A lighting change control method and system

Abstract

The present invention relates to the technical field of lighting control, and specifically discloses a method and system for controlling lighting changes. The method includes: obtaining real-time brightness values at multiple positions in the room based on brightness sensors arranged at multiple positions in the room; performing three-dimensional fitting of the spatial brightness distribution based on the real-time brightness values at multiple positions in the room and the three-dimensional spatial model of the indoor space to obtain a three-dimensional model of the real-time brightness distribution in the room; determining the real-time lighting parameters of the indoor lights based on the three-dimensional model of the real-time brightness distribution in the room, 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 lighting change control result; so as to reasonably determine the change lighting parameters of the indoor lights by performing real-time three-dimensional fitting analysis on the brightness distribution data in the indoor space, realizing green energy saving and efficient lighting control of the indoor lights.

Description

Technical Field

[0001] The present invention relates to the technical field of lighting control, and particularly to a method and system for controlling light changes. Background Art

[0002] Currently, the method for controlling light changes is a technology that integrates sensor technology, intelligent algorithms, and communication technology. It aims to accurately regulate parameters such as light brightness, color, and flicker frequency according to different scenario requirements, environmental conditions, and energy-saving requirements. Its system usually uses various sensors to real-time sense information such as environmental light and human activities, and realizes the interconnection and interoperability between devices through Internet of Things networking. At the same time, intelligent algorithms are used to analyze data to achieve the effects of green energy-saving and efficient lighting. For example, automatically reducing the light brightness or turning off the lights in unoccupied areas, and adaptively adjusting the light brightness according to the natural light intensity.

[0003] However, in practical applications, due to the difficulty in accurately evaluating the original brightness distribution of the indoor space, it may lead to excessive provision of lighting parameters of the lights, resulting in energy waste, or it may lead to insufficient provision of lighting parameters of the lights, resulting in the inability to meet the expected lighting effect of users.

[0004] Therefore, the present invention proposes a method and system for controlling light changes. Summary of the Invention

[0005] The present invention provides a method and system for controlling light changes. In S1, real-time brightness values are obtained 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. In S2, based on the real-time brightness values and a three-dimensional space model for fitting, a three-dimensional model of the real-time brightness distribution in the room is obtained, realizing the visualization and accurate modeling of the indoor brightness distribution, which helps to deeply understand the overall situation of indoor lighting. It can more accurately determine the areas with uneven lighting or over-bright or over-dark areas, providing a strong basis for optimizing lighting control. In S3, lighting parameters are determined according to the three-dimensional model of the real-time brightness distribution in the room and the lights are controlled, 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 results of controlling light changes can effectively meet the requirements for indoor lighting in different scenarios, such as working, studying, resting, etc., improving the quality of the indoor environment.

[0006] The present invention provides a method for controlling light changes, including:

[0007] S1: Obtain real-time brightness values of multiple positions in the room based on brightness sensors set at multiple positions in the room;

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

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

[0010] Preferably, for the lighting change control method, S1: Obtain the real-time brightness values at multiple indoor locations based on the brightness sensors set at multiple indoor locations, including:

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

[0012] Based on the setting conditions of the brightness sensors in the indoor, set the brightness sensors at multiple indoor locations respectively;

[0013] Obtain the real-time brightness values at multiple indoor locations based on the brightness sensors set at multiple indoor locations.

[0014] Preferably, for the lighting change control method, determine the setting conditions of the brightness sensors in the indoor based on the shape and size of the indoor space, including:

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

[0016] Determine the shape and size of the wall shielding surface of the light irradiation area in the indoor space;

[0017] Fit a three-dimensional space model of the indoor space based on the shape and size of the indoor space, and based on the light irradiation area in the complete enclosing surface of the indoor space and the shape and size of the wall shielding surface of the indoor space, mark the light direct irradiation coverage space area in the three-dimensional space model of the indoor space to obtain an indoor light direct irradiation space model;

[0018] Determine the setting conditions of the brightness sensors in the indoor based on the indoor light direct irradiation space model.

[0019] Preferably, for the lighting change control method, determine the setting conditions of the brightness sensors in the indoor based on the indoor light direct irradiation space model, including:

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

[0021] Determine the dividing lines formed by the light direct irradiation coverage space area in each first reference surface of the indoor space based on the indoor light direct irradiation space model;

[0022] Based on the dividing lines in each first reference plane in the indoor space, each first reference plane in the indoor space is divided to obtain all second reference planes of the indoor space;

[0023] Based on all second reference planes of the indoor space, the setting conditions of the brightness sensors in the room are determined.

[0024] Preferably, for the lighting change control method, based on all second reference planes of the indoor space, the setting conditions of the brightness sensors in the room are determined, including:

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

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

[0027] The sub-brightness sensor setting conditions of all second reference planes in the indoor space are aggregated to obtain the setting conditions of the brightness sensors in the room.

[0028] Preferably, for the lighting change control method, S2: Based on the real-time brightness values at multiple positions in the room and the three-dimensional space model of the indoor space, a three-dimensional fitting of the spatial brightness distribution is performed to obtain a three-dimensional model of the real-time brightness distribution in the room, including:

[0029] Based on the three-dimensional space model of the indoor space and the real-time brightness values at multiple positions in the room, interpolation processing is respectively performed on each second reference plane in the complete surrounding surface of the indoor space to obtain the two-dimensional real-time brightness distribution data of each second reference plane in the indoor space;

[0030] Based on the indoor direct light illumination space model, the indoor space is divided into multiple sub-spaces;

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

[0032] The three-dimensional real-time brightness distribution data of all sub-spaces in the indoor space are merged to obtain a three-dimensional model of the real-time brightness distribution in the room.

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

[0034] Regarding each spatial position point in all partial second reference planes in each subspace as each interpolation reference point of each subspace;

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

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

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

[0038] Based on all the 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, determine the real-time brightness value of each to-be-interpolated spatial position point in each subspace;

[0039] Merge the partial real-time brightness two-dimensional distribution data of all partial second reference planes of each subspace and the real-time brightness values of all to-be-interpolated spatial position points 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, for the lighting change control method, based on all the 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, determine the real-time brightness value of each to-be-interpolated spatial position point in each subspace, including:

[0041]

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

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

[0044] Marking the set positions of the lighting lights in the indoor space in the three-dimensional model of the real-time indoor brightness distribution to obtain the lighting and original brightness distribution model of the indoor space;

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

[0046] Controlling the indoor lights in real time based on the real-time lighting parameters of the indoor lights and the Internet of Things networking to obtain the lighting change control result.

[0047] The present invention provides a lighting change control system for executing any one of the lighting change control methods in Embodiments 1 to 9, including:

[0048] A brightness acquisition module, configured to acquire the real-time brightness values at multiple positions in the indoor based on the brightness sensors arranged at multiple positions in the indoor;

[0049] A three-dimensional fitting module, configured to perform three-dimensional fitting of the spatial brightness distribution based on the real-time brightness values at multiple positions in the indoor and the three-dimensional space model of the indoor space to obtain the three-dimensional model of the real-time indoor brightness distribution;

[0050] A lighting control module, configured to determine the real-time lighting parameters of the indoor lights based on the three-dimensional model of the real-time indoor brightness distribution, and control the indoor lights in real time based on the real-time lighting parameters of the indoor lights and the Internet of Things networking to obtain the lighting change control result.

[0051] The beneficial effects of the present invention compared with the prior art are as follows: In S1, real-time brightness values are obtained 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. In S2, based on the real-time brightness values and the three-dimensional space model, fitting is carried out to obtain a three-dimensional model of the real-time indoor brightness distribution, realizing the visualization and accurate modeling of the indoor brightness distribution, which helps to deeply understand the overall situation of indoor lighting. It can more accurately determine the areas with uneven lighting or over-bright or over-dark conditions, providing a strong basis for optimizing lighting control. In S3, lighting parameters are determined and the lights are controlled according to the three-dimensional model of the real-time indoor 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 lighting change control results can effectively meet the requirements for indoor lighting in different scenarios, such as working, studying, resting, etc., improving the quality of the indoor environment.

[0052] Other features and advantages of the present invention will be described in the following specification, and part of them will become obvious from the specification or be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structure specifically pointed out in this application document.

[0053] The technical solution of the present invention will be 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. They are used together with the embodiments of the present invention to explain the present invention, but do not constitute a limitation to the present invention. In the accompanying drawings:

[0055] Figure 1 is a flowchart of the lighting change control method in the embodiment of the present invention;

[0056] Figure 2 is a schematic diagram of the lighting change control system in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0057] The following describes the preferred embodiments of the present invention with reference to the accompanying drawings. It should be understood that the preferred embodiments described here 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 lighting change control method, referring to Figure 1 , including:

[0060] S1: Obtain real-time brightness values at multiple positions in the room based on brightness sensors set at multiple positions in the room;

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

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

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

[0064] In this embodiment, the real-time brightness values at multiple indoor locations refer to the brightness values obtained at different indoor locations through the brightness sensor at the current moment. For example, the 100 lux, 120 lux, 90 lux, 110 lux, and 105 lux measured at the four corners and the middle position 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 and size of the room and the positions of the furniture. It is like a virtual 3D room model that precisely shows the length, width, height of the room and the layout of various objects.

[0066] In this embodiment, the three-dimensional model of the real-time indoor brightness distribution is a three-dimensional model constructed by combining the real-time brightness values at multiple indoor locations and the three-dimensional space model, which can show the real-time brightness conditions at different indoor locations. For example, it is like a three-dimensional graph that can show the brightness intensity of each point in the room.

[0067] In this embodiment, the real-time lighting parameters of the indoor lights refer to the specific working state parameters such as the brightness, color, and irradiation angle of the current indoor lights. 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 networking connects various devices (such as lights, sensors, etc.) through the Internet to form a network for mutual communication and control. It is like connecting the indoor lights and sensors to a network for unified management and control.

[0069] In this embodiment, the lighting change control result is the final state achieved after operating the indoor lights through the above control method. For example, the overall light brightness is increased by 20%, or the light color in some areas changes from white to yellow.

[0070] The beneficial effects of the above technology are as follows: In S1, real-time brightness values are obtained 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. In S2, based on the real-time brightness values and the three-dimensional space model, a three-dimensional model of the real-time indoor brightness distribution is obtained, realizing the visualization and accurate modeling of the indoor brightness distribution, which helps to deeply understand the overall situation of indoor lighting. It can more accurately determine the areas with uneven lighting or over-bright or over-dark conditions, providing a strong basis for optimizing lighting control. In S3, lighting parameters are determined according to the three-dimensional model of the real-time indoor brightness distribution and the lights are controlled, 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 lighting change control results can effectively meet the requirements for indoor lighting in different scenarios, such as working, studying, resting, etc., improving the quality of the indoor environment.

[0071] Embodiment 2:

[0072] Based on Embodiment 1, for the lighting change control method, S1: Obtain the real-time brightness values of multiple positions in the room based on the brightness sensors set at multiple positions in the room, including:

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

[0074] Based on the setting conditions of the brightness sensors in the room, set brightness sensors at multiple positions in the room respectively;

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

[0076] In this embodiment, the shape and size of the indoor space refer to the specific form of the indoor space, such as rectangular, square, circular, etc., as well as 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 setting conditions of the brightness sensors are the requirements and rules for the placement of the brightness sensors determined according to the characteristics of the indoor space. For example, since the indoor is a relatively large rectangular space, it may be stipulated to set brightness sensors at the four corners of the room and the midpoints of the long sides and the wide sides.

[0078] The beneficial effects of the above technology are as follows: By determining the setting conditions of the brightness sensors based on the shape and size of the indoor space, it can ensure a scientific and reasonable layout of the sensors, maximize the coverage of the indoor space, and accurately obtain the brightness information of each area. Arranging brightness sensors at multiple positions according to reasonable setting conditions improves the comprehensiveness and accuracy of brightness data collection and avoids monitoring blind spots. The real-time brightness values accurately obtained at multiple positions indoors provide reliable basic data for subsequent indoor brightness distribution analysis, lighting parameter determination, and lighting control. It helps to achieve more precise indoor lighting control, meet the lighting requirements of different scenarios, and improve the lighting effect and comfort. A reasonable sensor layout and accurate data collection can effectively reduce the number of unnecessary sensors and lower the system cost. It provides a key prerequisite for realizing an intelligent and energy-saving indoor lighting system, helps to improve energy utilization efficiency, and reduce energy waste.

[0079] Embodiment 3:

[0080] Based on the method for controlling lighting changes in Embodiment 1, the setting conditions of the brightness sensors indoors are determined based on the shape and size of the indoor space, including:

[0081] Determine the complete surrounding surface of the indoor space based on the shape and size of the indoor space, and determine the light incident area in the complete surrounding surface of the indoor space;

[0082] Determine the shape and size of the wall shielding surface of the light incident area in the indoor space;

[0083] Fit a three-dimensional space model of the indoor space based on the shape and size of the indoor space, and mark the directly illuminated space area in the three-dimensional space model of the indoor space based on the light incident area in the complete surrounding surface of the indoor space and the shape and size of the wall shielding surface of the indoor space to obtain the indoor direct illumination space model;

[0084] Determine the setting conditions of the brightness sensors indoors based on the indoor direct illumination 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 the light, which is composed of all the walls, ceiling, floor, and furniture in the room. For example, in a rectangular room, its complete surrounding surface includes the four walls, ceiling, and floor, which are six surfaces in total.

[0086] In this embodiment, the light incident area refers to the part of the indoor space 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 this window is located is the light incident area.

[0087] In this embodiment, the wall shielding surface refers to the surface outdoors where the light propagation is blocked due to the presence of the wall, preventing the incident light from entering a certain area. For example, a flat or curved surface of a protruding wall outside a room that forms a certain angle with the light incident area.

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

[0089] In this embodiment, fitting a three-dimensional space model of the indoor space based on the shape and size of the indoor space means constructing a virtual three-dimensional solid model to represent this indoor space according to the shape and size information such as the length, width, and height of the indoor space. For example, using 3D modeling software to create a three-dimensional model with the same dimensions as the actual room.

[0090] In this embodiment, marking the direct light coverage space area in the three-dimensional space model of the indoor space based on the light incident area in the complete surrounding surface of the indoor space and the shape and size of the wall shielding surface of the indoor space means: comprehensively considering the area where light can directly enter and the situation of being blocked by the wall, clearly identifying the space range where light can directly shine in the already constructed indoor three-dimensional space model.

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

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

[0093] The beneficial effects of the above - mentioned technology are as follows: By determining the complete enclosing surface of the indoor space and the light - incident area, the light - source and distribution in the indoor space can be comprehensively understood, providing a basis for subsequent analysis. Defining the shape and size of the wall - blocking surface helps to more accurately evaluate the situation of light being blocked, thereby more accurately analyzing the actual indoor lighting conditions. Fitting the three - dimensional space model of the indoor space and marking the space area covered by direct light irradiation to obtain the indoor direct - light - irradiation space model realizes the three - dimensional visualization and accurate modeling of the indoor lighting situation. Based on this model, the setting conditions of the luminance sensors are more scientific and reasonable, ensuring that the sensors are set at key positions that can best reflect the real lighting situation. It improves the accuracy and effectiveness of the data collected by the luminance sensors, providing a reliable basis for subsequent lighting control and optimization. It helps to achieve more precise and efficient indoor lighting control, improve the lighting effect, meet the needs of different scenarios, while reducing energy consumption and improving energy utilization efficiency. The overall solution makes the design and management of the indoor lighting system more intelligent and refined, improving the quality and comfort of the indoor environment.

[0094] Embodiment 4:

[0095] Based on the indoor direct - light - irradiation space model on the basis of Embodiment 3, the method for controlling the light change determines the setting conditions of the luminance sensors in the indoor space, including:

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

[0097] Based on the indoor direct - light - irradiation space model, determining the demarcation line formed by the space area covered by direct light irradiation in each first reference plane of the indoor space;

[0098] Based on the demarcation line in each first reference plane in the indoor space, dividing each first reference plane in the indoor space to obtain all second reference planes in the indoor space;

[0099] Determining the setting conditions of the luminance sensors in the indoor space based on all the second reference planes of the indoor space.

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

[0101] In this embodiment, a complete curved surface is a surface with a curved feature in the indoor space, such as an arched 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 sunlight space model determines the demarcation line formed by the direct sunlight coverage space area in each first reference plane of the indoor space. In the indoor direct sunlight space model, it is the boundary line between the area that can be directly irradiated by the observed light and the area that cannot be directly irradiated on each first reference plane (such as the wall surface and the ceiling). For example, on a rectangular ceiling first reference plane, the farthest distance that the direct sunlight coming in from the window can reach forms a demarcation line.

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

[0104] The beneficial effects of the above technology are as follows: Regarding the planes and curved surfaces in the three-dimensional space model as the first reference planes provides a comprehensive and detailed basis for subsequent analysis, ensuring that no area that may affect lighting and brightness is omitted. Determining the demarcation line formed by the direct sunlight coverage space area in each first reference plane can accurately understand the distribution boundary of sunlight on different planes, providing a key basis for further plane division. Dividing the first reference plane based on the demarcation line to obtain the second reference plane makes the analysis of the indoor space more refined, more accurately reflecting the lighting characteristic differences in different areas. The brightness sensor setting conditions determined based on all the second reference planes are more scientific and accurate, ensuring that the sensors are set at positions that can best reflect the lighting changes and differences. It improves the pertinence and effectiveness of the data collected by the brightness sensors, 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, maximizing the lighting needs of users in different areas. This refined processing method helps to improve the design and management level of the indoor lighting system, reducing energy consumption while improving lighting quality.

[0105] Embodiment 5:

[0106] Based on the embodiment 4, for the lighting change control method, the brightness sensor setting conditions in the indoor space are determined based on all the second reference planes of the indoor space, including:

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

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

[0109] Summarize the sub-brightness sensor setting conditions of all the second reference planes in the indoor space to obtain the brightness sensor setting conditions for the interior.

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

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

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

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

[0114] The "preset list of single-curved surface relative shape size - brightness sensor setting conditions" may stipulate that:

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

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

[0117] For another example, for a curved surface of another shape, such as a semi-cylindrical shape, the list may stipulate that:

[0118] When the height of the semi-cylinder is between 1 and 2 meters and the bottom radius is between 0.3 and 0.5 meters, a brightness sensor is provided at the center of each of the two bottom surfaces of the semi-cylinder and at the middle position of the side surface.

[0119] Through 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, taking into account the characteristic differences of different surfaces, making the determination of the brightness sensor setting conditions more targeted and accurate. Retrieving the preset list based on the contour shape, size of the reference surface and the overall shape and size of the indoor space fully combines the specific situation of the indoor space, ensuring the scientific nature of the setting conditions. Determining the sub-brightness sensor setting conditions for each second reference surface separately and summarizing them can comprehensively consider the characteristics of each area in the room, and obtain comprehensive and perfect brightness sensor setting conditions. It improves the rationality and effectiveness of the brightness sensor layout, enabling it to collect brightness data in different areas more accurately, providing high-quality data support for subsequent lighting control and optimization. It helps to achieve more refined and personalized indoor lighting management, improve the lighting effect and comfort, and meet the lighting needs of different areas. Reasonable brightness sensor setting conditions help to reduce system costs and energy consumption, and improve the cost performance and energy-saving level of the indoor lighting system. The overall solution improves the intelligence and automation level of the indoor lighting system, providing a strong guarantee for creating a better indoor light environment.

[0121] Embodiment 6:

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

[0123] Interpolate the real-time brightness values at multiple positions in the room based on the three-dimensional space model of the indoor space, and perform interpolation processing on each second reference surface in the complete surrounding surface of the indoor space to obtain the two-dimensional real-time brightness distribution data of each second reference surface in the indoor space;

[0124] Divide the indoor space into multiple sub-spaces based on the indoor light direct illumination space model;

[0125] Interpolate each sub-space based on the partial two-dimensional real-time brightness distribution data of all partial second reference surfaces belonging to each sub-space to obtain the three-dimensional real-time brightness distribution data of each sub-space in the indoor space;

[0126] Merge the real-time three-dimensional brightness distribution data of all sub-spaces in the indoor space to obtain a three-dimensional model of the indoor real-time brightness distribution.

[0127] In this embodiment, based on the three-dimensional space model of the indoor space, for the real-time brightness values at multiple positions in the indoor space, interpolation processing is performed on each second reference plane in the complete surrounding surface of the indoor space to obtain the real-time two-dimensional brightness distribution data of each second reference plane in the indoor space, that is:

[0128] Using the three-dimensional structure information of the indoor space, for the real-time brightness values measured at multiple positions, the brightness of each point on each second reference plane (such as a part of the wall surface) is estimated by a mathematical method (interpolation), so as to obtain the two-dimensional brightness distribution of this surface. For example, given the brightness values of several points, the brightness distribution of the entire wall surface part is inferred.

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

[0130] In this embodiment, based on the indoor direct light space model, the indoor space is divided into multiple sub-spaces (a model constructed according to the situation of indoor direct light), and the entire indoor space is divided into several smaller and independent space regions. For example, a room is divided into a bright sub-space near the window and a darker sub-space far from the window according to the range of direct sunlight through the window.

[0131] In this embodiment, based on the partial real-time two-dimensional brightness distribution data of all partial second reference planes belonging to each sub-space, interpolation processing is performed on each sub-space to obtain the real-time three-dimensional brightness distribution data of each sub-space in the indoor space, that is:

[0132] For each divided sub-space, using the partial brightness data of those second reference planes belonging to it, the three-dimensional brightness distribution of each point in the sub-space is estimated again by methods such as interpolation. For example, the brightness values at different heights and different positions from the ground to the ceiling in a sub-space are determined.

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

[0134] Integrate the three-dimensional brightness distribution data of each sub-space together to form a three-dimensional model that can completely describe the brightness situation of the entire indoor space. Just like putting together pieces of a puzzle to form a complete picture.

[0135] The beneficial effects of the above technology are as follows: Interpolating each second reference plane to obtain real-time two-dimensional brightness distribution data can more precisely describe the brightness changes of each plane, improving the resolution and accuracy of the brightness data. The indoor space is divided into multiple subspaces, and based on the reference plane brightness data within the subspaces, interpolation is performed to obtain real-time three-dimensional brightness distribution data, achieving multi-level and multi-dimensional analysis of the indoor space brightness distribution. By merging the real-time three-dimensional brightness distribution data of all subspaces to obtain a three-dimensional model of the indoor real-time brightness distribution, it can comprehensively and accurately present the overall brightness distribution of the indoor space, providing a detailed and reliable model basis for lighting control. It helps to more precisely identify areas with uneven indoor brightness or areas that are too bright or too dark, thereby making targeted lighting adjustments to improve the lighting effect and comfort. It provides accurate data support for realizing intelligent lighting control, can dynamically adjust the lights according to the real-time brightness distribution, and achieves the purpose of energy conservation and optimized lighting environment. It improves the management efficiency and quality of the indoor lighting system, reduces the complexity and error of manual assessment of brightness distribution, and enhances the automation and intelligence level of the system.

[0136] Embodiment 7:

[0137] Based on the partial real-time two-dimensional brightness distribution data of all partial second reference planes belonging to each subspace, on the basis of Embodiment 6, interpolation is performed on each subspace to obtain the real-time three-dimensional brightness distribution data of each subspace in the indoor space, including:

[0138] Regarding each spatial position point in all partial second reference planes in each subspace as each interpolation reference point of each subspace;

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

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

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

[0142] Based on all the 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, determine the real-time brightness value of each to-be-interpolated spatial position point in each subspace;

[0143] Merge the partial real-time brightness two-dimensional distribution data of all partial second reference planes in each subspace and the real-time brightness values of all spatial position points to be interpolated according to their spatial distribution positions, so as 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, which can be any point within the subspace. For example, in a subspace, a point in a certain 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 planes in each subspace is a two-dimensional data set formed by the measured or estimated brightness values of each position point on those divided second reference planes (such as partial walls, ceilings, etc.) in each subspace. For example, it records the brightness values at different positions from one end to the other end of a certain part of the wall in the subspace.

[0146] In this embodiment, merge the partial real-time brightness two-dimensional distribution data of all partial second reference planes in each subspace and the real-time brightness values of all spatial position points to be interpolated according to their spatial distribution positions, so as to obtain the real-time brightness three-dimensional distribution data of each subspace in the indoor space, that is:

[0147] Integrate and arrange the known two-dimensional brightness data of the partial second reference planes in each subspace and the calculated brightness values of the spatial position points to be interpolated according to their actual positions in the space, so as to construct a three-dimensional data model that can comprehensively describe the brightness situation at different heights and different planar positions within this subspace. For example, first there is the two-dimensional brightness distribution of partial walls and ceilings, and then the brightness of some spatial points is calculated, and then these pieces of information are combined to form a three-dimensional data structure similar to a three-dimensional cube where each point has a brightness value, which is the real-time brightness three-dimensional distribution data of the subspace.

[0148] The beneficial effects of the above technology are as follows: Regarding the spatial position points of each subspace as interpolation reference points and determining their real-time brightness values provides a basis for subsequent interpolation calculations, ensuring the comprehensiveness and accuracy of brightness data. Regarding the line segments between the interpolation reference points in the subspace as interpolation reference line segments helps to more carefully analyze the change trend and spatial distribution law of brightness. Screening out the quasi-interpolation reference line segments passing through the spatial position points to be interpolated enables targeted calculation of brightness values, improving the efficiency and accuracy of interpolation. Determining the real-time brightness value of the spatial position points to be interpolated based on the quasi-interpolation reference line segments and the real-time brightness values of 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 some second reference planes and the brightness values of the spatial position points to be interpolated to obtain the real-time three-dimensional brightness 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 accurate brightness distribution data, improve the lighting effect and comfort, and reduce energy consumption at the same time. It enhances the design and management level of the indoor lighting system and provides strong technical support for optimizing the indoor light environment.

[0149] Embodiment 8:

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

[0151]

[0152] In the formula, 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 the quasi-interpolation reference line segments of the currently calculated spatial position point to be interpolated, L 1i is the distance between the currently calculated spatial position point to be interpolated and the first interpolation reference point of the i-th quasi-interpolation reference line segment corresponding thereto, B 1i is the real-time brightness value of the first interpolation reference point of the i-th quasi-interpolation reference line segment of the currently calculated spatial position point to be interpolated, L 2i is the distance between the currently calculated spatial position point to be interpolated and the second interpolation reference point of the i-th quasi-interpolation reference line segment corresponding thereto, 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 is the maximum value among the lengths of all the quasi-interpolation reference line segments of the currently calculated spatial position point to be interpolated, L minis the minimum value among the lengths of all quasi-interpolation reference line segments for the currently calculated space position point to be interpolated.

[0153] The beneficial effects of the above technology are as follows: It can accurately calculate the real-time brightness value of the space position point to be interpolated in each subspace, providing an accurate data basis for lighting control. Considering the real-time brightness values and distance relationships of multiple quasi-interpolation reference line segments and the corresponding two interpolation reference points, the calculation results are more comprehensive and reliable. It helps to achieve more refined lighting change control and improve the quality and expressiveness of lighting effects.

[0154] Embodiment 9:

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

[0156] Mark the installation positions of the lighting lights in the indoor space on the three-dimensional model of the real-time indoor brightness distribution to obtain the lighting and original brightness distribution model of the indoor space;

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

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

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

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

[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 location, brightness value, luminaire type, etc.;

[0164] Select model architecture: Neural networks in deep learning, such as convolutional neural networks, or regression models in traditional machine learning can be selected;

[0165] Train the model: Use the extracted features and corresponding lighting parameters to train the model, enabling the model to 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, calculate evaluation metrics such as mean squared error, etc.;

[0167] Adjustment and optimization: According to the evaluation results, adjust and optimize the model. For example, adjust the hyperparameters of the model, increase the data volume, improve the feature extraction method, or replace the model architecture until the model achieves satisfactory performance.

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

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

[0170] The beneficial effects of the above technology are as follows: Marking the installation positions of the lighting lights in the three-dimensional model of the indoor real-time brightness distribution to form a lighting and original brightness distribution model can intuitively and comprehensively display the initial situation of indoor lighting, providing a clear basis for subsequent parameter determination and control. Inputting the lighting and original brightness distribution model into the lighting parameter determination model can intelligently calculate accurate and appropriate real-time lighting parameters for indoor lights using professional algorithms and models, improving the scientificity and efficiency of parameter determination. Based on the real-time lighting parameters and the Internet of Things networking to control the indoor lights in real time, precise and timely adjustment of the lights is achieved, and the changes in indoor brightness requirements can be quickly responded to. This helps to optimize the indoor lighting effect, provide a more uniform and comfortable lighting environment, and meet the lighting requirements of different scenarios 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 lowers the operation complexity and errors. 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 also conforms to the development trend of energy conservation and environmental protection.

[0171] Embodiment 10:

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

[0173] A brightness acquisition module for acquiring real-time brightness values at multiple positions in the room based on brightness sensors set at multiple positions in the room;

[0174] A three-dimensional fitting module for performing three-dimensional fitting of the spatial brightness distribution based on the real-time brightness values at multiple positions in the room and the three-dimensional space model of the indoor space to obtain a three-dimensional model of the indoor real-time brightness distribution;

[0175] A lighting control module for determining the real-time lighting parameters of the indoor lights based on the three-dimensional model of the indoor real-time brightness distribution, and controlling the indoor lights in real time based on the real-time lighting parameters of the indoor lights and the Internet of Things networking to obtain a lighting change control result.

[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 positions, which can comprehensively and accurately reflect the brightness conditions in different areas of the room, providing a rich data basis for subsequent analysis and control. The three-dimensional fitting module fits based on the real-time brightness values and the three-dimensional space model to obtain a three-dimensional model of the real-time indoor brightness distribution, realizing the visualization and accurate modeling of the indoor brightness distribution, which helps to deeply understand the overall situation of indoor lighting. It can more accurately determine the areas with uneven lighting or over-bright or over-dark conditions, providing a strong basis for optimizing lighting control. The lighting control module determines lighting parameters and controls the lights according to the three-dimensional model of the real-time indoor brightness distribution, realizing the intelligent and refined management of the lighting system. It can adjust the lights in real time according to actual needs, 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 working, studying, resting, etc., improving the quality of the indoor environment.

[0177] Obviously, those skilled in the art can make various modifications and variations 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 equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A method for controlling light change, characterized in that, Including: S1: Obtain the real-time brightness values at multiple positions in the room based on brightness sensors set at multiple positions in the room; S2: Based on the three-dimensional space model of the indoor space, perform interpolation processing on the real-time brightness values at multiple positions in the room for each second reference surface in the complete surrounding surface of the indoor space, and obtain the two-dimensional real-time brightness distribution data of each second reference surface in the indoor space; Divide the indoor space into multiple sub-spaces based on the indoor light direct illumination space model; Regard each spatial position point in all partial second reference surfaces in each sub-space as each interpolation reference point in each sub-space; Based on the partial two-dimensional real-time brightness distribution data of all partial second reference surfaces in each sub-space, determine the real-time brightness value of each interpolation reference point in each sub-space; Regard the line segment between every two interpolation reference points in each sub-space as the interpolation reference line segment in each sub-space; Among all the interpolation reference line segments in each sub-space, screen out all the interpolation reference line segments passing through each interpolation space position point in each sub-space as all the quasi-interpolation reference line segments of each interpolation space position point; Based on all the quasi-interpolation reference line segments of each interpolation space position point in each sub-space and the real-time brightness values of the corresponding two interpolation reference points, determine the real-time brightness value of each interpolation space position point in each sub-space, including: ； Wherein, B is the real-time brightness value of the currently calculated position point of the space to be interpolated in the currently calculated subspace, n is the total number of all quasi-interpolation reference line segments of the currently calculated position point of the space to be interpolated, is the distance between the currently calculated position point of the space to be interpolated and the first interpolation reference point of the corresponding i-th quasi-interpolation reference line segment, is the real-time brightness value of the first interpolation reference point of the i-th quasi-interpolation reference line segment of the currently calculated position point of the space to be interpolated, is the distance between the currently calculated position point of the space to be interpolated and the second interpolation reference point of the corresponding i-th quasi-interpolation reference line segment, 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 position point of the space to be interpolated, is the maximum value among the lengths of all quasi-interpolation reference line segments of the currently calculated position point of the space to be interpolated, is the minimum value among the lengths of all quasi-interpolation reference line segments of the currently calculated position point of the space to be interpolated; Merge the partial two-dimensional real-time brightness distribution data of all partial second reference surfaces in each sub-space and the real-time brightness values of all interpolation space position points according to the spatial distribution position, and obtain the three-dimensional real-time brightness distribution data of each sub-space in the indoor space; Merge the three-dimensional real-time brightness distribution data of all sub-spaces in the indoor space to obtain the three-dimensional model of the indoor real-time brightness distribution; S3: Mark the installation positions of the lighting lights in the indoor space in the three-dimensional model of the indoor real-time brightness distribution to obtain the lighting and original brightness distribution model of the indoor space; Input the lighting and original brightness distribution model of the indoor space into the lighting parameter determination model to obtain the real-time lighting parameters of the indoor lights; Based on the real-time lighting parameters of the indoor lights and the Internet of Things networking, control the indoor lights in real time to obtain the lighting change control result.

2. The lighting change control method according to claim 1, wherein S1: Obtain the real-time brightness values at multiple positions in the room based on brightness sensors set at multiple positions in the room, including: Determine the brightness sensor setting conditions in the room based on the shape and size of the indoor space; Based on the brightness sensor setting conditions in the room, set brightness sensors at multiple positions in the room respectively; Obtain the real-time brightness values at multiple positions in the room based on the brightness sensors set at multiple positions in the room.

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

4. The lighting change control method according to claim 3, characterized in that, Based on the indoor direct light space model, the setting conditions of the brightness sensors in the indoor are determined, including: Each complete plane and each complete curved surface in the three-dimensional space model of the indoor space are regarded as a single first reference surface of the indoor space; Based on the indoor direct light space model, the demarcation lines formed by the direct light coverage space area in each first reference surface of the indoor space are determined; Based on the demarcation lines 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 of the indoor space; Based on all second reference surfaces of the indoor space, the setting conditions of the brightness sensors in the indoor are determined.

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

6. A lighting change control system, characterized in that, For implementing any one of the lighting change control methods described in claims 1 to 5, including: A brightness acquisition module for acquiring real-time brightness values at multiple positions in the indoor based on brightness sensors arranged at multiple positions in the indoor; A three-dimensional fitting module for performing three-dimensional fitting of the spatial brightness distribution based on the real-time brightness values at multiple positions in the indoor and the three-dimensional space model of the indoor space to obtain a three-dimensional model of the real-time brightness distribution in the indoor; A lighting control module for determining the real-time lighting parameters of the indoor lights based on the three-dimensional model of the real-time brightness distribution in the indoor and for controlling the indoor lights in real time based on the real-time lighting parameters of the indoor lights and the Internet of Things networking to obtain a lighting change control result.

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