Adaptive adjustment method and system for lighting equipment based on ambient light intensity

Abstract

The invention provides a lighting equipment self-adaptive adjustment method and system based on ambient light intensity, and relates to the technical field of lighting equipment, and the method comprises the steps: obtaining the application scene information and application area range of target lighting equipment, and carrying out the lighting strategy analysis; carrying out matching analysis on the ambient light intensity data and the ambient light segmented illumination strategy; historical illumination data mining is carried out based on a target illumination strategy, and global optimization is carried out in an illumination strategy parameter space according to an illumination application target; and based on the user activity information and the user illumination demand, carrying out adaptive regulation and control correction on the target illumination parameter, and based on the illumination correction parameter, carrying out closed-loop regulation and control on the target illumination equipment. According to the invention, the technical problem in the prior art that the lighting strategy cannot be accurately matched with the actual use demand of each functional area can be solved, the technical targets of dynamic lighting strategy construction and adaptive regulation and control are realized, and the technical effect of improving the multi-scene adaptability is achieved.

Description

Technical Field

[0001] This application relates to the technical field of lighting equipment, and particularly to an adaptive adjustment method and system for lighting equipment based on ambient light intensity. Background Art

[0002] Lighting control technology has gradually developed from traditional switch control to intelligent and adaptive adjustment. Especially in multi-scenario environments such as indoor offices, homes, commercial places, and public facilities, the application of intelligent lighting systems has become an important means to improve energy utilization efficiency and user comfort experience.

[0003] Currently, existing intelligent lighting solutions fail to conduct a detailed functional division of the application area and cannot specifically identify the differences in lighting requirements for different areas (such as corridors, reading areas, rest areas, etc.), resulting in unreasonable allocation of lighting resources and the phenomenon of some areas being too bright or too dark. At the same time, in the decision-making process, most rely on a single ambient light parameter or static model and fail to effectively combine real-time user behavior characteristics (such as movement trajectories, stay times) with personalized lighting preferences (such as high brightness for reading preferences, soft light for rest preferences) for refined control. In addition, during the adjustment process, some lighting equipment responses are delayed, and the response capabilities of the equipment are not fully evaluated, resulting in problems such as lagging compensation adjustment or over-adjustment, which affect lighting quality and user experience.

[0004] In summary, there are technical problems in the prior art that due to the lack of refined functional division of the application area and identification of different lighting requirements, the lighting strategy cannot accurately match the actual usage needs of each functional area, further affecting the overall performance of the lighting system in terms of energy utilization efficiency, user visual comfort, and scene adaptability. Summary of the Invention

[0005] The purpose of this application is to provide an adaptive adjustment method and system for lighting equipment based on ambient light intensity, so as to solve the technical problems in the prior art that due to the lack of refined functional division of the application area and identification of different lighting requirements, the lighting strategy cannot accurately match the actual usage needs of each functional area, further affecting the overall performance of the lighting system in terms of energy utilization efficiency, user visual comfort, and scene adaptability.

[0006] In view of the above problems, this application provides an adaptive adjustment method and system for lighting equipment based on ambient light intensity.

[0007] In a first aspect, the present application provides a method for adaptively adjusting a lighting device based on ambient light intensity, which is implemented through an adaptive adjustment system for a lighting device based on ambient light intensity, and includes: obtaining application scenario information and application area range of a target lighting device, analyzing lighting strategies based on the application scenario information and application area range, and establishing an ambient light segmented lighting strategy; arranging light intensity sensors to sense and obtain ambient light intensity data, performing matching analysis on the ambient light intensity data and the ambient light segmented lighting strategy to obtain a target lighting strategy; mining historical lighting data based on the target lighting strategy, constructing a lighting strategy parameter space, and globally optimizing within the lighting strategy parameter space according to lighting application objectives to determine target lighting parameters; monitoring and obtaining user activity information and user lighting requirements through an infrared sensor, adaptively adjusting and correcting the target lighting parameters based on the user activity information and user lighting requirements to obtain lighting correction parameters, and performing closed-loop adjustment control on the target lighting device based on the lighting correction parameters.

[0008] Preferably, the method for adaptively adjusting a lighting device based on ambient light intensity further includes: dividing the application area range into functional area ranges to obtain multiple application space areas; estimating the lighting conditions of the multiple application space areas based on the application scenario information to obtain multiple regional ambient light intensity ranges and multiple regional lighting intensity requirements; identifying the application attribute information of the target lighting device to obtain the lighting device type, lighting device location, and lighting coverage range; analyzing lighting strategies for the lighting device type, lighting device location, and lighting coverage range based on the multiple regional ambient light intensity ranges and multiple regional lighting intensity requirements to obtain an ambient light segmented lighting strategy.

[0009] Preferably, the method for adaptively adjusting a lighting device based on ambient light intensity further includes: performing segmented logic design on the multiple regional ambient light intensity ranges according to the multiple regional lighting intensity requirements to obtain multiple regional segmented lighting logics; performing ambient light compensation analysis based on the multiple regional segmented lighting logics to establish multiple regional ambient light segmented compensation strategies; performing lighting twin simulation based on the lighting device type, lighting device location, and lighting coverage range to construct a lighting device digital twin model; according to the lighting device digital twin model, simulating and generating multiple regional lighting intensity attenuation curves, and using the multiple regional lighting intensity attenuation curves to supplement and correct the multiple regional ambient light segmented compensation strategies to obtain the ambient light segmented lighting strategy.

[0010] Preferably, the method for adaptively adjusting a lighting device based on ambient light intensity further includes: determining a plurality of regional target lighting strategy intervals according to the segmented lighting logic for the plurality of regions, where the plurality of regional target lighting strategy intervals are lighting compensation intervals with light intensity requirements greater than the ambient light intensity; performing time period compensation analysis on the plurality of application space regions according to the light intensity requirements of the plurality of regions to obtain segmented time period lighting compensation coefficients for the plurality of regions; and performing a mapping connection on the segmented time period lighting compensation coefficients for the plurality of regions and the plurality of regional target lighting strategy intervals to establish a segmented ambient light compensation strategy for the plurality of regions.

[0011] Preferably, the method for adaptively adjusting a lighting device based on ambient light intensity further includes: extracting indicators of the lighting application target to obtain a set of lighting effect evaluation indicators; performing regression fitting on the set of lighting effect evaluation indicators based on the lighting strategy parameter space to construct a lighting effect fitness function; and using the lighting effect fitness function to perform global comparison and optimization within the lighting strategy parameter space until a preset termination condition is reached to determine the target lighting parameters.

[0012] Preferably, the method for adaptively adjusting a lighting device based on ambient light intensity further includes: extracting behavioral characteristics from the user activity information to obtain user behavioral characteristics, where the user behavioral characteristics include a movement trajectory and a stay duration; determining a user behavior pattern according to the user behavioral characteristics; and adaptively adjusting and correcting the target lighting parameters based on the user behavior pattern and the user lighting requirements to obtain lighting correction parameters.

[0013] Preferably, the method for adaptively adjusting a lighting device based on ambient light intensity further includes: performing lighting control analysis on the user behavior pattern and the user lighting requirements to determine a behavior pattern control parameter and a lighting requirement control parameter; setting a behavior weight and a requirement weight, and performing weighted adjustment and correction on the target lighting parameters based on the behavior weight and the requirement weight, as well as the behavior pattern control parameter and the lighting requirement control parameter to obtain the lighting correction parameters.

[0014] Preferably, the method for adaptively adjusting a lighting device based on ambient light intensity further includes: adjusting, controlling, and monitoring the response of the target lighting device based on the lighting correction parameters to obtain lighting device response parameters; determining a lighting device delay coefficient according to the lighting device response parameters; compensating and adjusting the lighting correction parameters based on the lighting device delay coefficient, and performing closed-loop adjustment and control on the target lighting device through the compensated and adjusted lighting correction parameters.

[0015] Preferably, the method for adaptively adjusting a lighting device based on ambient light intensity further includes: when there are multiple lighting devices, a multi-threaded processing mechanism is adopted to perform parallel lighting adjustment on the multiple lighting devices.

[0016] In a second aspect, the present application also provides an adaptive adjustment system for a lighting device based on ambient light intensity, which is used to execute the method for adaptively adjusting a lighting device based on ambient light intensity as described in the first aspect, including: a lighting strategy analysis module, configured to obtain the application scenario information and application area range of a target lighting device, perform lighting strategy analysis based on the application scenario information and application area range, and establish an ambient light segmented lighting strategy; a matching analysis module, configured to deploy a light intensity sensor and sense and obtain ambient light intensity data, perform matching analysis on the ambient light intensity data and the ambient light segmented lighting strategy to obtain a target lighting strategy; a global optimization module, configured to perform historical lighting data mining based on the target lighting strategy, construct a lighting strategy parameter space, perform global optimization within the lighting strategy parameter space according to the lighting application target, and determine target lighting parameters; a closed-loop adjustment control module, configured to monitor and obtain user activity information and user lighting requirements through an infrared sensor, perform adaptive regulation and correction on the target lighting parameters based on the user activity information and user lighting requirements to obtain lighting correction parameters, and perform closed-loop adjustment control on the target lighting device based on the lighting correction parameters.

[0017] The technical solution provided in the present application has at least the following technical effects or advantages: by achieving the technical goal of constructing a dynamic lighting strategy and adaptive regulation based on ambient light intensity and user behavior characteristics, the technical effects of improving the intelligent perception ability, fine control level, and multi-scenario adaptability of the lighting system are achieved.

[0018] The above description is only an overview of the technical solution of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features, and advantages of the present application more obvious and understandable, the following specifically describes the specific embodiments of the present application. It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. Description of the Drawings

[0019] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings described below are only exemplary, and for those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0020] Figure 1 This is a schematic flowchart of the adaptive adjustment method for lighting devices based on ambient light intensity in this application.

[0021] Figure 2 This is a schematic structural diagram of the adaptive adjustment system for lighting devices based on ambient light intensity in this application.

[0022] Explanation of reference numerals: Lighting strategy analysis module 11, matching analysis module 12, global optimization module 13, closed-loop adjustment control module 14. Detailed implementation manners

[0023] By providing the adaptive adjustment method and system for lighting devices based on ambient light intensity, this application solves the technical problem in the prior art that due to the lack of refined functional division of the application area and identification of differentiated lighting requirements, the lighting strategy cannot accurately match the actual usage requirements of each functional area, further affecting the overall performance of the lighting system in terms of energy utilization efficiency, user visual comfort, and scene adaptability. It realizes the technical goal of constructing a dynamic lighting strategy and adaptive control based on ambient light intensity and user behavior characteristics, and achieves the technical effect of improving the intelligent perception ability, fine control level, and multi-scene adaptability of the lighting system.

[0024] Next, the technical solutions in this application will be described clearly and completely with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments of this application. It should be understood that this application is not limited by the example embodiments described here. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application. Additionally, it should be noted that for the sake of description, only the parts related to this application are shown in the accompanying drawings rather than all of them.

[0025] Embodiment 1. Please refer to the attached Figure 1 , this application provides an adaptive adjustment method for lighting devices based on ambient light intensity, which is applied to the adaptive adjustment system for lighting devices based on ambient light intensity, and specifically includes the following steps: S1: Obtain the application scenario information and application area range of the target lighting device, perform lighting strategy analysis based on the application scenario information and application area range, and establish an ambient light segmented lighting strategy.

[0026] Specifically, the target lighting device is the lighting device to be adaptively adjusted. The application scenario information of the target lighting device and the application area range it serves are obtained. The application scenario information refers to the type of environment in which the target lighting device is located, such as an office building, classroom, warehouse, or exhibition hall. The lighting requirements corresponding to different application scenarios vary greatly; and the application area range refers to the actual spatial area covered by the device, such as the length, width, and height data of a conference room, the boundary walls, and the window positions. Through the application scenario information and application area range, the operating environment of the target lighting device can be clarified, and the application area range can be functionally divided accordingly, so as to facilitate the subsequent targeted lighting design.

[0027] Lighting strategy analysis is performed using the acquired application scenario information and application area range to establish a set of segmented ambient light lighting strategies for different lighting conditions. Lighting strategy analysis divides the ambient light intensity into several intervals and determines the lighting method to be adopted in different situations. Each interval corresponds to a specific lighting adjustment method. Based on the current detected ambient light intensity, the most appropriate lighting response strategy can be quickly matched to achieve precise fill light or energy-saving light reduction.

[0028] S2: deploying light intensity sensors to sense and acquire ambient light intensity data, matching and analyzing the ambient light intensity data with the ambient light segmented lighting strategy to obtain a target lighting strategy.

[0029] Specifically, real-time ambient light intensity data is collected by deploying light intensity sensors within a specific area. A light intensity sensor is a device that senses the intensity of light in a space and converts it into an electrical signal. Ambient light intensity data refers to the actual light levels at different times and locations collected by the light intensity sensor, reflecting the degree to which natural light or other external light sources affect the current space.

[0030] Next, the acquired ambient light intensity data is matched with the ambient light segmented lighting strategy for analysis. The matching analysis process is to determine which segmented interval the current ambient light intensity falls into and select the lighting strategy corresponding to that interval, thereby obtaining the target lighting strategy, which refers to the most appropriate light turning on, brightness adjustment or color temperature setting scheme under the current conditions.

[0031] S3: Perform historical lighting data mining based on the target lighting strategy, construct a lighting strategy parameter space, perform global optimization within the lighting strategy parameter space according to the lighting application target, and determine the target lighting parameters.

[0032] Specifically, historical lighting data mining is conducted based on the target lighting strategy. With the established target lighting strategy as the core analysis, relevant parameters and behavioral patterns are extracted from previously collected lighting operation data. Historical lighting data includes information such as lamp on / off status, brightness adjustment records, energy consumption curves, and ambient light intensity changes reported by sensors. By analyzing the patterns in historical lighting data, strategy combinations adopted in different scenarios are extracted to construct a lighting strategy parameter space. This involves organizing all historically valid or feasible parameter combinations into a multidimensional parameter space structure, encompassing multiple dimensions such as brightness level, time scheduling, light color temperature, switching frequency, and lamp position relationships. This supports subsequent fitting, optimization, and simulation.

[0033] Based on the lighting application objectives, a global optimization is performed within the lighting strategy parameter space. Using the predetermined lighting objectives as an optimization guide, the optimal parameter combination is found within the established lighting strategy parameter space to determine the target lighting parameters. Lighting application objectives typically encompass multiple aspects, such as meeting visual task requirements, improving energy efficiency, enhancing user comfort, or maintaining color reproduction accuracy. These objectives can be expressed in numerical terms such as illumination range, color temperature range, energy consumption limit, or frequency of use.

[0034] S4: Acquire user activity information and user lighting needs through infrared sensor monitoring, adaptively adjust and correct the target lighting parameters based on the user activity information and user lighting needs to obtain lighting correction parameters, and perform closed-loop regulation and control on the target lighting device based on the lighting correction parameters.

[0035] Specifically, infrared sensors are used to monitor user activity and lighting needs. Infrared sensors installed in the scene capture real-time human activity data, combined with the user's specific lighting requirements in specific situations. User activity information primarily includes movement, dwell time, and frequency of activity, while user lighting needs are expressed in parameters such as desired brightness levels, color temperature preferences, and lighting time periods.

[0036] Based on user activity information and lighting needs, the system determines whether existing lighting parameters are suitable for the current scenario. If any deviation exists, the target lighting parameters are adaptively adjusted and corrected. The target lighting device is then closed-loop controlled using the resulting lighting correction parameters, with feedback from the target lighting device monitored in real time. Closed-loop control involves collecting the post-execution status in real time after executing an adjustment command, such as whether the actual light intensity meets the target, and whether there are any delays or errors. This data is then fed back to further refine the control strategy, forming a continuously optimized closed-loop process.

[0037] Further, this application also includes: dividing the application area range into functional areas to obtain multiple application space areas; estimating the lighting conditions of the multiple application space areas based on the application scenario information to obtain multiple regional ambient light intensity ranges and multiple regional lighting intensity requirements; identifying the application attribute information of the target lighting device to obtain the lighting device type, lighting device location, and lighting coverage; and analyzing the lighting strategy for the lighting device type, lighting device location, and lighting coverage based on the multiple regional ambient light intensity ranges and multiple regional lighting intensity requirements to obtain an ambient light segmented lighting strategy.

[0038] Specifically, through the application scenario information of the target lighting device, the operating environment of the target lighting device can be determined, and the application area range can be divided into functional areas, that is, the overall application area range is subdivided into multiple application space areas with different uses.

[0039] Using the obtained application scenario information, estimate the lighting conditions of the application space area. Lighting condition estimation refers to evaluating the natural light intensity range of the application space area at different times of the day based on factors such as the number of windows, orientation, and occlusion in the area, so as to obtain the regional ambient light intensity range of each application space area. At the same time, combined with scene function analysis, it is possible to evaluate whether lighting compensation is required and the degree of compensation, and determine the artificial lighting intensity requirements for each application space area to obtain multiple regional lighting intensity requirements.

[0040] Identify the application attribute information of each target lighting device to obtain the lighting device type, lighting device location, and lighting coverage. The type of lighting device (such as LED ceiling lights, track lights, chandeliers, etc.) affects the light intensity, color temperature, and light distribution characteristics of the target lighting device; the location of the lighting device refers to the specific coordinates where the target lighting device is installed in the space, which affects its lighting coverage and shadow projection; the lighting coverage indicates the area that can be effectively illuminated by the light of the target lighting device, which usually depends on parameters such as installation height, light-emitting angle, and power.

[0041] Based on the multiple regional ambient light intensity ranges and multiple regional lighting intensity requirements, comprehensively analyze the lighting strategy, and finally form an ambient light segmented lighting strategy. Lighting strategy analysis refers to analyzing the areas that require additional lighting and the lighting devices that need to reach the target illuminance under different light intensity ranges. The ambient light segmented lighting strategy refers to dividing the ambient light intensity into several intervals, and each interval corresponds to a different regional ambient light segmented compensation strategy.

[0042] Furthermore, this application also includes: performing a segmented logic design on the ambient light intensity ranges of the multiple regions according to the lighting intensity requirements of the multiple regions to obtain segmented lighting logics for the multiple regions; performing ambient light compensation analysis based on the segmented lighting logics of the multiple regions to establish segmented ambient light compensation strategies for the multiple regions; performing lighting twin simulation based on the lighting device type, lighting device location, and lighting coverage to construct a digital twin model of the lighting device; according to the digital twin model of the lighting device, simulating and generating lighting intensity attenuation curves for the multiple regions, and using the lighting intensity attenuation curves for the multiple regions to supplement and correct the segmented ambient light compensation strategies for the multiple regions to obtain the segmented ambient light lighting strategy.

[0043] Specifically, perform a segmented logic design on the corresponding regional ambient light intensity ranges according to the lighting intensity requirements of multiple regions. The segmented logic design means dividing the ambient light intensity values that may occur in a region under natural conditions (for example, from 0 lux to 600 lux) into several sub-intervals, such as 0 to 100 lux, 101 to 300 lux, 301 to 500 lux, etc., and then formulating lighting control logics for each interval respectively. The lighting intensity requirement refers to the artificial lighting brightness required for each functional area to meet the usage comfort or specification requirements. By logically segmenting the ambient light range according to the requirements, segmented lighting logics for multiple regions can be obtained, and corresponding strategies can be formulated accordingly.

[0044] Immediately afterwards, based on the segmented lighting logics of multiple regions, perform ambient light compensation analysis on each segmented interval. Ambient light compensation means that when natural light is insufficient to meet the lighting requirements, calculate the supplementary light intensity required for each segment through the difference between the actual illuminance and the target illuminance in each segment, and then use it to control the lighting response in different states.

[0045] After formulating the segmented ambient light compensation strategies for multiple regions, it is also necessary to consider the physical characteristics and installation conditions of the actual target lighting devices. Therefore, based on the lighting device type, lighting device location, and lighting coverage, perform lighting twin simulation on the lighting effect, that is, simulate the operating state of the lamps in reality by constructing a digital model. The lighting device type involves its light output mode and dimming ability, such as whether it is a spotlight or a diffused light; the lighting location determines the light landing point and illuminance distribution; the lighting coverage reflects its irradiation radius and uniformity. By combining, a digital twin model is established, that is, the operating logic of the lamps and the light influence are truly restored in the virtual space.

[0046] With the help of the digital twin model of the lighting device, multiple regional lighting intensity attenuation curves can be further simulated and generated. The lighting intensity attenuation curve is the downward trend of illuminance during the diffusion process from the central position of the target lighting device to the edge. Through the analysis of multiple regional lighting intensity attenuation curves, the segmented ambient light compensation strategy for multiple regions can be supplemented and corrected, making the segmented ambient light compensation strategy for multiple regions more in line with the actual lighting distribution effect of the device. For example, if the light supplement ability of a device in the edge area is insufficient, the target output power of this area can be increased or additional lamps can be enabled to support. Finally, the strategy after integrating the true capabilities of the device constitutes an accurate and dynamically responsive segmented ambient light lighting strategy.

[0047] Furthermore, this application also includes: determining multiple regional target lighting strategy intervals according to the segmented lighting logic of multiple regions, where the multiple regional target lighting strategy intervals are lighting compensation intervals where the light intensity demand is greater than the ambient light intensity; performing time period compensation analysis on the multiple application space regions according to the light intensity demands of the multiple regions to obtain multiple regional time period segmented lighting compensation coefficients; mapping and connecting the multiple regional time period segmented lighting compensation coefficients and the multiple regional target lighting strategy intervals to establish the segmented ambient light compensation strategy for multiple regions.

[0048] Specifically, according to the segmented lighting logic of multiple regions, multiple regional target lighting strategy intervals are determined. The multiple regional target lighting strategy intervals refer to the light intensity range that needs to be compensated by artificial lighting when the natural ambient light cannot meet the spatial function requirements. According to the difference between the light intensity demand of each region and the actual ambient light intensity, the range that needs lighting compensation is determined as the target lighting strategy interval for each region.

[0049] Next, time period compensation analysis is performed on the multiple application space regions according to the light intensity demands of the multiple regions. Time period compensation analysis means dividing a day into multiple time periods, such as 6:00 to 9:00, 9:00 to 12:00, 12:00 to 18:00, 18:00 to 22:00, etc., and respectively evaluating the relationship between the change trend of natural ambient light and the target lighting difference within different time periods. Finally, multiple regional time period segmented lighting compensation coefficients for multiple regions in multiple time periods are obtained. Through historical data and real-time sampling, the approximate light supplement ratio required for each region at different time points can be obtained. For example, at 6:00 in the early morning, the external ambient light is only 100 lux, and the meeting room still needs to be compensated by 400 lux. While at 12:00 noon, the ambient light reaches 400 lux, and only 100 lux may need to be compensated, resulting in a morning compensation coefficient of 0.8 and a noon coefficient of 0.2.

[0050] Then, map and connect the lighting compensation coefficients for multiple regions in different time periods and the target lighting strategy intervals for multiple regions. The mapping process introduces the "time factor" into the "spatial compensation strategy" to establish a complete segmented ambient light compensation strategy for multiple regions, thereby guiding the target lighting device to make corresponding adjustments.

[0051] Furthermore, this application also includes: extracting indicators for the lighting application target to obtain a lighting effect evaluation indicator set; performing regression fitting on the lighting effect evaluation indicator set based on the lighting strategy parameter space to construct a lighting effect fitness function; using the lighting effect fitness function to perform global comparison and optimization within the lighting strategy parameter space until a preset termination condition is reached to determine the target lighting parameters.

[0052] Specifically, for a specific lighting application target, indicators are extracted. The lighting application target refers to the specific scenario or task served by the lighting system, such as office lighting, exhibition hall lighting, or operating room lighting, etc. And indicator extraction is to extract quantitative data that can be used to evaluate the lighting effect from this target, such as average illuminance, illuminance uniformity, glare level, energy consumption level, etc., which constitute the lighting effect evaluation indicator set. Table 1 shows partial records of the most recent lighting effect evaluation indicator set.

[0053] Table 1: Partial records of the most recent lighting effect evaluation indicator set Next, perform regression fitting analysis on the lighting effect evaluation indicator set using the lighting strategy parameter space. The lighting strategy parameter space refers to the set of all possible lighting strategy parameters, including combinations of multiple dimensions such as lamp brightness, current intensity, angular distribution, color temperature, etc. Regression fitting is the process of establishing a mathematical relationship between the lighting strategy parameter space and the lighting effect evaluation indicator set, and the output is a lighting effect fitness function, which is used to measure the matching degree or quality of the lighting strategy for the evaluation indicators under a specific parameter combination.

[0054] Subsequently, use the lighting effect fitness function to perform global comparison and optimization within the lighting strategy parameter space. Global comparison means traversing or searching all possible parameter combinations to find the best solution, and optimization means finding the parameter configuration that maximizes the fitness function. Continuously iterate and optimize until a preset termination condition is met, such as reaching a set accuracy or iteration count limit, and finally determine a set of optimal target lighting parameters.

[0055] Further, this application also includes: extracting behavioral characteristics from the user activity information to obtain user behavioral characteristics, where the user behavioral characteristics include movement trajectories and residence durations; determining a user behavior pattern based on the user behavioral characteristics; and adaptively adjusting and correcting the target lighting parameters based on the user behavior pattern and the user lighting requirements to obtain lighting correction parameters.

[0056] Specifically, when extracting behavioral characteristics from the user activity information, the extracted user behavioral characteristics include movement trajectories and residence durations. The movement trajectory represents the route of a person's movement in space, and the residence duration represents the length of time a person stays in a specific area.

[0057] Next, based on the user behavioral characteristics, a user behavior pattern is further analyzed, that is, an activity pattern with regularity is identified from historical data, such as activities in the kitchen area from 8 am to 9 am every day, frequent movement or long-term stay in the living room area in the evening, etc., which helps to predict the possible future positions and time periods of the user, thus providing a basis for adjusting the lighting strategy in advance.

[0058] Then, combining the identified user behavior pattern with the user lighting requirements, the target lighting parameters are dynamically adjusted. Adaptive adjustment means that the target lighting parameters will automatically adjust with the change of user behavior. For example, if it is detected that the user's residence time in the study has increased by 50% compared to usual, the lighting brightness in the study area may be automatically increased by 10%, or the color temperature may be adjusted from 4000K to 5000K more suitable for reading to improve visual comfort and lighting effect. The corrected output parameters are called lighting correction parameters.

[0059] Further, this application also includes: conducting lighting control analysis on the user behavior pattern and the user lighting requirements to determine behavior pattern control parameters and lighting requirement control parameters; setting behavior weights and requirement weights, and performing weighted adjustment and correction on the target lighting parameters based on the behavior weights and requirement weights, as well as the behavior pattern control parameters and lighting requirement control parameters to obtain the lighting correction parameters.

[0060] Specifically, when conducting lighting control analysis on the user behavior pattern and the user lighting requirements, by analyzing the activity rules (i.e., behavior pattern) of the user in a specific time and space, and combining the user's personalized lighting requirements, such as parameters like brightness, color temperature, or turn-on time, variables that will have a substantial impact on lighting control are identified. The behavior pattern control parameters are control variables generated based on behavior information such as user activity frequency, position residence time, and movement trajectory, and the lighting requirement control parameters are derived from the user's expectations for lighting effects.

[0061] Set the behavior weight and demand weight, which represent the relative importance of the behavior pattern and lighting demand in the final decision. The behavior weight reflects the influence degree of the user activity frequency and behavior consistency on the lighting setting, while the demand weight expresses the control priority of the user's subjective preference. Then, based on the behavior weight, demand weight, behavior pattern regulation parameter, and lighting demand regulation parameter, adaptively correct the target lighting parameter in a weighted manner.

[0062] Furthermore, this application also includes: adjusting and controlling the target lighting device based on the lighting correction parameter and monitoring the response, obtaining the lighting device response parameter; determining the lighting device delay coefficient according to the lighting device response parameter; compensating and adjusting the lighting correction parameter based on the lighting device delay coefficient, and performing closed-loop adjustment and control on the target lighting device through the compensated and adjusted lighting correction parameter.

[0063] Specifically, adjust and control the target lighting device based on the lighting correction parameter and monitor the response. After obtaining the lighting correction parameter (such as brightness, color temperature, turn-on time) generated through behavior and demand analysis, send an adjustment instruction to the specific target lighting device, and continuously monitor the actual feedback of the target lighting device after receiving the control instruction.

[0064] Immediately afterwards, determine the lighting device delay coefficient according to the lighting device response parameter. Calculate the delay characteristic of the target lighting device's response to the control signal by comparing the response difference between the adjustment instruction sent by the system and the actual completion of the adjustment by the device. The lighting device response parameter includes the response time, the degree of actually reaching the set value, and the possible error during the adjustment process, etc. The delay coefficient is an index reflecting the time or lag degree required for the target lighting device to reach the target state from receiving the control command.

[0065] Subsequently, compensate and adjust the lighting correction parameter based on the lighting device delay coefficient, that is, correct the lighting control parameter according to the delay situation, such as sending the adjustment instruction in advance or adjusting the control intensity, to overcome the influence of the delay on the lighting effect. Perform closed-loop adjustment and control on the target lighting device again through the compensated and adjusted lighting correction parameter, continuously monitor the feedback, and further optimize the control according to the feedback result to form an automatically corrected and continuously optimized closed-loop system.

[0066] Furthermore, this application also includes: when there are multiple lighting devices, adopting a multi-thread processing mechanism to perform parallel lighting adjustment on the multiple lighting devices.

[0067] Specifically, when deploying multiple lighting terminals in the same system, to improve the system response efficiency and adjustment speed, a multi-threaded approach is used to parallel process the control tasks of each lighting device. Multiple lighting devices refer to multiple independently controlled lamps operating simultaneously in the same lighting application scenario, such as multiple ceiling lights in an office or distributed lamp groups in different areas of a factory building. The multi-threaded processing mechanism refers to using the thread management capabilities of the operating system or programming language to allocate independent threads to the control tasks of each lighting device, thereby avoiding the waiting and bottlenecks caused by serial execution and improving the overall response speed and execution efficiency. Parallel lighting adjustment means that the adjustment instructions for all lighting devices can be executed simultaneously.

[0068] In summary, the lighting device adaptive adjustment method based on ambient light intensity provided by this application has the following technical effects: By achieving the technical goal of constructing a dynamic lighting strategy and adaptive control based on ambient light intensity and user behavior characteristics, the technical effects of improving the intelligent perception ability, fine control level, and multi-scenario adaptability of the lighting system are achieved.

[0069] Embodiment 2, based on the same inventive concept as the lighting device adaptive adjustment method based on ambient light intensity in the foregoing embodiment, this application also provides a lighting device adaptive adjustment system based on ambient light intensity. Please refer to the appendix Figure 2 , including: a lighting strategy parsing module 11, configured to obtain the application scenario information and application area range of the target lighting device, parse the lighting strategy based on the application scenario information and application area range, and establish an ambient light segmented lighting strategy; a matching analysis module 12, configured to deploy light intensity sensors and sense and obtain ambient light intensity data, perform matching analysis on the ambient light intensity data and the ambient light segmented lighting strategy to obtain a target lighting strategy; a global optimization module 13, configured to perform historical lighting data mining based on the target lighting strategy, construct a lighting strategy parameter space, and perform global optimization within the lighting strategy parameter space according to the lighting application target to determine target lighting parameters; a closed-loop adjustment control module 14, configured to monitor and obtain user activity information and user lighting requirements through an infrared sensor, adaptively adjust and correct the target lighting parameters based on the user activity information and user lighting requirements to obtain lighting correction parameters, and perform closed-loop adjustment control on the target lighting device based on the lighting correction parameters.

[0070] Furthermore, the adaptive adjustment system for lighting equipment based on ambient light intensity is also used to: divide the application area range into functional areas to obtain multiple application space areas; estimate the lighting conditions of the multiple application space areas based on the application scenario information to obtain multiple regional ambient light intensity ranges and multiple regional lighting intensity requirements; identify the application attribute information of the target lighting equipment to obtain the lighting equipment type, lighting equipment position and lighting coverage range; analyze the lighting strategy of the lighting equipment type, lighting equipment position and lighting coverage range based on the multiple regional ambient light intensity ranges and multiple regional lighting intensity requirements to obtain an ambient light segmented lighting strategy.

[0071] Furthermore, the adaptive adjustment system of lighting equipment based on ambient light intensity is also used to: perform segmented logic design on the ambient light intensity ranges of the multiple areas according to the light intensity requirements of the multiple areas to obtain multiple area segmented lighting logics; perform ambient light compensation analysis based on the multiple area segmented lighting logics to establish multiple area ambient light segmented compensation strategies; perform lighting twin simulation based on the lighting equipment type, lighting equipment location and lighting coverage range to construct a lighting equipment digital twin model; based on the lighting equipment digital twin model, simulate and generate multiple area lighting intensity attenuation curves, use the multiple area lighting intensity attenuation curves to supplement and correct the multiple area ambient light segmented compensation strategies to obtain the ambient light segmented lighting strategy.

[0072] Furthermore, the adaptive adjustment system for lighting equipment based on ambient light intensity is also used to: determine multiple regional target lighting strategy intervals according to the multiple regional segmented lighting logics, and the multiple regional target lighting strategy intervals are lighting compensation intervals in which the light intensity requirements are greater than the ambient light intensity; perform time period compensation analysis on the multiple application space areas according to the multiple regional light intensity requirements to obtain multiple regional time period lighting compensation coefficients; map and connect the multiple regional time period lighting compensation coefficients and the multiple regional target lighting strategy intervals to establish the multiple regional ambient light segmented compensation strategies.

[0073] Furthermore, the adaptive adjustment system for lighting equipment based on ambient light intensity is also used to: extract indicators for the lighting application target to obtain a lighting effect evaluation indicator set; perform regression fitting on the lighting effect evaluation indicator set based on the lighting strategy parameter space to construct a lighting effect fitness function; use the lighting effect fitness function to perform global comparison and optimization in the lighting strategy parameter space until a preset termination condition is reached to determine the target lighting parameters.

[0074] Furthermore, the adaptive adjustment system for lighting equipment based on ambient light intensity is also used to: extract behavioral features of the user activity information to obtain user behavior features, wherein the user behavior features include motion trajectory and stay duration; determine the user behavior pattern based on the user behavior features; and adaptively control and correct the target lighting parameters based on the user behavior pattern and user lighting needs to obtain lighting correction parameters.

[0075] Furthermore, the adaptive adjustment system for lighting equipment based on ambient light intensity is also used to: perform lighting control analysis on the user behavior pattern and user lighting demand, and determine the behavior pattern control parameters and lighting demand control parameters; set behavior weights and demand weights, and perform weighted control correction on the target lighting parameters based on the behavior weights and demand weights, as well as the behavior pattern control parameters and lighting demand control parameters, to obtain the lighting correction parameters.

[0076] Furthermore, the adaptive adjustment system for lighting equipment based on ambient light intensity is also used to: adjust and control the target lighting equipment and monitor its response based on the lighting correction parameters to obtain lighting equipment response parameters; determine the lighting equipment delay coefficient based on the lighting equipment response parameters; compensate and adjust the lighting correction parameters based on the lighting equipment delay coefficient, and perform closed-loop adjustment control on the target lighting equipment through the compensated and adjusted lighting correction parameters.

[0077] Furthermore, the ambient light intensity-based adaptive adjustment system for lighting devices is further configured to: when there are multiple lighting devices, perform parallel lighting adjustment on the multiple lighting devices using a multi-threaded processing mechanism.

[0078] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The adaptive adjustment method of lighting equipment based on ambient light intensity and the specific examples in the aforementioned embodiment one are also applicable to the adaptive adjustment system of lighting equipment based on ambient light intensity in this embodiment. Through the aforementioned detailed description of the adaptive adjustment method of lighting equipment based on ambient light intensity, those skilled in the art can clearly understand the adaptive adjustment system of lighting equipment based on ambient light intensity in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here.

[0079] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0080] Obviously, those skilled in the art can make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of this application and its equivalent technologies, this application is also intended to include these changes and modifications.

Claims

1. An adaptive adjustment method for a lighting device based on ambient light intensity, characterized in that, The method includes: Obtain the application scenario information and application area range of the target lighting device, analyze the lighting strategy based on the application scenario information and application area range, and establish an ambient light segmented lighting strategy; Deploy light intensity sensors and sense and obtain ambient light intensity data, perform matching analysis on the ambient light intensity data and the ambient light segmented lighting strategy to obtain a target lighting strategy; Mine historical lighting data based on the target lighting strategy, construct a lighting strategy parameter space, and perform global optimization within the lighting strategy parameter space according to the lighting application target to determine target lighting parameters; Monitor and obtain user activity information and user lighting requirements through an infrared sensor, adaptively adjust and correct the target lighting parameters based on the user activity information and user lighting requirements to obtain lighting correction parameters, and perform closed-loop adjustment control on the target lighting device based on the lighting correction parameters.

2. The adaptive adjustment method of the lighting device based on the ambient light intensity according to claim 1, characterized in that The establishment of the ambient light segmented lighting strategy includes: Divide the application area range into functional area divisions to obtain multiple application space areas; Estimate the lighting conditions of the multiple application space areas based on the application scenario information to obtain multiple regional ambient light intensity ranges and multiple regional lighting intensity requirements; [[ID=⑧]]Identify the application attribute information of the target lighting device to obtain the lighting device type, lighting device location, and lighting coverage range; Analyze the lighting strategy for the lighting device type, lighting device location, and lighting coverage range based on the multiple regional ambient light intensity ranges and multiple regional lighting intensity requirements to obtain an ambient light segmented lighting strategy.

3. The adaptive adjustment method of the lighting device based on the ambient light intensity according to claim 2, wherein The obtaining of the ambient light segmented lighting strategy includes: Perform segmented logic design on the multiple regional ambient light intensity ranges according to the multiple regional lighting intensity requirements to obtain multiple regional segmented lighting logics; Perform ambient light compensation analysis based on the multiple regional segmented lighting logics to establish multiple regional ambient light segmented compensation strategies; Perform lighting twin simulation based on the lighting device type, lighting device location, and lighting coverage range to construct a lighting device digital twin model; According to the lighting device digital twin model, simulate and generate multiple regional lighting intensity attenuation curves, and use the multiple regional lighting intensity attenuation curves to supplement and correct the multiple regional ambient light segmented compensation strategies to obtain the ambient light segmented lighting strategy.

4. The adaptive adjustment method of the lighting device based on the ambient light intensity according to claim 3, characterized in that, The establishment of the multiple regional ambient light segmented compensation strategies includes: Determine multiple regional target lighting strategy intervals according to the multiple regional segmented lighting logics, and the multiple regional target lighting strategy intervals are lighting compensation intervals where the lighting intensity requirement is greater than the ambient light intensity; Perform time period compensation analysis on the multiple application space areas according to the multiple regional lighting intensity requirements to obtain multiple regional time period lighting compensation coefficients; Map and connect the multiple regional time period lighting compensation coefficients and the multiple regional target lighting strategy intervals to establish the multiple regional ambient light segmented compensation strategies.

5. The adaptive adjustment method of the lighting device based on the ambient light intensity according to claim 1, characterized in that The determination of the target lighting parameters includes: Extract indicators for the lighting application target to obtain a lighting effect evaluation index set; Perform regression fitting on the lighting effect evaluation index set based on the lighting strategy parameter space to construct a lighting effect fitness function; Use the lighting effect fitness function to perform global comparison and optimization within the lighting strategy parameter space until a preset termination condition is reached to determine the target lighting parameters.

6. The adaptive adjustment method of the lighting device based on the ambient light intensity according to claim 1, wherein, The obtaining of the lighting correction parameters includes: Extract behavioral characteristics from the user activity information to obtain user behavioral characteristics, where the user behavioral characteristics include movement trajectories and residence durations; Determine the user behavior pattern according to the user behavioral characteristics; Based on the user behavior pattern and the user lighting requirements, adaptively adjust and correct the target lighting parameters to obtain lighting correction parameters.

7. The adaptive adjustment method of the lighting device based on the ambient light intensity according to claim 6, characterized in that The obtaining of the lighting correction parameters includes: Conduct lighting control analysis on the user behavior pattern and the user lighting requirements to determine the behavior pattern control parameters and the lighting requirement control parameters; Set the behavior weight and the requirement weight, and based on the behavior weight and the requirement weight, as well as the behavior pattern control parameters and the lighting requirement control parameters, perform weighted adjustment and correction on the target lighting parameters to obtain the lighting correction parameters.

8. The adaptive adjustment method of the lighting device based on the ambient light intensity according to claim 1, characterized in that The closed-loop adjustment control of the target lighting device based on the lighting correction parameters includes: Perform adjustment control and response monitoring on the target lighting device based on the lighting correction parameters to obtain lighting device response parameters; Determine the lighting device delay coefficient according to the lighting device response parameters; Perform compensation adjustment on the lighting correction parameters based on the lighting device delay coefficient, and perform closed-loop adjustment control on the target lighting device through the compensated lighting correction parameters.

9. The adaptive adjustment method of the lighting device based on the ambient light intensity according to claim 1, wherein The method further includes: When there are multiple lighting devices, adopt a multi-thread processing mechanism to perform parallel lighting adjustment on the multiple lighting devices.

10. An adaptive adjustment system for lighting equipment based on ambient light intensity, characterized in that, Steps for implementing the lighting device adaptive adjustment method based on ambient light intensity according to any one of claims 1 to 9 include: A lighting strategy analysis module, configured to obtain the application scenario information and the application area range of the target lighting device, perform lighting strategy analysis based on the application scenario information and the application area range, and establish an ambient light segmented lighting strategy; A matching analysis module, configured to deploy light intensity sensors and sense and obtain ambient light intensity data, perform matching analysis on the ambient light intensity data and the ambient light segmented lighting strategy to obtain a target lighting strategy; A global optimization module, configured to perform historical lighting data mining based on the target lighting strategy, construct a lighting strategy parameter space, perform global optimization within the lighting strategy parameter space according to the lighting application target, and determine the target lighting parameters; A closed-loop adjustment control module, configured to monitor and obtain user activity information and user lighting requirements through an infrared sensor, perform adaptive adjustment and correction on the target lighting parameters based on the user activity information and the user lighting requirements to obtain lighting correction parameters, and perform closed-loop adjustment control on the target lighting device based on the lighting correction parameters.

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