Scene-based LED lamp strip adaptive control method, device and equipment

Abstract

The invention relates to the technical field of illumination control, solves the problem that in the prior art, illumination control lacks self-learning ability, and consequently comfort and individual requirements are difficult to consider, and provides a scene-based LED lamp strip self-adaptive control method, device and equipment. The method comprises the steps of obtaining scene information of a physical space where an LED lamp strip is located, and obtaining illumination control strategies of the LED lamp strip in different time periods in a first preset period according to the scene information; in a first preset period, in response to a user switch instruction, illumination is performed according to the illumination control strategy and the environmental parameters of the current time period; updating the illumination control strategy according to historical illumination data in a first preset period; and after a first preset period, in response to a user switch instruction, controlling the LED lamp strip to illuminate according to the adjusted illumination control strategy and environmental parameters in the current time period. The intelligent level and the user satisfaction degree of the lighting system can be effectively improved.

Description

Technical Field

[0001] This invention relates to the field of lighting control technology, and in particular to a scene-based adaptive control method, device, and equipment for LED light strips. Background Technology

[0002] With the increasing popularity of smart homes and commercial smart lighting, LED light strips are widely used in various scenarios such as residences, offices, retail displays, and entertainment venues due to their flexible arrangement, colorful display, and low power consumption. Existing technologies typically employ the following two control methods: Several static or dynamic lighting scenes, such as "reading, leisure, and cinema," can be preset via a light strip controller or mobile app, and then manually switched by the user as needed. This method can meet the brightness, color temperature, and color requirements of different usage scenarios to a certain extent, but once the scene parameters are set, they remain fixed for a long time, making it difficult to take into account changes in natural light and individual preferences.

[0003] Some improvement solutions incorporate ambient light sensors into the LED strip system, enabling the controller to automatically compensate for the light based on real-time illuminance or color temperature. However, most of these solutions only execute simple logic (such as threshold switching or linear compensation) at the "current moment," without forming a periodic strategy update mechanism; moreover, the compensation logic is usually based on a single environmental quantity and cannot simultaneously coordinate the three-dimensional parameters of brightness, color temperature, and color, which can easily lead to inconsistent light effects or color imbalance.

[0004] Existing scene lighting systems based on LED light strips generally lack the self-learning capability driven by historical data: they cannot dynamically optimize the lighting control strategy for subsequent cycles based on information such as the actual usage time, ambient light changes, and user switching commands within a complete cycle. This results in the initial scene parameters still being used after long-term operation, making it difficult to balance comfort, energy efficiency, and personalized needs. Summary of the Invention

[0005] In view of this, embodiments of the present invention provide a scene-based adaptive control method, device, equipment and storage medium for LED light strips, in order to solve the problem that the lighting control in the prior art lacks self-learning ability, making it difficult to balance comfort, energy saving and personalized needs.

[0006] In a first aspect, embodiments of the present invention provide a scene-based adaptive control method for LED light strips, the method comprising: Obtain scene information of the physical space where the LED light strip is located, wherein the scene information includes scene type, space area and number of light strips in the physical space; Based on the scene information, the lighting control strategy of the LED light strip in different time periods within the first preset period is obtained, wherein the lighting control strategy includes brightness parameters, color temperature parameters and color parameters; Within the first preset period, in response to the user's on / off command, the LED light strip is controlled to provide illumination based on the lighting control strategy and environmental parameters for the current time period; The lighting control strategy is updated based on the historical lighting data of the LED light strip within the first preset period. After the first preset cycle, in response to the user's on / off command, the LED light strip is controlled to provide illumination based on the lighting control strategy and environmental parameters adjusted according to the current time period.

[0007] Preferably, obtaining the lighting control strategy of the LED light strip at different time periods within a first preset period based on the scene information includes: Based on the scene type, the target lighting parameters of the physical space are obtained, wherein the target lighting parameters include the illuminance target range, color temperature target range, and color target range of the scene type within a preset time period; Based on the space area and the target illuminance range, the total target illuminance of the physical space in different time periods is obtained; The lighting contribution ratio of the light strips is obtained based on the space area, the number of light strips, and the scene type. The lighting contribution ratio of the light strips is positively correlated with the number of light strips and negatively correlated with the space area. Based on the total target illuminance, the lighting contribution ratio of the LED strips, and the number of LED strips, obtain the brightness control curve for each LED strip; Based on the curve variation characteristics of the brightness control curve, the color temperature target range, and the color target range, obtain the color temperature control curve and color control curve for each LED light strip; The brightness control curve, color temperature control curve, and color control curve are smoothed to obtain the lighting control strategy of the LED light strip at different time periods.

[0008] Preferably, the step of controlling the LED light strip to illuminate within a first preset period in response to a user's on / off command, based on the lighting control strategy and environmental parameters for the current time period, includes: In response to user on / off commands, obtain the command issuance time and environmental parameters; According to the lighting control strategy corresponding to the time the instruction is issued, the target lighting parameters are obtained, including the target brightness parameters, the target color temperature parameters, and the target color parameters; Set the target brightness parameter and target color temperature parameter as endpoints to establish a multi-channel target endpoint set; Based on the multi-channel target endpoint set and the preset slope value, the initial control curves for brightness and color temperature are obtained respectively through a smooth interpolation algorithm; Based on the initial lighting control curve and the target color parameters, the LED light strip is controlled to gradually light up; During the gradual lighting process, the endpoint of the lighting control curve that adjusts brightness and color temperature according to the environmental parameters; The LED light strip is controlled to provide illumination according to the adjusted lighting control curve.

[0009] Preferably, the endpoint of the lighting control curve for adjusting brightness and color temperature according to the environmental parameters during the gradual lighting process includes: Environmental parameters are collected according to a preset sampling period, wherein the environmental parameters include an ambient light illuminance sequence and an ambient light color temperature sequence; The environmental parameters are smoothed to obtain smoothed illuminance and smoothed color temperature; Based on the changing trends of the smoothed illuminance and smoothed color temperature, the predicted illuminance and predicted color temperature are obtained; Based on the smoothed illuminance and smoothed color temperature, as well as the target brightness parameters and target color temperature parameters, the actual brightness deviation and actual color temperature deviation are obtained. Based on the predicted illuminance and predicted color temperature, as well as the target luminance parameters and target color temperature parameters, obtain the trend luminance deviation and trend color temperature deviation; The overall brightness deviation is obtained by weighting the actual brightness deviation and the trend brightness deviation. The overall color temperature deviation is obtained by weighting the actual color temperature deviation and the trend color temperature deviation. Based on the overall brightness deviation and the overall color temperature deviation, the brightness endpoint value and the color temperature endpoint value are determined respectively. The lighting control curves for brightness and color temperature are adjusted using the smooth interpolation algorithm based on the brightness endpoint value, the color temperature endpoint value, and the preset slope value.

[0010] Preferably, updating the lighting control strategy based on the weighted intensity index includes: Based on the weighted intensity index and the brightness parameters of each time cluster, the brightness correction index of each time cluster is obtained, wherein the brightness correction index and the weighted intensity index are positively correlated. Based on the brightness correction index and the color temperature and color parameters of each time cluster, obtain the color temperature correction index and color correction index of each time cluster. The lighting control strategy is updated based on the brightness correction index, color temperature correction index, and color correction index.

[0011] Preferably, controlling the LED light strip for illumination according to the adjusted lighting control curve includes: Based on the current time and the adjusted lighting control curve, obtain the lighting parameters for the current time period and the next time period, and record them as the current lighting parameters and the lighting parameters to be switched, respectively. The lighting parameters include brightness parameters and color temperature parameters. Based on the current lighting parameters, control the LED light strip to provide illumination; Based on the current lighting parameters and the lighting parameters to be switched, obtain the parameter difference, wherein the parameter difference includes the color temperature difference and the brightness difference; Based on the current time and the next time period, determine the remaining duration of the current time period; Based on the parameter difference, the preset brightness adjustment rate range and color temperature adjustment rate range, the brightness adjustment time interval and color temperature adjustment time interval are obtained. The longer of the brightness adjustment time interval and the color temperature adjustment time interval shall be taken as the target adjustment time interval; The target adjustment time interval and the remaining duration are compared to obtain the adjustment strategy and adjustment start time. When the remaining duration is greater than or equal to the target adjustment time interval, the adjustment strategy is a phased adjustment strategy; otherwise, the adjustment strategy is a linear adjustment strategy. If the adjustment strategy is a phased adjustment strategy, the phase adjustment duration of each adjustment phase is obtained according to the target adjustment time interval and the preset segmentation ratio. Based on the adjustment duration and the parameter difference, obtain the color temperature adjustment rate and brightness adjustment rate for each adjustment stage; If the adjustment strategy is a linear adjustment strategy, the color temperature adjustment rate and the brightness adjustment rate are obtained based on the remaining duration and the upper limit of the brightness adjustment rate range and the color temperature adjustment rate range. At the start time of the adjustment, the LED light strip is controlled to switch from the current lighting parameters to the lighting parameters to be switched, based on the color temperature adjustment rate and the brightness adjustment rate.

[0012] Preferably, when the physical space includes multiple LED light strips, the step of controlling the LED light strips to switch from the current lighting parameters to the lighting parameters to be switched, based on the color temperature adjustment rate and brightness adjustment rate, at the adjustment start time, includes: Obtain the physical parameters of each LED strip within the physical space, wherein the physical parameters include the number of LED beads, the spacing between LED beads, and the length of the strip; The density of LEDs per unit length is obtained based on the number of LEDs and the spacing between them. Based on the LED chip density and LED strip length, the luminous coverage value of each LED strip is obtained, wherein the luminous coverage value is positively correlated with the LED chip density and LED strip length; The LED strip corresponding to the largest luminous coverage value is designated as the main LED strip, and the remaining LED strips are designated as secondary LED strips. Obtain the physical parameter difference between each desired light strip and the main light strip, wherein the physical parameter difference includes density difference and light strip length difference; Based on the difference in physical parameters, the color temperature adjustment rate and brightness adjustment rate of the light strip are adjusted for each time. The color temperature adjustment rate is negatively correlated with the density difference and positively correlated with the difference in light strip length. The brightness adjustment rate is positively correlated with the density difference and negatively correlated with the difference in light strip length. At the start time of the adjustment, the main light strip is controlled to switch from the current lighting parameters to the lighting parameters to be switched according to the color temperature adjustment rate and the brightness adjustment rate. At the same time, the secondary light strip is controlled to switch from the current lighting parameters to the lighting parameters to be switched according to the adjusted color temperature adjustment rate and brightness adjustment rate.

[0013] Secondly, embodiments of the present invention provide a scene-based adaptive control device for LED light strips, the device comprising: The scene information acquisition module is used to acquire scene information of the physical space where the LED light strip is located, wherein the scene information includes scene type, space area and number of light strips in the physical space; The initial lighting strategy acquisition module is used to acquire the lighting control strategy of the LED light strip in different time periods within a first preset period based on the scene information, wherein the lighting control strategy includes brightness parameters, color temperature parameters and color parameters; The first lighting control module is used to control the LED light strip to provide illumination in response to a user's on / off command within a first preset period, based on the lighting control strategy and environmental parameters of the current time period. The lighting strategy update module is used to update the lighting control strategy based on the historical lighting data of the LED light strip within a first preset period. The second lighting control module is used to control the LED light strip to provide illumination in response to a user's on / off command after a first preset period, based on the lighting control strategy and environmental parameters adjusted for the current time period.

[0014] Thirdly, embodiments of the present invention provide a light-emitting device, including: an LED light strip, at least one processor, at least one memory, and computer program instructions stored in the memory, wherein when the computer program instructions are executed by the processor, the method of the first aspect of the above embodiments is implemented to control the LED light strip to emit light.

[0015] In summary, the beneficial effects of the present invention are as follows: The scene-based adaptive control method, device, equipment, and storage medium provided in this invention acquire scene information of the physical space where the LED light strip is located, including scene type, space area, and number of light strips, and generate a more targeted initial lighting strategy based on the spatial attributes and structural constraints of the lighting task. By acquiring scene information of the physical space where the LED light strip is located, including scene type, space area, and number of light strips, a more targeted initial lighting strategy can be generated. Within a first preset period, by combining the time-period lighting control strategy with environmental parameters to respond to user switching commands in real time, the system possesses environmental perception and instant compensation capabilities. The lighting process of the LED light strip not only follows the strategy value but also dynamically adjusts the output effect based on changes in ambient light, achieving refined collaborative control under natural light intervention, thereby improving the visual comfort and energy efficiency of the lighting. Continuously recording user activation behavior and environmental parameters within the first preset period, and updating the strategy based on historical data after the period ends, achieves data-driven self-learning optimization of the lighting system. This enables the system to identify high-frequency usage periods, dynamic lighting needs, and strategy deviations, thereby generating dimming parameters that better match actual user preferences in subsequent periods. Finally, based on the strategy update results, response control continues to be executed in the new cycle, thereby possessing continuous adaptive capabilities. It can automatically adjust the strategy as the spatial environment, user preferences, and behavioral habits evolve, avoiding problems such as light effect mismatch and frequent manual intervention by users in long-term use, thus enhancing the long-term operational stability, low maintenance, and personalized experience of the LED light strip system. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments of the present invention will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort, and these are all within the protection scope of the present invention.

[0017] Figure 1 This is a schematic flowchart of a scene-based adaptive control method for LED light strips according to an embodiment of the present invention.

[0018] Figure 2 This is another schematic diagram of the scene-based adaptive control method for LED light strips in this embodiment of the invention.

[0019] Figure 3 This is a schematic diagram of the scene-based adaptive control device for LED light strips according to an embodiment of the present invention.

[0020] Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0021] The features and exemplary embodiments of various aspects of the present invention will now be described in detail. To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only configured to explain the present invention and are not configured to limit the present invention. For those skilled in the art, the present invention can be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present invention by illustrating examples of the invention.

[0022] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0023] It should be noted that all actions involving the acquisition of signals, information, or data in this invention are carried out in compliance with the relevant data protection laws and regulations of the locality and with authorization from the owner of the relevant device.

[0024] Example 1 Please see Figures 1-2 This invention provides a scene-based adaptive control method for LED light strips, the method comprising: S1. Obtain scene information of the physical space where the LED light strip is located, wherein the scene information includes scene type, space area and number of light strips in the physical space; Specifically, scene information refers to a set of data that describes the physical and functional attributes of the current lighting space. This typically includes: scene type (the main function of the space, such as a living room, office, corridor, or exhibition area); space area (the actual area of ​​the physical space, usually measured in square meters); and the number of LED strips (the total number of identifiable LED strips installed in the space). The purpose of this step is to provide necessary spatial context information for subsequent strategy development. Because the target output intensity, color temperature style, and color usage habits of lighting vary depending on the scene, and the space area affects the luminous flux budget, while the number of LED strips affects control granularity and light distribution uniformity, identifying this basic information provides structured input for generating a suitable initial lighting strategy. Scene information can be actively entered through the user configuration interface, or it can be automatically scanned by the device during the system deployment phase (e.g., automatically identifying the number of LED strips) or imported in conjunction with spatial planning drawings.

[0025] S2. Based on the scene information, obtain the lighting control strategy of the LED light strip in different time periods within the first preset period, wherein the lighting control strategy includes brightness parameters, color temperature parameters and color parameters; Based on the scene information obtained in step S1, the lighting control strategy for LED light strips at different time periods within the first preset period is obtained. This strategy includes three core parameters: brightness parameters (such as percentage or luminous flux level), color temperature parameters, and color parameters (such as RGB ratio or hue / saturation values ​​under the HSL model) to provide a periodic basic lighting scheme, enabling the generation of usable and targeted light effect output even in the absence of user historical preferences. The process of formulating the lighting strategy is based on matching the scene type with the corresponding lighting template library. For example, office scenes use high brightness and cool white tones, while residential scenes tend to use soft and warm colors. The brightness parameters are scaled and calculated in combination with the space area and the number of light strips. The preset period (such as 24 hours) is divided into multiple time periods, such as "morning", "noon", "evening", and "night", and a set of three-parameter lighting values ​​is assigned to each time period to form a complete lighting control table.

[0026] S3. Within the first preset period, in response to the user's switch command, control the LED light strip to provide illumination according to the lighting control strategy and environmental parameters of the current time period; Specifically, within the first preset cycle, the system responds in real-time to user on / off commands, controlling the LED strip for illumination based on the lighting control strategy and environmental parameters for the current time period. On / off commands can be issued via wall panels, an app interface, or a voice assistant. Upon receiving a command, the system retrieves the time period to which the current point in time belongs and extracts the corresponding brightness, color temperature, and color parameters from the lighting control strategy. Simultaneously, it acquires real-time environmental parameters, including current ambient illuminance and color temperature information, to appropriately adjust the extracted control parameters. For example, if the ambient illuminance is already high, the target brightness can be relatively lowered to avoid illuminance redundancy; if the ambient color temperature is cool while the target color temperature is warm white, the output color temperature can be fine-tuned for a more natural blend. The processed control parameters are converted into PWM duty cycle, current setpoint, or address control commands and sent to the LED driver circuit, enabling the LED strip to illuminate smoothly and gradually. By combining static strategies with real-time status, a natural, energy-saving, and intelligent lighting environment response is achieved.

[0027] S4. Update the lighting control strategy based on the historical lighting data of the LED light strip within the first preset period; Specifically, all lighting behaviors are recorded within the first preset period, and the lighting control strategy is updated based on the accumulated historical lighting data at the end of the period. Historical lighting data includes, but is not limited to, the lighting duration corresponding to each user activation behavior, the ambient illuminance and color temperature collected during the lighting process, and the output values ​​of the three parameters executed. In the absence of proactive adjustment behavior, the effectiveness of the strategy for each time period can be evaluated by statistically analyzing usage frequency and duration. For example, if the usage frequency is significantly high and the ambient illuminance is low during a certain time period, it indicates that the current strategy's brightness is slightly low and should be appropriately increased; conversely, if the lighting activation rate is low during a certain time period and the illuminance environment is good, it can be determined that the current brightness parameter is over-output, and an downward adjustment operation can be performed. Based on the above processing, the brightness, color temperature, and color parameters for each time period are slightly adjusted to generate a lighting control strategy for the next period that better reflects actual usage behavior.

[0028] S5. After the first preset period, in response to the user's switch command, control the LED light strip to provide illumination based on the lighting control strategy and environmental parameters adjusted according to the current time period.

[0029] In step S5, after entering a new lighting cycle, when the user issues a switch command again, the original strategy table will no longer be invoked. Instead, the updated lighting control strategy will be used, combined with the current time period and environmental parameters, to control the LED strip to achieve intelligent lighting. Consistent with step S3, the control process still includes time period identification, strategy reading, environmental perception, and drive output, but the three-parameter control values ​​used are now dynamically updated versions. Through this closed-loop update mechanism, the lighting strategy can be continuously optimized in consecutive cycles, achieving personalized dimming effects without relying on user-initiated configuration. Simultaneously, it effectively improves the matching degree between lighting behavior and natural light rhythms and user preferences, demonstrating high adaptability and energy efficiency.

[0030] Preferably, see Figure 2 The step of obtaining the lighting control strategy for the LED light strip at different time periods within a first preset period based on the scene information includes: S21. According to the scene type, obtain the target lighting parameters of the physical space, wherein the target lighting parameters include the illuminance target range, color temperature target range and color target range of the scene type within a preset time period; Specifically, the target lighting parameters for the physical space are obtained based on the scene type. These target lighting parameters refer to the set of target optical parameters retrieved from a preset strategy library based on the lighting requirements of different functional scenes. These typically include the target illuminance range (e.g., 300–500 lx), the target color temperature range (e.g., 2700–4000K), and the target color range (e.g., low-saturation warm colors or neutral RGB ratios). By clearly defining the function of the space, such as a family bedroom, meeting room, or display shelf, the scene-lighting effect mapping table can be invoked to quickly determine the required light intensity, hue bias, and color activity range for each time period within a preset time frame.

[0031] S22. Based on the space area and the illuminance target range, obtain the total target illuminance of the physical space in different time periods; Based on the space area and the target illuminance range, the total target illuminance of the physical space is obtained over different time periods. Since illuminance is the luminous flux received per unit area, the total luminous flux requirement is directly related to the space area. The purpose of this step is to expand the unit illuminance requirement to the overall lighting intensity required for the space, serving as a reference baseline for subsequent allocation to each light strip. For example, if the target illuminance for a certain time period is 400 lx and the space area is 30 square meters, the total target illuminance can be understood as a corresponding luminous flux output requirement of 12000 lm (not representing an actual value, but only used for logical explanation). This total target will serve as the upper limit constraint basis for the subsequent "light strip brightness control curve".

[0032] S23. Based on the space area, the number of light strips, and the scene type, obtain the light strip lighting contribution ratio, wherein the light strip lighting contribution ratio is positively correlated with the number of light strips and negatively correlated with the space area; Specifically, the lighting contribution ratio of the LED strips is obtained based on the space area, the number of LED strips, and the scene type. The lighting contribution ratio measures the proportion of illuminance output that each LED strip should bear in the overall lighting. Its value is affected by the space size (the larger the space, the lower the contribution ratio of a single LED strip) and the number of LED strips (the more strips, the smaller the contribution ratio of a single strip). Furthermore, the role of the LED strips varies in different scene types. For example, in display case or decorative outline lighting, LED strips may bear a higher lighting weight, while in bright office spaces, they are mostly used for supplementary lighting. Considering all these factors, a set of ratios will be used to calculate the light output ratio that each LED strip needs to bear, providing a quantitative basis for the subsequent generation of the brightness curve.

[0033] S24. Based on the total target illuminance, the lighting contribution ratio of the LED strips, and the number of LED strips, obtain the brightness control curve for each LED strip. Specifically, based on the total target illuminance, the contribution ratio of the LED strips to the lighting, and the number of LED strips, a brightness control curve is obtained for each LED strip. Specifically, the total target illuminance for each time period is broken down into individual LED strips according to their contribution ratio. Then, based on the time period sequence and the selected curve interpolation method (such as linear, cubic spline, or exponentially increasing curve), a continuous and smooth brightness control curve is generated. This curve not only includes the target brightness point but should also ensure that the transition slope during the control process is within the user-perceptible threshold to avoid discomfort caused by sudden brightness changes.

[0034] S25. Based on the curve change characteristics of the brightness control curve, the color temperature target range, and the color target range, obtain the color temperature control curve and color control curve for each LED light strip. Based on the curve variation characteristics of the brightness control curve, the target color temperature range, and the target color range, the color temperature control curve and color control curve for each LED light strip are obtained. Considering the physiological perception coupling relationship between brightness, color temperature, and color parameters (e.g., high brightness should be matched with high color temperature, and warm colors are more suitable for low brightness scenes), a linkage interpolation method is used to derive the synchronous control trajectory of color temperature and color from the brightness change trend. For example, in the brightness increase segment, the color temperature can be appropriately cooler, and the saturation slightly reduced; in the brightness decrease segment, the color temperature gradually warms up, and the color saturation rebounds, thus presenting a harmonious and consistent visual experience overall.

[0035] S26. Smooth the brightness control curve, color temperature control curve and color control curve to obtain the lighting control strategy of the LED light strip at different time periods.

[0036] Finally, the brightness control curve, color temperature control curve, and color control curve are smoothed to obtain the lighting control strategy for the LED light strip at different time periods. The smoothing process mainly employs low-pass filtering or weighted interpolation to ensure continuous and natural changes in light output across time periods or scene transitions, without abrupt jumps or sudden brightening / dimening. The final generated lighting control strategy will serve as the base output benchmark for each time period within the first preset cycle and will support subsequent real-time adjustments and strategy iterations.

[0037] Preferably, the step of controlling the LED light strip to illuminate within a first preset period in response to a user's on / off command, based on the lighting control strategy and environmental parameters for the current time period, includes: S31. In response to the user's switch command, obtain the command issuance time and environmental parameters; Specifically, in response to user on / off commands, the system acquires the time of the command issuance and environmental parameters. The on / off command can originate from a wall controller, mobile terminal, voice control, etc.; the environmental parameters include at least the current ambient illuminance and ambient color temperature, reflecting the existing lighting environment in the physical space at the time the user issues the command. The purpose of acquiring this information is to establish a real-time mapping between time points and environmental states, in order to match appropriate strategies and execute light-sensing compensation.

[0038] S32. According to the lighting control strategy corresponding to the time the instruction is issued, obtain the target lighting parameters, which include target brightness parameters, target color temperature parameters, and target color parameters; Specifically, the system matches the current time period based on the time the instruction is issued, and extracts the target lighting parameters, including target brightness, target color temperature, and target color, from the lighting control strategy corresponding to that time period within the first preset cycle. These target parameters are the expected output values ​​set for that time period in the initial strategy phase, and are usually determined by the scene, representing the ideal output baseline without considering user preferences and real-time light environment interference.

[0039] S33. Set the target brightness parameter and target color temperature parameter as the endpoint and establish a multi-channel target endpoint set; Specifically, the target brightness parameter and target color temperature parameter are used as endpoint values, and combined with the target color parameter to establish a multi-channel control target endpoint set. This endpoint set is used in the LED driver system to define the target output state that each control channel (such as the brightness channel, color temperature adjustment channel, and RGB channel) ultimately wants to reach. The purpose of constructing this endpoint set is to provide a convergence target for the subsequent gradation process, ensuring that the lighting process is targeted.

[0040] S34. Based on the multi-channel target endpoint set and the preset slope value, the initial control curves of brightness and color temperature are obtained respectively through a smooth interpolation algorithm; Specifically, based on the target endpoint set and a preset slope threshold, a smooth interpolation algorithm is used to generate brightness control curves and color temperature control curves, respectively. The interpolation method used here can be cubic spline, exponential curve, or cosine interpolation, etc. The key is that the derivative of the output curve is continuous and the growth rate is controlled, thus ensuring a smooth visual change without abrupt changes during the illumination process. Slope limiting is used to prevent visual discomfort or glare caused by sudden brightening in scenes with low initial illuminance and high target brightness.

[0041] S35. Based on the initial lighting control curve and the target color parameters, control the LED light strip to gradually light up; Using the aforementioned brightness and color temperature control curves as the basic control path, and combining them with the target color parameters, the PWM duty cycle or channel ratio for each time slot is calculated uniformly, thereby controlling the LED strip to light up smoothly in a gradual manner. At this time, the color parameters can remain constant or scale proportionally with the brightness curve, ensuring that no color shift or saturation drift occurs at low brightness, thus presenting a consistent and natural color experience throughout the lighting process.

[0042] S36. During the gradual lighting process, the endpoint of the lighting control curve that adjusts the brightness and color temperature according to the environmental parameters; Before the lighting process is complete, the system continuously collects ambient illuminance and color temperature, and dynamically adjusts the endpoints of the current brightness and color temperature control curves based on their real-time trends. For example, if the initial setting is high brightness output and a rapid increase in ambient illuminance is detected (such as sunlight entering the room), the system can appropriately lower the target brightness endpoint; conversely, if natural light decreases, the target brightness point can be smoothly moved upwards along the current lighting path. Color temperature adjustment can also be linked to brightness correction, ensuring that the output state always blends naturally with the actual light field.

[0043] S37. Control the LED light strip to provide illumination according to the adjusted lighting control curve.

[0044] Based on the adjusted control curve, the LED light strip continues to be driven to complete the lighting process. At this time, the control command already includes dynamically corrected brightness and color temperature information, ensuring that the output results not only follow the original strategy structure but also integrate real-time environmental perception results. The LED light strip can complete environmental perception, target calculation, and smooth transition in a continuous natural gradual brightening process, achieving true "the best lighting environment is reached as soon as the lights are turned on," and the user is completely unaware of the process.

[0045] Preferably, the endpoint of the lighting control curve for adjusting brightness and color temperature according to the environmental parameters during the gradual lighting process includes: S361. Collect environmental parameters according to a preset sampling period, wherein the environmental parameters include an ambient light illuminance sequence and an ambient light color temperature sequence; Specifically, environmental parameters are collected according to a preset sampling period, including an ambient light illuminance sequence and an ambient light color temperature sequence. Here, the sampling period refers to the time interval during the lighting process (such as every 50 milliseconds or every frame). Continuous sampling can form a time series of illuminance and color temperature values, reflecting the dynamic trend of current spatial ambient light changes.

[0046] S362. Smooth the environmental parameters to obtain smoothed illuminance and smoothed color temperature; Specifically, the acquired ambient light intensity and color temperature sequences are smoothed to obtain the smoothed illuminance and smoothed color temperature values ​​at the current moment. The purpose of this step is to suppress the impact of occasional noise or short-term interference on subsequent judgments. Smoothing methods such as moving average, exponentially weighted moving average, or Kalman filtering can be used to ensure that subsequent judgments are based on stable and continuous perceived information.

[0047] S363. Based on the changing trends of the smoothed illuminance and smoothed color temperature, obtain the predicted illuminance and predicted color temperature; Specifically, based on the trends in smoothed illuminance and smoothed color temperature, predicted illuminance and predicted color temperature are obtained to assess the direction and magnitude of changes in ambient light that may occur within a short time window. This prediction can be generated based on linear extrapolation, differential trends, or short-period fitting. For example, if the smoothed illuminance increases continuously, the system can predict that the ambient light will further increase in the next time period, thereby adjusting the LED output in advance to prevent excessive brightness.

[0048] S364. Based on the smoothed illuminance and smoothed color temperature, as well as the target brightness parameter and target color temperature parameter, obtain the actual brightness deviation and actual color temperature deviation; The current smoothed illuminance is compared with the target luminance parameter to obtain the actual luminance deviation; the smoothed color temperature is compared with the target color temperature parameter to obtain the actual color temperature deviation. Here, the "target luminance parameter" and "target color temperature parameter" are the static values ​​set by the lighting control strategy for the current time period, used to assess whether the current environment has deviated from the preset light field.

[0049] S365. Based on the predicted illuminance and predicted color temperature, as well as the target luminance parameters and target color temperature parameters, obtain the trend luminance deviation and trend color temperature deviation; Similar to the previous step, the predicted illuminance is compared with the target luminance parameter to obtain the trend luminance deviation; the predicted color temperature is compared with the target color temperature parameter to obtain the trend color temperature deviation. Unlike the "instant comparison" of S364, this step emphasizes predictive error to determine whether the system will deviate further from the target in subsequent moments if the current trend continues.

[0050] S366. Perform a weighted calculation based on the actual brightness deviation and the trend brightness deviation to obtain the comprehensive brightness deviation; The actual brightness deviation and the trend brightness deviation are weighted and calculated to generate a comprehensive brightness deviation value. This weighting coefficient can be set to a fixed weight (e.g., 0.6 for instantaneous error and 0.4 for trend error), or it can be dynamically adjusted according to the stability of the environment, so that the system pays more attention to instantaneous accuracy in a stable light field and more attention to trend prediction in a dynamic light field.

[0051] S367. Perform a weighted calculation based on the actual color temperature deviation and the trend color temperature deviation to obtain the comprehensive color temperature deviation; Similarly, the system performs weighted fusion on the actual color temperature deviation and the trend color temperature deviation to obtain the comprehensive color temperature deviation. Through comprehensive error processing, the system can construct a dynamic adaptation benchmark that takes into account both the current state and future trends, improving the foresight and stability of the control response.

[0052] S368. Determine the brightness endpoint value and the color temperature endpoint value based on the comprehensive brightness deviation and the comprehensive color temperature deviation, respectively. Based on the overall brightness deviation and overall color temperature deviation, the original target brightness and target color temperature are corrected to determine new endpoint values ​​for brightness and color temperature, respectively. The correction amount can be set within a limited range to prevent the system from making large dimming decisions due to occasional errors, while the adjustment of the endpoint values ​​still maintains consistency with the user's original strategy.

[0053] S369. Based on the brightness endpoint value, the color temperature endpoint value, and the preset slope value, adjust the lighting control curves of brightness and color temperature using the smooth interpolation algorithm.

[0054] Specifically, based on the updated brightness and color temperature endpoint values, and combined with a preset maximum slope threshold, a smooth interpolation algorithm is used to regenerate the brightness and color temperature control curves, allowing the lighting process to naturally transition to the new endpoints within the remaining time. This process does not change the overall trend of the current control curves; it only performs re-interpolation on the endpoint position and the shape of the final curve, ensuring that the output light effect remains stable and without visual jumps.

[0055] Through the above nine consecutive steps, the system can continuously sense the environment and dynamically correct the final output parameters during the LED light strip lighting process, realizing full-process control from static strategy, real-time adaptation and dynamic replanning, effectively improving the softness of the lighting experience, environmental fit and intelligent response, and is especially suitable for complex spatial environments with frequent day-night transitions or sudden changes in natural light.

[0056] Preferably, updating the lighting control strategy based on historical lighting data of the LED light strip within a first preset period includes: S41. Obtain the historical lighting dataset of the LED light strip within a first preset period, wherein the historical lighting dataset includes historical lighting data corresponding to each user activation command, and the historical lighting data includes the lighting duration and the historical ambient illuminance and historical ambient color temperature corresponding to the lighting process. The system acquires historical lighting datasets for the LED light strip within a first preset period. These "historical lighting datasets" refer to usage information recorded by the system for each user activation command during the entire first period. This information includes the actual lighting duration after the user activates the LED light strip (e.g., 5 minutes, 2 hours), as well as the historical ambient illuminance and color temperature collected during this lighting process, reflecting the natural light conditions of the space at the time of actual use. The purpose of this step is to obtain a data foundation reflecting lighting needs and environmental conditions from actual user behavior, providing objective input for subsequent strategy optimization.

[0057] S42. Based on the historical ambient illuminance and historical ambient color temperature, the historical lighting dataset is clustered by time period to obtain a time period cluster set; The system clusters the historical lighting dataset into time periods based on historical ambient illuminance and color temperature, resulting in a set of time period clusters. Unlike traditional time division methods that use "hours / half-hours" as units, this method uses ambient light characteristics for clustering, grouping lighting behaviors occurring under similar lighting conditions into the same "time period cluster." For example, on multiple different dates in the morning or evening, if the ambient illuminance and color temperature are similar when a user turns on the lights, these records can be clustered into the same cluster. Through this clustering method, the system can construct a time period structure based on the "light environment dimension," more realistically reflecting lighting usage scenarios.

[0058] S43. Obtain the intensity index of each cluster based on the cumulative lighting duration of each cluster in each time period; The total duration of historical lighting records included in each time period cluster is statistically analyzed to obtain the intensity index for each time period cluster. The "intensity index" refers to the sum of the frequency and duration of use of that time period cluster throughout the entire cycle; it reflects the user's dependence on lighting in that lighting environment. High intensity indicates that the time period cluster has significant lighting importance, while low intensity may indicate a lower necessity for lighting in that environment.

[0059] S44. Based on the instruction issuance time of each user's activation instruction, obtain the forgetting coefficient of each of the historical lighting data. Furthermore, based on the time of each user's activation command, a forgetting coefficient is calculated for each historical data point. The forgetting coefficient measures the timeliness of historical data and is typically designed to be inversely proportional to the time interval between the command time and the end of the cycle. In other words, data closer to the current cycle has a higher weight, while older data has a smaller impact. This mechanism allows the policy update process to better reflect recent lighting habits without being interfered with by occasional early behaviors.

[0060] S45. Weight the forgetting coefficient and the intensity index to obtain the weighted intensity index; Specifically, the intensity index obtained in step S43 is weighted with the forgetting coefficient obtained in step S44 to obtain a weighted intensity index. Specifically, the system first multiplies the illumination duration of each historical data point by its corresponding forgetting coefficient, and then sums or normalizes the results according to the time period cluster to form the final weighted intensity index.

[0061] S46. Update the lighting control strategy according to the weighted intensity index.

[0062] Specifically, the original lighting control strategy is updated based on the weighted intensity index. The update can be based on methods such as offset functions, incremental correction, or weight reallocation. For example, if the weighted intensity of a certain time period cluster is significantly higher than the overall average, it indicates that users are using lighting frequently in that environment. The system can increase the brightness parameter for that time period, extend the lighting duration, or fine-tune the color temperature to improve comfort. Conversely, for periods with lower intensity, the brightness parameter can be appropriately reduced to save energy. After the update, the strategy will replace the original static control parameters and be used for intelligent lighting scheduling at the start of the second cycle.

[0063] Through the sequential execution of steps S41–S46, the system implements a strategy self-learning update mechanism centered on "historical lighting behavior + environmental perception, usage intensity, and data timeliness." This mechanism boasts technical advantages such as requiring no manual intervention, strong self-optimization capabilities, and a balance between energy saving and comfort. It is particularly suitable for residential and commercial environments with diverse user behaviors and significant changes in natural light, sustainably improving the intelligence level of lighting systems and user satisfaction.

[0064] Preferably, updating the lighting control strategy based on the weighted intensity index includes: S451. Based on the weighted intensity index and the brightness parameter of each time cluster, obtain the brightness correction index for each time cluster, wherein the brightness correction index and the weighted intensity index are positively correlated. Specifically, the system obtains a brightness correction index for each time cluster based on the weighted intensity index and the brightness parameter of each time cluster. Here, the "weighted intensity index" represents the "lighting necessity" of the time cluster within the first preset period, taking into account usage frequency, lighting duration, and data timeliness; the "brightness parameter" is the preset brightness output value for that time period in the current lighting strategy. The system generates the brightness correction index based on the relative magnitude of the weighted intensity and the absolute value of the brightness parameter through a mapping function (such as linear gain, normalized scaling, etc.). This correction index is positively correlated with the weighted intensity, meaning that the higher the usage intensity, the more the system tends to increase the brightness output, thereby improving user lighting comfort and response sensitivity during high-demand periods.

[0065] S452. Based on the brightness correction index and the color temperature and color parameters of each time cluster, obtain the color temperature correction index and color correction index of each time cluster. The system further obtains the color temperature correction index and the color correction index based on the brightness correction index, combined with the color temperature and color parameters corresponding to the time cluster. Here, the system derives the correction by analyzing the correlation between brightness change trends and color temperature and color: when the brightness correction index is positive (indicating increased brightness), the color temperature correction index can be slightly adjusted towards the cooler color side to adapt to visual adaptation under higher illumination; simultaneously, color saturation can be moderately reduced to prevent oversaturation or color cast under high brightness conditions; conversely, when the brightness correction index is negative, the color temperature correction index can be finely adjusted towards the warmer color side, while the color parameters can be moderately increased in saturation or hue variation to maintain visual temperature perception and color expressiveness in low-light environments. This correction relationship can be flexibly defined based on empirical mapping tables, control rules, or interpolation functions, forming a perceptual coordination mechanism among the three parameters of "brightness-color temperature-color".

[0066] S453. Update the lighting control strategy based on the brightness correction index, color temperature correction index, and color correction index.

[0067] The system applies the aforementioned brightness correction index, color temperature correction index, and color correction index to the current lighting control strategy, performing parameter update operations. Updates can be achieved through methods such as overlay, weighted multiplication, or direct replacement. For example, for the brightness parameter, the formula L' = L + ΔL can be used, where ΔL is calculated from the brightness correction index; for color temperature and color parameters, slight adjustments are also made according to their respective correction indices to ensure a controllable and gradual change in the strategy update. Ultimately, the updated lighting control strategy will override the original strategy and be used for the execution of the next lighting cycle, providing users with a lighting environment output that better matches their usage behavior and environmental rhythms.

[0068] Preferably, the historical lighting data further includes user adjustment instructions and corresponding adjustment times, the user adjustment instructions including parameter adjustment values, the parameter adjustment values ​​including at least one of brightness adjustment values, color temperature adjustment values, and color adjustment values, and updating the lighting control strategy according to the weighted intensity index further includes: S454. Based on the adjustment time of each user adjustment instruction, establish a mapping relationship between the user adjustment instruction and the corresponding time cluster; Specifically, in this embodiment, the historical lighting data also includes user adjustment instructions and corresponding adjustment times. The user adjustment instructions include parameter adjustment values, which include at least one of brightness adjustment values, color temperature adjustment values, and color adjustment values. The system establishes a mapping relationship between user adjustment instructions and corresponding time clusters based on the adjustment time of each user adjustment instruction. Since each user adjustment behavior has a specific occurrence time, the system can classify the adjustment behavior into a specific time cluster by matching it with the already clustered time period clusters based on the historical ambient illuminance and color temperature corresponding to that time point. In this way, each adjustment instruction is directly associated with a strategy item under a certain type of lighting environment, constituting a mapping between user behavior and strategy.

[0069] S455. Based on the mapping relationship, obtain the deviation value between the parameter adjustment value and the lighting control strategy of the corresponding time cluster, wherein the deviation value includes brightness difference, color temperature difference and color difference. Based on the aforementioned mapping relationship, the system extracts the parameter adjustment values ​​input by the user and compares them with the current lighting control strategy for that time cluster to calculate the corresponding deviation value. Specifically, when the user manually adjusts the brightness, color temperature, or color parameters, the system records the difference between the adjusted value and the original strategy parameter, forming offsets in three dimensions: "brightness difference," "color temperature difference," and "color difference." These deviation values ​​accurately reflect the user's dissatisfaction with the original strategy output or their need for correction, serving as an important basis for personalized preference extraction.

[0070] S456. Based on the deviation value, obtain the user adjustment preference vector for each time cluster; Specifically, based on the set of deviation values ​​of all user adjustment instructions belonging to each time cluster, statistical normalization is performed to obtain the user adjustment preference vector for that time cluster. This vector is a three-dimensional data structure, representing the user's preferred brightness, color temperature, and color direction (positive or negative) under that lighting environment, as well as the relative strength of the preference correction. It can be generated using methods such as weighted averaging and maximum consistency direction analysis to ensure that it reflects representative user preference trends.

[0071] S457. Adjust the brightness correction index, color temperature correction index, and color correction index according to the user's adjustment preference vector; Specifically, the brightness correction index, color temperature correction index, and color correction index calculated based on weighted intensity in steps S451–S453 are fused and adjusted with the aforementioned user adjustment preference vector. This fusion process can employ a linear weighting method, where the user preference vector can be assigned a higher weight to reflect the priority of proactive adjustment behavior in strategy optimization. The final output correction index will incorporate user-specific biases on top of the original weighted intensity-driven basis, forming a composite correction result that considers both behavioral data and user intent.

[0072] S458. Update the lighting control strategy based on the adjusted brightness correction index, color temperature correction index, and color correction index.

[0073] Specifically, the lighting control strategy is updated based on the fused brightness correction index, color temperature correction index, and color correction index. The update can be implemented using incremental adjustment, sliding overlay, or alternative rewriting methods, and can be combined with curve smoothing algorithms to ensure the continuity of the dimming curve and visual comfort. The updated strategy will directly affect the next lighting cycle, achieving a closed-loop, personalized strategy evolution.

[0074] Through the five steps S454–S458 described above, this embodiment combines user-initiated behavior adjustment with an automatic statistical learning mechanism to form a lighting strategy optimization process that integrates usage habits, real-time perception, and individual preferences. This allows LED light strips to gradually adapt to users, understand scenarios, and optimize responses during long-term operation, effectively improving the intelligence level, user satisfaction, and energy-saving control effect of the lighting system.

[0075] In one embodiment, controlling the LED light strip for illumination according to the adjusted lighting control curve includes: S51. Based on the current time and the adjusted lighting control curve, obtain the lighting parameters for the current time period and the next time period, and record them as the current lighting parameters and the lighting parameters to be switched, respectively. The lighting parameters include brightness parameters and color temperature parameters. Specifically, the adjusted lighting control curve refers to the target curve that changes over time, obtained by combining ambient light trends and historical learning based on a predetermined scene strategy. Lighting parameters include brightness and color temperature parameters, used to describe the brightness and warmth to be output at a given moment. The purpose of this step is to locate the target for the current and next time period on the time axis, forming a pair of references between the current lighting parameters and the lighting parameters to be switched. Based on the current time index curve, the target points at the end of the current segment and the beginning of the next segment are read. If the current time falls on the segment boundary, the parameters at the boundary are taken first. If the curve is a discrete point sequence, a smooth interpolation can be performed to avoid quantization jumps.

[0076] S52. Control the LED light strip to provide illumination based on the current lighting parameters; Before switching, the current output is maintained to ensure the continuity of curve execution. This is achieved by outputting the duty cycle and color temperature ratio according to the control cycle, and executing the single-step amplitude limit and anti-flicker threshold. When the device has a minimum resolution step size, minor changes below the minimum step size are accumulated and then output all at once. This maintains a stable, flicker-free lighting environment before switching.

[0077] S53. Based on the current lighting parameters and the lighting parameters to be switched, obtain the parameter difference, wherein the parameter difference includes the color temperature difference and the brightness difference; Specifically, the parameter difference refers to the target difference between the current lighting parameters and the lighting parameters to be switched, including color temperature difference and brightness difference. The purpose of this step is to quantify the workload required for the switch, providing a basis for rate and time planning. In implementation, the difference is calculated separately for both types of parameters, and differences that significantly exceed equipment capabilities or strategy boundaries are limited. If a color temperature target crosses segment boundaries (such as a preset warm / cool threshold), the total difference can be divided into several sub-segments for more refined transition control later. This avoids subsequent planning based on unattainable or unreasonable targets, improving the feasibility of execution.

[0078] S54. Determine the remaining duration of the current time period based on the current time and the next time period; The remaining duration of the current time period refers to the available adjustment time from the current moment until the end of this time period. Its purpose is to provide time constraints for strategy selection and rate calculation. In implementation, the time period boundary time is read and compared with the current time. If the remaining duration is less than one control cycle, it is recorded as the minimum effective duration to ensure at least one effective output. If clock drift or configuration update is detected, recalculation is required within the same control cycle to ensure that subsequent decisions are consistent with the actual time window.

[0079] S55. Based on the parameter difference, the preset brightness adjustment rate range and color temperature adjustment rate range, obtain the brightness adjustment time interval and the color temperature adjustment time interval. Specifically, the preset brightness and color temperature adjustment rate range refers to the slowest and fastest adjustment speeds allowed under the constraints of device capabilities and visual comfort; the brightness and color temperature adjustment time range is the range of the fastest and slowest completion times derived from the difference and the two preset adjustment rate ranges.

[0080] Specifically, based on the current brightness difference and the brightness adjustment rate range, estimate the shortest and longest completion times under ideal conditions; then, perform the same estimation for the color temperature difference. The estimation process considers not only the nominal rate upper / lower limits but also the maximum single-step change within the control cycle, device output resolution, anti-flicker threshold, power / thermal management boundaries, and the necessary minimum smoothing duration at the start and end points. When the target color temperature crosses the preset warm / cool boundary or crosses color temperature segmentation rules, the change is broken down into continuous sub-segments, estimated separately, and their times are accumulated.

[0081] S56. The longer of the brightness adjustment time interval and the color temperature adjustment time interval is taken as the target adjustment time interval. Specifically, the longer of the two intervals is chosen as the target adjustment time interval. The aim is to use the more time-consuming channel as the global rhythm benchmark to maintain consistency between brightness and color temperature. In practice, the upper and lower bounds of the two intervals are compared, and the longer set is selected as a reference for subsequent decisions. If the two intervals are significantly inconsistent, the dominant channel can be recorded internally for use in rate coupling and phase misalignment in subsequent stages. This avoids the uncoordinated feeling of one channel arriving first and the other lagging behind.

[0082] S57. Compare the target adjustment time interval with the remaining duration to obtain the adjustment strategy and adjustment start time. When the remaining duration is greater than or equal to the target adjustment time interval, the adjustment strategy is a phased adjustment strategy; otherwise, the adjustment strategy is a linear adjustment strategy. Specifically, this step determines the adjustment strategy and adjustment start time by comparing the target adjustment time interval with the remaining time. The aim is to adopt a more comfortable phased transition when time is ample, and a linear transition to reach the target when time is tight. The adjustment start time refers to the trigger time obtained by extrapolating the target adjustment time interval backward from the starting point of the next phase. In implementation, if the remaining duration is greater than or equal to the lower bound, a phased adjustment strategy is obtained, and the duration ratio of each phase is determined by combining the scene preset segment ratio and power / glare constraints. If the remaining duration is less than the lower bound, a linear adjustment strategy is obtained, and a fixed slope is set to advance in a manner that does not exceed the upper limit of the rate. In one embodiment, a minimum smoothing of one control cycle can be inserted at the beginning and end of the adjustment to suppress spikes. S58. If the adjustment strategy is a phased adjustment strategy, the phase adjustment duration of each adjustment phase is obtained according to the target adjustment time interval and the preset segmentation ratio. When choosing a phased strategy, the adjustment duration for each phase needs to be generated based on the target adjustment time interval and the preset segmentation ratio. A more natural feel is achieved through gradual changes at the beginning and end and stable progression in the middle. In implementation, the total duration is allocated proportionally, and fine-tuning is made to each segment when constraints are triggered (such as power or glare thresholds) to ensure safety as a priority; if the next time period continues to advance along the same target direction, splicing margin can be reserved in the gradual withdrawal phase. This significantly reduces the probability of visible abrupt changes and overshoot pullback.

[0083] S59. Based on the adjustment duration and the parameter difference, obtain the color temperature adjustment rate and brightness adjustment rate for each adjustment stage. After obtaining the duration of each stage, the color temperature adjustment rate and brightness adjustment rate for each stage need to be generated based on the stage duration and parameter difference. The goal is to achieve the segmented completion of the overall difference using a stable and monotonous progression within each stage. In a specific embodiment, a lower rate is used for the initial and final stages, while a moderate or slightly higher rate is used for the middle stages. To conform to visual habits, the color temperature can lag slightly behind the brightness by several control cycles and be executed at a smaller rate amplitude. Single-step change limits and monotonicity constraints are enforced throughout the process to avoid reverse callbacks at any stage. This ensures that the segmented transitions are completed as planned while maintaining comfort.

[0084] S510. If the adjustment strategy is a linear adjustment strategy, obtain the color temperature adjustment rate and the brightness adjustment rate based on the remaining time and the upper limit of the brightness adjustment rate range and the color temperature adjustment rate range. Specifically, when choosing a linear strategy, the linear adjustment rate of color temperature and brightness needs to be determined based on the remaining time and the upper limit of the rate range. The goal is to get as close to the target as possible within a limited time, while not exceeding the boundaries of device comfort. In implementation, a rate close to the upper limit is preferred, but a minimum smoothing of one control cycle is inserted at the beginning and end to suppress visible spikes. If the remaining time is still insufficient to completely reach the endpoint, the residual is recorded for seamless stitching in the next time segment. This ensures both fast response and basic visual smoothness.

[0085] S511. At the start time of the adjustment, the LED light strip is controlled to switch from the current lighting parameters to the lighting parameters to be switched according to the color temperature adjustment rate and the brightness adjustment rate.

[0086] When the adjustment start time arrives, transition control from the current lighting parameters to the lighting parameters to be switched is executed at the previously determined rate. The aim is to transform the planning results into stable and controllable output behavior. In practice, new targets for brightness and color temperature are issued in each control cycle, and constraints such as single-step amplitude, power, and glare are verified in real time; thus, a switching effect without visible jumps, consistent with the time plan, and operating within constraints can be obtained.

[0087] Preferably, when the physical space includes multiple LED light strips, the step of controlling the LED light strips to switch from the current lighting parameters to the lighting parameters to be switched, based on the color temperature adjustment rate and brightness adjustment rate, at the adjustment start time, includes: S5111. Obtain the physical parameters of each LED light strip in the physical space, wherein the physical parameters of the light strip include the number of LED beads, the spacing between LED beads, and the length of the light strip; The number of LED beads in this step refers to the actual number of controllable light-emitting units on the light strip; "LED bead spacing" refers to the installation distance between adjacent LED beads; and the light strip length refers to the actual length of the light strip from one end to the other. For example, a strip light around a conference room might be 5 meters long, with 60 LED beads per meter and a spacing of approximately 16.7 millimeters. The purpose of this step is to establish the objective basic data necessary for subsequent speed adjustments and to ensure comparability between multiple light strips.

[0088] S5112. Obtain the LED density per unit length based on the number of LEDs and the spacing between LEDs; LED density per unit length can be understood as the number of LEDs per meter (or per fixed length), used to approximately reflect the uniformity and blending of light emission. For example, 120 LEDs per meter is significantly higher than 30 LEDs per meter, and it is less likely to appear as dots over the same length.

[0089] It can be calculated directly based on the number of LEDs per unit length; if there are uneven spacing in some areas of the same LED strip, take the segmented data from the installation document as the average or record the segments separately, and if necessary, use different density values ​​for each segment within the control period. S5113. Based on the LED bead density and LED strip length, obtain the luminous coverage value of each LED strip, wherein the luminous coverage value is positively correlated with the LED bead density and LED strip length; Specifically, the luminous coverage value is used to quantify the overall impact of a single light strip on spatial illuminance and coverage area. Higher density and longer length generally result in stronger overall illumination capacity and coverage uniformity, thus both are positively correlated with this value. The purpose of this step is to create a comprehensive scale for selecting main light strips and ranking their relative capabilities, avoiding biases caused by using only a single dimension (such as comparing only length or only density).

[0090] S5114. The LED strip corresponding to the largest luminous coverage value is used as the main LED strip, and the remaining LED strips are used as secondary LED strips. The primary light strip serves as the reference benchmark for this transition, typically located in the visual core area or possessing the greatest spatial influence. Secondary light strips coordinate with the rhythm of the primary light strip during the transition. The aim is to establish a globally consistent reference, avoiding visual disjointedness caused by multiple light strips operating independently. The light strip with the highest luminous coverage value is directly selected as the primary light strip. If multiple light strips are used simultaneously, priority is given to those located in the center of the space, in areas sensitive to user vision, or in locations with high historical usage frequency. This ensures stable control rhythm and a clear benchmark.

[0091] S5115. Obtain the physical parameter difference between each light strip and the main light strip, wherein the physical parameter difference includes density difference and light strip length difference; Density difference refers to the difference in density per unit length of the secondary light strip relative to the primary light strip; length difference refers to the difference in actual paving length relative to the primary light strip. The purpose of this step is to convert the objective differences into data that can drive the speed adjustment, which can then be used to determine the speed adjustment.

[0092] S5116. Based on the physical parameter difference, adjust the color temperature adjustment rate and brightness adjustment rate of the light strip for each time, wherein the color temperature adjustment rate is negatively correlated with the density difference and positively correlated with the light strip length difference, and the brightness adjustment rate is positively correlated with the density difference and negatively correlated with the light strip length difference. This step employs a differentiation rule: the brightness adjustment rate is positively correlated with the density difference and negatively correlated with the length difference; the color temperature adjustment rate is negatively correlated with the density difference and positively correlated with the length difference. Intuitively, this means that denser light strips should adjust brightness more slowly to avoid abrupt point-like changes, but can adjust color temperature slightly faster to compensate for uneven warm / cool tones; longer light strips should adjust brightness more slowly to suppress overall abrupt changes, but can adjust color temperature slightly faster to maintain spatial color consistency. The goal is to achieve perceptual consistency in both brightness and warm / cool tones for light strips with different structures: brightness should prioritize uniformity, and color temperature should prioritize color harmony.

[0093] Specifically, a baseline rate for the main LED strip is first generated, and secondary LED strips are then fine-tuned based on this according to the aforementioned rules. Simultaneously, upper / lower rate limits, single-step change amounts, flicker prevention, and smooth start / end points are applied. To improve the user experience, the color temperature can be delayed relative to brightness by several control cycles. If the difference is too large, causing the adjustment value to reach the boundary, comfort is prioritized, and any deficiencies are carried over to the next time period. This allows for a stable and coordinated transition of multiple LED strips without introducing complex weights and formulas.

[0094] S5117. At the start time of the adjustment, based on the color temperature adjustment rate and the brightness adjustment rate, the main light strip is controlled to switch from the current lighting parameters to the lighting parameters to be switched, and at the same time, based on the adjusted color temperature adjustment rate and brightness adjustment rate, the secondary light strip is controlled to switch from the current lighting parameters to the lighting parameters to be switched.

[0095] Specifically, the transition is triggered at the start time: the main light strip executes at the reference rate, and the secondary light strips advance synchronously at the adjusted rate; the single-step amplitude, power, and glare threshold are continuously verified within the control cycle; when the remaining time is insufficient to fully achieve the target, the residual is recorded and seamlessly spliced ​​in the next time period to ensure the continuity of values ​​and trends. This achieves a scene switching effect that is visually synchronized, engineering-stable, and without abrupt changes at the boundaries.

[0096] By calculating the luminous coverage value using the density of LED beads per unit length and the length of the LED strip, and then selecting the LED strip with the strongest coverage as the main LED strip, the overall light effect transition of the space is based on the most representative LED strip. The master-slave mechanism allows the system to determine only the reference rate of one main LED strip, and secondary LED strips can be corrected by the difference, eliminating the need to generate complex complete curves for each LED strip individually. In the rate correction rule, brightness is positively correlated with density and negatively correlated with length, while color temperature is negatively correlated with density and positively correlated with length, forming a complementary adjustment. This ensures that there are no abrupt point changes when brightness changes, and compensates for the warm or cool deviations of sparse or long LED strips when color temperature changes, resulting in a more natural overall visual transition.

[0097] Example 2 Please see Figure 3 This invention provides a scene-based adaptive control device for LED light strips, the device comprising: The scene information acquisition module is used to acquire scene information of the physical space where the LED light strip is located, wherein the scene information includes scene type, space area and number of light strips in the physical space; The initial lighting strategy acquisition module is used to acquire the lighting control strategy of the LED light strip in different time periods within a first preset period based on the scene information, wherein the lighting control strategy includes brightness parameters, color temperature parameters and color parameters; The first lighting control module is used to control the LED light strip to provide illumination in response to a user's on / off command within a first preset period, based on the lighting control strategy and environmental parameters of the current time period. The lighting strategy update module is used to update the lighting control strategy based on the historical lighting data of the LED light strip within a first preset period. The second lighting control module is used to control the LED light strip to provide illumination in response to a user's on / off command after a first preset period, based on the lighting control strategy and environmental parameters adjusted for the current time period.

[0098] It should be noted that each module and unit in the scene-based adaptive control device of this embodiment corresponds one-to-one with each step in the scene-based adaptive control method of the aforementioned embodiment. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned scene-based adaptive control method of the LED strip, and will not be repeated here.

[0099] Example 3 In addition, combined Figure 1 The scene-based adaptive control method for LED light strips described in this embodiment of the invention can be implemented by a light-emitting device. Figure 4 A schematic diagram of the hardware structure of the light-emitting device provided in an embodiment of the present invention is shown.

[0100] Specifically, the light-emitting device includes: an LED light strip, at least one processor, at least one memory, and computer program instructions stored in the memory. When the computer program instructions are executed by the processor, they implement the method described in Embodiment 1 above to control the LED light strip to emit light.

[0101] Electronic devices may include processors and memory storing computer program instructions.

[0102] Specifically, the processor may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement embodiments of the present invention.

[0103] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0104] Computer-readable media include both permanent and non-permanent, removable and non-removable media, which can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient media, such as modulated communication signals and carrier waves.

[0105] The processor reads and executes computer program instructions stored in the memory to implement any of the scene-based adaptive control methods for LED light strips in the above embodiments.

[0106] In one example, the electronic device may also include a communication interface and a bus. For example, Figure 4 As shown, the processor 401, memory 402, and communication interface 403 are connected through bus 410 and complete communication with each other.

[0107] The communication interface is mainly used to enable communication between various modules, devices, units and / or equipment in the embodiments of the present invention.

[0108] A bus, including hardware, software, or both, couples components of an electronic device together. For example, and not limitingly, a bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, a bus may include one or more buses. While specific buses are described and illustrated in embodiments of the invention, the invention contemplates any suitable bus or interconnect.

[0109] Example 4 Furthermore, in conjunction with the scene-based adaptive control method for LED light strips in the above embodiments, this invention can be implemented using a computer-readable storage medium. This computer-readable storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the scene-based adaptive control methods for LED light strips in the above embodiments.

[0110] It should be clarified that the present invention is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of the present invention.

[0111] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0112] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0113] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0114] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0115] It should also be noted that the exemplary embodiments mentioned in this invention describe methods or systems based on a series of steps or apparatus. However, this invention is not limited to the order of the steps described above; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0116] The above description is merely a specific embodiment of the present invention. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the protection scope of the present invention.

Claims

1. A scene-based adaptive control method for LED light strips, characterized in that, The method includes: Obtain scene information of the physical space where the LED light strip is located, wherein the scene information includes scene type, space area and number of light strips in the physical space; Based on the scene information, the lighting control strategy of the LED light strip in different time periods within the first preset period is obtained, wherein the lighting control strategy includes brightness parameters, color temperature parameters and color parameters; Within the first preset period, in response to the user's on / off command, the LED light strip is controlled to provide illumination based on the lighting control strategy and environmental parameters for the current time period; The lighting control strategy is updated based on the historical lighting data of the LED light strip within the first preset period. After the first preset cycle, in response to the user's on / off command, the LED light strip is controlled to provide illumination based on the lighting control strategy and environmental parameters adjusted according to the current time period.

2. The scene-based adaptive control method for LED light strips according to claim 1, characterized in that, The step of obtaining the lighting control strategy of the LED light strip at different time periods within a first preset period based on the scene information includes: Based on the scene type, the target lighting parameters of the physical space are obtained, wherein the target lighting parameters include the illuminance target range, color temperature target range, and color target range of the scene type within a preset time period; Based on the space area and the target illuminance range, the total target illuminance of the physical space in different time periods is obtained; The lighting contribution ratio of the light strips is obtained based on the space area, the number of light strips, and the scene type. The lighting contribution ratio of the light strips is positively correlated with the number of light strips and negatively correlated with the space area. Based on the total target illuminance, the lighting contribution ratio of the LED strips, and the number of LED strips, obtain the brightness control curve for each LED strip; Based on the curve variation characteristics of the brightness control curve, the color temperature target range, and the color target range, obtain the color temperature control curve and color control curve for each LED light strip; The brightness control curve, color temperature control curve, and color control curve are smoothed to obtain the lighting control strategy of the LED light strip at different time periods.

3. The scene-based adaptive control method for LED light strips according to claim 2, characterized in that, Within the first preset period, in response to a user's on / off command, the LED light strip is controlled to provide illumination based on the lighting control strategy and environmental parameters for the current time period, including: In response to user on / off commands, obtain the command issuance time and environmental parameters; According to the lighting control strategy corresponding to the time the instruction is issued, the target lighting parameters are obtained, including the target brightness parameters, the target color temperature parameters, and the target color parameters; Set the target brightness parameter and target color temperature parameter as endpoints to establish a multi-channel target endpoint set; Based on the multi-channel target endpoint set and the preset slope value, the initial control curves for brightness and color temperature are obtained respectively through a smooth interpolation algorithm; Based on the initial lighting control curve and the target color parameters, the LED light strip is controlled to gradually light up; During the gradual lighting process, the endpoint of the lighting control curve that adjusts brightness and color temperature according to the environmental parameters; The LED light strip is controlled to provide illumination according to the adjusted lighting control curve.

4. The scene-based adaptive control method for LED light strips according to claim 3, characterized in that, The endpoint of the lighting control curve, which adjusts brightness and color temperature according to the environmental parameters during the gradual lighting process, includes: Environmental parameters are collected according to a preset sampling period, wherein the environmental parameters include an ambient light illuminance sequence and an ambient light color temperature sequence; The environmental parameters are smoothed to obtain smoothed illuminance and smoothed color temperature; Based on the changing trends of the smoothed illuminance and smoothed color temperature, the predicted illuminance and predicted color temperature are obtained; Based on the smoothed illuminance and smoothed color temperature, as well as the target brightness parameters and target color temperature parameters, the actual brightness deviation and actual color temperature deviation are obtained. Based on the predicted illuminance and predicted color temperature, as well as the target luminance parameters and target color temperature parameters, obtain the trend luminance deviation and trend color temperature deviation; The overall brightness deviation is obtained based on the actual brightness deviation and the trend brightness deviation. Based on the actual color temperature deviation and the trend color temperature deviation, the comprehensive color temperature deviation is obtained; Based on the overall brightness deviation and the overall color temperature deviation, the brightness endpoint value and the color temperature endpoint value are determined respectively. The lighting control curves for brightness and color temperature are adjusted using the smooth interpolation algorithm based on the brightness endpoint value, the color temperature endpoint value, and the preset slope value.

5. The scene-based adaptive control method for LED light strips according to claim 1, characterized in that, The step of updating the lighting control strategy based on historical lighting data of the LED light strip within a first preset period includes... Obtain the historical lighting dataset of the LED light strip within a first preset period, wherein the historical lighting dataset includes historical lighting data corresponding to each user activation command, and the historical lighting data includes the lighting duration and the historical ambient illuminance and historical ambient color temperature corresponding to the lighting process. Based on the historical ambient illuminance and historical ambient color temperature, the historical lighting dataset is clustered by time period to obtain a set of time period clusters; Based on the cumulative lighting duration of each cluster in each time period, the intensity index of each cluster in each time period is obtained; Based on the time when each user's activation command was issued, the forgetting coefficient of each set of historical lighting data is obtained. The weighted intensity index is obtained by weighting the forgetting coefficient and the intensity index. The lighting control strategy is updated based on the weighted intensity index.

6. The scene-based adaptive control method for LED light strips according to claim 5, characterized in that, The step of updating the lighting control strategy based on the weighted intensity index includes: Based on the weighted intensity index and the brightness parameters of each time cluster, the brightness correction index of each time cluster is obtained, wherein the brightness correction index and the weighted intensity index are positively correlated. Based on the brightness correction index and the color temperature and color parameters of each time cluster, obtain the color temperature correction index and color correction index of each time cluster. The lighting control strategy is updated based on the brightness correction index, color temperature correction index, and color correction index.

7. The scene-based adaptive control method for LED light strips according to claim 5, characterized in that, The step of controlling the LED light strip for illumination according to the adjusted lighting control curve includes: Based on the current time and the adjusted lighting control curve, obtain the lighting parameters for the current time period and the next time period, and record them as the current lighting parameters and the lighting parameters to be switched, respectively. The lighting parameters include brightness parameters and color temperature parameters. Based on the current lighting parameters, control the LED light strip to provide illumination; Based on the current lighting parameters and the lighting parameters to be switched, obtain the parameter difference, wherein the parameter difference includes the color temperature difference and the brightness difference; Based on the current time and the next time period, determine the remaining duration of the current time period; Based on the parameter difference, the preset brightness adjustment rate range and color temperature adjustment rate range, the brightness adjustment time interval and color temperature adjustment time interval are obtained. The longer of the brightness adjustment time interval and the color temperature adjustment time interval shall be taken as the target adjustment time interval; The target adjustment time interval and the remaining duration are compared to obtain the adjustment strategy and adjustment start time. When the remaining duration is greater than or equal to the target adjustment time interval, the adjustment strategy is a phased adjustment strategy; otherwise, the adjustment strategy is a linear adjustment strategy. If the adjustment strategy is a phased adjustment strategy, the phase adjustment duration of each adjustment phase is obtained according to the target adjustment time interval and the preset segmentation ratio. Based on the adjustment duration and the parameter difference, obtain the color temperature adjustment rate and brightness adjustment rate for each adjustment stage; If the adjustment strategy is a linear adjustment strategy, the color temperature adjustment rate and the brightness adjustment rate are obtained based on the remaining duration and the upper limit of the brightness adjustment rate range and the color temperature adjustment rate range. At the start time of the adjustment, the LED light strip is controlled to switch from the current lighting parameters to the lighting parameters to be switched, based on the color temperature adjustment rate and the brightness adjustment rate.

8. The scene-based adaptive control method for LED light strips according to claim 7, characterized in that, When the physical space includes multiple LED light strips, the step of controlling the LED light strips to switch from the current lighting parameters to the lighting parameters to be switched at the adjustment start time, based on the color temperature adjustment rate and brightness adjustment rate, includes: Obtain the physical parameters of each LED strip within the physical space, wherein the physical parameters include the number of LED beads, the spacing between LED beads, and the length of the strip; The density of LEDs per unit length is obtained based on the number of LEDs and the spacing between them. Based on the LED chip density and LED strip length, the luminous coverage value of each LED strip is obtained, wherein the luminous coverage value is positively correlated with the LED chip density and LED strip length; The LED strip corresponding to the largest luminous coverage value is designated as the main LED strip, and the remaining LED strips are designated as secondary LED strips. Obtain the physical parameter difference between each desired light strip and the main light strip, wherein the physical parameter difference includes density difference and light strip length difference; Based on the difference in physical parameters, the color temperature adjustment rate and brightness adjustment rate of the light strip are adjusted for each time. The color temperature adjustment rate is negatively correlated with the density difference and positively correlated with the difference in light strip length. The brightness adjustment rate is positively correlated with the density difference and negatively correlated with the difference in light strip length. At the start time of the adjustment, the main light strip is controlled to switch from the current lighting parameters to the lighting parameters to be switched according to the color temperature adjustment rate and the brightness adjustment rate. At the same time, the secondary light strip is controlled to switch from the current lighting parameters to the lighting parameters to be switched according to the adjusted color temperature adjustment rate and brightness adjustment rate.

9. A scene-based adaptive control device for LED light strips, characterized in that, The device includes: The scene information acquisition module is used to acquire scene information of the physical space where the LED light strip is located, wherein the scene information includes scene type, space area and number of light strips in the physical space; The initial lighting strategy acquisition module is used to acquire the lighting control strategy of the LED light strip in different time periods within a first preset period based on the scene information, wherein the lighting control strategy includes brightness parameters, color temperature parameters and color parameters; The first lighting control module is used to control the LED light strip to provide illumination in response to a user's on / off command within a first preset period, based on the lighting control strategy and environmental parameters of the current time period. The lighting strategy update module is used to update the lighting control strategy based on the historical lighting data of the LED light strip within a first preset period. The second lighting control module is used to control the LED light strip to provide illumination in response to a user's on / off command after a first preset period, based on the lighting control strategy and environmental parameters adjusted for the current time period.

10. A light-emitting device, characterized in that, include: An LED light strip, at least one processor, at least one memory, and computer program instructions stored in the memory, wherein when the computer program instructions are executed by the processor, the method as described in any one of claims 1-8 is used to control the LED light strip to emit light.

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