Indoor space layout optimization system based on data analysis

Abstract

The invention discloses an indoor space layout optimization system based on data analysis, which relates to the technical field of indoor space layout optimization and comprises an indoor space acquisition module, a space analysis module, a data analysis module and an optimization execution module. An existing system has the main defects that an algorithm model often depends too much on historical data, and accurate prediction of future trends and personalized requirements is lacked; meanwhile, a user interaction interface of the system is relatively complex, the operation threshold is high, and wide application of the system is limited; according to the invention, by analyzing the user demand and the space use behavior and combining various influence factors, various optimization schemes are provided for the user, and the problems of different scenes and demands are met; through calculation and combination of various influence factors, various optimization schemes are generated, and the diversified schemes enable the user to select the layout scheme which most meets the requirements according to personal preferences and use scenes, so that the space utilization efficiency and the living experience are further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of indoor space layout optimization, and in particular to an indoor space layout optimization system based on data analysis. Background Art

[0002] Existing indoor space layout optimization systems based on data analysis usually collect data such as human traffic, lighting, air quality, etc. in the space and combine them with algorithm models to optimize the space layout. Such systems are widely used in commercial spaces, office buildings, public places, etc., and can improve space utilization efficiency and enhance user experience.

[0003] However, the main defects of the existing system are: the data collection is not comprehensive and accurate enough, making it difficult to reflect spatial dynamic changes in real time; the algorithm model is often too dependent on historical data and lacks accurate predictions of future trends and personalized needs; at the same time, the system's user interaction interface is relatively complex and the operation threshold is high, which limits its wide application. Summary of the invention

[0004] The purpose of the present invention is to solve the above-mentioned problems and to propose an indoor space layout optimization system based on data analysis.

[0005] The object of the present invention can be achieved by the following technical solutions: an indoor space layout optimization system based on data analysis, comprising a space analysis module, a data analysis module and an optimization execution module;

[0006] The spatial analysis module is used to analyze the spatial structure data and the indoor items and furniture data, collect the geometric dimensions and three-dimensional model data of the room through measurement tools, including the specific dimensions of the walls, floors, and ceilings; construct an indoor three-dimensional model with the three-dimensional model data, and import the architectural design drawings of the room into the constructed indoor three-dimensional model to determine the specific furniture in the room;

[0007] The data analysis module is used to analyze the indoor space layout, specifically:

[0008] Divide the indoor functional areas based on the collected architectural design drawing information: By analyzing the design drawings, identify the structure and boundaries of the room, including the physical boundaries of walls, columns, doors, and windows, mark the boundaries of traffic flow lines, and mark the structure as the preliminary dividing line of the functional area;

[0009] Analyze the impact of equipment layout on functional areas, obtain the score of each equipment factor, and comprehensively calculate the score of each equipment factor to obtain the overall impact coefficient of the equipment layout functional area;

[0010] Make a preliminary division of room function identification; the preliminary division of functional areas is consistent with the purpose of room design; according to the design of door and corridor traffic flow lines, divide the main channel area and secondary channel area, and ensure the smooth and reasonable traffic in the space, and make preliminary division confirmation analysis on this basis:

[0011] Analyze the noise and sound insulation effect to get the total noise level inside the bedroom; analyze the light brightness to get the light intensity; analyze the area to get the area requirement value; and comprehensively calculate all factors to get the preliminary division confirmation value of the room;

[0012] The optimization execution module obtains the step division confirmation value and the overall influence coefficient of the equipment layout functional area for combined analysis to generate multiple overall influence coefficient combination optimization solutions.

[0013] As a preferred embodiment of the present invention, it also includes an indoor space acquisition module; the indoor space acquisition module is used to obtain indoor space data, which includes space structure data, indoor items and furniture data, space usage behavior data, space perception data and user input data; and obtain the source of environment and usage data through various sensors installed indoors; then use laser scanning technology to obtain high-precision three-dimensional indoor space data, accurately measure room dimensions and furniture positions; and obtain accurate space structure information on building design drawings, equipment layout, and material usage through building information models.

[0014] As a preferred embodiment of the present invention, the specific process of constructing an indoor three-dimensional model with the three-dimensional model data, importing the architectural design drawings of the room into the indoor three-dimensional model, and determining the specific furniture in the room is as follows:

[0015] Construct several position points on the indoor wall, ground or ceiling of the required area corresponding to the indoor 3D model, and then connect each point with the surrounding adjacent position points to obtain a grid structure; calculate the distance between each position point in the grid model and the surrounding adjacent position points, select a fixed point in the point set model as the XYZ coordinate system, and use the formula: Output the distance d between position point i and the surrounding adjacent position point j ij , and (x i ,y i , z i ) and (x j ,y j , z j ) are the three-dimensional coordinates of the position point i and the surrounding adjacent position point j, and the sum of the distances d between the position point and the surrounding adjacent position points is calculated by the formula Output the sum dz of the position point and its surrounding adjacent positions, where N is the total number of the position points surrounding the position point. The sum dz of each position point and its surrounding adjacent positions and the total mean dJ of each position point and its surrounding adjacent positions in the grid structure are obtained, and then dz is compared with dJ. If dz is greater than dJ, the corresponding position point is marked; the marked position point is obtained by marking the marked contour, and the marked contour feature is analyzed. According to the design drawings of the room, the area, length, width, height of the corresponding wall, floor and ceiling in the room and the proportion of the marked contour in the indoor three-dimensional model are obtained to obtain the size of the marked contour; the marked contour feature and the corresponding size are compared with the standard furniture model library. If the overlap rate of the compared contour features reaches 90% and the corresponding size matching rate reaches 95%, the contour feature is determined to be the model corresponding to the standard furniture model library, and the indoor furniture is determined.

[0016] As a preferred implementation of the present invention, the specific process of comprehensively calculating the score of each equipment factor to obtain the overall influence coefficient of the equipment layout functional area is:

[0017] By obtaining the score of each equipment factor; L is the lighting impact score, by the formula: Among them, I l is the ideal lighting intensity required for the area, I s is the actual collected illumination intensity, D L is the distance factor of equipment layout on lighting; V is the ventilation impact score, which is given by the formula: Among them, V l is the ideal ventilation volume required for the area, V s is the actual collected ventilation volume, D V is the distance factor of equipment layout on ventilation; P is obtained by analogy, where P is the power supply impact score; N is the noise interference impact score, and the formula is: V = N s ×D V , where N s is the actual noise level generated, D N It is the distance factor between the equipment and the noise source; the score of each equipment factor is calculated comprehensively to obtain the overall influence coefficient SYZ of the functional area of ​​the equipment layout.

[0018] As a preferred embodiment of the present invention, the specific process of comprehensively calculating all factors to obtain the preliminary division confirmation value of the room is as follows:

[0019] Analysis of noise and sound insulation effect, according to the formula: Output the total noise level inside the bedroom ZYZ, where Z1 is the noise level of the external noise source; Z2 is the noise inside the bedroom, Z i is the noise of the ith device or environmental source, n is the number of noise sources; X is the impact value of the room sound insulation effect, Among them, A j is the area of ​​the jth material, α j is the sound absorption coefficient of the jth material, RF is the room sound insulation performance coefficient; for the light brightness analysis, the formula Output light intensity GQZ, Cm is the window area, GQ is the light intensity outside the window, Cf is the room area, Tg is the light transmittance of the window, RZ is the reflection coefficient of the wall and ceiling in the room; and by considering the influence of the incident angle of light, the actual available light brightness B in the room is output through the formula: B = GQZ × Gc × cos (θ), Gc is the light direction coefficient, θ is the incident angle of light and the window surface; analyze the area, by determining the area required for the basic functional area, the number of bedrooms in the room and the expected number of people living in the room, as well as the additional area required for other functions; output the area requirement value M through the formula: M = JM + (Rs × Rm) + Mq, JM is the area value required for the basic functional area, Rs is the expected number of people living in the room, Rm is the number of bedrooms in the room, and Mq is the additional area value required for other functional requirements;

[0020] All factors are calculated comprehensively to obtain the preliminary confirmation value of the room division, specifically through:

[0021] CBQZ=ZYZ×a1+X×a2+GQZ×a3+B×a4+M×a5 outputs the preliminary division confirmation value CBQZ, where a1, a2, a3, a4 and a5 are all weight coefficients of the corresponding factors.

[0022] As a preferred embodiment of the present invention, the specific process of obtaining the step division confirmation value and the overall influence coefficient of the equipment layout functional area and combining the analysis is:

[0023] By calculating the step-division confirmation value and the overall influence coefficient SYZ of the functional area of ​​the equipment layout, the current status of each area in terms of functional division and equipment layout is determined; the two indicators are linearly combined to generate an optimization objective function YHS, YHZ = σ × CBQZ + τ × SYZ, where σ and τ are weight coefficients, which are used to express the preference for the rationality of the functional area and the influence of the equipment layout;

[0024] Optimize the design of functional areas and equipment layout, and generate different optimization schemes based on different combination strategies: change the proportion of σ and τ to generate different optimization schemes; display the advantages and disadvantages of different optimization schemes for users to choose.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] 1. The present invention intelligently divides functional areas by analyzing user needs and space usage behavior. The optimization scheme can be adjusted according to factors such as lighting, ventilation, and noise, so that the layout of each room is more in line with actual needs and improves living or use comfort; for example, the noise level and lighting optimization of the bedroom can effectively improve sleep quality, and the layout of the public area can improve usage efficiency.

[0027] 2. The present invention can not only collect spatial data in real time through sensors and LIDAR technology, but also generate multiple optimization schemes by calculating and combining multiple influencing factors, such as equipment layout, space division, etc.; users can choose different schemes according to their needs, such as schemes that focus more on functional area division or equipment energy efficiency optimization; this diversified scheme enables users to choose the layout scheme that best meets their needs based on personal preferences and usage scenarios, thereby further improving space utilization efficiency and living experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0029] Figure 1 It is a principle block diagram of the present invention;

[0030] Figure 2 It is the front view of the hypothetical indoor model of the present invention;

[0031] Figure 3 A top view of a hypothetical indoor model of the present invention;

[0032] Description of the drawings: 1-aisle window frame; 2-aisle floor; 3-indoor window frame one; 4-structural column one; 5-indoor window frame two; 6-indoor window frame three; 7-indoor drain outlet; 8-structural column two; 9-indoor window frame four; 10-structural column three; 11-indoor wall; 12-indoor floor, 13-door frame. DETAILED DESCRIPTION

[0033] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] It should be understood that the terms “include” and “comprising” used in the specification and claims of the present disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0035] It should also be understood that the terms used in this disclosure are only for the purpose of describing specific embodiments and are not intended to limit the disclosure. As used in this disclosure and claims, the singular forms of "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise. It should also be further understood that the term "and / or" used in this disclosure and claims refers to any combination of one or more of the associated listed items and all possible combinations, including these combinations.

[0036] See also Figure 1 As shown, an indoor space system based on data analysis includes an indoor space acquisition module, a space analysis module, a data analysis module and an optimization execution module;

[0037] See also Figure 2 , 3 As shown, the indoor space acquisition module is used to obtain indoor space data, including space structure data, indoor items and furniture data, space usage behavior data, space perception data and user input data; and obtain the main source of environment and usage data through various sensors installed indoors (light, temperature and humidity, infrared, noise, etc.); then use laser scanning technology (such as LIDAR) to obtain high-precision indoor space three-dimensional data, accurately measure room dimensions, furniture positions, etc.; through Building Information Modeling (BIM), obtain accurate space structure information such as building design drawings, equipment layout, material usage, etc.; it should be noted that user input data is through mobile applications or system interfaces, and users can manually input their needs, preferences and feedback on the use of space;

[0038] The spatial analysis module analyzes the spatial structure data and the indoor objects and furniture data, specifically:

[0039] Through measuring tools such as laser radar (LIDAR), infrared sensors, and rangefinders, the geometric dimensions (such as length, width, and height) and 3D model data of the room, including the specific dimensions of the walls, floors, and ceilings, are collected; the indoor 3D model is constructed based on the 3D model data, and the architectural design drawings of the room are imported, including detailed information such as the location of doors and windows, structural support points, and load-bearing walls;

[0040] Based on the constructed indoor 3D model, the indoor 3D model is divided into corresponding demand areas according to user needs, and the corresponding demand areas are displayed in the indoor 3D model; then the flatness of the indoor walls, floors and ceilings in the indoor 3D model is measured, specifically: a number of position points are constructed on the indoor walls, floors or ceilings of the demand areas corresponding to the indoor 3D model, and each point is connected with the surrounding adjacent position points to obtain a grid structure; then the distance between each position point in the grid model and the surrounding adjacent position points is calculated, and a fixed point is selected in the point set model as the XYZ coordinate system, and then the formula is used: Output the distance d between position point i and the surrounding adjacent position point j ij , and (x i ,y i , z i ) and (x j ,y j , z j ) are the three-dimensional coordinates of the position point i and the surrounding adjacent position points j, i = 1, 2, 3, ..., n, j = 1, 2, 3, ..., n; then the sum of the distances d between the position point and the surrounding adjacent position points is calculated by the formula Output the sum dz of the position point and its neighboring position points, where N is the total number of the position points neighboring the position point, L = 1, 2, 3, ..., N; obtain the sum dz of each position point and its neighboring position points and the total mean dJ of each position point and its neighboring position points in the grid structure, and then compare dz with dJ. If dz is greater than dJ, the corresponding position point will be marked; otherwise, it will not be marked;

[0041] Next, the marked position points are analyzed to obtain the marked contour, and the marked contour features are analyzed. According to the design drawings of the room, the area, length, width, height of the corresponding wall, floor and ceiling in the room and the proportion of the marked contour in the indoor three-dimensional model are obtained to obtain the size of the marked contour; the marked contour features and the corresponding size are compared with the standard furniture model library. If the overlap rate of the compared contour features reaches 90% and the corresponding size matching rate reaches 95%, it is determined that the contour feature is the model corresponding to the standard furniture model library, and the specific furniture in the room (such as tables, sofas, cabinets, etc.) is determined;

[0042] The data analysis module is used to analyze the indoor space layout, specifically:

[0043] Based on the collected accurate spatial structure information such as architectural design drawings, equipment layout, material usage, etc., the drawings provide accurate information about the building framework such as walls, doors and windows, structural columns, beams, etc., and divide the indoor functional areas (before dividing the space, the system needs to understand the owner's intention for the use of the space, such as whether certain areas are used as public spaces, whether certain rooms have special functional requirements, etc.);

[0044] By making a preliminary functional area division: By analyzing the design drawings, the main structures and boundaries of the room are identified, including physical boundaries such as walls, columns, doors, windows, etc. It is also necessary to mark the boundaries of the traffic flow lines (traffic routes) and mark these structures as the preliminary dividing lines of the functional areas; it should be noted that on the design drawings: such as corridors, doorways, etc., these are the key parts of the indoor traffic flow lines and cannot be blocked by furniture or other functional areas; such as the paths connecting the functional areas inside the room, ensure that people can move easily in the space; for example, the traffic line between the kitchen and the dining room should be short and smooth, and the passage between the bedroom and the bathroom should be convenient and hidden;

[0045] Analyze the impact of equipment layout on functional areas; for example, the location of air-conditioning outlets, drainage pipes, and power sockets will affect the layout of furniture, which in turn affects the division of functional areas; for example, the kitchen area needs to be divided based on the location of water pipes and exhaust systems; specifically, analyze:

[0046] By obtaining the score of each equipment factor (L, V, P, N); L is the lighting impact score, by the formula: Among them, I l is the ideal lighting intensity required for the area, I s is the actual collected illumination intensity, D L is the distance factor of the equipment layout on the lighting. The closer the distance, the higher the score. The score decreases when the distance is farther or unevenly distributed. V is the ventilation impact score, which is given by the formula: Among them, V l is the ideal ventilation volume required for the area, V s is the actual collected ventilation volume, D V It is the distance factor of equipment layout on ventilation, reflecting the distance between ventilation equipment and target area; P is obtained by analogy, where P is the power supply impact score; N is the noise interference impact score, which is calculated by the formula: V = N s ×D V , where N s is the actual noise level generated (the greater the noise, the lower the impact score), D N It is the distance factor between the device and the noise source. The farther the distance is, the higher the score is. The impact increases when the device is close to the functional area.

[0047] Then, the score of each equipment factor (L, V, P, N) is calculated comprehensively, and the overall influence coefficient SYZ of the equipment layout functional area is output through the formula: SYZ = L×L'+V×V'+P×P'+N×N', where L', V', P', and N' are weight coefficients of different equipment factors respectively (the weights can be set according to demand or actual design requirements); SYZ is compared with the influence interval of the equipment layout on the functional area. If SYZ belongs to the influence interval of the corresponding equipment layout functional area, it is a normal layout; if SYZ does not belong to the influence interval of the corresponding equipment layout functional area, and is less than the influence interval of the corresponding equipment layout functional area, it is an excellent layout; if SYZ does not belong to the influence interval of the corresponding equipment layout functional area, and is greater than the influence interval of the corresponding equipment layout functional area, it is a poor layout;

[0048] Then, make a preliminary division by identifying the room functions (such as bedroom, kitchen, living room, etc.); the preliminary division of functional areas is consistent with the purpose of the room design; according to the design of traffic flow lines such as doors and corridors, divide the main channel area and the secondary channel area, and ensure the smooth and reasonable traffic in the space. On this basis, make a preliminary division confirmation analysis:

[0049] Analysis of noise and sound insulation effect: The impact of noise on the bedroom mainly comes from the external environment and internal equipment, so it is necessary to calculate the noise and sound insulation effect. The noise level is calculated by the formula: Output the total noise level inside the bedroom ZYZ, where Z1 is the noise level of the external noise source (for example, traffic noise, construction, etc.); Z2 is the noise inside the bedroom (for example, the noise generated by air conditioners, televisions, etc.), and Z i is the noise of the ith device or environmental source, n is the number of noise sources; X is the impact value of the room sound insulation effect, Among them, A j is the area of ​​the jth material (such as carpets, curtains, etc.), α jis the sound absorption coefficient of the jth material (such as the sound absorption coefficient of carpet is usually higher), RF is the room sound insulation performance coefficient (specifically, by placing a sound pressure meter outside the room, recording the sound pressure level F1 on one side of the sound source, and then placing another sound pressure meter at the corresponding position in the room, recording the sound pressure level F2 after passing through the room enclosure structure, and outputting the preliminary room sound insulation coefficient R through the formula: R=F1-F2, and then collecting and calculating the preliminary room sound insulation coefficient R at different positions inside and outside the room, obtaining multiple preliminary room sound insulation coefficients R, calculating the average sound insulation coefficient, and using the average sound insulation coefficient as the room sound insulation performance coefficient RF); comparing the obtained total noise level ZYZ inside the bedroom with the preset ideal noise level thresholds LYZ1 and LYZ2 (LYZ1<LYZ2) of the bedroom, if ZYZ>LYZ1, the bedroom noise level is judged to be in an excellent state; if ZYZ≥LYZ1, ZYZ≤LYZ2, the bedroom noise level is judged to be in an ideal state; if ZYZ<LYZ2, the bedroom noise level is judged to be in a poor state;

[0050] For light brightness analysis, by calculating the light intensity, the formula

[0051] Output light intensity GQZ, Cm is the window area, GQ is the light intensity outside the window, Cf is the room area, Tg is the light transmittance of the window, RZ is the reflection coefficient of the wall and ceiling in the room; and by considering the influence of the incident angle of the light, the actual available light brightness B in the room is output through the formula: B = GQZ × Gc × cos (θ), Gc is the light direction coefficient (positive for the sun and negative for the shade, the value range is usually 0 to 1), θ is the incident angle (degrees) of the light and the window surface;

[0052] Then the area is analyzed. After the area analysis, the area required for the basic functional area (such as the minimum requirements for bedrooms, kitchens, etc.), the number of bedrooms in the room, the expected number of people living in the room, and the additional area required according to other functional requirements (such as storage space, furniture arrangement, etc.) are determined; it should be noted that all of them are obtained by asking the user; and the area requirement value M is output through the formula: M=JM+(Rs×Rm)+Mq, where JM is the area value required for the basic functional area, Rs is the expected number of people living in the room, Rm is the number of bedrooms in the room, and Mq is the additional area value required for other functional requirements;

[0053] Then all factors are calculated comprehensively to get the preliminary division confirmation value of the room, specifically through:

[0054] CBQZ=ZYZ×a1+X×a2+GQZ×a3+B×a4+M×a5 outputs the preliminary classification confirmation value CBQZ, where a1, a2, a3, a4 and a5 are weight coefficients of corresponding factors, which are set according to actual usage requirements and comfort, and the sum is 1;

[0055] The optimization execution module obtains the step division confirmation value CBQZ and the overall influence coefficient SYZ of the equipment layout functional area for combined analysis, and generates a variety of overall influence coefficient combination optimization schemes, specifically:

[0056] According to the calculation results of CBQZ and SYZ, the current status of each area in terms of functional division and equipment layout is first determined; the two indicators are linearly combined to generate an optimization objective function YHS, YHZ = σ × CBQZ + τ × SYZ, σ and τ are weight coefficients, which are used to express the preference for the rationality of functional areas and the impact of equipment layout; in order to optimize the design of functional areas and equipment layout, different optimization schemes can be generated based on different combination strategies: the proportion of σ and τ is changed to generate different optimization schemes; for example, the weight of σ can be increased to prioritize the rationality of functional division, or the weight of τ can be increased to prioritize the impact of equipment layout; and the advantages and disadvantages of different optimization schemes are displayed for users to choose; for example: a certain scheme focuses on the reasonable division of functional areas, especially in terms of room use, light, noise, etc., to ensure that the functionality and living comfort of each room reach a high level. Advantages: the spatial layout is more in line with living or use needs; the living comfort is high, especially factors such as noise and lighting are optimized; Disadvantages: the energy efficiency optimization of equipment layout is weak, which may lead to higher energy consumption; the location of equipment may affect the convenience and efficiency of space.

[0057] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An indoor space layout optimization system based on data analysis, comprising a space analysis module, a data analysis module and an optimization execution module; characterized in that: The spatial analysis module is used to analyze the spatial structure data and the indoor items and furniture data, collect the geometric dimensions and three-dimensional model data of the room through measurement tools, including the specific dimensions of the walls, floors, and ceilings; construct an indoor three-dimensional model with the three-dimensional model data, and import the architectural design drawings of the room into the constructed indoor three-dimensional model to determine the specific furniture in the room; The data analysis module is used to analyze the indoor space layout, specifically: Divide the indoor functional areas based on the collected architectural design drawing information: By analyzing the design drawings, identify the structure and boundaries of the room, including the physical boundaries of walls, columns, doors, and windows, mark the boundaries of traffic flow lines, and mark the structure as the preliminary dividing line of the functional area; Analyze the impact of equipment layout on functional areas, obtain the score of each equipment factor, and comprehensively calculate the score of each equipment factor to obtain the overall impact coefficient of the equipment layout functional area; Make a preliminary division of room function identification; the preliminary division of functional areas is consistent with the purpose of room design; according to the design of door and corridor traffic flow lines, divide the main channel area and secondary channel area, and ensure the smooth and reasonable traffic in the space, and make preliminary division confirmation analysis on this basis: Analyze the noise and sound insulation effect to get the total noise level inside the bedroom; analyze the light brightness to get the light intensity; analyze the area to get the area requirement value; and comprehensively calculate all factors to get the preliminary division confirmation value of the room; The optimization execution module obtains the step division confirmation value and the overall influence coefficient of the equipment layout functional area for combined analysis to generate multiple overall influence coefficient combination optimization solutions.

2. The indoor space layout optimization system based on data analysis according to claim 1, characterized in that: It also includes an indoor space acquisition module; the indoor space acquisition module is used to acquire indoor space data, which includes space structure data, indoor items and furniture data, space use behavior data, space perception data and user input data; The environment and usage data are obtained through various sensors installed indoors. Laser scanning technology is then used to obtain high-precision three-dimensional data of indoor spaces and accurately measure room dimensions and furniture positions. Through the building information model, accurate spatial structure information of the building's design drawings, equipment layout, and material usage can be obtained.

3. The indoor space layout optimization system based on data analysis according to claim 1, characterized in that: The specific process of constructing an indoor three-dimensional model with the three-dimensional model data, and importing the architectural design drawings of the room into the indoor three-dimensional model, and determining the specific furniture in the room is as follows: Construct several position points on the indoor wall, floor or ceiling of the required area corresponding to the indoor 3D model, and then connect each point with the surrounding adjacent position points to obtain a grid structure; calculate the distance between each position point in the grid model and the surrounding adjacent position points, select a fixed point in the point set model as the XYZ coordinate system, and use the formula: Output the distance d between position point i and the surrounding adjacent position point j ij , and (x i ,y i , z i ) and (x j ,y j , z j ) are the three-dimensional coordinates of the position point i and the surrounding adjacent position point j, and the sum of the distances d between the position point and the surrounding adjacent position points is calculated by the formula Output the sum dz of the position point and its surrounding adjacent positions, where N is the total number of the position points surrounding the position point. The sum dz of each position point and its surrounding adjacent positions and the total mean dJ of each position point and its surrounding adjacent positions in the grid structure are obtained, and then dz is compared with dJ. If dz is greater than dJ, the corresponding position point is marked; the marked position point is obtained by marking the marked contour, and the marked contour feature is analyzed. According to the design drawings of the room, the area, length, width, height of the corresponding wall, floor and ceiling in the room and the proportion of the marked contour in the indoor three-dimensional model are obtained to obtain the size of the marked contour; the marked contour feature and the corresponding size are compared with the standard furniture model library. If the overlap rate of the compared contour features reaches 90% and the corresponding size matching rate reaches 95%, the contour feature is determined to be the model corresponding to the standard furniture model library, and the indoor furniture is determined.

4. The indoor space layout optimization system based on data analysis according to claim 1 is characterized in that: The specific process of comprehensively calculating the score of each equipment factor to obtain the overall influence coefficient of the equipment layout functional area is: By obtaining the score of each equipment factor; L is the lighting impact score, which is calculated by the formula: Among them, I l is the ideal lighting intensity required for the area, I s is the actual collected illumination intensity, D L is the distance factor of equipment layout on lighting; V is the ventilation impact score, which is given by the formula: Among them, V l is the ideal ventilation volume required for the area, V s is the actual collected ventilation volume, D V is the distance factor of equipment layout on ventilation; P is obtained by analogy, where P is the power supply impact score; N is the noise interference impact score, and the formula is: V = N s ×D V , where N s is the actual noise level generated, D N It is the distance factor between the equipment and the noise source; the score of each equipment factor is calculated comprehensively to obtain the overall influence coefficient SYZ of the functional area of ​​the equipment layout.

5. The indoor space layout optimization system based on data analysis according to claim 1 is characterized in that: The specific process of comprehensively calculating all factors to obtain the preliminary division confirmation value of the room is as follows: Analysis of noise and sound insulation effect, according to the formula: Output the total noise level inside the bedroom ZYZ, where Z1 is the noise level of the external noise source; Z2 is the noise inside the bedroom, Z i is the noise of the ith device or environmental source, n is the number of noise sources; X is the impact value of the room sound insulation effect, Among them, A j is the area of ​​the jth material, α j is the sound absorption coefficient of the jth material, RF is the room sound insulation performance coefficient; for the light brightness analysis, the formula Output light intensity GQZ, Cm is the window area, GQ is the light intensity outside the window, Cf is the room area, Tg is the light transmittance of the window, RZ is the reflection coefficient of the wall and ceiling in the room; and by considering the influence of the incident angle of light, the actual available light brightness B in the room is output through the formula: B = GQZ × Gc × cos (θ), Gc is the light direction coefficient, θ is the incident angle of light and the window surface; analyze the area, by determining the area required for the basic functional area, the number of bedrooms in the room and the expected number of people living in the room, as well as the additional area required for other functions; output the area requirement value M through the formula: M = JM + (Rs × Rm) + Mq, JM is the area value required for the basic functional area, Rs is the expected number of people living in the room, Rm is the number of bedrooms in the room, and Mq is the additional area value required for other functional requirements; All factors are calculated comprehensively to obtain the preliminary confirmation value of the room division, specifically through: CBQZ=ZYZ×a1+X×a2+GQZ×a3+B×a4+M×a5 outputs the preliminary division confirmation value CBQZ, where a1, a2, a3, a4 and a5 are all weight coefficients of the corresponding factors.

6. The indoor space layout optimization system based on data analysis according to claim 1, characterized in that: The specific process of obtaining the step division confirmation value and the overall influence coefficient of the equipment layout functional area and combining the analysis is as follows: By calculating the step-division confirmation value and the overall influence coefficient SYZ of the functional area of ​​the equipment layout, the current status of each area in terms of functional division and equipment layout is determined; the two indicators are linearly combined to generate an optimization objective function YHS, YHZ = σ × CBQZ + τ × SYZ, where σ and τ are weight coefficients, which are used to express the preference for the rationality of the functional area and the influence of the equipment layout; Optimize the design of functional areas and equipment layout, and generate different optimization schemes based on different combination strategies: change the proportion of σ and τ to generate different optimization schemes; display the advantages and disadvantages of different optimization schemes for users to choose.

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