Method and system for adaptive adjustment of lighting equipment based on ambient light intensity

Abstract

This application provides a method and system for adaptively adjusting lighting equipment based on ambient light intensity, relating to the field of lighting equipment technology. The method includes: obtaining application scenario information and application area range of target lighting equipment and performing lighting strategy analysis; matching and analyzing ambient light intensity data with ambient light segmented lighting strategies; mining historical lighting data based on the target lighting strategy, and performing global optimization within the lighting strategy parameter space according to the lighting application goals; adaptively adjusting and correcting target lighting parameters based on user activity information and user lighting needs, and performing closed-loop adjustment and control of the target lighting equipment based on the lighting correction parameters. This application can solve the technical problem in the prior art that lighting strategies cannot accurately match the actual usage needs of various functional areas, achieve the technical goals of dynamic lighting strategy construction and adaptive adjustment, and achieve the technical effect of improving multi-scenario adaptability.

Description

Technical Field

[0001] The present application relates to the technical field of lighting equipment, and in particular to a method and system for adaptively adjusting lighting equipment based on ambient light intensity. Background Art

[0002] Lighting control technology has gradually evolved from traditional on-off control to intelligent and adaptive adjustment. Especially in multiple scenarios 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 smart lighting solutions fail to provide detailed functional divisions within application areas, and are unable to specifically identify the varying lighting requirements of different areas (such as corridors, reading areas, and rest areas). This leads to irrational allocation of lighting resources and the phenomenon of some areas being too bright or too dark. Furthermore, most decision-making processes rely on single ambient light parameters or static models, failing to effectively integrate real-time user behavior (such as movement trajectory and dwell time) with personalized lighting preferences (such as brighter light for reading and softer light for resting) for refined control. Furthermore, some lighting devices exhibit response delays during the control process, failing to fully assess their responsiveness. This can lead to delayed or over-adjusted compensation, impacting lighting quality and user experience.

[0004] In summary, the existing technology has technical problems such as the lack of refined functional division of application areas and identification of differentiated lighting needs, which leads to the inability of lighting strategies to 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 a method and system for adaptive adjustment of lighting equipment based on ambient light intensity, so as to solve the technical problem in the existing technology that due to the lack of refined functional division of application areas and identification of differentiated lighting needs, 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, the present application provides a method and system for adaptively adjusting lighting equipment based on ambient light intensity.

[0007] In the first aspect, the present application provides an adaptive adjustment method for lighting equipment based on ambient light intensity, which is implemented through an adaptive adjustment system for lighting equipment based on ambient light intensity, including: obtaining application scenario information and application area range of the target lighting equipment, performing lighting strategy analysis based on the application scenario information and application area range, and establishing an ambient light segmented lighting strategy; deploying light intensity sensors and sensing and obtaining ambient light intensity data, matching and analyzing 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, performing global optimization within the lighting strategy parameter space according to the lighting application target, and determining the target lighting parameters; obtaining user activity information and user lighting needs through infrared sensor monitoring, adaptively adjusting and correcting the target lighting parameters based on the user activity information and user lighting needs to obtain lighting correction parameters, and performing closed-loop adjustment control on the target lighting equipment based on the lighting correction parameters.

[0008] Preferably, the method for adaptively adjusting lighting equipment based on ambient light intensity 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 equipment to obtain the lighting equipment type, lighting equipment position and lighting coverage range; performing lighting strategy analysis on 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.

[0009] Preferably, the method for adaptive adjustment of lighting equipment based on ambient light intensity also includes: performing 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; performing ambient light compensation analysis based on the multiple area segmented lighting logics to establish multiple area ambient light segmented compensation strategies; performing 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, simulating and generating multiple area lighting intensity attenuation curves, using 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.

[0010] Preferably, the adaptive adjustment method of lighting equipment based on ambient light intensity also includes: determining multiple regional target lighting strategy intervals according to the multiple regional segmented lighting logics, the multiple regional target lighting strategy intervals being lighting compensation intervals in which the light intensity requirement is greater than the ambient light intensity; performing 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; mapping and connecting 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.

[0011] Preferably, the method for adaptively adjusting lighting equipment based on ambient light intensity also includes: extracting indicators from 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; and using 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.

[0012] Preferably, the method for adaptively adjusting lighting equipment based on ambient light intensity also includes: extracting behavioral features of the user activity information to obtain user behavior features, wherein the user behavior features include motion trajectory and stay duration; determining the user behavior pattern based on the user behavior features; and adaptively regulating and correcting the target lighting parameters based on the user behavior pattern and user lighting needs to obtain lighting correction parameters.

[0013] Preferably, the method for adaptively adjusting lighting equipment based on ambient light intensity also includes: performing lighting control analysis on the user behavior pattern and user lighting demand, determining the behavior pattern control parameters and lighting demand control parameters; setting behavior weights and demand weights, and performing 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.

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

[0015] Preferably, the method for adaptively adjusting lighting devices based on ambient light intensity further comprises: when there are multiple lighting devices, performing lighting adjustment on the multiple lighting devices in parallel using a multi-threaded processing mechanism.

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

[0017] The technical solution provided in this application has at least the following technical effects or advantages: by achieving the technical goal of constructing and adaptively controlling dynamic lighting strategies based on ambient light intensity and user behavior characteristics, the technical effect of improving the intelligent perception capability, fine control level and multi-scenario adaptability of the lighting system is achieved.

[0018] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, which can be implemented in accordance with the contents of the description, and to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically listed below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in this application or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely exemplary, and a person of ordinary skill in the art can obtain other drawings based on the provided drawings without creative work.

[0020] Figure 1 This is a flow chart of the method for adaptively adjusting lighting equipment based on ambient light intensity in this application.

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

[0022] Description of reference numerals: lighting strategy analysis module 11 , matching analysis module 12 , global optimization module 13 , closed-loop adjustment and control module 14 . DETAILED DESCRIPTION

[0023] This application provides a method and system for adaptively adjusting lighting equipment based on ambient light intensity. This addresses the existing technical issues of the lighting system's inability to accurately match the actual usage requirements of each functional area due to a lack of refined functional division of application areas and identification of differentiated lighting needs, further impacting the lighting system's overall performance in terms of energy efficiency, user visual comfort, and scenario adaptability. This application achieves the technical goal of constructing and adaptively adjusting dynamic lighting strategies based on ambient light intensity and user behavior characteristics, thereby enhancing the lighting system's intelligent perception capabilities, refined control levels, and multi-scenario adaptability.

[0024] Below, the technical solutions in this application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only 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 to the example embodiments described herein. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. It should also be noted that, for the convenience of description, only the parts related to this application, rather than all of them, are shown in the accompanying drawings.

[0025] For example, see the attached Figure 1 The present application provides a method for adaptively adjusting a lighting device based on ambient light intensity, which is applied to a system for adaptively adjusting a lighting device based on ambient light intensity, and specifically includes the following steps:

[0026] S1: Acquire 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 segmentation lighting strategy.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] Furthermore, the present 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 position and lighting coverage range; performing lighting strategy analysis on the lighting device type, lighting device 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.

[0039] Specifically, through the application scenario information of the target lighting device, the operating environment of the target lighting device can be clarified, 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.

[0040] Using the acquired application scenario information, we estimate lighting conditions for the application space. This involves evaluating the natural light intensity range for the application space at different times of the day based on factors such as the number of windows, orientation, and occlusion within the area. This provides the regional ambient light intensity range for each application space. Simultaneously, combined with scenario function analysis, we assess the need for lighting compensation and the degree of compensation, determining the required artificial lighting intensity for each application space, and ultimately determining the required lighting intensity for multiple areas.

[0041] Identify the application attributes of each target lighting device to determine its type, location, and coverage. The type of lighting device (e.g., LED ceiling lights, track lights, pendant lights, etc.) affects the target lighting device's light intensity, color temperature, and light distribution characteristics. The location of the lighting device refers to the specific coordinates of the target lighting device within the space where it is installed, affecting its lighting coverage and shadow casting. The lighting coverage represents the area where the target lighting device's light can effectively illuminate, typically determined by parameters such as mounting height, beam angle, and power.

[0042] Based on multiple regional ambient light intensity ranges and regional lighting intensity requirements, a comprehensive lighting strategy analysis is performed to ultimately develop a segmented ambient light lighting strategy. Lighting strategy analysis involves analyzing areas requiring additional lighting within different light intensity ranges and the lighting equipment required to achieve the target illumination. A segmented ambient light lighting strategy divides ambient light intensity into several intervals, each corresponding to a different regional ambient light compensation strategy.

[0043] Furthermore, the present application also includes: performing segmented logic design on the ambient light intensity ranges of the multiple areas according to the illumination intensity requirements of the multiple areas to obtain multiple area segmented lighting logics; performing ambient light compensation analysis based on the multiple area segmented lighting logics to establish multiple area 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; based on the lighting device digital twin model, simulating and generating multiple area lighting intensity attenuation curves, using 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.

[0044] Specifically, segmented logic design is performed based on the lighting intensity requirements of multiple areas, corresponding to the ambient light intensity range of the area. Segmented logic design involves dividing the ambient light intensity values ​​that may occur in an area under natural conditions (for example, from 0 lux to 600 lux) into several sub-ranges, such as 0 to 100 lux, 101 to 300 lux, 301 to 500 lux, and so on, and then developing lighting control logic for each interval. Light intensity requirements refer to the artificial light brightness required for each functional area to meet user comfort or regulatory requirements. By logically segmenting the ambient light range according to requirements, multiple regional segmented lighting logics are obtained, allowing targeted response strategies to be formulated.

[0045] Next, based on the multi-zone segmented lighting logic, ambient light compensation analysis is performed on each segmented area. When natural light is insufficient to meet lighting requirements, ambient light compensation is performed by calculating the required fill light intensity for each segment based on the difference between the actual illuminance in each segment and the target illuminance. This is then used to control the lighting response under different conditions.

[0046] After developing segmented compensation strategies for ambient light in multiple areas, the physical characteristics and installation conditions of the actual target lighting fixtures must be considered. Therefore, a lighting twin simulation is performed based on the lighting fixture type, location, and coverage. This involves building a digital model to simulate the actual operating state of the lighting fixture. The lighting fixture type involves its light output mode and dimming capabilities, such as whether it is a spotlight or diffuse light; the lighting location determines the light impact point and illuminance distribution; and the lighting coverage reflects the illumination radius and uniformity. By combining these factors to create a digital twin model, the lighting fixture's operating logic and lighting effects are realistically reproduced in a virtual space.

[0047] The digital twin model of lighting equipment can be used to further simulate and generate multiple regional lighting intensity attenuation curves. The lighting intensity attenuation curve represents the decreasing trend in illuminance as it diffuses from the center of the target lighting device toward the edges. By analyzing these multiple regional lighting intensity attenuation curves, it is possible to supplement and modify the segmented ambient light compensation strategies for these multiple regions, ensuring they better align with the lighting distribution of the actual device. For example, if a device's fill light capability in an edge area is insufficient, the target output power in that area can be increased or additional lighting fixtures can be enabled. Ultimately, a strategy that incorporates the device's true capabilities creates a precise and dynamically responsive segmented ambient light lighting strategy.

[0048] Furthermore, the present application also includes: determining multiple regional target lighting strategy intervals based on the multiple regional segmented lighting logics, the multiple regional target lighting strategy intervals being lighting compensation intervals in which the illumination intensity requirements are greater than the ambient light intensity; performing time period compensation analysis on the multiple application space areas according to the multiple regional illumination intensity requirements to obtain multiple regional time period lighting compensation coefficients; mapping and connecting 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.

[0049] Specifically, multiple target lighting strategy intervals are determined based on the segmented lighting logic for multiple zones. These target lighting strategy intervals represent the light intensity ranges that require artificial lighting to compensate when natural ambient light fails to meet the functional requirements of a space. Based on the difference between the required light intensity and the actual ambient light intensity in each zone, the range for lighting compensation is determined and serves as the target lighting strategy interval for each zone.

[0050] Next, a time-of-day compensation analysis is performed for multiple application space areas based on the lighting intensity requirements of multiple areas. Time-of-day compensation analysis involves dividing a day into multiple time periods, such as 6:00 to 9:00, 9:00 to 12:00, 12:00 to 18:00, and 18:00 to 22:00. The relationship between the changing trend of natural ambient light and the target lighting difference during each time period is evaluated, ultimately resulting in multiple time-of-day lighting compensation coefficients for multiple areas in multiple time periods. Using historical data and real-time sampling, the approximate proportion of supplemental lighting required for each area at different time points can be determined. For example, at 6:00 a.m., the ambient light is only 100 lux, and the conference room still needs to compensate for 400 lux. However, at noon, when the ambient light reaches 400 lux, only 100 lux may be required, resulting in a compensation coefficient of 0.8 in the morning and 0.2 at noon.

[0051] Then, the lighting compensation coefficients for multiple zones and time periods are mapped to the target lighting strategy intervals for multiple zones. The mapping process introduces the "time factor" into the "spatial compensation strategy" to establish a complete multi-zone segmented ambient light compensation strategy, thereby guiding the target lighting equipment to make corresponding adjustments.

[0052] Furthermore, the present 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 in the lighting strategy parameter space until a preset termination condition is reached to determine the target lighting parameters.

[0053] Specifically, indicators are extracted based on specific lighting application objectives. Lighting application objectives refer to the specific scenarios or tasks served by the lighting system, such as office lighting, exhibition hall lighting, or operating room lighting. Indicator extraction involves extracting quantitative data from these objectives that can be used to evaluate lighting performance, such as average illuminance, illuminance uniformity, glare levels, and energy consumption levels. These form the lighting performance evaluation indicator set. Table 1 shows a partial record of the most recent lighting performance evaluation indicator set.

[0054] Table 1: Partial records of the latest lighting effect evaluation index set

[0055]

[0056] Next, a regression fitting analysis is performed on the lighting effect evaluation index 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, and color temperature. Regression fitting is the process of establishing a mathematical relationship between the lighting strategy parameter space and the lighting effect evaluation index set. The output is a lighting effect fitness function, which is used to measure the degree of match or superiority of the lighting strategy to the evaluation index under a specific parameter combination.

[0057] Subsequently, the lighting effect fitness function is used to perform a global comparison and optimization within the lighting strategy parameter space. Global comparison involves traversing or searching all possible parameter combinations to find the optimal solution, while optimization involves finding the parameter configuration that maximizes the fitness function. Optimization continues iteratively until a pre-defined termination condition is met, such as reaching a set accuracy or iteration limit, ultimately determining a set of optimal target lighting parameters.

[0058] Furthermore, the present application also includes: extracting behavioral features of the user activity information to obtain user behavior features, wherein the user behavior features include motion trajectory and stay duration; determining user behavior patterns based on the user behavior features; and adaptively adjusting and correcting the target lighting parameters based on the user behavior patterns and user lighting needs to obtain lighting correction parameters.

[0059] Specifically, behavioral features are extracted from user activity information. The extracted user behavioral features include movement trajectory and residence time. The movement trajectory represents the route a person moves in space, and the residence time represents the length of time a person stays in a specific area.

[0060] Then, based on user behavior characteristics, we further analyze user behavior patterns. That is, we identify regular activity patterns from historical data, such as activities in the kitchen area from 8 to 9 am every day, frequent movements or long stays in the living room area at night, etc. This helps to predict the user's possible future locations and time periods, thus providing a basis for adjusting lighting strategies in advance.

[0061] Then, based on the identified user behavior patterns and their lighting needs, the target lighting parameters are dynamically adjusted. Adaptive control means that the target lighting parameters are automatically adjusted as user behavior changes. For example, if it detects that a user spends 50% more time in the study than usual, the lighting brightness in the study area may be automatically increased by 10%, or the color temperature may be adjusted from 4000 Kelvin to 5000 Kelvin, which is more suitable for reading, to improve visual comfort and lighting effects. The corrected output parameters are called lighting correction parameters.

[0062] Furthermore, the present application also includes: performing lighting control analysis on the user behavior pattern and user lighting demand, determining the behavior pattern control parameters and lighting demand control parameters; setting behavior weights and demand weights, and performing 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.

[0063] Specifically, lighting control analysis is conducted based on user behavior patterns and lighting needs. By analyzing user activity patterns (i.e., behavior patterns) within specific time and space, and combining them with individual lighting needs such as brightness, color temperature, and on-time parameters, we can identify variables that have a substantial impact on lighting control. Behavioral pattern control parameters are generated based on behavioral information such as user activity frequency, location dwell time, and movement trajectory. Lighting demand control parameters are derived from user expectations for lighting effects.

[0064] Behavior and demand weights are set to indicate the relative importance of behavior patterns and lighting needs in the final decision. Behavior weights reflect the influence of user activity frequency and behavioral consistency on lighting settings, while demand weights express the control priority of user preferences. Then, based on the behavior and demand weights, along with the behavior pattern control parameters and lighting demand control parameters, the target lighting parameters are adaptively modified using a weighted approach.

[0065] Furthermore, the present application also includes: adjusting and controlling the target lighting device and monitoring the response based on the lighting correction parameters to obtain lighting device response parameters; determining the lighting device delay coefficient based on 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 of the target lighting device through the compensated and adjusted lighting correction parameters.

[0066] Specifically, the target lighting equipment is adjusted and controlled and the response is monitored based on the lighting correction parameters. After obtaining the lighting correction parameters (such as brightness, color temperature, and turn-on time) generated after behavior and demand analysis, adjustment instructions are sent to the specific target lighting equipment, and the actual feedback of the target lighting equipment after receiving the control instructions is monitored in real time.

[0067] Next, the lighting device latency coefficient is determined based on the lighting device's response parameters. By comparing the difference between the system's response to an adjustment command and the device's actual completed adjustment, the target lighting device's latency characteristics in responding to the control signal are calculated. Lighting device response parameters include response time, actual achievement of the setpoint, and potential errors during the adjustment process. The latency coefficient reflects the time or lag required for the target lighting device to reach the target state after receiving a control command.

[0068] Subsequently, the lighting correction parameters are adjusted based on the lighting device's delay coefficient. This means that the lighting control parameters are modified based on the delay, such as sending adjustment commands in advance or adjusting the control intensity to overcome the delay's impact on the lighting effect. Using these compensated lighting correction parameters, the target lighting device is again subjected to closed-loop control. Feedback is continuously monitored and further optimized based on the feedback, forming a closed-loop system that automatically corrects and continuously optimizes.

[0069] Furthermore, the present application also includes: when there are multiple lighting devices, a multi-threaded processing mechanism is used to perform parallel lighting adjustments on the multiple lighting devices.

[0070] Specifically, when multiple lighting terminals are deployed in the same system, multithreading is used to parallelize the control tasks of each lighting device in order to improve system response efficiency and adjustment speed. Multiple lighting devices refer to multiple independently controlled lamps running simultaneously in the same lighting application scenario, such as multiple ceiling lights in an office or distributed lighting groups in different areas of a factory building. The multithreaded processing mechanism refers to the use of the thread management capabilities of the operating system or programming language to assign independent threads to the control tasks of each lighting device, thereby avoiding the waiting and bottlenecks caused by serial execution and improving overall response speed and execution efficiency. Parallel lighting adjustment means that the adjustment instructions of all lighting devices can be executed simultaneously.

[0071] To sum up, the adaptive adjustment method of lighting equipment based on ambient light intensity provided in this application has the following technical effects: by realizing the technical goal of dynamic lighting strategy construction and adaptive regulation based on ambient light intensity and user behavior characteristics, the technical effect of improving the intelligent perception ability, fine control level and multi-scene adaptability of the lighting system is achieved.

[0072] In the second embodiment, based on the same inventive concept as the method for adaptively adjusting the lighting device based on the ambient light intensity in the above embodiment, the present application also provides an adaptively adjusting system for the lighting device based on the ambient light intensity, as shown in the attached figure. Figure 2 , including: a lighting strategy parsing module 11, used to obtain application scenario information and application area range of the target lighting device, perform lighting strategy parsing based on the application scenario information and application area range, and establish an ambient light segmented lighting strategy; a matching analysis module 12, used to deploy light intensity sensors and sense and obtain ambient light intensity data, match and analyze the ambient light intensity data with the ambient light segmented lighting strategy, and obtain a target lighting strategy; a global optimization module 13, used to mine historical lighting data 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 and control module 14, used to monitor and obtain user activity information and user lighting needs through infrared sensors, adaptively adjust and correct the target lighting parameters based on the user activity information and user lighting needs, obtain lighting correction parameters, and perform closed-loop adjustment and control on the target lighting device based on the lighting correction parameters.

[0073] 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.

[0074] 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.

[0075] 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.

[0076] 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.

[0077] 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.

[0078] 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.

[0079] 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.

[0080] 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.

[0081] 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.

[0082] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one 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 is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

[0083] Obviously, those skilled in the art may make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.

Claims

1. A method for adaptively adjusting lighting equipment based on ambient light intensity, characterized in that: The method comprises: Obtain 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 segmentation lighting strategy; Deploy light intensity sensors and sense and obtain ambient light intensity data, match and analyze the ambient light intensity data with the ambient light segmented lighting strategy to obtain a target lighting strategy; 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 goal, and determine the target lighting parameters; Acquiring user activity information and user lighting needs through infrared sensor monitoring, adaptively adjusting and correcting the target lighting parameters based on the user activity information and user lighting needs to obtain lighting correction parameters, and performing closed-loop regulation and control on the target lighting device based on the lighting correction parameters; Obtaining the lighting correction parameter includes: Extracting behavioral features from the user activity information to obtain user behavioral features, wherein the user behavioral features include movement trajectory and stay duration; determining a user behavior pattern based on the user behavior characteristics; Adaptively regulating and correcting the target lighting parameters based on the user behavior pattern and the user lighting needs to obtain lighting correction parameters; The obtaining of the lighting correction parameters includes: Performing lighting control analysis on the user behavior pattern and the user lighting demand, and determining behavior pattern control parameters and lighting demand control parameters; Setting a behavior weight and a demand weight, and performing weighted control correction on the target lighting parameter based on the behavior weight and the demand weight, as well as the behavior mode control parameter and the lighting demand control parameter to obtain the lighting correction parameter; The step of establishing the ambient light segmentation lighting strategy includes: Dividing the application area into functional areas to obtain multiple application space areas; Based on the application scenario information, the lighting conditions of the multiple application space areas are estimated to obtain the ambient light intensity ranges of the multiple areas and the lighting intensity requirements of the multiple areas; Identify the application attribute information of the target lighting device to obtain the lighting device type, lighting device location, and lighting coverage; Performing a lighting strategy analysis on the lighting device type, lighting device position, and lighting coverage based on the multiple regional ambient light intensity ranges and the multiple regional illumination intensity requirements to obtain an ambient light segmented lighting strategy; The step of obtaining the ambient light segmentation lighting strategy includes: Performing segmented logic design on the ambient light intensity ranges of the multiple regions according to the illumination intensity requirements of the multiple regions to obtain segmented lighting logic for the multiple regions; Performing ambient light compensation analysis based on the multiple regional segmented lighting logics to establish multiple regional segmented ambient light compensation strategies; Perform lighting twin simulation based on the lighting device type, lighting device location, and lighting coverage to build a lighting device digital twin model; According to the digital twin model of the lighting device, multiple regional lighting intensity attenuation curves are simulated and generated, and the multiple regional lighting intensity attenuation curves are used to supplement and correct the multiple regional ambient light segmented compensation strategies to obtain the ambient light segmented lighting strategy.

2. The method for adaptively adjusting lighting equipment based on ambient light intensity according to claim 1, wherein: The establishment of multiple regional ambient light segmentation compensation strategies includes: Determining, according to the plurality of regional segmented lighting logics, a plurality of regional target lighting strategy intervals, wherein the plurality of regional target lighting strategy intervals are lighting compensation intervals in which the required illumination intensity is greater than the ambient light intensity; Performing time period compensation analysis on the multiple application space areas according to the illumination intensity requirements of the multiple areas to obtain time period lighting compensation coefficients for the multiple areas; The multiple regional time-division lighting compensation coefficients and the multiple regional target lighting strategy intervals are mapped and connected to establish the multiple regional ambient light segmentation compensation strategies.

3. The method for adaptively adjusting lighting equipment based on ambient light intensity according to claim 1, wherein: Determining the target lighting parameters includes: Extracting indicators from the lighting application target to obtain a lighting effect evaluation indicator set; Performing regression fitting on the lighting effect evaluation index set based on the lighting strategy parameter space to construct a lighting effect fitness function; The lighting effect fitness function is used 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.

4. The method for adaptively adjusting lighting equipment based on ambient light intensity according to claim 1, wherein: The performing closed-loop regulation and control on the target lighting device based on the lighting correction parameter includes: Performing adjustment control and response monitoring on the target lighting device based on the lighting correction parameter to obtain a lighting device response parameter; Determining a delay coefficient of the lighting device according to the lighting device response parameter; The lighting correction parameter is compensated and adjusted based on the lighting device delay coefficient, and the target lighting device is closed-loop adjusted and controlled using the compensated and adjusted lighting correction parameter.

5. The method for adaptively adjusting lighting equipment based on ambient light intensity according to claim 1, wherein: The method further comprises: When there are multiple lighting devices, a multi-threaded processing mechanism is used to perform lighting adjustments on the multiple lighting devices in parallel.

6. A lighting equipment adaptive adjustment system based on ambient light intensity, characterized in that: The steps for implementing the method for adaptively adjusting a lighting device based on ambient light intensity as recited in any one of claims 1 to 5 include: A lighting strategy analysis module is used to obtain 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 segmentation lighting strategy; A matching analysis module is used to deploy light intensity sensors and sense and obtain ambient light intensity data, and to match and analyze the ambient light intensity data with the ambient light segmented lighting strategy to obtain a target lighting strategy; A global optimization module is used to mine historical lighting data 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 goal, and determine the target lighting parameters; A closed-loop adjustment and control module is used to monitor and obtain user activity information and user lighting needs through infrared sensors, adaptively adjust and correct the target lighting parameters based on the user activity information and user lighting needs, obtain lighting correction parameters, and perform closed-loop adjustment and control of the target lighting equipment based on the lighting correction parameters.

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