A high-end spatial lighting control system with scene adaptability

Abstract

The application discloses a high-end space light illumination control system with scene adaptability, relates to the technical field of intelligent light control, acquires structure geometric information and surface material distribution of a space, constructs a light path simulation model, combines a preset lighting demand template, identifies positions with lighting deviation, performs lighting coverage simulation on each position point based on a lamp type and a light-emitting angle, calculates a lighting coverage contribution value, constructs a reference matrix, performs lamp selection and angle adjustment according to the matrix result, and executes a partition control operation, so that dynamic optimization and adjustment of brightness, angle and color temperature are realized; and closed-loop correction is completed through illumination feedback; the application improves the self-adaptability of lighting control to complex space structures and dynamic scenes, has higher control precision and energy efficiency, and is suitable for intelligent lighting systems in scenes such as exhibition and display, commercial retail and high-end residence.

Description

Technical Field

[0001] This invention relates to the field of intelligent lighting control technology, specifically to a high-end spatial lighting control system with scene adaptability. Background Technology

[0002] In high-end commercial exhibition spaces, art galleries, customized residences, and multi-functional conference venues, the functions of these spaces frequently change with time and usage needs, placing higher demands on the scene adaptability and fine-tuning of lighting systems. Existing lighting control systems typically use a library of preset lighting scenes triggered by sensors, making it difficult to accurately match the dynamic fluctuations in the light environment caused by pedestrian traffic, object movement, and changes over time. Furthermore, some spaces, such as rotating exhibition areas, embedded 3D display cases, and highly reflective background areas, have complex geometric shapes and reflective characteristics, leading to problems such as overexposure, overlapping shadows, or color temperature drift in localized areas using conventional lighting algorithms, severely impacting the display effect and visual experience.

[0003] Especially in high-contrast, variable-structure, or dynamic scene settings, traditional lighting systems struggle to perceive and optimize changes in spatial details in real time, often requiring manual intervention for correction. This is not only inefficient but also leads to issues such as false triggering and the accumulation of lighting errors. Summary of the Invention

[0004] The purpose of this invention is to provide a high-end spatial lighting control system with scene adaptability to address the shortcomings of the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a high-end spatial lighting control system with scene adaptability, comprising: Structure perception module: acquires structural geometric information and surface material distribution map within the target space, wherein the structural geometric information includes spatial block layout, facade tilt angle and multi-layer reflective surface distribution; Lighting modeling module: Based on the obtained structural geometry information, construct a lighting path simulation model L, and combine it with the material distribution map to calculate the reflection weight coefficient R corresponding to each irradiated surface; Scene matching module: Based on the functional type and usage time of the lighting area, it searches the scene requirement database to obtain the lighting parameter template T of the target scene, including the target brightness range, color temperature range and dynamic response threshold. Deviation identification module: Matches and compares the constructed model L with the template T to identify the set of locations P where there is illumination matching deviation under the current spatial structure; Parameter calculation module: Based on each location point Pi in the location set P, calculate the contribution value Ci,j of location point Pi to the lighting coverage of different types of lamps at different angles, and establish a reference matrix M for lamp selection and angle adjustment based on this. Intelligent control module: Controls the lighting fixtures to perform zone adjustment operations based on matrix M, including turning on / off, angle rotation, brightness fine-tuning, and color temperature correction.

[0006] Preferably, the step of constructing a lighting path simulation model L based on the obtained structural geometric information, and calculating the reflection weight coefficient R corresponding to each irradiated surface in conjunction with the material distribution map, includes: Based on the obtained spatial block layout and facade tilt angle, a lighting path simulation model L, including the light source position, path propagation direction and occlusion relationship, is constructed using a ray tracing algorithm. Mark the position index of each irradiated surface in the simulation model and import the corresponding surface material distribution map; Based on the diffuse reflectance, specular reflectance, and surface roughness parameters of each irradiated surface material, the reflection energy attenuation coefficient of each irradiated surface is calculated in conjunction with the incident angle of the light.

[0007] Preferably, the step of constructing a lighting path simulation model L using a ray tracing algorithm, which includes the light source position, path propagation direction, and occlusion relationship, includes: The obtained spatial block layout is converted into a three-dimensional mesh model, and the normal vector direction of each structural surface is calibrated. Based on the preset installation location and type parameters of the light source, the light emission source and emission angle range are set, and the light is emitted from the light source into the spatial grid at the set angle; During the propagation of light, it is determined whether the light intersects or collides with any structural surface based on the spatial grid structure. If a collision occurs, the position of the collision point and the angle of incidence are recorded. For the light rays that collide, the reflection path is calculated based on the normal vector of the corresponding structural surface and the surface material type. The reflection path is then incorporated into the simulation model L until the light intensity decays to a set threshold or the maximum number of reflections is reached.

[0008] Preferably, the step of matching and comparing the constructed model L with the template T to identify the location set P where there is illumination matching deviation under the current spatial structure includes: The illumination intensity corresponding to each illumination surface in the constructed illumination path simulation model L is compared with the target brightness range in the template T one by one. The illumination deviation value on each illumination surface is calculated, and the position where the deviation exceeds the allowable range is determined. Based on the illumination deviation value, mark the locations of the illuminated surfaces where the deviation exceeds the threshold, and record their spatial location index; A deviation location set P is generated using spatial location indexing, which contains all location points where the illumination deviation exceeds a set threshold.

[0009] Preferably, based on each location point Pi in the location set P, the contribution value Ci,j of location point Pi to the lighting coverage of different luminaire types at different angles is calculated, including: For each location point Pi in the location set P, simulate the illumination coverage intensity of different types of lamps at multiple emission angles, and record the coverage value as the initial illumination response data; Based on the simulated lighting response data, calculate the lighting coverage contribution value Ci,j of each type of luminaire j to location point Pi at a set angle θj; Arrange and combine all luminaire types and their corresponding angles to construct a reference matrix M containing luminaire number, emission angle and coverage contribution value for each Pi. Based on the values ​​of Ci,j in matrix M, determine the optimal combination of lighting fixtures and the adjustment angle.

[0010] Preferably, the calculation of the illumination coverage contribution value Ci,j of each type of luminaire j to position point Pi at a set angle θj includes: The illuminance Ij of lamp type j illuminating position point Pi at a set angle θj is collected, and the actual illuminance response value is obtained through the illuminance simulation model. Based on the target brightness value Itarget of Pi in the light path simulation model L, calculate the fitting error value of the lighting fixture combination to Pi. ; The illumination error value ΔI is input into the coverage contribution function, and the illumination coverage contribution value Ci,j is calculated using an exponential decay function.

[0011] Preferably, the zoning adjustment operation is performed on the lighting fixtures according to matrix M, including: Based on the reference matrix M for luminaire selection and angle adjustment, for each illumination deviation point Pi, select the luminaire type j with the largest illumination coverage contribution value Ci,j and its corresponding luminous angle θj. Pi location points with similar luminaire types and angle combinations are spatially clustered to form multiple lighting zones, each zone corresponding to a set of luminaire control parameters; Control commands are issued to the luminaires in each lighting zone to perform at least one of the following operations: brightness adjustment, angle rotation, and color temperature adjustment. After the adjustment is completed, real-time illuminance feedback detection is performed on the lighting area. If there are still areas where the deviation exceeds the allowable range, the matrix M is updated again and a second adjustment is performed.

[0012] The technical effects and advantages provided by the present invention in the above technical solution are as follows: 1. This invention can accurately construct a light path simulation model based on spatial structural features, surface material reflectivity, and lighting requirement templates. Through coverage contribution calculation and zoning control strategies, it enables dynamic adjustment of various types of luminaires at different angles and brightness levels. This method effectively solves the problems of uneven illumination, localized overexposure, or insufficient illuminance caused by traditional static preset control schemes in complex spatial structures, significantly improving the adaptability of lighting systems to changing environments.

[0013] 2. This invention achieves coordinated optimization of luminaire selection, angle adjustment, and brightness control by introducing a contribution value calculation model based on location-based illuminance fitting and a closed-loop feedback optimization mechanism, and supports real-time response to changes in spatial illumination. Through matrix control and spatial clustering and zoning management, this invention not only reduces control complexity but also improves the overall energy efficiency ratio and intelligence level of the lighting system, making it suitable for applications with high lighting quality requirements, such as exhibitions, retail, and high-end residences. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0015] Figure 1 This is a flowchart of the system modules of the present invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] For examples, please refer to Figure 1 As shown in this embodiment, a high-end spatial lighting control system with scene adaptability includes: Structure perception module: acquires structural geometric information and surface material distribution map within the target space, wherein the structural geometric information includes spatial block layout, facade tilt angle and multi-layer reflective surface distribution.

[0018] Specifically, the structure perception module collects the three-dimensional structural information of the target space through 3D scanning equipment (such as LiDAR, structured light cameras, TOF cameras, etc.) or data interfaces based on BIM (Building Information Modeling) systems. The structural information includes at least the following: Spatial block layout: refers to the spatial position, volume outline and relative relationship of the main structural elements in the target space, including three-dimensional entities such as ceilings, columns, walls, partitions, and display stands; Facade tilt angle: For non-vertical components (such as sloping walls, sloping roofs, or sloping surfaces), measure the tilt angle θ relative to the ground and record it as the incident angle parameter facing the calculation model; Multi-layer reflective surface distribution: Identify areas in space with multiple reflection characteristics, such as mirrors, stainless steel, glass, polished stone, etc., and record their location, area, material number and surface roughness parameters (for subsequent reflectivity modeling).

[0019] After the above-mentioned structural geometry information is collected, the system further obtains the surface material distribution map of each structural surface through image recognition, material recognition algorithm or BIM data call. The distribution map is used to record the material type and optical property parameters of each surface, such as diffuse reflection coefficient, specular reflection coefficient, reflection color temperature correction factor, etc.

[0020] Lighting modeling module: Based on the obtained structural geometry information, construct a lighting path simulation model L, and combine it with the material distribution map to calculate the reflection weight coefficient R corresponding to each irradiated surface.

[0021] First, the acquired spatial block layout data is converted into a computer-recognizable 3D spatial mesh model. A polygonal mesh modeling method is then used to geometrically discretize components such as walls, ceilings, and display structures within the space. Each mesh surface serves as an independent structural surface, and its geometric information includes 3D coordinates and facing direction.

[0022] Subsequently, the normal vectors of all mesh structure surfaces are calibrated. The normal vector is a unit vector describing the orientation of the structure surface and is used in subsequent calculations of the incident and reflection angles of light. The direction of the normal vector is calculated sequentially from the mesh surface vertices using the right-hand rule to ensure accurate simulation of the reflection path.

[0023] Based on the preset installation location and type of the light source (such as a point light source, spotlight, or strip light), the specific position of the light emission point in three-dimensional coordinates is set, and the emission angle range and emission density are configured according to the light emission characteristics of the light source. The light rays are projected from the emission point into multiple directions in space in an equally spaced or randomly distributed manner, forming an initial light beam.

[0024] The emission angle range can be achieved by setting an emission cone within a solid angle. For example, for directional luminaires, the emission direction can be limited to a cone with a vertex angle of θ, the value of which is set according to the luminaire specification table.

[0025] During light propagation, a line-by-line projection detection method is used to determine whether each ray intersects with a structural surface in the 3D mesh model. If a ray collides with a structural surface, the 3D coordinates of the collision point, the structural surface index, and the angle between the ray and the normal vector are recorded as the incident angle parameter. The incident angle α is defined as the angle between the ray direction vector and the normal vector of the structural surface, in degrees.

[0026] Collision detection can be accelerated using BVH (Bounding Volume Hierarchy) algorithms to ensure efficient ray tracing in large-scale mesh environments.

[0027] For light rays that collide, their reflection path is calculated based on the normal vector of the colliding structural surface and the corresponding material type. The reflection direction is calculated according to the specular reflection formula, where the reflection vector is determined by the incident vector and the normal vector. The formula is: Reflection vector = Incident vector minus twice its projection in the direction of the normal vector.

[0028] Based on the reflection path, the newly generated light rays are projected into space again, and collision detection, incident angle calculation and reflection path generation are continued to form a complete path chain of light rays in space.

[0029] The recursive process continues until either of the following conditions is met: (a) the light intensity attenuation value of the current light ray is less than the set energy threshold E_min; or (b) the cumulative number of reflections of the light ray reaches the preset maximum number N_max. Specifically, the energy threshold E_min is 0.05 (in relative light intensity), and the maximum number of reflections N_max is 5.

[0030] After completing the above steps, the lighting path simulation model L is constructed. This model records the propagation trajectories of all light rays in space, the interaction relationships between structural surfaces, the reflection angles, and the path energy attenuation.

[0031] After constructing the lighting path simulation model L, the pre-acquired surface material distribution map is imported and mapped onto each illumination surface of the 3D mesh structure. Each illumination surface is associated with its optical properties based on its material number, including: Diffuse reflectance D represents the proportion of light energy scattered by a surface in all directions, and ranges from 0 to 1. Specular reflectivity S represents the proportion of light energy reflected by a surface in a specific direction, and ranges from 0 to 1. The surface roughness parameter ρ represents the microscopic unevenness of the surface and determines the degree of light scattering under high-angle incident light.

[0032] Based on the above parameters and combined with the incident light angle α, a weighted energy attenuation model is used to calculate the reflection energy attenuation coefficient of each irradiated surface. This coefficient is defined as: Reflection weight coefficient R = Incident light intensity × (D × Scattering attenuation function + S × Directional reflection function) × Surface roughness correction factor.

[0033] Scene matching module: Based on the functional type and usage time of the lighting area, it retrieves the scene requirement database and obtains the lighting parameter template T of the target scene, including the target brightness range, color temperature range and dynamic response threshold.

[0034] First, each lighting area in the space is labeled according to its function. For example, the exhibition area is labeled "Exhibition," the meeting area is labeled "Meeting," and the rest area is labeled "Rest." These function types can be obtained through manual configuration or automatic identification of sensor data.

[0035] Once the functional type identifier of the target area is obtained, the system will access a pre-established scene requirement database through a query interface to retrieve the lighting requirement model corresponding to that functional type. The database stores lighting requirement parameters for different functional types, such as target brightness range and color temperature range. The query process is based on the uniqueness of the functional type identifier, and each functional type corresponds to one or more predefined lighting requirement templates.

[0036] The current usage time period refers to the time range corresponding to the current system runtime, usually obtained through the internal clock system, in hours (e.g., 08:00-18:00 is the daytime period, 18:00-08:00 is the nighttime period). The system determines the current time period by querying the current device's time, and then searches for relevant lighting parameter templates in the scene requirement database based on this time period.

[0037] The extracted illumination parameter template T includes three main components: Target brightness range: This refers to the range of brightness values ​​required for a lighting area within a specific time period, usually measured in lumens (lm), representing the luminous flux of the lighting area. For example, the target brightness range for an exhibition area during the day might be 1000 to 2000 lumens, and at night it might be 500 to 1000 lumens.

[0038] Color temperature range: This refers to the color temperature range of the required light source, usually expressed in Kelvin (K), indicating the color of the light emitted by the light source. For example, a light source with a color temperature between 4000K and 5000K may be needed during the day, while warm light with a color temperature between 2700K and 3000K is needed at night.

[0039] Dynamic response threshold: This threshold represents the range of changes in lighting parameters under specific environmental conditions, ensuring that lighting adjustments do not exceed the set range. The dynamic response threshold automatically adjusts according to current indoor and outdoor lighting conditions, ensuring consistent lighting comfort across different time periods. The dynamic response threshold is calculated based on the difference between outdoor natural light intensity (in lux) and a preset indoor illuminance target, typically set within an allowable error range.

[0040] Once the system determines the current time period, it will extract the relevant lighting parameter template T from the scene requirement database. The system will match the time period to retrieve the corresponding lighting parameters and extract the template T. This template will include the target brightness range, color temperature range, and dynamic response threshold; these parameters will be used in subsequent lighting path adjustment and optimization processes.

[0041] Deviation identification module: Matches and compares the constructed model L with the template T to identify the location set P where there is illumination matching deviation under the current spatial structure.

[0042] First, the illumination intensity of each illuminated surface in the constructed illumination path simulation model L is compared one by one with the target brightness range in the template T. The illumination path simulation model L is a three-dimensional illumination intensity distribution map that records the illumination intensity of each illuminated surface. The template T defines the expected brightness range of the region within a specific time period, usually in lumens (lm).

[0043] In this step, assume the illumination intensity on a certain irradiated surface is I_actual, and the target brightness range in template T is [I_min, I_max], where I_min is the minimum brightness value and I_max is the maximum brightness value. The formula for calculating the illumination deviation value D is: This formula calculates the difference between the actual light intensity on the irradiated surface and the median value of the target brightness range, and the resulting deviation value D represents the magnitude of the light deviation.

[0044] If D exceeds the set permissible illumination deviation threshold δ, then the illumination deviation at that location is considered to be outside the permissible range. The permissible deviation threshold δ is a preset value, usually set to the maximum allowable brightness deviation, such as 5% of the target brightness.

[0045] For each illuminated surface, if the calculated illumination deviation value D exceeds the set allowable threshold δ, the position of the illuminated surface is marked as the location where the deviation exceeds the threshold. Specifically, the system records the position index of the illuminated surface in space, which is the coordinate or index value of the illuminated surface in the three-dimensional space grid.

[0046] When the marked location of the illuminated surface deviates beyond the threshold, the system stores the spatial coordinates of that location (e.g., x, y, z coordinates) or the unique identifier of that illuminated surface in the spatial grid (e.g., index number) in a data structure to facilitate subsequent illumination adjustments.

[0047] Based on the location index of each deviation exceeding the threshold recorded in step two, the system aggregates these locations into a deviation location set P. The deviation location set P is a collection of all location points where the illumination deviation exceeds a set threshold. Specifically, the deviation location set P includes all location points that satisfy the following condition: P = {Pi | Di > δ}; where Pi is the location index, Di is the illumination deviation value on the illuminated surface i, and δ is the set allowable deviation threshold. This set P will contain all illuminated surface locations where the illumination deviation value is greater than δ, and these locations are the focus of subsequent illumination adjustments.

[0048] The deviation location set P will serve as the basis for subsequent lighting adjustments. In subsequent steps, lighting adjustments will be performed on the locations in set P to ensure that the lighting intensity meets the target brightness range requirements, ultimately achieving a uniform lighting effect within the target space.

[0049] Parameter calculation module: Based on each location point Pi in the location set P, calculate the lighting coverage contribution value Ci,j of location point Pi to different types of lamps at different angles, and establish a reference matrix M for lamp selection and angle adjustment based on this.

[0050] For each location point Pi in the deviation location set, several types of lamps j (e.g., point light source, strip light source, floodlight, etc.) and their adjustable emission angles θj (e.g., 0 degrees, 15 degrees, 30 degrees, 45 degrees, 60 degrees, 90 degrees) are selected, and a three-dimensional spatial grid-based illuminance simulation model is used to perform lighting simulation for each combination.

[0051] The illuminance simulation model uses ray tracing technology, combined with the spatial geometric information and surface material reflection characteristics recorded in the aforementioned illumination path simulation model L, to simulate the light emitted by each type of lamp towards position point Pi at a specific angle θj, and obtain the actual lighting response value Ij at that point.

[0052] The illumination response value Ij is the light intensity received by Pi under this combination of conditions, in lux, forming an initial illumination response data table for subsequent analysis.

[0053] Based on the target brightness value Itarget of point Pi in the illumination path simulation model L (provided by the illumination parameter template T), calculate the illumination fitting error ΔI of each group of luminaire types j and emission angles θj on Pi.

[0054] The lighting fitting error ΔI is calculated as follows: Where Ij is the actual response value obtained from the illuminance simulation, Itarget is the target luminance value of the template, and ΔI is the absolute difference between the two. The smaller this difference, the closer the luminaire combination is to the target lighting requirement.

[0055] To quantify the illumination coverage quality of each combination, an illumination coverage contribution function F is defined to convert the fitting error ΔI into contribution values ​​Ci,j. The contribution function F adopts an exponential decay form, specifically expressed as: Where k is the illumination sensitivity coefficient, representing the sensitivity to brightness deviation, and Ci,j is the final contribution value of illumination coverage, ranging from 0 to 1. The smaller ΔI is, the closer Ci,j is to 1; the larger ΔI is, the faster Ci,j decays to near 0.

[0056] This contribution function has a strong nonlinear response capability, which can more effectively distinguish the quality of different lighting combinations.

[0057] Each type of luminaire j and its corresponding illumination coverage contribution value Ci,j at each emission angle θj are arranged and combined using Pi as the index to form a reference matrix M with a three-dimensional structure.

[0058] In matrix M, rows represent luminaire type j, columns represent emission angle θj, and matrix elements are Ci,j. Each element in the matrix reflects the illumination capability of a certain luminaire at a certain angle to a target point Pi.

[0059] By sorting and analyzing the Ci,j values ​​in matrix M, we can select the lighting fixture combinations and angle settings that contribute the most to each Pi under the premise of minimum energy consumption or minimum adjustment cost, and use them as the input basis for subsequent lighting control strategies.

[0060] Intelligent control module: Controls the lighting fixtures to perform zone adjustment operations based on matrix M, including turning on / off, angle rotation, brightness fine-tuning, and color temperature correction.

[0061] For each location point Pi in the lighting deviation location set P, the system searches for the lighting coverage contribution values ​​Ci,j of all corresponding luminaire types j and their emission angles θj in the reference matrix M. The system sorts the Ci,j values ​​for each Pi and selects the combination with the largest contribution value, i.e., the luminaire type j and emission angle θj corresponding to the largest Ci,j. This combination is considered the optimal matching combination and is used to guide the lighting compensation at that location point.

[0062] The reference matrix M is a three-dimensional structure, where the matrix element Ci,j represents the illumination coverage effect of lamp j on point Pi at angle θj. The larger the value, the stronger the ability to fit the target brightness.

[0063] To reduce control complexity and improve lighting adjustment efficiency, multiple Pis with similar optimal lighting type j and angle θj are spatially clustered. The spatial clustering employs a density-based Euclidean distance algorithm, combining spatial coordinate distance and lighting configuration similarity indices to group Pis with similar distances and control parameters into the same lighting zone.

[0064] Each lighting zone corresponds to a set of unified control parameters, including luminaire type, beam angle, brightness target, and color temperature requirements, which are used to guide the unified adjustment of luminaires within the zone.

[0065] For each defined lighting zone, control commands are issued to the luminaires covering that zone according to the corresponding combination of control parameters. The control operations include: Brightness adjustment: Adjust the output light intensity value to make the illuminance in the irradiated area close to the target brightness; Angle rotation: Physically rotate the light fixture to adjust the beam angle, allowing the light to more precisely cover a designated location. Color temperature adjustment: Adjust the output color temperature range in luminaires with variable color temperature capability to match the color temperature requirements in template T.

[0066] The control commands can be sent via a preset communication protocol such as DMX or DALI bus to ensure that the luminaires can respond accurately according to the expected parameters.

[0067] After a lighting adjustment is completed, illuminance sensors deployed throughout the space immediately perform real-time feedback detection on each lighting area. The detection results will collect the current actual brightness value at each location point and compare it with the corresponding target brightness value Itarget in the light path simulation model L.

[0068] If any location is found to have an illuminance deviation value ΔI greater than the set allowable deviation threshold δ (where δ is the preset luminance error limit, for example, 20 lux), these points are remarked as points to be optimized, their corresponding Ci,j calculation results in matrix M are updated, and secondary optimization and adjustment operations of lamp combination and angle are triggered.

[0069] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A high-end spatial lighting control system with scene adaptability, characterized in that: include: Structure perception module: acquires structural geometric information and surface material distribution map within the target space, wherein the structural geometric information includes spatial block layout, facade tilt angle and multi-layer reflective surface distribution; Lighting modeling module: Based on the obtained structural geometry information, constructs a lighting path simulation model L, and combines it with the material distribution map to calculate the reflection weight coefficient R corresponding to each irradiated surface, including: Based on the obtained spatial block layout and facade tilt angle, a lighting path simulation model L, including the light source position, path propagation direction and occlusion relationship, is constructed using a ray tracing algorithm. Mark the position index of each irradiated surface in the simulation model and import the corresponding surface material distribution map; Based on the diffuse reflectance, specular reflectance, and surface roughness parameters of each irradiated surface material, the reflection energy attenuation coefficient of each irradiated surface is calculated in conjunction with the incident angle of light. Scene matching module: Based on the functional type and usage time of the lighting area, it searches the scene requirement database to obtain the lighting parameter template T of the target scene, including the target brightness range, color temperature range and dynamic response threshold. Deviation identification module: Matches and compares the constructed model L with the template T to identify the set of locations P where there is illumination matching deviation under the current spatial structure; Parameter calculation module: Based on each location point Pi in the location set P, calculates the contribution value Ci,j of location point Pi to the lighting coverage of different luminaire types at different angles, and establishes a reference matrix M for luminaire selection and angle adjustment based on this, including: For each location point Pi in the location set P, simulate the illumination coverage intensity of different types of lamps at multiple emission angles, and record the coverage value as the initial illumination response data; Based on the simulated lighting response data, calculate the lighting coverage contribution value Ci,j of each type of luminaire j to location point Pi at a set angle θj; Arrange and combine all luminaire types and their corresponding angles to construct a reference matrix M containing luminaire number, emission angle and coverage contribution value for each Pi. Based on the values ​​of Ci,j in matrix M, determine the optimal combination of lighting fixtures and the adjustment angle; The calculation of the illumination coverage contribution value Ci,j of each type of lamp j to position point Pi at a set angle θj further includes: collecting the illuminance Ij of lamp type j illuminating position point Pi at the set angle θj, obtaining the actual illuminance response value through an illuminance simulation model; and calculating the fitting error value ΔI=|Ij of the lamp combination to Pi based on the target brightness value Itarget of Pi in the illuminance path simulation model L. Itarget|; Input the illumination error value ΔI into the coverage contribution function, and calculate the illumination coverage contribution value Ci,j using the exponential decay function form; Intelligent control module: Controls the lighting fixtures via matrix M to perform zone adjustment operations, including on / off, angle rotation, brightness fine-tuning, and color temperature correction. Based on the reference matrix M for luminaire selection and angle adjustment, for each illumination deviation point Pi, select the luminaire type j with the largest illumination coverage contribution value Ci,j and its corresponding luminous angle θj. Pi location points with similar luminaire types and angle combinations are spatially clustered to form multiple lighting zones, each zone corresponding to a set of luminaire control parameters; Control commands are issued to the luminaires in each lighting zone to perform at least one of the following operations: brightness adjustment, angle rotation, and color temperature adjustment. After the adjustment is completed, real-time illuminance feedback detection is performed on the lighting area. If there are still areas where the deviation exceeds the allowable range, the matrix M is updated again and a second adjustment is performed.

2. The high-end spatial lighting control system with scene adaptability according to claim 1, characterized in that: The lighting path simulation model L, constructed using a ray tracing algorithm, includes the following: The obtained spatial block layout is converted into a three-dimensional mesh model, and the normal vector direction of each structural surface is calibrated. Based on the preset installation location and type parameters of the light source, the light emission source and emission angle range are set, and the light is emitted from the light source into the spatial grid at the set angle; During the propagation of light, it is determined whether the light intersects or collides with any structural surface based on the spatial grid structure. If a collision occurs, the position of the collision point and the angle of incidence are recorded. For the light rays that collide, the reflection path is calculated based on the normal vector of the corresponding structural surface and the surface material type. The reflection path is then incorporated into the simulation model L until the light intensity decays to a set threshold or the maximum number of reflections is reached.

3. A high-end spatial lighting control system with scene adaptability according to claim 1, characterized in that: The step of matching and comparing the constructed model L with the template T to identify the set of locations P where there is illumination matching deviation under the current spatial structure includes: The illumination intensity corresponding to each illumination surface in the constructed illumination path simulation model L is compared with the target brightness range in the template T one by one. The illumination deviation value on each illumination surface is calculated, and the position where the deviation exceeds the allowable range is determined. Based on the illumination deviation value, mark the locations of the illuminated surfaces where the deviation exceeds the threshold, and record their spatial location index; A deviation location set P is generated using spatial location indexing, which contains all location points where the illumination deviation exceeds a set threshold.

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