditions in each activity area, including light source type, brightness, color temperature, and lighting coverage, etc.; identify the material, flatness, anti-slip performance, and cleaning status of the floor.

[0067] S300. Identify the safety hazards of the household electrical appliances and environment in each activity area, and assign a comprehensive hazard weight to each activity area respectively;

[0068] In the specific implementation process, the specific steps of step S300 are:

[0069] S301. Collect the specific equipment and environmental information identified in each activity area, and judge the safety hazard level of each activity area through a preset safety parameter threshold section, specifically including judging the equipment safety hazard level and environmental information of each activity area respectively;

[0070] Specifically, corresponding to the specific equipment information identified in step S203, use the preset equipment safety parameter threshold section to evaluate the operating status, maintenance conditions, etc. of each piece of equipment, determine its safety hazard level, and assign a corresponding weight value according to the safety hazard level; based on the collected environmental information, according to the preset environmental safety parameter threshold section, specifically the suitable temperature range threshold section, humidity threshold section, and air quality standard threshold section, compare and evaluate the environmental conditions of each activity area, and assign a weight value corresponding to the evaluation value.

[0071] S302. Based on the results of judging the safety hazard levels of each activity area, calculate a comprehensive hazard weight for each activity area in a multiplicative manner;

[0072] Specifically, based on the weight values corresponding to the safety hazard levels obtained in step S301 and the weight values corresponding to the environmental condition evaluation values, multiply the two weight values to obtain the comprehensive hazard weight.

[0073] S400. Dynamically adjust the furniture layout weight based on the physical conditions and behavior habits of the elderly;

[0074] In the specific implementation process, step S400 is specifically as follows:

[0075] S401. Obtain the physical condition data and behavior habit data of the elderly. Among them, the physical condition data is specifically the mobility and vision conditions, and the behavior habit data is specifically the wake-up time and dining habits;

[0076] Extract the physical condition data of the elderly by collecting the data monitored by wearable devices and the data of vision tests; and collect the record data of the eating habits and dining times of the elderly.

[0077] S402. Based on the physical condition data and behavior habit data of the elderly, set the furniture layout weights in different scenarios of each activity area;

[0078] Specifically, according to the functions of the activity areas and the physical condition data and behavior habit data of the elderly, set different usage scenarios. In this embodiment, it is set as the rest scenario in the bedroom, the entertainment scenario in the living room, and the cooking scenario in the kitchen, etc., and set weights for the furniture layout in each scenario. In this embodiment, in the rest scenario in the bedroom, if the mobility of the elderly is poor, then increase the weight of the position of the bed close to the door or the bathroom, and increase the weight of the brightness of the night lighting.

[0079] S403. Monitor and identify changes in the physical conditions and behavior habits of the elderly, and regularly evaluate and adjust the furniture layout weights;

[0080] Specifically, regularly monitor the physical conditions and behavior habits of the elderly to identify any potential changes, and analyze the impact of the changes in physical conditions and behavior habits on the furniture layout through existing data analysis methods. According to the evaluation results, the furniture layout weights can be selectively adjusted manually or automatically to obtain the adjusted furniture layout weights.

[0081] S500. Integrate the hazard weights and furniture layout weights of each activity area to generate corresponding layout suggestion plans;

[0082] In the specific implementation process, the specific steps of step S500 are as follows:

[0083] S501. Standardize the hazard weights and furniture layout weights of each activity area to obtain the integrated weight data;

[0084] Specifically, use the Min-Max Scaling or Z-score standardization method to convert the hazard weights and furniture layout weights of each activity area into dimensionless values and integrate them to obtain the integrated weight data.

[0085] S502. Input the integrated weight data into a preset genetic algorithm and output multiple candidate layout plans;

[0086] Specifically, set the parameters of the genetic algorithm, including the population size, crossover rate, mutation rate, number of iterations, etc., and use the integrated weight data obtained in step 501 as the input of the genetic algorithm. The genetic algorithm generates multiple candidate layout plans through an iterative process (selection, crossover, mutation), where each candidate layout plan is a specific combination of layout parameters such as the position and direction of the furniture.

[0087] S503. Set evaluation criteria, evaluate and screen multiple candidate layout plans to obtain the screened layout suggestion plan;

[0088] Specifically, set the evaluation criteria for specific traffic convenience, line of sight accessibility, reduction of safety hazards, and space comfort, evaluate each candidate layout plan, calculate its score for meeting the evaluation criteria, and screen according to the score. Select the layout plan with the highest score or meeting specific conditions as the final layout suggestion plan.

[0089] S600. Use the layout suggestion plan as the input and generate a 3D model of the indoor space through 3D modeling technology;

[0090] In the specific implementation process, step S600 is specifically:

[0091] S601. Use the layout suggestion plan as the input and construct a 3D model of the indoor space using 3D modeling software;

[0092] Specifically, use the layout suggestion plan as the input, which specifically includes detailed information such as the position, direction, and size of the furniture. At the same time, input the collected 3D space data and use any one of the 3D modeling software such as SketchUp, AutoCAD, or 3ds Max to construct a 3D model of the indoor space.

[0093] S602. Preview the effect of the 3D model and verify the 3D model. After verification, obtain the final 3D model;

[0094] Specifically, through the preview function of 3D modeling software, view the 3D model effect of the indoor space from different angles and perspectives, check whether the dimensions of the furniture and the space in the 3D modeling are consistent with the dimensions in the layout suggestion plan. After verifying that the dimensions are correct, the final 3D model is obtained.

[0095] Embodiment 2

[0096] As Figure 2 shown, an indoor design system based on image processing technology applied to an indoor design method based on image processing technology, wherein the design system includes:

[0097] An acquisition and processing module, configured to acquire the layout image and 3D space data of the indoor space, and preprocess the layout image to obtain the preprocessed layout image;

[0098] Specifically, the acquisition and processing module collects the layout image of the indoor space acquired by devices such as high-definition cameras or scanners, and the 3D space data obtained by devices such as lidar or depth cameras; and preprocesses the acquired layout image, including image denoising, contrast enhancement, edge detection, etc., to improve the image quality.

[0099] An identification module, configured to identify the activity routes of the elderly and divide multiple activity areas according to the monitoring data, and identify the specific devices and environment within the activity areas;

[0100] Specifically, the identification module monitors the activities of the elderly through a sensor network (specifically infrared sensors, pressure sensors, etc.), records their activity routes and staying times, and according to the monitoring data, identifies the areas where the elderly frequently move, and divides multiple activity areas accordingly; within each divided activity area, use image recognition technology to identify the specific device and environment information, specifically the furniture position, the type of electrical appliances, the lighting conditions, etc.

[0101] A weight assignment module, configured to identify the potential safety hazards of the household electrical appliances and the environment in each activity area, and assign a comprehensive hazard weight to each activity area respectively;

[0102] Specifically, the weight assignment module uses a preset safety parameter threshold range to evaluate the potential safety hazards of the household electrical appliances in each activity area, specifically the aging degree of the electrical appliances, the rationality of the socket layout, etc. At the same time, evaluate the environmental factors of the activity area, such as the wetness degree of the ground, the lighting brightness, etc. According to the potential safety hazard evaluation results, assign a comprehensive hazard weight to each activity area by means of multiplication, where the hazard weight reflects the safety risk level of this area.

[0103] A dynamic adjustment module, configured to dynamically adjust the furniture layout weight based on the physical conditions and behavior habits of the elderly;

[0104] Specifically, regularly monitor the physical conditions of the elderly, specifically mobility, vision conditions, etc., and behavior habits, specifically wake-up time, dining habits, etc. Set different usage scenarios according to the monitoring results, and the furniture layout weights for each set usage scenario are different. Exemplarily, in the rest scenario in the bedroom, if the elderly have poor mobility, then increase the weight of the position of the bed close to the door or the bathroom, and increase the weight of the brightness of the night lighting.

[0105] A suggestion generation module, configured to generate a corresponding layout suggestion plan by integrating the hidden danger weights and furniture layout weights of each activity area;

[0106] Specifically, integrate the hidden danger weights and furniture layout weights of each activity area, and calculate the optimal layout suggestion plan through a genetic algorithm.

[0107] A three-dimensional modeling module, configured to use the layout suggestion plan as an input and generate a three-dimensional model of the indoor space through three-dimensional modeling technology.

[0108] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more flows and / or Figure 1 blocks or multiple blocks.

[0109] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program, and this program can be stored in a computer-readable storage medium. The storage medium includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc memories, magnetic disc memories, tape memories, or any other medium that can be used to carry or store data and is computer-readable.

[0110] It should also be noted that the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device comprising a series of elements not only includes those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the existence of another identical element in the process, method, commodity or device comprising the element.

Claims

1. An interior design method based on image processing technology, characterized in that: The design method comprises the following steps: Collecting layout images and three-dimensional space data of the indoor space, and preprocessing the layout images to obtain preprocessed layout images; Identify the activity routes and ranges of the elderly based on monitoring data and divide them into multiple activity areas, and identify the specific equipment and environment in the activity areas; Identify the safety hazards of household appliances and environment in each activity area, and assign comprehensive hazard weights to each activity area; Dynamically adjust the weight of furniture layout based on the physical conditions and behavioral habits of the elderly; The hidden danger weights and furniture layout weights of each activity area are combined to generate corresponding layout suggestions; Taking the layout proposal as input, a 3D model of the interior space is generated through 3D modeling technology; The specific steps of identifying the potential safety hazards of household appliances and environment in each activity area and assigning a comprehensive potential safety hazard weight to each activity area are as follows: Collect specific equipment and environmental information identified in each activity area, and judge the safety hazard level of each activity area through the preset safety parameter threshold section, specifically including judging the equipment safety hazard level and environmental information of each activity area respectively; Based on the results of the safety hazard level judgment of each activity area, a comprehensive hazard weight is calculated for each activity area in a multiplication manner; The specific steps of dynamically adjusting the furniture layout weight based on the physical condition and behavioral habits of the elderly are as follows: Obtaining the physical condition data and behavioral habit data of the elderly, wherein the physical condition data specifically includes mobility and vision status, and the behavioral habit data specifically includes waking time and dining habits; Based on the physical condition and behavioral habit data of the elderly, the weights of furniture layout in different scenes of each activity area are set; Monitor and identify changes in the physical conditions and behavioral habits of the elderly, and regularly evaluate and adjust the weight of furniture layout.

2. The interior design method based on image processing technology according to claim 1, characterized in that: The specific steps of collecting the layout image and three-dimensional space data of the indoor space and preprocessing the layout image to obtain the preprocessed layout image are: The indoor space is photographed from all angles by using a camera device to acquire layout images, and the indoor space is scanned by a scanning device to acquire three-dimensional point cloud data; Preprocessing the collected layout images, including denoising, contrast enhancement and color correction; The preprocessed layout images are size-standardized and stored.

3. The interior design method based on image processing technology according to claim 1, characterized in that: The specific steps of identifying the activity routes and ranges of the elderly according to the monitoring data, dividing into multiple activity areas, and identifying the specific equipment and environment in the activity areas are as follows: Collect daily activity data of the elderly, and use data analysis tools to collect statistics on the collected activity data to obtain statistical results, where the daily activity data specifically includes walking tracks and stay time; According to the statistical results, the indoor space is divided into different activity areas; In each activity area, specific equipment and environmental information is identified, including furniture layout data, safety facility data, lighting data, and ground data.

4. The interior design method based on image processing technology according to claim 1, characterized in that: The specific steps of generating the corresponding layout suggestion scheme by combining the hidden danger weights and furniture layout weights of each activity area are as follows: The hidden danger weights and furniture layout weights of each activity area are standardized to obtain integrated weight data; The integrated weight data is input into a preset genetic algorithm to output multiple candidate layout solutions; Evaluation criteria are set to evaluate and screen multiple candidate layout solutions to obtain screened layout recommendation solutions.

5. The interior design method based on image processing technology according to claim 1, characterized in that: The specific steps of generating a 3D model of the indoor space by using the 3D modeling technology with the layout suggestion as input are as follows: Taking the layout proposal as input, a 3D model of the interior space is constructed using 3D modeling software; Preview the effect of the 3D model and verify the 3D model to obtain the final 3D model after verification.

6. An interior design system based on image processing technology, applied to an interior design method based on image processing technology according to any one of claims 1 to 5, characterized in that: The design system includes: The acquisition and processing module is used to acquire the layout image and three-dimensional space data of the indoor space, and pre-process the layout image to obtain the pre-processed layout image; An identification module is used to identify the activity routes and ranges of the elderly according to the monitoring data, divide them into multiple activity areas, and identify the specific equipment and environment in the activity areas; A weight allocation module is used to identify the safety hazards of household appliances and the environment in each activity area, and assign a comprehensive hazard weight to each activity area; Dynamic adjustment module, used to dynamically adjust the furniture layout weight based on the physical conditions and behavioral habits of the elderly; The suggestion generation module is used to integrate the hidden danger weights and furniture layout weights of each activity area to generate corresponding layout suggestion plans; The 3D modeling module is used to generate a 3D model of the indoor space through 3D modeling technology using the layout suggestion plan as input.

Images