Light change control method and system

Abstract

The invention relates to the technical field of illumination control, and particularly discloses a light change control method and system, and the method comprises the steps: obtaining the real-time brightness values of a plurality of indoor positions based on brightness sensors disposed at the plurality of indoor positions; based on the real-time brightness values of the multiple indoor positions and the three-dimensional space model of the indoor space, space brightness distribution three-dimensional fitting is carried out, and an indoor real-time brightness distribution three-dimensional model is obtained; real-time illumination parameters of indoor light are determined based on the indoor real-time brightness distribution three-dimensional model, the indoor light is controlled in real time based on the real-time illumination parameters of the indoor light and networking of the Internet of Things, and a light change control result is obtained; the method and the device are used for performing real-time three-dimensional fitting analysis on brightness distribution data in an indoor space, reasonably determining variable illumination parameters of indoor light, and realizing green energy-saving and efficient illumination control of the indoor light.

Description

Technical Field

[0001] The present invention relates to the technical field of lighting control, and in particular to a lighting change control method and system. Background Art

[0002] At present, the light change control method is a technical means that integrates sensor technology, intelligent algorithms and communication technology, and aims to achieve precise control of parameters such as light brightness, color and flickering frequency according to different scene requirements, environmental conditions and energy-saving requirements. Its system usually uses various sensors to perceive information such as ambient light and personnel activities in real time, and realizes interconnection between devices through the Internet of Things. At the same time, intelligent algorithms are used to analyze data to achieve green energy saving and efficient lighting effects, such as automatically reducing or turning off the light brightness in unmanned areas, and adaptively adjusting the light brightness according to the intensity of natural light.

[0003] However, in practical applications, since the original brightness distribution of indoor spaces is difficult to accurately assess, this may lead to excessive provision of lighting parameters, resulting in energy waste, or insufficient provision of lighting parameters, resulting in a lighting effect that fails to meet user expectations.

[0004] Therefore, the present invention provides a lighting change control method and system. Summary of the invention

[0005] The present invention provides a light change control method and system. In S1, real-time brightness values ​​are obtained through brightness sensors at multiple positions, which can fully and accurately reflect the brightness conditions of different indoor areas, providing a rich data basis for subsequent analysis and control. S2 is based on the real-time brightness value and the three-dimensional space model for fitting, and a three-dimensional model of indoor real-time brightness distribution is obtained, which realizes the visualization and accurate modeling of indoor brightness distribution, and helps to deeply understand the overall condition of indoor lighting. It can more accurately determine the areas with uneven lighting or too bright or too dark, providing a strong basis for optimizing lighting control. S3 determines the lighting parameters and controls the lights according to the three-dimensional model of indoor real-time brightness distribution, realizing intelligent and refined management of the lighting system. The lights can be adjusted in real time according to actual needs, improving the comfort and energy-saving effect of lighting, and reducing energy consumption. The obtained light change control results can effectively meet the requirements for indoor lighting in different scenes, such as work, study, rest, etc., and improve the quality of the indoor environment.

[0006] The present invention provides a lighting change control method, comprising:

[0007] S1: obtaining real-time brightness values ​​of multiple locations indoors based on brightness sensors set at multiple locations indoors;

[0008] S2: Perform three-dimensional fitting of spatial brightness distribution based on real-time brightness values ​​of multiple positions in the room and the three-dimensional spatial model of the indoor space to obtain a three-dimensional model of indoor real-time brightness distribution;

[0009] S3: Determine the real-time lighting parameters of indoor lights based on the indoor real-time brightness distribution three-dimensional model, and control the indoor lights in real time based on the real-time lighting parameters of the indoor lights and the Internet of Things network to obtain the lighting change control results.

[0010] Preferably, the lighting change control method, S1: obtaining real-time brightness values ​​of multiple positions indoors based on brightness sensors arranged at multiple positions indoors, comprises:

[0011] Determine the indoor brightness sensor setting conditions based on the shape and size of the indoor space;

[0012] Based on the indoor brightness sensor setting conditions, brightness sensors are respectively set at multiple locations indoors;

[0013] The real-time brightness values ​​of multiple positions in the room are obtained based on the brightness sensors set at multiple positions in the room.

[0014] Preferably, the lighting change control method determines the indoor brightness sensor setting conditions based on the shape and size of the indoor space, including:

[0015] Determine a complete enclosing surface of the indoor space based on the shape and size of the indoor space, and determine a light-irradiating area in the complete enclosing surface of the indoor space;

[0016] Determine the shape and size of the wall shielding surface of the light-irradiating area of ​​the indoor space;

[0017] A three-dimensional space model of the indoor space is fitted based on the shape and size of the indoor space, and based on the light entry area in the complete enclosing surface of the indoor space and the shape and size of the wall shielding surface of the indoor space, the light direct coverage space area is marked in the three-dimensional space model of the indoor space to obtain the indoor light direct space model;

[0018] The indoor brightness sensor setting conditions are determined based on the indoor direct light space model.

[0019] Preferably, the lighting change control method determines the indoor brightness sensor setting conditions based on the indoor light direct illumination space model, including:

[0020] Treat each complete plane and each complete curved surface in the three-dimensional spatial model of the indoor space as a single first reference surface of the indoor space;

[0021] Determine, based on the indoor direct illumination space model, a boundary line formed by the direct illumination coverage space area in each first reference surface of the indoor space;

[0022] Based on the dividing line in each first reference surface in the indoor space, each first reference surface in the indoor space is divided to obtain all second reference surfaces in the indoor space;

[0023] The indoor brightness sensor setting conditions are determined based on all second reference surfaces in the indoor space.

[0024] Preferably, the lighting change control method determines the indoor brightness sensor setting conditions based on all second reference surfaces in the indoor space, including:

[0025] When the single second reference surface of the indoor space is a plane, based on the contour shape and size of the second reference surface and the shape and size of the indoor space, a preset single-plane relative shape and size-brightness sensor setting condition list is retrieved to determine the sub-brightness sensor setting condition of the second reference surface;

[0026] When the single second reference surface of the indoor space is a curved surface, based on the contour shape and size of the second reference surface and the shape and size of the indoor space, a preset single curved surface relative shape and size-brightness sensor setting condition list is retrieved to determine the sub-brightness sensor setting condition of the second reference surface;

[0027] The sub-brightness sensor setting conditions of all second reference surfaces in the indoor space are summarized to obtain the indoor brightness sensor setting conditions.

[0028] Preferably, the lighting change control method, S2: performing three-dimensional fitting of spatial brightness distribution based on real-time brightness values ​​of multiple positions indoors and a three-dimensional spatial model of the indoor space to obtain a three-dimensional model of indoor real-time brightness distribution, comprising:

[0029] Based on the three-dimensional space model of the indoor space, the real-time brightness values ​​of multiple positions in the indoor space are interpolated for each second reference surface in the complete enclosing surface of the indoor space to obtain the real-time brightness two-dimensional distribution data of each second reference surface in the indoor space;

[0030] The indoor space is divided into multiple subspaces based on the indoor direct light space model;

[0031] Based on the partial real-time two-dimensional brightness distribution data of all partial second reference surfaces belonging to each subspace, interpolation processing is performed on each subspace to obtain real-time three-dimensional brightness distribution data of each subspace in the indoor space;

[0032] The real-time 3D brightness distribution data of all subspaces in the indoor space are combined to obtain a 3D model of indoor real-time brightness distribution.

[0033] Preferably, the lighting change control method performs interpolation processing on each subspace based on the partial real-time brightness two-dimensional distribution data of all partial second reference surfaces belonging to each subspace to obtain the real-time brightness three-dimensional distribution data of each subspace in the indoor space, including:

[0034] Taking each spatial position point in all partial second reference surfaces in each subspace as each interpolation reference point in each subspace;

[0035] Based on partial real-time brightness two-dimensional distribution data of all partial second reference surfaces of each subspace, determining a real-time brightness value of each interpolation reference point in each subspace;

[0036] The line segment between every two interpolation reference points in each subspace is regarded as the interpolation reference line segment of each subspace;

[0037] Among all interpolation reference line segments in each subspace, all interpolation reference line segments passing through each spatial position point to be interpolated in each subspace are screened out as all quasi-interpolation reference line segments of each spatial position point to be interpolated;

[0038] Determine the real-time brightness value of each to-be-interpolated spatial position point in each subspace based on all quasi-interpolation reference line segments of each to-be-interpolated spatial position point in each subspace and the real-time brightness values ​​of the corresponding two interpolation reference points;

[0039] The partial real-time brightness two-dimensional distribution data of all partial second reference surfaces of each subspace and the real-time brightness values ​​of all spatial position points to be interpolated are merged according to the spatial distribution positions to obtain the real-time brightness three-dimensional distribution data of each subspace in the indoor space.

[0040] Preferably, the lighting change control method determines the real-time brightness value of each to-be-interpolated spatial position point of each subspace based on all quasi-interpolation reference line segments of each to-be-interpolated spatial position point of each subspace and the real-time brightness values ​​of the corresponding two interpolation reference points, including:

[0041]

[0042] Where B is the real-time brightness value of the currently calculated spatial position point to be interpolated in the currently calculated subspace, n is the total number of all quasi-interpolation reference line segments of the currently calculated spatial position point to be interpolated, and L is 1i is the distance between the currently calculated interpolation spatial position point and the first interpolation reference point of the corresponding ith quasi-interpolation reference line segment, B 1i is the real-time brightness value of the first interpolation reference point of the ith quasi-interpolation reference line segment of the currently calculated spatial position point to be interpolated, L 2iis the distance between the currently calculated interpolation spatial position point and the second interpolation reference point of the corresponding ith quasi-interpolation reference line segment, B 2i is the real-time brightness value of the second interpolation reference point of the i-th quasi-interpolation reference line segment of the currently calculated spatial position point to be interpolated, L max L is the maximum value of the lengths of all quasi-interpolation reference line segments of the currently calculated spatial position point to be interpolated. min It is the minimum value among the lengths of all quasi-interpolation reference line segments of the currently calculated spatial position point to be interpolated.

[0043] Preferably, the light change control method, S3: determining the real-time lighting parameters of the indoor lights based on the indoor real-time brightness distribution three-dimensional model, and controlling the indoor lights in real time based on the real-time lighting parameters of the indoor lights and the Internet of Things network to obtain the light change control result, including:

[0044] Mark the setting position of the indoor lighting in the indoor real-time brightness distribution three-dimensional model to obtain the indoor lighting and original brightness distribution model;

[0045] Input the indoor space lighting and the original brightness distribution model into the lighting parameter determination model to obtain the real-time lighting parameters of the indoor lighting;

[0046] Based on the real-time lighting parameters of indoor lights and the Internet of Things networking, indoor lights are controlled in real time to obtain lighting change control results.

[0047] The present invention provides a lighting change control system, which is used to execute the lighting change control method described in any one of Embodiments 1 to 9, including:

[0048] A brightness acquisition module, used to acquire real-time brightness values ​​of multiple locations indoors based on brightness sensors arranged at multiple locations indoors;

[0049] A three-dimensional fitting module is used to perform three-dimensional fitting of spatial brightness distribution based on real-time brightness values ​​of multiple positions in the room and a three-dimensional spatial model of the indoor space, so as to obtain a three-dimensional model of indoor real-time brightness distribution;

[0050] The lighting control module is used to determine the real-time lighting parameters of indoor lights based on the real-time brightness distribution three-dimensional model of the indoor lights, and to control the indoor lights in real time based on the real-time lighting parameters of the indoor lights and the Internet of Things network to obtain the lighting change control results.

[0051] The beneficial effects of the present invention compared with the prior art are as follows: S1 obtains real-time brightness values ​​through brightness sensors at multiple positions, which can comprehensively and accurately reflect the brightness conditions of different areas in the room, providing a rich data basis for subsequent analysis and control. S2 is based on the real-time brightness value and the three-dimensional space model for fitting, and obtains the three-dimensional model of indoor real-time brightness distribution, which realizes the visualization and accurate modeling of indoor brightness distribution, and helps to deeply understand the overall condition of indoor lighting. It can more accurately determine the areas with uneven lighting or too bright or too dark, providing a strong basis for optimizing lighting control. S3 determines the lighting parameters and controls the lights according to the three-dimensional model of indoor real-time brightness distribution, realizing the intelligent and refined management of the lighting system. The lights can be adjusted in real time according to actual needs, improving the comfort and energy-saving effect of lighting, and reducing energy consumption. The obtained light change control results can effectively meet the requirements for indoor lighting in different scenes, such as work, study, rest, etc., and improve the quality of the indoor environment.

[0052] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in this application document.

[0053] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0055] Figure 1 is a flow chart of a method for controlling light changes in an embodiment of the present invention;

[0056] Figure 2 Schematic diagram of a lighting change control system in an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0058] Embodiment 1:

[0059] The present invention provides a method for controlling light changes, referring to Figure 1 ,include:

[0060] S1: obtaining real-time brightness values ​​of multiple locations indoors based on brightness sensors set at multiple locations indoors;

[0061] S2: Perform three-dimensional fitting of spatial brightness distribution based on real-time brightness values ​​of multiple positions in the room and the three-dimensional spatial model of the indoor space to obtain a three-dimensional model of indoor real-time brightness distribution;

[0062] S3: Determine the real-time lighting parameters of indoor lights based on the indoor real-time brightness distribution three-dimensional model, and control the indoor lights in real time based on the real-time lighting parameters of the indoor lights and the Internet of Things network to obtain the lighting change control results.

[0063] In this embodiment, the brightness sensor is a device capable of detecting the brightness of the surrounding environment, such as a common photoresistor sensor, which can convert the received light signal into an electrical signal, thereby measuring the brightness value of the location.

[0064] In this embodiment, the real-time brightness values ​​at multiple locations in the room refer to the brightness values ​​obtained by the brightness sensor at different locations in the room at the current moment, for example, 100 lux, 120 lux, 90 lux, 110 lux and 105 lux measured at the four corners and the middle of the room respectively.

[0065] In this embodiment, the three-dimensional space model of the indoor space is a digital three-dimensional representation of the indoor space, including information such as the shape, size, and location of furniture in the room. It is like a virtual 3D room model that accurately displays the length, width, height, and layout of various objects in the room.

[0066] In this embodiment, the indoor real-time brightness distribution three-dimensional model is a three-dimensional model that combines the real-time brightness values ​​of multiple locations in the room and the three-dimensional space model to show the real-time brightness conditions of different locations in the room. For example, it is like a stereogram that can show the brightness strength of each point in the room.

[0067] In this embodiment, the real-time lighting parameters of the indoor light refer to specific working state parameters such as the brightness, color, and irradiation angle of the current indoor light, for example, the light brightness is 80%, the color is warm white, and the irradiation angle is 45 degrees.

[0068] In this embodiment, the Internet of Things network connects various devices (such as lights, sensors, etc.) through the Internet to realize a network of mutual communication and control. Just like connecting all the lights and sensors in the room to a network, they can be managed and controlled in a unified manner.

[0069] In this embodiment, the light change control result is the final state achieved after operating the indoor light through the above control method, for example, the overall light brightness is increased by 20%, or the light color of certain areas is changed from white to yellow.

[0070] The beneficial effects of the above technology are as follows: S1 obtains real-time brightness values ​​through brightness sensors at multiple locations, which can fully and accurately reflect the brightness conditions of different areas in the room, providing a rich data basis for subsequent analysis and control. S2 obtains a three-dimensional model of indoor real-time brightness distribution based on the real-time brightness value and the three-dimensional space model, realizes the visualization and accurate modeling of indoor brightness distribution, and helps to gain a deeper understanding of the overall condition of indoor lighting. It can more accurately determine areas with uneven lighting or too bright or too dark, providing a strong basis for optimizing lighting control. S3 determines lighting parameters and controls lighting according to the three-dimensional model of indoor real-time brightness distribution, realizing intelligent and refined management of the lighting system. The lighting can be adjusted in real time according to actual needs to improve the comfort and energy-saving effect of lighting and reduce energy consumption. The obtained lighting change control results can effectively meet the requirements for indoor lighting in different scenarios, such as work, study, rest, etc., and improve the quality of the indoor environment.

[0071] Embodiment 2:

[0072] Based on Example 1, the light change control method, S1: obtaining real-time brightness values ​​of multiple positions indoors based on brightness sensors set at multiple positions indoors, includes:

[0073] Determine the indoor brightness sensor setting conditions based on the shape and size of the indoor space;

[0074] Based on the indoor brightness sensor setting conditions, brightness sensors are respectively set at multiple locations indoors;

[0075] The real-time brightness values ​​of multiple positions in the room are obtained based on the brightness sensors set at multiple positions in the room.

[0076] In this embodiment, the shape and size of the indoor space refers to the specific form of the indoor space, such as rectangle, square, circle, etc., and the specific values ​​of length, width and height. For example, a room is a rectangle with a length of 5 meters, a width of 4 meters and a height of 3 meters.

[0077] In this embodiment, the brightness sensor setting conditions are requirements and rules for the placement of brightness sensors determined according to the characteristics of the indoor space. For example, since the indoor space is a large rectangular space, it may be stipulated that brightness sensors are set at the four corners of the room and at the midpoints of the long side and the wide side.

[0078] The beneficial effects of the above technology are as follows: by determining the setting conditions of the brightness sensor based on the shape and size of the indoor space, it can ensure that the layout of the sensor is scientific and reasonable, cover the indoor space to the greatest extent, and accurately obtain the brightness information of each area. Arranging brightness sensors at multiple locations according to reasonable setting conditions improves the comprehensiveness and accuracy of brightness data collection and avoids monitoring blind spots. The accurately acquired real-time brightness values ​​at multiple locations indoors provide reliable basic data for subsequent indoor brightness distribution analysis, lighting parameter determination and lighting control. It helps to achieve more accurate indoor lighting control, meet the lighting requirements of different scenes, and improve lighting effects and comfort. Reasonable sensor layout and accurate data collection can effectively reduce the number of unnecessary sensors and reduce system costs. It provides key prerequisites for realizing intelligent and energy-saving indoor lighting systems, helps to improve energy efficiency and reduce energy waste.

[0079] Embodiment 3:

[0080] Based on Example 1, the lighting change control method determines the indoor brightness sensor setting conditions based on the shape and size of the indoor space, including:

[0081] Determine a complete enclosing surface of the indoor space based on the shape and size of the indoor space, and determine a light-irradiating area in the complete enclosing surface of the indoor space;

[0082] Determine the shape and size of the wall shielding surface of the light-irradiating area of ​​the indoor space;

[0083] A three-dimensional space model of the indoor space is fitted based on the shape and size of the indoor space, and based on the light entry area in the complete enclosing surface of the indoor space and the shape and size of the wall shielding surface of the indoor space, the light direct coverage space area is marked in the three-dimensional space model of the indoor space to obtain the indoor light direct space model;

[0084] The indoor brightness sensor setting conditions are determined based on the indoor direct light space model.

[0085] In this embodiment, the complete surrounding surface of the indoor space refers to the closed surface of the space that needs to be illuminated by lights, which is composed of all indoor walls, ceilings, floors and furniture. For example, the complete surrounding surface of a rectangular room includes six surfaces: four walls, ceilings and floors.

[0086] In this embodiment, the light-irradiating area refers to the part of the room that can directly receive external light, such as the area where the window is located. For example, if there is a large window on the south-facing wall of the room, the area where the window is located is the light-irradiating area.

[0087] In this embodiment, the wall shielding surface refers to an outdoor surface that blocks the propagation of light from the area where the incident light enters due to the existence of the wall, such as a plane or curved surface protruding from the wall outside the room that forms a certain angle with the area where the light enters.

[0088] In this embodiment, the shape and size of the wall shielding surface describes the specific shape of the wall shielding surface (such as a rectangle, a triangle, etc.) and specific measurement data such as its length, width, height, etc. For example, a wall shielding surface is a rectangle with a length of 2 meters and a height of 1.5 meters.

[0089] In this embodiment, the three-dimensional space model of the indoor space is constructed based on the shape and size of the indoor space by using computer software or algorithms to construct a virtual three-dimensional model to represent the indoor space according to the shape and size information of the indoor space such as length, width, height, etc. For example, a three-dimensional model with the same size as the actual room is created using 3D modeling software.

[0090] In this embodiment, based on the shape and size of the light-irradiated area in the complete enclosing surface of the indoor space and the wall-blocking surface of the indoor space, the space area directly covered by light is marked in the three-dimensional space model of the indoor space, that is: taking into account the area where light can directly shine in and the situation blocked by the wall, the space range that light can directly shine on is clearly marked in the constructed three-dimensional space model of the indoor space.

[0091] In this embodiment, the space area covered by direct illumination refers to the specific space range directly illuminated by the light in the indoor space. For example, the light coming in from the window can directly illuminate an area 3 meters away from the window and 2 meters wide in the room.

[0092] In this embodiment, the indoor direct light space model is a model obtained by marking the space area covered by direct light on the basis of the original indoor three-dimensional space model.

[0093] The beneficial effects of the above technologies are as follows: by determining the complete enclosing surface of the indoor space and the area where light enters, the indoor light source and distribution can be fully understood, providing a basis for subsequent analysis. Clarifying the shape and size of the wall blocking surface helps to more accurately evaluate the situation where light is blocked, thereby more accurately analyzing the actual indoor lighting conditions. Fitting the three-dimensional spatial model of the indoor space and marking the spatial area covered by direct light to obtain the indoor direct light spatial model realizes the three-dimensional visualization and accurate modeling of the indoor lighting conditions. The brightness sensor setting conditions determined based on this model are more scientific and reasonable, which can ensure that the sensor is set at the key position that best reflects the actual lighting conditions. The accuracy and effectiveness of the data collected by the brightness sensor are improved, providing a reliable basis for subsequent lighting control and optimization. It helps to achieve more accurate and efficient indoor lighting control, improve lighting effects, meet the needs of different scenarios, and at the same time reduce energy consumption and improve energy efficiency. The overall solution makes the design and management of the indoor lighting system more intelligent and refined, and improves the quality and comfort of the indoor environment.

[0094] Embodiment 4:

[0095] On the basis of Example 3, the lighting change control method determines the indoor brightness sensor setting conditions based on the indoor light direct illumination space model, including:

[0096] Treat each complete plane and each complete curved surface in the three-dimensional spatial model of the indoor space as a single first reference surface of the indoor space;

[0097] Determine, based on the indoor direct illumination space model, a boundary line formed by the direct illumination coverage space area in each first reference surface of the indoor space;

[0098] Based on the dividing line in each first reference surface in the indoor space, each first reference surface in the indoor space is divided to obtain all second reference surfaces in the indoor space;

[0099] The indoor brightness sensor setting conditions are determined based on all second reference surfaces in the indoor space.

[0100] In this embodiment, a complete plane refers to a completely flat surface in the indoor space, such as a flat surface such as a wall, ceiling or floor, etc. For example, a rectangular wall of a room is a complete plane.

[0101] In this embodiment, the complete curved surface is a surface with curved features in the indoor space, such as a curved ceiling or a curved decorative shape. For example, the surface of a circular arch in the room is a complete curved surface.

[0102] In this embodiment, the indoor direct light space model determines the boundary line formed by the direct light coverage space area in each first reference surface of the indoor space. In the indoor direct light space model, the boundary line of the area that can be directly illuminated by the light and the area that cannot be directly illuminated on each first reference surface (such as the wall and ceiling) is observed. For example, on a rectangular ceiling first reference surface, the farthest distance that the direct light coming in from the window can illuminate forms a boundary line.

[0103] In this embodiment, based on the dividing line in each first reference surface in the indoor space, each first reference surface in the indoor space is divided to obtain all second reference surfaces in the indoor space. Based on the dividing line found on each first reference surface, these surfaces are further divided into different parts, and these smaller surfaces obtained are the second reference surfaces. For example, a rectangular wall first reference surface is divided into two second reference surfaces, a light-receiving part and a non-light-receiving part, according to the light dividing line.

[0104] The beneficial effects of the above technology are: taking the plane and curved surface in the three-dimensional space model as the first reference surface provides a comprehensive and detailed basis for subsequent analysis, ensuring that no area that may affect the illumination and brightness is missed. Determining the dividing line formed by the direct illumination coverage space area in each first reference surface can accurately understand the distribution boundary of the illumination on different surfaces, providing a key basis for further surface division. Dividing the first reference surface based on the dividing line to obtain the second reference surface makes the analysis of the indoor space more refined and more accurately reflects the differences in illumination characteristics in different areas. The brightness sensor setting conditions determined based on all second reference surfaces are more scientific and accurate, which can ensure that the sensor is set at the position that best reflects the illumination changes and differences. The pertinence and effectiveness of the brightness sensor data collection are improved, providing a reliable guarantee for more accurate lighting control and optimization. It helps to achieve a more intelligent, energy-saving and comfortable indoor lighting environment, and to meet the lighting needs of users in different areas to the greatest extent. This refined processing method helps to improve the design and management level of indoor lighting systems, reduce energy consumption and improve lighting quality.

[0105] Embodiment 5:

[0106] On the basis of Embodiment 4, the lighting change control method determines the indoor brightness sensor setting conditions based on all second reference surfaces in the indoor space, including:

[0107] When the single second reference surface of the indoor space is a plane, based on the contour shape and size of the second reference surface and the shape and size of the indoor space, a preset single-plane relative shape and size-brightness sensor setting condition list is retrieved to determine the sub-brightness sensor setting condition of the second reference surface;

[0108] When the single second reference surface of the indoor space is a curved surface, based on the contour shape and size of the second reference surface and the shape and size of the indoor space, a preset single curved surface relative shape and size-brightness sensor setting condition list is retrieved to determine the sub-brightness sensor setting condition of the second reference surface;

[0109] The sub-brightness sensor setting conditions of all second reference surfaces in the indoor space are summarized to obtain the indoor brightness sensor setting conditions.

[0110] In this embodiment, the outline shape and size of the second reference surface refers to the shape of the second reference surface (such as a rectangle, a circle, etc.) and specific measurement information such as its length, width, area, etc. For example, a second reference surface is a square with a side length of 2 meters, which is its outline shape and size.

[0111] In this embodiment, the preset single-plane relative shape and size-brightness sensor setting condition list is a table or database set in advance, which records the relationship between planes of different shapes and sizes and corresponding brightness sensor setting conditions. For example, for a square plane with a side length of 1-2 meters, it is specified that a brightness sensor should be set at its center.

[0112] In this embodiment, the sub-brightness sensor setting conditions of the second reference surface are specific setting requirements for the brightness sensor determined for a single second reference surface, such as the setting position, number, etc. For example, for a second reference surface of a plane shape, the sub-brightness sensor setting conditions are to set a sensor at each of the four corners.

[0113] In this embodiment, the preset single curved surface relative shape size-brightness sensor setting condition list is similar to the single plane list, but for curved surfaces, it records the corresponding relationship between curved surfaces of different shapes and sizes and brightness sensor setting conditions. That is, it is also a table or database set in advance, which records the relationship between curved surfaces of different shapes and sizes and corresponding brightness sensor setting conditions. Suppose we have an indoor space, in which there is a hemispherical curved surface as the second reference surface;

[0114] The "Preset Single Curved Surface Relative Shape Size-Brightness Sensor Setting Condition List" may specify:

[0115] For a hemispherical surface with a radius of 0.5-1 meter, a brightness sensor needs to be set at the top and bottom of the surface;

[0116] For a hemispherical surface with a radius of 1-1.5 meters, three brightness sensors need to be evenly distributed on the top, bottom and sides of the surface.

[0117] For another example, for a surface of another shape, such as a semi-cylinder, the list might specify:

[0118] When the height of the semi-cylinder is 1-2 meters and the bottom radius is 0.3-0.5 meters, a brightness sensor is respectively arranged at the center of the two bottoms and the middle position of the side of the semi-cylinder.

[0119] With such a preset list, the corresponding brightness sensor setting conditions can be determined according to the shape and size of the specific curved surface.

[0120] The beneficial effects of the above technology are as follows: the second reference surfaces of the plane and the curved surface are processed separately, and the characteristic differences of different surfaces are taken into account, so that the determination of the setting conditions of the brightness sensor is more targeted and accurate. The preset list is retrieved based on the contour shape, size and overall shape and size of the reference surface, which fully combines the specific conditions of the indoor space and ensures the scientific nature of the setting conditions. The sub-brightness sensor setting conditions of each second reference surface are determined separately and summarized, which can fully consider the characteristics of each area in the room and obtain comprehensive and complete brightness sensor setting conditions. The rationality and effectiveness of the brightness sensor layout are improved, so that it can collect brightness data of different areas more accurately, and provide high-quality data support for subsequent lighting control and optimization. It helps to achieve more refined and personalized indoor lighting management, improve lighting effects and comfort, and meet the lighting needs of different areas. Reasonable brightness sensor setting conditions help reduce system costs and energy consumption, and improve the cost-effectiveness and energy-saving level of indoor lighting systems. The overall solution improves the intelligence and automation of indoor lighting systems, and provides a strong guarantee for creating a better indoor light environment.

[0121] Embodiment 6:

[0122] Based on Example 1, the lighting change control method, S2: performing three-dimensional fitting of spatial brightness distribution based on real-time brightness values ​​of multiple positions in the room and a three-dimensional spatial model of the indoor space to obtain a three-dimensional model of indoor real-time brightness distribution, including:

[0123] Based on the three-dimensional space model of the indoor space, the real-time brightness values ​​of multiple positions in the indoor space are interpolated for each second reference surface in the complete enclosing surface of the indoor space to obtain the real-time brightness two-dimensional distribution data of each second reference surface in the indoor space;

[0124] The indoor space is divided into multiple subspaces based on the indoor direct light space model;

[0125] Based on the partial real-time two-dimensional brightness distribution data of all partial second reference surfaces belonging to each subspace, interpolation processing is performed on each subspace to obtain real-time three-dimensional brightness distribution data of each subspace in the indoor space;

[0126] The real-time 3D brightness distribution data of all subspaces in the indoor space are combined to obtain a 3D model of indoor real-time brightness distribution.

[0127] In this embodiment, based on the three-dimensional space model of the indoor space, the real-time brightness values ​​of multiple positions in the room are interpolated for each second reference surface in the complete enclosing surface of the indoor space, and the real-time brightness two-dimensional distribution data of each second reference surface in the indoor space is obtained, which is:

[0128] Using the three-dimensional structural information of the indoor space, the real-time brightness values ​​of multiple locations are measured, and the brightness of each point on each second reference surface (such as a part of the wall) is estimated through mathematical methods (interpolation), so as to obtain the two-dimensional distribution of the brightness of this surface. For example, if the brightness values ​​of several points are known, the brightness distribution of the entire wall can be inferred.

[0129] In this embodiment, the real-time two-dimensional brightness distribution data of the second reference surface is a set of brightness values ​​at different positions on each second reference surface, forming a two-dimensional brightness distribution image or data table. For example, the specific brightness values ​​of each point on a certain part of the wall from left to right and from top to bottom are recorded.

[0130] In this embodiment, the indoor space is divided into multiple subspaces based on the indoor direct light space model. The model constructed according to the indoor direct light situation divides the entire indoor space into several smaller, independent space areas. For example, a room is divided into a bright subspace near the window and a darker subspace far from the window according to the range of direct light from the window.

[0131] In this embodiment, based on the partial real-time luminance two-dimensional distribution data of all partial second reference surfaces belonging to each subspace, each subspace is interpolated to obtain the real-time luminance three-dimensional distribution data of each subspace in the indoor space, namely:

[0132] For each divided subspace, the partial brightness data of the second reference surfaces belonging to it are used to estimate the three-dimensional brightness distribution of each point in the subspace again through interpolation and other methods. For example, the brightness values ​​at different heights and positions from the ground to the ceiling in a subspace are determined.

[0133] In this embodiment, the real-time three-dimensional brightness distribution data of all subspaces in the indoor space are merged to obtain a three-dimensional model of indoor real-time brightness distribution, which is:

[0134] The 3D brightness distribution data of each subspace is integrated together to form a 3D model that can fully describe the brightness of the entire indoor space, just like putting together a puzzle piece by piece to form a complete picture.

[0135] The beneficial effects of the above technology are: interpolation processing is performed on each second reference surface to obtain real-time brightness two-dimensional distribution data, which can more finely describe the brightness change of each surface and improve the resolution and accuracy of the brightness data. The indoor space is divided into multiple subspaces, and the real-time brightness three-dimensional distribution data is obtained based on the reference surface brightness data in the subspace. The multi-level and multi-dimensional analysis of the brightness distribution of the indoor space is realized. By merging the real-time brightness three-dimensional distribution data of all subspaces to obtain the indoor real-time brightness distribution three-dimensional model, the overall brightness distribution of the room can be fully and accurately presented, providing a detailed and reliable model basis for lighting control. It helps to more accurately find areas with uneven indoor brightness or too bright or too dark, so as to make targeted lighting adjustments to improve lighting effects and comfort. It provides accurate data support for the realization of intelligent lighting control, and can dynamically adjust the lights according to the real-time brightness distribution to achieve the purpose of energy saving and optimizing the lighting environment. It improves the management efficiency and quality of the indoor lighting system, reduces the complexity and error of manual evaluation of brightness distribution, and improves the automation and intelligence level of the system.

[0136] Embodiment 7:

[0137] On the basis of Example 6, the lighting change control method performs interpolation processing on each subspace based on the partial real-time brightness two-dimensional distribution data of all partial second reference surfaces belonging to each subspace to obtain the real-time brightness three-dimensional distribution data of each subspace in the indoor space, including:

[0138] Taking each spatial position point in all partial second reference surfaces in each subspace as each interpolation reference point in each subspace;

[0139] Based on partial real-time brightness two-dimensional distribution data of all partial second reference surfaces of each subspace, determining a real-time brightness value of each interpolation reference point in each subspace;

[0140] The line segment between every two interpolation reference points in each subspace is regarded as the interpolation reference line segment of each subspace;

[0141] Among all interpolation reference line segments in each subspace, all interpolation reference line segments passing through each spatial position point to be interpolated in each subspace are screened out as all quasi-interpolation reference line segments of each spatial position point to be interpolated;

[0142] Determine the real-time brightness value of each to-be-interpolated spatial position point in each subspace based on all quasi-interpolation reference line segments of each to-be-interpolated spatial position point in each subspace and the real-time brightness values ​​of the corresponding two interpolation reference points;

[0143] The partial real-time brightness two-dimensional distribution data of all partial second reference surfaces of each subspace and the real-time brightness values ​​of all spatial position points to be interpolated are merged according to the spatial distribution positions to obtain the real-time brightness three-dimensional distribution data of each subspace in the indoor space.

[0144] In this embodiment, the spatial position point refers to a point with specific coordinates in the indoor space, and can be any point in the subspace. For example, in a subspace, a point in a corner or a point in the middle is a spatial position point.

[0145] In this embodiment, the partial real-time brightness two-dimensional distribution data of all partial second reference surfaces of each subspace is a two-dimensional data set formed by the brightness measurement or estimated values ​​of each position point on the divided second reference surfaces (such as partial wall surfaces, ceiling, etc.) in each subspace. For example, the brightness values ​​of different positions of a certain part of the wall surface from one end to the other end in the subspace are recorded.

[0146] In this embodiment, the partial real-time brightness two-dimensional distribution data of all parts of the second reference surface of each subspace and the real-time brightness values ​​of all spatial position points to be interpolated are merged according to the spatial distribution position to obtain the real-time brightness three-dimensional distribution data of each subspace in the indoor space, which is:

[0147] The known two-dimensional brightness data of part of the second reference surface in each subspace and the brightness values ​​of the spatial position points to be interpolated obtained by calculation are integrated and arranged according to their actual positions in space, so as to construct a three-dimensional data model that can fully describe the brightness conditions at different heights and plane positions in this subspace. For example, the two-dimensional brightness distribution of part of the wall and ceiling is obtained first, and the brightness of some spatial points is calculated. Then, this information is combined to form a three-dimensional data structure similar to a three-dimensional block with brightness values ​​for each point. This is the real-time three-dimensional brightness distribution data of the subspace.

[0148] The beneficial effects of the above technology are: taking the spatial position point of each subspace as an interpolation reference point and determining its real-time brightness value, which provides a basis for subsequent interpolation calculations and ensures the comprehensiveness and accuracy of brightness data. Taking the line segments between the interpolation reference points in the subspace as interpolation reference segments helps to analyze the brightness change trend and spatial distribution law in more detail. Screening out the quasi-interpolation reference line segments passing through the spatial position points to be interpolated can calculate the brightness value in a targeted manner, thereby improving the efficiency and accuracy of interpolation. Determining the real-time brightness value of the spatial position point to be interpolated based on the real-time brightness value of the quasi-interpolation reference line segments and the corresponding interpolation reference points makes the distribution of brightness data in the subspace more continuous and uniform, reducing brightness mutations and errors. Merging the brightness data of part of the second reference surface and the brightness values ​​of the spatial position points to be interpolated to obtain the real-time brightness three-dimensional distribution data of the subspace can comprehensively and accurately present the brightness distribution in the subspace, providing high-quality data for the construction of the overall indoor brightness model. It helps to achieve more refined and intelligent lighting control, adjust the lights according to the precise brightness distribution data, improve the lighting effect and comfort, and reduce energy consumption. It has improved the design and management level of indoor lighting systems and provided strong technical support for optimizing the indoor light environment.

[0149] Embodiment 8:

[0150] On the basis of Example 7, the lighting change control method determines the real-time brightness value of each to-be-interpolated spatial position point of each subspace based on all quasi-interpolation reference line segments of each to-be-interpolated spatial position point of each subspace and the real-time brightness values ​​of the corresponding two interpolation reference points, including:

[0151]

[0152] Where B is the real-time brightness value of the currently calculated spatial position point to be interpolated in the currently calculated subspace, n is the total number of all quasi-interpolation reference line segments of the currently calculated spatial position point to be interpolated, and L is 1i is the distance between the currently calculated interpolation spatial position point and the first interpolation reference point of the corresponding ith quasi-interpolation reference line segment, B 1i is the real-time brightness value of the first interpolation reference point of the ith quasi-interpolation reference line segment of the currently calculated spatial position point to be interpolated, L 2i is the distance between the currently calculated interpolation spatial position point and the second interpolation reference point of the corresponding ith quasi-interpolation reference line segment, B 2i is the real-time brightness value of the second interpolation reference point of the i-th quasi-interpolation reference line segment of the currently calculated spatial position point to be interpolated, L max L is the maximum value of the lengths of all quasi-interpolation reference line segments of the currently calculated spatial position point to be interpolated. minIt is the minimum value among the lengths of all quasi-interpolation reference line segments of the currently calculated spatial position point to be interpolated.

[0153] The beneficial effects of the above technology are: it can accurately calculate the real-time brightness value of the spatial position point to be interpolated in each subspace, providing an accurate data basis for lighting control. It takes into account the real-time brightness value and distance relationship of multiple quasi-interpolation reference segments and the corresponding two interpolation reference points, making the calculation results more comprehensive and reliable. It helps to achieve more precise control of lighting changes and improve the quality and expressiveness of lighting effects.

[0154] Embodiment 9:

[0155] Based on Example 1, the light change control method, S3: determining the real-time lighting parameters of the indoor lights based on the indoor real-time brightness distribution three-dimensional model, and controlling the indoor lights in real time based on the real-time lighting parameters of the indoor lights and the Internet of Things network, to obtain the light change control result, including:

[0156] Mark the setting position of the indoor lighting in the indoor real-time brightness distribution three-dimensional model to obtain the indoor lighting and original brightness distribution model;

[0157] Input the indoor space lighting and the original brightness distribution model into the lighting parameter determination model to obtain the real-time lighting parameters of the indoor lighting;

[0158] Based on the real-time lighting parameters of indoor lights and the Internet of Things networking, indoor lights are controlled in real time to obtain lighting change control results.

[0159] In this embodiment, the location of the lighting fixture refers to the specific location where the lighting fixture is installed indoors, such as the center of the ceiling, a corner, etc. For example, a chandelier in the living room is installed in the center of the ceiling, and a wall lamp is installed on a wall near the sofa. These locations are the locations where the lighting fixture is installed.

[0160] In this embodiment, the lighting parameter determination model is a model constructed by data training or algorithm, which can calculate appropriate lighting parameters based on the input information about the indoor brightness distribution and the information about the light setting position. It may be a model based on machine learning, which can output lighting parameters such as light brightness, color temperature, and irradiation angle after inputting the light position and original brightness distribution model of the indoor space.

[0161] The process of building the lighting parameter determination model includes the following steps:

[0162] Data collection: Collect a large amount of indoor brightness distribution model data and the corresponding ideal lighting parameters. ;

[0163] Feature extraction: Extract meaningful features related to brightness distribution and lighting parameters from the collected data, such as spatial position, brightness value, lamp type, etc.

[0164] Choose a model architecture: You can choose a neural network in deep learning, such as a convolutional neural network, or a regression model in traditional machine learning;

[0165] Training model: Use the extracted features and corresponding lighting parameters to train the model, so that the model can learn how to predict lighting parameters based on the input brightness distribution data;

[0166] Model evaluation: Use the test set to evaluate the trained model, by comparing the predicted lighting parameters with the actual ideal parameters, and calculating evaluation indicators such as mean square error;

[0167] Adjustment and optimization: Based on the evaluation results, adjust and optimize the model, such as adjusting the model's hyperparameters, increasing the amount of data, improving feature extraction methods, or changing the model architecture, until the model achieves satisfactory performance.

[0168] In this embodiment, the indoor lights are controlled in real time based on the real-time lighting parameters of the indoor lights and the Internet of Things network, and the light change control result is obtained, namely:

[0169] By using the real-time lighting parameters of indoor lights, the indoor lights can be adjusted and controlled instantly through the Internet of Things networking technology (which can be a wireless network connecting various devices). The final lighting state is the result of the lighting change control. For example, if the light is originally dim, the brightness is increased according to the parameters, and the color becomes warmer. This adjusted lighting state is the control result.

[0170] The beneficial effects of the above technology are: marking the setting position of the lighting light in the indoor real-time brightness distribution three-dimensional model to form a light and original brightness distribution model, which can intuitively and comprehensively display the initial status of the indoor lighting and provide a clear basis for subsequent parameter determination and control. By inputting the light and original brightness distribution model into the lighting parameter determination model, the accurate and appropriate real-time lighting parameters of the indoor lighting can be intelligently calculated using professional algorithms and models, which improves the scientificity and efficiency of parameter determination. Based on real-time lighting parameters and Internet of Things networking, the indoor lighting is controlled in real time, and the precise and timely adjustment of the lighting is achieved, which can quickly respond to changes in indoor brightness requirements. It helps to optimize the indoor lighting effect, provide a more uniform and comfortable lighting environment, and meet the lighting requirements of different scenes and activities. Using the Internet of Things networking to achieve real-time control improves the automation and intelligence level of the system, reduces manual intervention, and reduces the complexity and error of operation. It can effectively save energy, adjust the light brightness and distribution according to actual needs, avoid unnecessary energy waste, and achieve green and energy-saving lighting control. The overall solution improves the performance and management level of the indoor lighting system, creates a better lighting experience for users, and is also in line with the development trend of energy conservation and environmental protection.

[0171] Embodiment 10:

[0172] The present invention provides a lighting change control system for executing the lighting change control method described in any one of embodiments 1 to 9, referring to Figure 2 ,include:

[0173] A brightness acquisition module, used to acquire real-time brightness values ​​of multiple locations indoors based on brightness sensors arranged at multiple locations indoors;

[0174] A three-dimensional fitting module is used to perform three-dimensional fitting of spatial brightness distribution based on real-time brightness values ​​of multiple positions in the room and a three-dimensional spatial model of the indoor space, so as to obtain a three-dimensional model of indoor real-time brightness distribution;

[0175] The lighting control module is used to determine the real-time lighting parameters of indoor lights based on the real-time brightness distribution three-dimensional model of the indoor lights, and to control the indoor lights in real time based on the real-time lighting parameters of the indoor lights and the Internet of Things network to obtain the lighting change control results.

[0176] The beneficial effects of the above technology are as follows: the brightness acquisition module obtains real-time brightness values ​​through brightness sensors at multiple locations, which can comprehensively and accurately reflect the brightness conditions of different areas in the room, providing a rich data basis for subsequent analysis and control. The three-dimensional fitting module performs fitting based on the real-time brightness value and the three-dimensional space model to obtain a three-dimensional model of indoor real-time brightness distribution, realizing the visualization and accurate modeling of indoor brightness distribution, which helps to gain a deeper understanding of the overall condition of indoor lighting. It can more accurately determine areas with uneven lighting or too bright or too dark, providing a strong basis for optimizing lighting control. The lighting control module determines lighting parameters and controls lighting according to the three-dimensional model of indoor real-time brightness distribution, realizing intelligent and refined management of the lighting system. The lighting can be adjusted in real time according to actual needs to improve the comfort and energy-saving effect of lighting and reduce energy consumption. The obtained lighting change control results can effectively meet the requirements for indoor lighting in different scenarios, such as work, study, rest, etc., and improve the quality of the indoor environment.

[0177] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for controlling light changes, It is characterized in that include: S1: obtaining real-time brightness values ​​of multiple locations indoors based on brightness sensors set at multiple locations indoors; S2: Perform three-dimensional fitting of spatial brightness distribution based on real-time brightness values ​​of multiple positions in the room and the three-dimensional spatial model of the indoor space to obtain a three-dimensional model of indoor real-time brightness distribution; S3: Determine the real-time lighting parameters of indoor lights based on the indoor real-time brightness distribution three-dimensional model, and control the indoor lights in real time based on the real-time lighting parameters of the indoor lights and the Internet of Things network to obtain the lighting change control results.

2. The lighting change control method according to claim 1, It is characterized in that S1: Acquire real-time brightness values ​​of multiple locations indoors based on brightness sensors set at multiple locations indoors, including: Determine the indoor brightness sensor setting conditions based on the shape and size of the indoor space; Based on the indoor brightness sensor setting conditions, brightness sensors are respectively set at multiple locations indoors; The real-time brightness values ​​of multiple positions in the room are obtained based on the brightness sensors set at multiple positions in the room.

3. The lighting change control method according to claim 1, It is characterized in that The indoor brightness sensor setting conditions are determined based on the shape and size of the indoor space, including: Determine a complete enclosing surface of the indoor space based on the shape and size of the indoor space, and determine a light-irradiating area in the complete enclosing surface of the indoor space; Determine the shape and size of the wall shielding surface of the light-irradiating area of ​​the indoor space; A three-dimensional space model of the indoor space is fitted based on the shape and size of the indoor space, and based on the light entry area in the complete enclosing surface of the indoor space and the shape and size of the wall shielding surface of the indoor space, the light direct coverage space area is marked in the three-dimensional space model of the indoor space to obtain the indoor light direct space model; The indoor brightness sensor setting conditions are determined based on the indoor direct light space model.

4. The lighting change control method according to claim 3, It is characterized in that Based on the indoor direct light space model, the indoor brightness sensor setting conditions are determined, including: Treat each complete plane and each complete curved surface in the three-dimensional spatial model of the indoor space as a single first reference surface of the indoor space; Determine, based on the indoor direct illumination space model, a boundary line formed by the direct illumination coverage space area in each first reference surface of the indoor space; Based on the dividing line in each first reference surface in the indoor space, each first reference surface in the indoor space is divided to obtain all second reference surfaces in the indoor space; The indoor brightness sensor setting conditions are determined based on all second reference surfaces in the indoor space.

5. The lighting change control method according to claim 4, It is characterized in that The indoor brightness sensor setting conditions are determined based on all second reference surfaces of the indoor space, including: When the single second reference surface of the indoor space is a plane, based on the contour shape and size of the second reference surface and the shape and size of the indoor space, a preset single-plane relative shape and size-brightness sensor setting condition list is retrieved to determine the sub-brightness sensor setting condition of the second reference surface; When the single second reference surface of the indoor space is a curved surface, based on the contour shape and size of the second reference surface and the shape and size of the indoor space, a preset single curved surface relative shape and size-brightness sensor setting condition list is retrieved to determine the sub-brightness sensor setting condition of the second reference surface; The sub-brightness sensor setting conditions of all second reference surfaces in the indoor space are summarized to obtain the indoor brightness sensor setting conditions.

6. The lighting change control method according to claim 1, It is characterized in that S2: Performing a three-dimensional fitting of the spatial brightness distribution based on the real-time brightness values ​​of multiple positions in the room and the three-dimensional spatial model of the indoor space to obtain a three-dimensional model of the indoor real-time brightness distribution, including: Based on the three-dimensional space model of the indoor space, the real-time brightness values ​​of multiple positions in the indoor space are interpolated for each second reference surface in the complete enclosing surface of the indoor space to obtain the real-time brightness two-dimensional distribution data of each second reference surface in the indoor space; The indoor space is divided into multiple subspaces based on the indoor direct light space model; Based on the partial real-time two-dimensional brightness distribution data of all partial second reference surfaces belonging to each subspace, interpolation processing is performed on each subspace to obtain real-time three-dimensional brightness distribution data of each subspace in the indoor space; The real-time 3D brightness distribution data of all subspaces in the indoor space are combined to obtain a 3D model of indoor real-time brightness distribution.

7. The lighting change control method according to claim 6, It is characterized in that Based on the partial real-time luminance two-dimensional distribution data of all partial second reference surfaces belonging to each subspace, each subspace is interpolated to obtain the real-time luminance three-dimensional distribution data of each subspace in the indoor space, including: Taking each spatial position point in all partial second reference surfaces in each subspace as each interpolation reference point in each subspace; Based on partial real-time brightness two-dimensional distribution data of all partial second reference surfaces of each subspace, determining a real-time brightness value of each interpolation reference point in each subspace; The line segment between every two interpolation reference points in each subspace is regarded as the interpolation reference line segment of each subspace; Among all the interpolation reference line segments in each subspace, all the interpolation reference line segments passing through each spatial position point to be interpolated in each subspace are screened out as all the quasi-interpolation reference line segments of each spatial position point to be interpolated; Determine the real-time brightness value of each to-be-interpolated spatial position point in each subspace based on all quasi-interpolation reference line segments of each to-be-interpolated spatial position point in each subspace and the real-time brightness values ​​of the corresponding two interpolation reference points; The partial real-time brightness two-dimensional distribution data of all partial second reference surfaces of each subspace and the real-time brightness values ​​of all spatial position points to be interpolated are merged according to the spatial distribution positions to obtain the real-time brightness three-dimensional distribution data of each subspace in the indoor space.

8. The lighting change control method according to claim 7, It is characterized in that Based on all quasi-interpolation reference line segments of each to-be-interpolated spatial position point of each subspace and the corresponding real-time brightness values ​​of two interpolation reference points, determining the real-time brightness value of each to-be-interpolated spatial position point of each subspace includes: Where B is the real-time brightness value of the currently calculated spatial position point to be interpolated in the currently calculated subspace, n is the total number of all quasi-interpolation reference line segments of the currently calculated spatial position point to be interpolated, and L is 1i is the distance between the currently calculated interpolation spatial position point and the first interpolation reference point of the corresponding ith quasi-interpolation reference line segment, B 1i is the real-time brightness value of the first interpolation reference point of the ith quasi-interpolation reference line segment of the currently calculated spatial position point to be interpolated, L 2i is the distance between the currently calculated interpolation spatial position point and the second interpolation reference point of the corresponding ith quasi-interpolation reference line segment, B 2i is the real-time brightness value of the second interpolation reference point of the i-th quasi-interpolation reference line segment of the currently calculated spatial position point to be interpolated, L max L is the maximum value of the lengths of all quasi-interpolation reference line segments of the currently calculated spatial position point to be interpolated. min It is the minimum value among the lengths of all quasi-interpolation reference line segments of the currently calculated spatial position point to be interpolated.

9. The lighting change control method according to claim 1, It is characterized in that S3: Determine the real-time lighting parameters of indoor lights based on the indoor real-time brightness distribution three-dimensional model, and control the indoor lights in real time based on the real-time lighting parameters of the indoor lights and the Internet of Things network to obtain the lighting change control results, including: Mark the setting position of the indoor lighting in the indoor real-time brightness distribution three-dimensional model to obtain the indoor lighting and original brightness distribution model; Input the indoor space lighting and the original brightness distribution model into the lighting parameter determination model to obtain the real-time lighting parameters of the indoor lighting; Based on the real-time lighting parameters of indoor lights and the Internet of Things networking, indoor lights are controlled in real time to obtain lighting change control results.

10. A lighting change control system, It is characterized in that The method for controlling light changes according to any one of claims 1 to 9 comprises: A brightness acquisition module, used to acquire real-time brightness values ​​of multiple locations indoors based on brightness sensors arranged at multiple locations indoors; A three-dimensional fitting module is used to perform three-dimensional fitting of spatial brightness distribution based on real-time brightness values ​​of multiple positions in the room and a three-dimensional spatial model of the indoor space, so as to obtain a three-dimensional model of indoor real-time brightness distribution; The lighting control module is used to determine the real-time lighting parameters of indoor lights based on the real-time brightness distribution three-dimensional model of the indoor lights, and to control the indoor lights in real time based on the real-time lighting parameters of the indoor lights and the Internet of Things network to obtain the lighting change control results.

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