Brightness AI adaptive adjustment method and system for illumination system

Abstract

The invention relates to the field of intelligent illumination, in particular to a brightness AI adaptive adjustment method and system for an illumination system, and the method comprises the steps: obtaining the light environment parameters of an illumination region in real time; determining an interference parameter of the reflection light source to the target area based on the spatial distribution characteristics and the intensity of the reflection light source, and generating a compensation trigger signal when the interference parameter exceeds a preset interference threshold value; in response to the compensation trigger signal, acquiring environment data of the illumination area; calculating a reflection interference compensation amount according to the environment data, wherein the environment data comprises a mobile object reflection characteristic, a high reflection object position and an environment light fluctuation trend; generating an illumination adjustment strategy according to the reflection interference compensation amount, wherein the strategy comprises a cooperative control parameter for the target area illumination unit; and dynamically adjusting the brightness output of the target area illumination unit based on the illumination adjustment strategy. And the reflection interference compensation amount is dynamically calculated, so that a targeted illumination adjustment strategy is generated, and cooperative control of the illumination unit is realized.

Description

Technical Field

[0001] This application relates to the field of intelligent lighting technology, and particularly to a method and system for AI adaptive brightness adjustment for a lighting system. Background Art

[0002] The brightness adaptive adjustment of a lighting system is an intelligent lighting technology aimed at automatically adjusting the brightness of artificial light sources according to the lighting conditions of the environment, so as to improve energy efficiency, comfort, and the visual effect of the working environment. Such a system can automatically adjust the intensity of indoor lighting according to changes in external or internal light sources, avoid human intervention, and ensure the best lighting under different ambient light conditions.

[0003] In existing intelligent lighting systems, simple light intensity sensors are usually relied on to detect light intensity, but these sensors cannot effectively distinguish direct light sources and reflected light sources. This means that when there are highly reflective objects (such as glass windows, mirror surfaces, or smooth floors), the reflected light will be detected by the sensors and misinterpreted as effective illuminance, resulting in the system wrongly adjusting the brightness. The reflected light is often lower in intensity than the direct light source, but it still affects the sensor readings. Without distinguishing the spatial characteristics and spectra of these light sources, the system may treat the reflected light as a direct light source, leading to inaccurate brightness adjustment. Specifically, areas that originally need to be darker are misidentified as having insufficient light, and the system will wrongly increase the lighting intensity, resulting in an over-bright effect instead, or areas that originally do not need to increase lighting are misidentified as being over-bright, and the lighting is instead reduced. Secondly, when the light from multiple light sources overlaps in certain areas, the existing calculation methods are difficult to accurately estimate the contributions of each light source. For example, when natural light and artificial light coexist, overexposure or underexposure may occur in certain areas. The simple superposition calculation method may cause the lighting intensity in some areas to be too high (overexposed), while in other areas it may be too low (underexposed).

[0004] Therefore, there are deficiencies in the existing technology and improvements are needed. Summary of the Invention

[0005] In order to solve one or several problems in the existing technology, the main object of this application is to provide a method and system for AI adaptive brightness adjustment for a lighting system.

[0006] To achieve the above-mentioned invention object, this application proposes a method for AI adaptive brightness adjustment for a lighting system, the method comprising:

[0007] Obtaining in real time the light environment parameters of the lighting area, the light environment parameters including the direct light source intensity, the reflected light source intensity, and the spatial distribution characteristics;

[0008] Based on the spatial distribution characteristics and the intensity of the reflected light source, determine the interference parameter of the reflected light source on the target area, and generate a compensation trigger signal when the interference parameter exceeds a preset interference threshold;

[0009] In response to the compensation trigger signal, obtain the environmental data of the illumination area;

[0010] Calculate the reflection interference compensation amount according to the environmental data, where the environmental data includes the reflection characteristics of moving objects, the positions of highly reflective objects, and the trend of ambient light fluctuations;

[0011] Generate an illumination adjustment strategy according to the reflection interference compensation amount, and the strategy includes the cooperative control parameters of the lighting units in the target area, which are used to offset the interference of the reflected light source and maintain the effective illuminance of the target area;

[0012] Dynamically adjust the brightness output of the lighting units in the target area based on the illumination adjustment strategy.

[0013] An embodiment of the present application further provides a brightness AI adaptive adjustment system for an illumination system, including:

[0014] A first acquisition module, configured to acquire the optical environment parameters of the illumination area in real time, where the optical environment parameters include the intensity of the direct light source, the intensity of the reflected light source, and the spatial distribution characteristics;

[0015] A determination module, configured to determine the interference parameter of the reflected light source on the target area based on the spatial distribution characteristics and the intensity of the reflected light source, and generate a compensation trigger signal when the interference parameter exceeds a preset interference threshold;

[0016] A second acquisition module, configured to acquire the environmental data of the illumination area in response to the compensation trigger signal;

[0017] A calculation module, configured to calculate the reflection interference compensation amount according to the environmental data, where the environmental data includes the reflection characteristics of moving objects, the positions of highly reflective objects, and the trend of ambient light fluctuations;

[0018] A generation module, configured to generate an illumination adjustment strategy according to the reflection interference compensation amount, and the strategy includes the cooperative control parameters of the lighting units in the target area, which are used to offset the interference of the reflected light source and maintain the effective illuminance of the target area;

[0019] An adjustment module, configured to dynamically adjust the brightness output of the lighting units in the target area based on the illumination adjustment strategy.

[0020] The present application further provides a computer device, including a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the method described in any one of the above when executing the computer program.

[0021] The present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described in any one of the above are implemented.

[0022] The brightness AI adaptive adjustment method and system for a lighting system according to an embodiment of the present application can accurately identify the interference degree of the reflected light source on the target area by obtaining the intensity and spatial distribution characteristics of the direct light source and the reflected light source in the lighting area in real time, and can actively trigger a compensation mechanism. Combining the reflection characteristics of moving objects, the positions of highly reflective objects, and the environmental light fluctuation trend in the environmental data, dynamically calculate the reflection interference compensation amount, and then generate a targeted lighting adjustment strategy to achieve coordinated control of the lighting unit. This method effectively cancels out the interference caused by the reflected light source, ensuring that the effective illuminance in the target area is stable and uniform. Overall, the present invention improves the intelligent adaptation ability and adjustment accuracy of the lighting system, optimizes the lighting effect, enhances the visual comfort of users, and is particularly suitable for intelligent lighting applications in complex reflection environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a schematic flow chart of a brightness AI adaptive adjustment method for a lighting system according to an embodiment of the present application;

[0024] Figure 2 is a schematic flow chart of a brightness AI adaptive adjustment method for a lighting system according to an embodiment of the present application;

[0025] Figure 3 is a schematic block diagram of the structure of a brightness AI adaptive adjustment system for a lighting system according to an embodiment of the present application;

[0026] Figure 4 is a schematic block diagram of the structure of a computer device according to an embodiment of the present application.

[0027] The implementation, functional features, and advantages of the objectives of the present application will be further described in conjunction with the embodiments with reference to the accompanying drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] In order to make the objectives, technical solutions, and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0029] Refer to Figure 1 , an embodiment of the present application provides a brightness AI adaptive adjustment method for a lighting system, and the method includes:

[0030] S1. Obtain the light environment parameters of the lighting area in real time, where the light environment parameters include the direct light source intensity, the reflected light source intensity, and the spatial distribution characteristics;

[0031] S2. Determine the interference parameter of the reflected light source on the target area based on the spatial distribution characteristics and the intensity of the reflected light source, and generate a compensation trigger signal when the interference parameter exceeds a preset interference threshold;

[0032] S3. In response to the compensation trigger signal, obtain the environmental data of the lighting area;

[0033] S4. Calculate the reflection interference compensation amount according to the environmental data, where the environmental data includes the reflection characteristics of moving objects, the positions of highly reflective objects, and the trend of ambient light fluctuations;

[0034] S5. Generate a lighting adjustment strategy according to the reflection interference compensation amount, and the strategy includes cooperative control parameters for the lighting units in the target area, which are used to cancel the interference of the reflected light source and maintain the effective illuminance in the target area;

[0035] S6. Dynamically adjust the brightness output of the lighting units in the target area based on the lighting adjustment strategy.

[0036] As described in the above steps S1 - S3, first, the lighting environment is monitored in real time through means such as sensors to obtain different light source information within the area, including direct light sources (such as lamps and sunlight) and reflected light sources (such as light reflected by glass and the ground). Additionally, the spatial distribution characteristics need to be obtained. The spatial distribution characteristics refer to the spatial distribution of light sources and the distribution patterns of different light sources within the area, which will help distinguish different types of light sources. By comprehensively collecting light environment parameters, the system can obtain the actual lighting conditions of different light sources, including the intensity, distribution of direct and reflected light sources, and their impact on the target area. This information provides the basic data for subsequent calculations and reflection interference compensation. According to the light environment parameters, especially the spatial distribution characteristics and the intensity of the reflected light source, calculate the degree of interference of the reflected light source on the target area. The interference parameter of the reflected light source is a quantitative index reflecting the impact of the reflected light source on the area lighting, usually determined based on the intensity of the reflected light, the properties of the reflecting object, and the complexity of the reflection path. When the interference parameter exceeds the preset threshold, it indicates that the reflected light source has a greater impact on the lighting effect, and the system needs to perform compensation adjustment. Identify in advance the possible interference of the reflected light source on the illuminance of the target area and trigger it through the set threshold. If the interference is too large, the system will activate the compensation mechanism to prevent the lighting system from misadjusting the brightness due to the reflected light source. When the system identifies that the reflected light source interference exceeds the standard and generates a compensation signal, the system will further obtain the environmental data related to the reflected light source. The environmental data includes the reflection characteristics of moving objects (for example, the reflection changes caused by the movement of people within the area), the positions of highly reflective objects (such as mirrors or glass), and the trend of ambient light fluctuations (such as the lighting changes between day and night). Accurately identify the dynamic changes affecting the illuminance, especially the factors related to object reflection and environmental changes. This data acquisition enables the system to make timely adjustments when the environment changes, ensuring that the brightness adjustment is more accurate and adapted to the actual scenario.

[0037] As described in the above steps S4 - S6, using the obtained environmental data, the system calculates the compensation amount for reflection interference through a model or algorithm. The compensation amount takes into account the changes in the reflection characteristics of the object, the spatial position of the reflecting object, and the trend of external light fluctuations. These factors all affect the light intensity. In particular, the reflected light source may fluctuate due to environmental changes. Therefore, the system needs to dynamically adjust the compensation amount to balance the influence of the reflected light. By calculating the compensation amount for reflection interference, the system can achieve more accurate brightness adjustment. The reflected light source may produce strong fluctuations under the influence of certain time periods or certain objects. The calculation of the compensation amount can effectively reduce these interferences, thereby avoiding inaccurate brightness adjustment. Based on the compensation amount for reflection interference, a specific lighting adjustment strategy is generated. This strategy adjusts the brightness, direction, or other parameters of multiple lighting units (such as lamps or LEDs) through coordinated control, thereby effectively offsetting the influence of the reflected light source on the illuminance of the area. By dynamically adjusting the output of multiple lighting units, it is ensured that the illuminance of the target area remains within the expected range. By coordinating and controlling parameters such as the brightness of the lighting units, the system can accurately compensate for the interference caused by the reflected light source, avoid the system from adjusting the wrong brightness due to the misdetection of the reflected light, and ensure the uniformity and stability of the lighting effect. According to the lighting adjustment strategy generated in the previous step, the system dynamically adjusts the brightness output of the lighting units (such as lamps) in the target area. This adjustment is based on the interference situation of the reflected light source and the compensation amount calculated from the environmental data. The dynamically changing process can adapt to different lighting environments. The intelligent adjustment of brightness is realized, which can cope with the changes in different lighting environments and reflected light sources. The system automatically adjusts the brightness of the lighting units so that the effective illuminance of the target area always remains at the required level, avoiding overexposure or insufficient lighting, and improving the overall lighting experience.

[0038] As described above, by obtaining the intensity and spatial distribution characteristics of the direct light source and the reflected light source in the lighting area in real time, accurately identifying the interference degree of the reflected light source on the target area, the compensation mechanism can be actively triggered. Combining the reflection characteristics of moving objects, the positions of highly reflective objects, and the trend of ambient light fluctuations in the environmental data, the compensation amount for reflection interference is dynamically calculated, and then a targeted lighting adjustment strategy is generated to achieve coordinated control of the lighting units. This method effectively offsets the interference brought by the reflected light source, ensuring that the effective illuminance of the target area is stable and uniform. Overall, the present invention improves the intelligent adaptation ability and adjustment accuracy of the lighting system, optimizes the lighting effect, enhances the visual comfort of users, and is particularly suitable for intelligent lighting applications in complex reflection environments.

[0039] Refer to Figure 2 , in one embodiment, the step of generating a lighting adjustment strategy according to the compensation amount for reflection interference includes:

[0040] S51. Obtain the environmental data, and calculate the spatial weight distribution coefficients of each lighting unit according to the relative spatial relationship between the position of the high-reflection object and the target area, where the lighting unit closest to the high-reflection object is assigned the highest suppression weight;

[0041] S52. Combine the real-time change rate of the reflection characteristics of the moving object to generate a compensation intensity correction coefficient that is positively correlated with the dynamic reflection interference intensity;

[0042] S53. Based on the environmental light fluctuation trend, set a dynamic response rate threshold for brightness adjustment, where the rate threshold is negatively correlated with the light fluctuation frequency;

[0043] S54. Multidimensionally fuse the spatial weight distribution coefficient, the compensation intensity correction coefficient, and the dynamic response rate threshold to generate a collaborative control parameter set including light intensity modulation gradient, regional priority sequence, and phase delay parameter, where the phase delay parameter is used to match the adaptation time constant of the human eye to sudden brightness changes.

[0044] As described in the above steps, in the lighting system, the reflection of the light source by the highly reflective object may cause uneven light intensity in the target area. To solve this problem, it is necessary to adjust the distribution of the lighting units, taking into account the relative positions of each lighting unit and the highly reflective object. Since the reflection effect of the highly reflective object on light is most significant in the nearby area, the lighting units close to these objects need to be assigned higher suppression weights to reduce their over-illumination of the target area. By reasonably allocating the weights of each lighting unit, the lighting system can be intelligently adjusted, thereby reducing the interference of the highly reflective object and ensuring more uniform lighting in the target area, avoiding problems such as light pollution or excessive reflection. In a dynamic environment, the reflection characteristics of the moving object will change with factors such as the position and speed of the object. To more accurately cope with the reflected light interference, it is necessary to track these reflection characteristics in real time. By analyzing the change rate of the reflection characteristics of the moving object, the change trend of the reflection interference intensity can be obtained, and then a compensation intensity correction coefficient related thereto can be generated. This compensation coefficient can dynamically adjust the lighting intensity to cope with the continuously changing reflection interference. For the change of the reflection interference in the dynamic environment, the compensation strategy is automatically adjusted to ensure the continuous stability of the lighting effect in the target area and reduce the uneven or over-bright lighting caused by the reflection change. The change of the ambient light fluctuation trend reflects the volatility of the surrounding ambient light conditions. To ensure that the response of the lighting system will not be too drastic and cause visual discomfort or over-regulation, it is necessary to set a dynamic response rate threshold. This threshold is negatively correlated with the frequency of the light fluctuation, which means that the higher the light fluctuation frequency, the lower the response rate threshold, and the slower the response speed of the system. In this way, the system can avoid overreacting to high-frequency fluctuations and causing unnecessary brightness adjustments. By reasonably setting the response rate threshold, the lighting system can smoothly adjust the brightness, avoid frequent changes due to short-term fluctuations of the ambient light, reduce visual interference to the user, and enhance the user's comfort. The calculated multiple parameters (spatial weight distribution coefficient, compensation intensity correction coefficient, and dynamic response rate threshold) are multi-dimensionally fused to form a collaborative control parameter set. This parameter set includes: light intensity modulation gradient: controlling the adjustment amplitude of the lighting. Regional priority sequence: determining the areas to be adjusted first to ensure that the areas most in need of adjustment are compensated first. Phase delay parameter: Considering the adaptation time characteristics of the human eye to brightness changes, a phase delay parameter is set to smooth the brightness adjustment process and avoid discomfort caused by sudden brightness changes to the user. This multi-dimensionally fused collaborative control strategy can comprehensively consider various factors of the lighting environment and achieve more intelligent and smooth lighting adjustment. The phase delay parameter is particularly crucial. It enables the system to simulate the adaptation ability of the human eye to brightness changes, avoid overly abrupt brightness changes, make the adjustment of the lighting system more natural and comfortable, and conform to the perception law of the human eye.

[0045] In one embodiment, the step of calculating the reflection interference compensation amount according to the environmental data includes:

[0046] Based on the geometric topological relationship between the positions of the high-reflection objects and the target area, calculate the reflection suppression factors of each high-reflection object on the target area, where the reflection suppression factor is positively correlated with the object reflectivity and the square of the distance;

[0047] Combine the real-time change rate of the reflection characteristics of the moving object to generate a dynamic compensation gain coefficient, and the gain coefficient increases exponentially with the increase of the change rate of the surface reflectivity of the moving object;

[0048] According to the spectral characteristics of the ambient light fluctuation trend, extract the main frequency of the light intensity fluctuation and calculate the time-series smoothing coefficient, and the time-series smoothing coefficient is used to suppress the instantaneous interference of the high-frequency fluctuation on the compensation amount;

[0049] Perform weighted fusion on the reflection suppression factor, the dynamic compensation gain coefficient and the time-series smoothing coefficient to generate the reflection interference compensation amount of the target area, where the fusion weight is dynamically adjusted according to the spatial coverage density of the lighting unit.

[0050] As described above, the reflection suppression factor is a quantitative index used to describe the illumination interference of high-reflective objects on the target area. According to the principles of physical optics, the reflectivity of an object (i.e., the ability of the object's surface to reflect light) and the distance between the object and the target area have important effects on the reflection intensity. Specifically, the higher the reflectivity and the closer the distance, the stronger the reflection interference. The magnitude of the reflection interference is usually inversely proportional to the square of the distance between the object and the target area, while the reflectivity is proportional to the interference intensity. Based on the geometric topological relationship (i.e., the spatial position relationship between the object and the target area), the influence degree of each high-reflective object on the target area can be accurately calculated. By introducing the reflection suppression factor, the system can accurately quantify the reflection interference according to the reflection characteristics and positions of the objects, thus avoiding over-compensation for areas far from high-reflective objects and ensuring appropriate compensation for areas with close high-reflective objects. This can improve the accuracy of compensation and reduce the situations of over-compensation or under-compensation. The reflection characteristics of a moving object change as the object moves, especially the reflectivity of the object. The change rate of the reflectivity affects the intensity of the reflected light, and thus affects the illumination distribution of the target area. To accurately compensate for the reflection interference caused by dynamic objects, a dynamic compensation gain coefficient needs to be generated to quantify the influence of the change in reflectivity. This gain coefficient increases exponentially, meaning that when the change rate of the object's surface reflectivity is faster, the compensation gain coefficient will increase rapidly. This is because a rapidly changing reflection characteristic means that the interference of the reflected light is also changing rapidly, and a more sensitive compensation mechanism is required. This gain coefficient can adapt to the changes of moving objects in real time and dynamically adjust the illumination compensation. Through the exponential increase setting, the system can effectively cope with the rapidly changing reflectivity and avoid uneven or unstable illumination phenomena caused by too rapid changes. Ambient light fluctuations are usually accompanied by frequency fluctuations. In particular, high-frequency fluctuations in light intensity can lead to instantaneous instability in compensation calculations. If these high-frequency fluctuations are directly used to adjust the compensation amount, it may cause the lighting system to react too violently, resulting in visual discomfort. By analyzing the spectral characteristics of ambient light fluctuations, the main fluctuation frequencies can be identified. Then, by calculating the temporal smoothing coefficient, the instantaneous interference of high-frequency fluctuations can be suppressed. The temporal smoothing coefficient can help smooth the rapidly changing light intensity fluctuations and reduce their influence on the compensation amount, thus avoiding over-reaction of the compensation strategy. The temporal smoothing coefficient can effectively reduce the interference of high-frequency fluctuations in light intensity on the compensation calculation and ensure the stability of the compensation amount. In this way, over-regulation of the lighting system due to short-term fluctuations in the light environment can be avoided, ensuring the long-term stability and comfort of the lighting system. The final compensation amount is obtained by weighted fusion of different factors (reflection suppression factor, dynamic compensation gain coefficient, and temporal smoothing coefficient). The weight of each factor will be adjusted according to different situations. For example, if the spatial coverage density of a certain lighting unit is relatively high, then its compensation requirement may be greater than that of other areas, so a higher weight needs to be assigned.This weighted fusion strategy can comprehensively consider physical reflection characteristics, dynamic object interference, and environmental noise to ensure more accurate and dynamically adjustable compensation amounts. By weighted fusing multiple compensation factors, the system can provide more accurate compensation amounts under different environmental conditions. This can not only cope with the interference of static reflection sources but also dynamically adjust the lighting to handle the reflection changes of moving objects and suppress the influence of environmental noise. The weighted adjustment weights can also ensure the compensation accuracy of each region according to the spatial coverage density of different regions.

[0051] In one embodiment, before the step of obtaining the environmental data of the lighting area in response to the compensation trigger signal, the method further includes:

[0052] Obtain the spectral characteristics of the direct light source intensity and the reflected light source intensity;

[0053] Based on the spectral characteristics of the direct light source intensity and the reflected light source intensity, analyze the differences in their spectral characteristics;

[0054] According to the analysis results, determine the superimposed area of the natural light source and the artificial light source;

[0055] Calculate the light intensity proportion weights of various light sources in the superimposed area. When the proportion of the artificial light source exceeds the preset dominant threshold, reduce the interference threshold by the first adjustment coefficient;

[0056] When the proportion of the natural light source exceeds the preset dominant threshold, increase the interference threshold by the second adjustment coefficient;

[0057] Re-determine the validity of the compensation trigger signal according to the adjusted interference threshold. If the interference parameter still exceeds the standard in the area dominated by the artificial light source, the local compensation mechanism is preferentially triggered.

[0058] As described above, the direct light source intensity refers to the change in the light intensity of a light source (such as an LED lamp, sunlight, etc.) directly irradiating the target area. The reflected light source intensity refers to the light intensity reflected or scattered into the target area (such as sunlight reflection, indoor light reflection, etc.). Different light sources (natural light and artificial light) have different spectral characteristics. Natural light (such as sunlight) usually has a relatively smooth and broadband spectral distribution, while artificial light sources (such as LED light) may exhibit a more concentrated spectrum. By analyzing these spectral characteristics, the characteristics of the two light sources can be distinguished, providing a basis for subsequent light source identification and interference threshold adjustment. By obtaining the spectral characteristics of the light source, the system can distinguish between the direct light source and the reflected light source and analyze based on their different spectral distributions. This provides a reliable data basis for subsequent light source analysis and interference threshold adjustment, effectively coping with the light source mixing situation and preventing misjudgment. The spectral characteristics of the direct light source and the reflected light source usually have significant differences. The direct light source may show relatively concentrated frequency peaks (especially for artificial light sources), while the reflected light source presents a more dispersed or broad spectrum. By comparing the spectral characteristic differences between the two, it can be determined which part of the light intensity is from direct irradiation and which part is from reflection. For example, the intensity of the reflected light source may be closely related to environmental changes (such as weather, time, etc.), while the direct light source may be more stable. Analyzing the spectral differences can help the system accurately distinguish between the direct light source and the reflected light source. Natural light sources (such as sunlight) and artificial light sources (such as LED lamps) usually have different characteristics in the spectrum. By analyzing the spectral differences between the two, the system can determine the superimposed area of the light sources, that is, the area where natural light and artificial light interact with each other. This determination is based on the spectral differences. The identified superimposed area is a key part of the mixed lighting scene, and they will be affected by both light sources, so special interference threshold adjustment is required. By accurately determining the superimposed area of natural light and artificial light sources, the system can optimize for this specific area to avoid misjudgment caused by the interference of mixed light sources. This step helps to identify the key areas in the complex lighting environment and provides a basis for interference threshold adjustment. Within the superimposed area, the light intensity ratio of artificial light sources and natural light sources will affect the final lighting effect. Calculating the weight of the light intensity ratio of various light sources can more accurately evaluate the influence degree of each light source on the lighting environment. This weight calculation is based on the difference in light source intensity. When the proportion of artificial light sources is higher, it means that the artificial light source has a greater influence on this area, and vice versa, it means that the natural light source dominates. By calculating the light source proportion weight, the system can dynamically adjust the compensation strategy within the light source superimposed area to ensure that the compensation is more in line with the actual lighting conditions. This calculation helps to optimize the threshold setting and avoid misjudgment caused by changes in the light source ratio. When the proportion of artificial light sources in the superimposed area exceeds the preset threshold, it indicates that the artificial light source has a greater influence on the lighting of this area. At this time, it is necessary to reduce the interference threshold to better identify and suppress the reflection interference caused by the artificial light source.This adjustment strategy is to improve the system's sensitivity to artificial light sources, so as to promptly activate the compensation mechanism and prevent the artificial light source from causing excessive reflection interference to the target area. Lowering the interference threshold can make the system respond more sensitively in areas dominated by artificial light sources, and give priority to solving the interference problems caused by artificial light sources. This helps the system to perform interference compensation in a timely and accurate manner and improve the accuracy of the compensation effect. On the contrary, when the proportion of natural light sources exceeds the threshold, it means that the illumination of the natural light source (such as sunlight) in this area is dominant. At this time, the system needs to increase the interference threshold to reduce the overreaction to the changes of natural light sources and avoid misjudging as reflection interference. Increasing the interference threshold is to improve the system's tolerance to the changes of natural light sources, so that the system will not frequently trigger the compensation mechanism due to the changes of ambient light. After adjusting the interference threshold, the system needs to re-evaluate the effectiveness of the compensation trigger signal. Re-determining the effectiveness of the signal is to ensure that the compensation mechanism can still be accurately triggered under the new lighting conditions. If the adjusted interference threshold still cannot effectively eliminate the interference in the area dominated by artificial light sources, the system will give priority to activating the local compensation mechanism. The local compensation mechanism can perform refined compensation in the area dominated by artificial light sources, so as to effectively eliminate the interference caused by artificial light sources and ensure the lighting quality of the target area.

[0059] In one embodiment, after the step of calculating the light intensity proportion weights of various light sources in the calculation superposition area, the method further includes:

[0060] When neither the proportion of the natural light source nor the artificial light source exceeds the preset dominant threshold, the original interference threshold is maintained.

[0061] As described above, in the calculation of the superimposed area, first calculate the light intensity ratio of the natural light source and the artificial light source. The purpose of this step is to accurately evaluate the lighting conditions to determine which light sources contribute more to the lighting of the area. By quantifying the ratio of each light source, the relative intensity between natural light and artificial light can be further identified. By calculating the light source ratio, it is clear how much natural light and artificial light contribute to the final lighting effect. Calculating this ratio helps to understand the lighting characteristics of the environment, and then formulate a reasonable lighting adjustment strategy. Set a "dominant threshold" to distinguish between "dominant light sources" and "non-dominant light sources". If the ratios of natural light and artificial light do not exceed this dominant threshold, it means that their contributions are relatively close, and there is no obvious dominant single light source. Set a threshold to determine when the influence of both light sources is insufficient to reach a balanced state. Avoid misjudgment when natural light and artificial light are close. If an appropriate dominant threshold is not set, it may lead to unnecessary adjustments, thus affecting the system stability and efficiency. When the ratios of the natural light source and the artificial light source do not exceed the dominant threshold, keep the original interference threshold unchanged. The purpose of this is to prevent miscompensation in this "balanced" state, because at this time the system cannot determine whether there is an obvious change in the light source or adjustment is needed. If misoperation compensation is performed in this case, it will cause unnecessary fluctuations in the lighting, affecting the stability and comfort of the lighting. Define the processing rules for non-dominant lighting areas and prevent mis-triggering of compensation in the intermediate state (when neither natural light nor artificial light is dominant). By ensuring that adjustments are made only when a light source clearly dominates, avoiding unreasonable system responses when the contributions of natural light and artificial light are close, this helps to improve the overall system efficiency and accuracy. In practical applications, such settings can prevent misjudgment of the balanced state of the light source ratio, avoid over-intervention, and ensure the accuracy and stability of lighting adjustment.

[0062] In one embodiment, the step of determining the superimposed area of the natural light source and the artificial light source includes:

[0063] Based on the spectral feature differences between the direct light source intensity and the reflected light source intensity, identify the sub-areas with the continuous spectrum energy ratio higher than the preset natural light threshold and the discrete spectrum peak intensity higher than the preset artificial light threshold;

[0064] According to the identification results, mark the sub-areas that simultaneously meet the following conditions as the superimposed area.

[0065] As described above, there are certain differences in the spectral characteristics between natural light sources and artificial light sources. Natural light usually has a relatively continuous spectral distribution, especially in the visible light range; while artificial light sources (such as incandescent lamps, fluorescent lamps, etc.) may have relatively obvious discrete spectral peaks. This step classifies and demarcates the light sources by comparing the spectral characteristic differences between the direct light source intensity (the light directly irradiating the object) and the reflected light source intensity (the light irradiating on the reflecting surface). Direct light source intensity: It represents the light directly irradiated on the surface by natural light or artificial light sources, characterized by a relatively strong continuous spectrum. Reflected light source intensity: The reflected light is usually weak, and its spectral characteristics are affected by the material of the object surface. It may be closer to the spectrum of natural light sources, but there will still be certain differences. Through the analysis of spectral differences, the characteristics of natural light and artificial light can be distinguished, thereby identifying sub-regions with different light source characteristics. Two threshold criteria are combined: Natural light threshold: When the proportion of continuous spectrum energy in a sub-region (i.e., the proportion of continuous light energy in the total energy in the spectrum) is higher than the set natural light threshold, it indicates that the light source in this region is mainly natural light. Artificial light threshold: When the intensity of discrete spectral peaks in a sub-region (i.e., the light intensity manifested as discrete peaks in the spectrum) is higher than the set artificial light threshold, it indicates that the light source in this region is mainly artificial light. By setting the two thresholds, sub-regions with both natural light and artificial light can be accurately identified. If a sub-region meets both of these conditions (i.e., has both a high proportion of continuous spectrum energy and strong discrete spectral peak intensity) at the same time, then this sub-region is determined to be a superposition region of natural light and artificial light. These regions are marked as superposition regions, that is, in these regions, the characteristics of the light source come from both natural light and artificial light at the same time. Through this marking, the lighting system can perform specific lighting intensity calculations, adjustments, and optimizations for these regions. Clearly identifying these sub-regions as superposition regions enables the system to perform subsequent light source proportion calculations and adjustments based on this identification. For example, the proportion calculation can perform spatial distribution analysis based on these marked superposition regions, so as to more accurately understand and adjust the specific contributions of natural light and artificial light.

[0066] In one embodiment, after the step of dynamically adjusting the brightness output parameters of the lighting unit in the target region based on the lighting adjustment strategy, the method further includes:

[0067] Obtain the reflected light source intensity in real time;

[0068] When the reflected light source intensity suddenly increases by more than a preset sudden increase threshold within a preset time, start the temporary compensation mode, temporarily reduce the interference threshold to the emergency threshold, and implement pre-attenuation control on the lighting units adjacent to the suddenly increasing region.

[0069] As described above, the intensity of the reflected light source is monitored in real time. The intensity of the reflected light source may be disturbed by external factors (such as car lights, street lights, etc.), especially around glass curtain walls or other reflective surfaces. To identify the interference sources in a timely manner, the system needs to continuously monitor the intensity of the reflected light source through sensors or optical detection devices. By obtaining the intensity of the reflected light source in real time, sudden changes in the intensity of the reflected light source can be identified in real time. The intensity of the reflected light source may be affected by external disturbances, such as sudden car light illumination. In this step, by setting a sudden increase threshold, that is, when the intensity of the reflected light source suddenly increases and exceeds this threshold within a preset time range, the system will determine that this is a reflected interference event, and then start the temporary compensation mode. The goal of the temporary compensation mode is to reduce the impact of reflected interference by quickly adjusting the output parameters of the lighting unit. When abnormal light intensity changes occur, the system can respond quickly, start the temporary compensation mechanism, and avoid the impact of reflected interference on the lighting effect of the target area. This response is faster than traditional compensation methods, reducing the lighting fluctuations caused by delays. After the temporary compensation mode is started, the system will temporarily lower the interference threshold, that is, reduce the tolerance for changes in the intensity of the reflected light source, thereby enhancing the sensitivity of the interference response. In this way, even small changes in the intensity of the reflected light source can be captured in a timely manner and compensated. This measure is mainly to cope with sudden strong reflected light sources, enabling the system to respond more quickly. By lowering the interference threshold, the system can more sensitively identify changes in the reflected light source within a short period of time, ensure a quick response to sudden interference, and avoid response delays caused by too high a threshold. When a sudden increase in the reflected light source is detected, the system not only makes adjustments in the target area, but also performs pre-attenuation control on the lighting units adjacent to the sudden increase area. This is because the sudden increase in the reflected light source may affect the surrounding areas, especially the lighting units in the adjacent areas. Therefore, by performing pre-attenuation control on the adjacent units in advance, the interference of the reflected light source can be prevented from spreading further and the overall impact can be reduced. Pre-attenuation control can reduce the lighting intensity in the adjacent areas in advance, prevent the influence of the reflected light source from spreading to a larger area, and ensure the lighting stability of the target area. By attenuating in advance, not only can the interference of the sudden increase in the light source be reduced, but also unnecessary lighting adjustments to other areas can be avoided.

[0070] It is worth mentioning that due to the inability of existing systems to distinguish the spatial / spectral characteristics of reflected light and direct light, two typical error adjustment modes are caused: 1. Negative interference scenario: A highly reflective object (such as a mirror, glass) reflects the effective illumination light to a non-target area, and at the same time, the sensor reduces the brightness due to receiving the reflected light. This results in insufficient illuminance in the target area (for example, the actual illuminance of a desk is lower than the standard due to wall reflection). 2. Positive interference scenario: Outdoor reflected light (such as sunlight reflected by a building glass curtain wall) invades the indoor sensor, and the system misjudges that the indoor light is sufficient and turns off the supplementary light, resulting in insufficient illuminance in the actual working area. It is necessary to distinguish the spatial source differences between outdoor reflected light and indoor effective illumination light.

[0071] In one embodiment, after the step of dynamically adjusting the brightness output parameter of the lighting unit in the target area based on the lighting adjustment strategy, the method further includes:

[0072] Obtain the light environment parameters;

[0073] According to the light environment parameters, analyze the spatial distribution direction vectors of the direct light source and the reflected light source;

[0074] Combining the spatial distribution direction vectors of the direct light source and the reflected light source, determine the included angle value between the direct light source direction vector and the reflected light source direction vector;

[0075] When the included angle value is greater than a preset intrusion determination threshold, then determine that the reflected light source is outdoor intrusion reflected light

[0076] According to the spatial distribution included angle, analyze whether the conditions for outdoor reflected light intrusion are met;

[0077] Based on the determination result of outdoor reflected light intrusion, activate the anti-interference compensation mode, and perform illuminance enhancement control on the reverse area of the incident direction of the reflected light source;

[0078] Record the duration of the reflected light source. When the duration exceeds a preset time threshold, generate a physical light shielding linkage signal.

[0079] As described above, the spatial distribution of the light source can be captured by a direction-sensitive element (such as a fish-eye lens + optical flow method), providing original data support for the tracing of reflected light and solving the defect that a traditional single light intensity sensor cannot locate the direction of the light source. Based on LiDAR point cloud or binocular vision technology, reconstruct the three-dimensional propagation path of the direct light source (such as a lamp) and the reflected light source, convert the abstract light intensity signal into a concrete spatial vector, and for the first time realize the digital modeling of the lighting optical path. The included angle threshold determination can set an intrusion determination threshold of 60° - 90° (verified by experiments, the included angle of indoor reflected light is usually < 45°), and quantify the difference in light direction through cosine similarity. Accurately distinguish between building reflections outside the window (large angles) and indoor mirror reflections (small angles), and avoid misjudging the evening sunlight as lamp light. Start the "vector compensation" algorithm in the reverse area of the reflected light, and dynamically calculate the intensity and direction of the compensated light according to the incident angle. Break through the limitation of traditional uniform light compensation. For example, when sunlight is reflected on the ground outside the window, preferentially enhance the lighting of the workstations facing away from the window rather than globally brightening. The physical light shielding linkage can form a double-layer defense of "photoelectric compensation → physical blockage" by establishing a communication protocol between the duration of the reflected light and the building management system (BMS), and trigger the action of the sunshade device after exceeding the threshold, solving the energy consumption problem of long-term strong reflections (such as continuous reflection of glass curtain walls).

[0080] Refer to Figure 3, an embodiment of the present application also provides a brightness AI adaptive adjustment system for a lighting system, including:

[0081] A first acquisition module 1 for real-time acquisition of light environment parameters of the lighting area, where the light environment parameters include direct light source intensity, reflected light source intensity, and spatial distribution characteristics;

[0082] A determination module 2 for determining an interference parameter of the reflected light source on the target area based on the spatial distribution characteristics and the reflected light source intensity, and generating a compensation trigger signal when the interference parameter exceeds a preset interference threshold;

[0083] A second acquisition module 3 for acquiring environmental data of the lighting area in response to the compensation trigger signal;

[0084] A calculation module 4 for calculating a reflection interference compensation amount according to the environmental data, where the environmental data includes moving object reflection characteristics, high-reflection object positions, and environmental light fluctuation trends;

[0085] A generation module 5 for generating a lighting adjustment strategy according to the reflection interference compensation amount, where the strategy includes cooperative control parameters for lighting units in the target area, and is used to cancel the interference of the reflected light source and maintain the effective illuminance of the target area;

[0086] An adjustment module 6 for dynamically adjusting the brightness output of lighting units in the target area based on the lighting adjustment strategy.

[0087] As described above, it can be understood that each component of the brightness AI adaptive adjustment system for the lighting system proposed in the present application can implement the functions of any one of the brightness AI adaptive adjustment methods for the lighting system described above, and the specific structure will not be elaborated.

[0088] Refer to Figure 4 , an embodiment of the present application also provides a computer device, which may be a server, and its internal structure may be as Figure 4 shown. The computer device includes a processor, a memory, a network interface, and a database connected through a system bus. Among them, the processor of the computer design is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data such as monitoring data. The network interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements a brightness AI adaptive adjustment method for a lighting system.

[0089] The above-mentioned processor executes the above-mentioned brightness AI adaptive adjustment method for the lighting system, including: obtaining the light environment parameters of the lighting area in real time, where the light environment parameters include direct light source intensity, reflected light source intensity and spatial distribution characteristics; determining the interference parameter of the reflected light source on the target area based on the spatial distribution characteristics and the reflected light source intensity, and generating a compensation trigger signal when the interference parameter exceeds a preset interference threshold; in response to the compensation trigger signal, obtaining the environmental data of the lighting area; calculating the reflected interference compensation amount according to the environmental data, where the environmental data includes moving object reflection characteristics, high-reflection object positions and environmental light fluctuation trends; generating a lighting adjustment strategy according to the reflected interference compensation amount, and the strategy includes cooperative control parameters for the lighting units in the target area, which are used to offset the interference of the reflected light source and maintain the effective illuminance of the target area; dynamically adjusting the brightness output of the lighting units in the target area based on the lighting adjustment strategy.

[0090] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements a brightness AI adaptive adjustment method for a lighting system, including the steps of: obtaining the light environment parameters of the lighting area in real time, where the light environment parameters include direct light source intensity, reflected light source intensity and spatial distribution characteristics; determining the interference parameter of the reflected light source on the target area based on the spatial distribution characteristics and the reflected light source intensity, and generating a compensation trigger signal when the interference parameter exceeds a preset interference threshold; in response to the compensation trigger signal, obtaining the environmental data of the lighting area; calculating the reflected interference compensation amount according to the environmental data, where the environmental data includes moving object reflection characteristics, high-reflection object positions and environmental light fluctuation trends; generating a lighting adjustment strategy according to the reflected interference compensation amount, and the strategy includes cooperative control parameters for the lighting units in the target area, which are used to offset the interference of the reflected light source and maintain the effective illuminance of the target area; dynamically adjusting the brightness output of the lighting units in the target area based on the lighting adjustment strategy.

[0091] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium provided in this application and used in the embodiments can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0092] It should be noted that in this text, the term "including", "comprising", or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, device, article, or method including a series of elements not only includes those elements but also includes other elements not explicitly listed, or further includes elements inherent to such a process, device, article, or method. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, device, article, or method including that element.

[0093] The above are only the preferred embodiments of this application, and do not limit the patent scope of this application accordingly. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of this application, or directly or indirectly applied in other related technical fields, shall be included in the patent protection scope of this application by the same token.

Claims

1. An AI self - adaptive brightness adjustment method for a lighting system, characterized in that, The method includes: Obtaining the light environment parameters of the illumination area in real time, where the light environment parameters include the direct light source intensity, the reflected light source intensity, and the spatial distribution characteristics; Based on the spatial distribution characteristics and the reflected light source intensity, determining the interference parameter of the reflected light source on the target area, and generating a compensation trigger signal when the interference parameter exceeds a preset interference threshold; In response to the compensation trigger signal, obtaining the environmental data of the illumination area; Calculating the reflection interference compensation amount according to the environmental data, where the environmental data includes the reflection characteristics of moving objects, the positions of highly reflective objects, and the environmental light fluctuation trend; Generating an illumination adjustment strategy according to the reflection interference compensation amount, where the strategy includes the collaborative control parameters for the lighting units in the target area, and is used to cancel the interference of the reflected light source and maintain the effective illuminance of the target area; Dynamically adjusting the brightness output of the lighting units in the target area based on the illumination adjustment strategy.

2. The brightness AI adaptive adjustment method for a lighting system according to claim 1, characterized in that, The step of generating the illumination adjustment strategy according to the reflection interference compensation amount includes: Obtaining the environmental data, and calculating the spatial weight distribution coefficient of each lighting unit according to the relative spatial relationship between the position of the highly reflective object and the target area, where the lighting unit closest to the highly reflective object is assigned the highest suppression weight; Combining the real-time change rate of the reflection characteristics of moving objects to generate a compensation intensity correction coefficient that is positively correlated with the dynamic reflection interference intensity; Based on the environmental light fluctuation trend, setting a dynamic response rate threshold for brightness adjustment, where the rate threshold is negatively correlated with the light fluctuation frequency; Performing multi-dimensional fusion on the spatial weight distribution coefficient, the compensation intensity correction coefficient, and the dynamic response rate threshold to generate a set of collaborative control parameters including the light intensity modulation gradient, the regional priority sequence, and the phase delay parameter, where the phase delay parameter is used to match the adaptation time constant of the human eye to sudden brightness changes.

3. The brightness AI adaptive adjustment method for a lighting system according to claim 2, characterized in that, The step of calculating the reflection interference compensation amount according to the environmental data includes: Based on the geometric topological relationship between the position of the highly reflective object and the target area, calculating the reflection suppression factor of each highly reflective object on the target area, where the reflection suppression factor is positively correlated with the object reflectivity and the square of the distance; Combining the real-time change rate of the reflection characteristics of moving objects to generate a dynamic compensation gain coefficient, and the gain coefficient increases exponentially with the increase of the change rate of the surface reflectivity of the moving object; According to the spectral characteristics of the environmental light fluctuation trend, extracting the main frequency of light intensity fluctuation and calculating the time series smoothing coefficient, where the time series smoothing coefficient is used to suppress the instantaneous interference of high-frequency fluctuations on the compensation amount; Performing weighted fusion on the reflection suppression factor, the dynamic compensation gain coefficient, and the time series smoothing coefficient to generate the reflection interference compensation amount of the target area, where the fusion weight is dynamically adjusted according to the spatial coverage density of the lighting units.

4. The brightness AI adaptive adjustment method for a lighting system according to claim 1, characterized in that, Before the step of obtaining the environmental data of the illumination area in response to the compensation trigger signal, the method further includes: Obtaining the spectral characteristics of the direct light source intensity and the reflected light source intensity; Based on the spectral characteristics of the direct light source intensity and the reflected light source intensity, analyzing the differences between the two spectral characteristics; According to the analysis result, determining the superimposed area of the natural light source and the artificial light source; Calculate the light intensity proportion weights of various light sources in the superimposed area. When the proportion of artificial light sources exceeds the preset dominant threshold, reduce the interference threshold by the first adjustment coefficient; When the proportion of natural light sources exceeds the preset dominant threshold, increase the interference threshold by the second adjustment coefficient; Re-determine the validity of the compensation trigger signal according to the adjusted interference threshold. If the interference parameter still exceeds the standard in the area dominated by artificial light sources, the local compensation mechanism will be triggered preferentially.

5. The brightness AI adaptive adjustment method for a lighting system according to claim 4, characterized in that, After the step of calculating the light intensity proportion weights of various light sources in the superimposed area, the method further includes: When neither the proportion of natural light sources nor that of artificial light sources exceeds the preset dominant threshold, keep the original interference threshold.

6. The brightness AI adaptive adjustment method for a lighting system according to claim 4, wherein The step of determining the superimposed area of natural light sources and artificial light sources includes: Based on the spectral feature differences between the direct light source intensity and the reflected light source intensity, identify the sub-areas with the continuous spectrum energy proportion higher than the preset natural light threshold and the discrete spectrum peak intensity higher than the preset artificial light threshold; According to the recognition result, mark the sub-areas that meet the following conditions simultaneously as the superimposed area.

7. The brightness AI adaptive adjustment method for a lighting system according to claim 1, wherein After the step of dynamically adjusting the brightness output parameters of the lighting units in the target area based on the lighting adjustment strategy, the method further includes: Obtain the light environment parameters; According to the light environment parameters, analyze the spatial distribution direction vectors of the direct light source and the reflected light source; Combined with the spatial distribution direction vectors of the direct light source and the reflected light source, determine the included angle value between the direct light source direction vector and the reflected light source direction vector; When the included angle value is greater than the preset intrusion determination threshold, determine that the reflected light source is outdoor intrusion reflected light Analyze whether the conditions for outdoor reflected light intrusion are met according to the spatial distribution included angle; Based on the determination result of outdoor reflected light intrusion, activate the anti-interference compensation mode and implement illuminance enhancement control on the reverse area of the incident direction of the reflected light source; Record the duration of the reflected light source. When the duration exceeds the preset time threshold, generate a physical light shielding linkage signal.

8. An AI self-adaptive brightness adjustment system for a lighting system, characterized in that, Includes: The first acquisition module is used to acquire the light environment parameters of the lighting area in real time. The light environment parameters include the direct light source intensity, the reflected light source intensity and the spatial distribution characteristics; The determination module is used to determine the interference parameters of the reflected light source on the target area based on the spatial distribution characteristics and the reflected light source intensity, and generate a compensation trigger signal when the interference parameters exceed the preset interference threshold; The second acquisition module is used to acquire the environmental data of the lighting area in response to the compensation trigger signal; The calculation module is used to calculate the reflection interference compensation amount according to the environmental data. The environmental data includes the reflection characteristics of moving objects, the positions of highly reflective objects and the environmental light fluctuation trend; The generation module is used to generate a lighting adjustment strategy according to the reflection interference compensation amount. The strategy includes the collaborative control parameters for the lighting units in the target area, which are used to offset the interference of the reflected light source and maintain the effective illuminance of the target area; The adjustment module is used to dynamically adjust the brightness output of the lighting units in the target area based on the lighting adjustment strategy.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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