Whole house intelligent lighting adjustment method and intelligent lamp

Abstract

The present invention relates to the field of smart light adjustment technology, and specifically to a whole-house smart light adjustment method and smart light, including obtaining a set reference light-off duration T of the smart light; obtaining the current light-off duration T1 of the smart light, and comparing the current light-off duration T1 with the reference light-off duration T: if, then turn on the smart light for the next time according to a first light parameter; wherein the first light parameter is the light parameter of the smart light when the light was turned off the previous time; if, then turn on the smart light for the next time according to a second light parameter; wherein the second light parameter is the light parameter of the smart light when the light was turned on the previous time at the same time. The whole-house smart light adjustment method and smart light described in the present invention dynamically adjust the initial dimming value according to the actual usage of the user, thereby significantly reducing the dimming time from dimming to the target light and accelerating the dimming response speed.

Description

Technical Field

[0001] The present invention relates to the technical field of lighting adjustment of smart lamps, and in particular to a whole-house smart lighting adjustment method and a smart lamp. Background Art

[0002] With the continuous advancement of technology, smart home systems have gradually entered people's daily lives. Among them, smart lamps, as an important part of smart homes, are not limited to simple lighting, but are also important tools for realizing personalized space environments. The brightness and color temperature range of smart lamps can be continuously adjusted, and they can be automatically or manually dimmed according to user needs, aiming to improve user comfort and optimize the living environment.

[0003] At present, the dimming settings of most smart lamps when turning on the lights rely on the reset dimming parameters preset at the factory. This means that when the user turns on the lamp at any time, the system will dim the light with the fixed reset dimming parameters as the initial value. Although the factory reset dimming parameters have been debugged to a certain extent and can produce satisfactory dimming effects for most users, there are still significant problems in actual use: under the influence of various environmental factors such as different time periods and weather changes, the user's lighting needs will change. Starting dimming with the factory reset dimming parameters as the initial value will take a long time for the smart lamp to reach the target value with the best user comfort, and the dimming response is slow, which affects the use effect. Summary of the invention

[0004] To this end, the technical problem to be solved by the present invention is to overcome the problem in the prior art that the initial dimming value of the smart lamp when the smart lamp is turned on is fixed as the factory setting parameter, resulting in a long dimming time and slow dimming response speed of the smart lamp. A whole-house smart lighting adjustment method and a smart lamp are provided, which dynamically adjust the initial dimming value according to the actual usage of the user, thereby significantly reducing the dimming time to the target light and speeding up the dimming response speed.

[0005] In a first aspect, in order to solve the above technical problems, the present invention provides a whole-house intelligent lighting adjustment method for intelligent lamp adjustment, and the intelligent lamp performs lighting adjustment according to a dimming strategy. The method comprises:

[0006] Obtaining a set reference light-off duration T of the smart light; wherein the reference light-off duration is a preset time interval between the last light-off moment and the next light-on moment;

[0007] Obtain the current light-off duration T1 of the smart light, and compare the current light-off duration T1 with the reference light-off duration T:

[0008] like , then the next time the smart light is turned on is executed according to the first light parameter; wherein the first light parameter is the light parameter of the smart light when it was turned off last time;

[0009] like , then the smart light is turned on for the next time according to the second light parameter; wherein the second light parameter is the light parameter of the smart light when it was turned on at the same time point last time;

[0010] The lighting parameters include brightness parameters and color temperature parameters.

[0011] In one embodiment of the present invention, after the smart lamp executes the first lighting parameter or the second lighting parameter to turn on the lamp, it also includes running dimming according to a dimming strategy; the dimming strategy is determined according to the target brightness value and target color temperature value of the user of the smart lamp.

[0012] In one embodiment of the present invention, determining the dimming strategy includes:

[0013] Acquire environmental characteristic parameters of the installation area of ​​the smart lamp; wherein the environmental characteristic parameters include an ambient light brightness value and an ambient light color temperature value;

[0014] Determining a brightness adjustment strategy according to the ambient light brightness value and the target brightness value;

[0015] Determining a color temperature adjustment strategy according to the ambient light color temperature value and the target color temperature value;

[0016] The dimming strategy is determined according to the brightness adjustment strategy and the color temperature adjustment strategy.

[0017] In one embodiment of the present invention, a brightness adjustment strategy is determined based on the ambient light brightness value and the target brightness value, including applying the ambient light brightness value and the target brightness value as PID control parameters, iteratively calculating all brightness values ​​of the smart lamp within a control cycle, and determining the brightness adjustment strategy based on all brightness values ​​of the smart lamp within the control cycle.

[0018] In one embodiment of the present invention, a color temperature adjustment strategy is determined based on the ambient light color temperature value and the target color temperature value, including applying the ambient light color temperature value and the target color temperature value as PID control parameters, iteratively calculating all color temperature values ​​of the smart lamp within a control cycle, and determining the color temperature adjustment strategy based on all color temperature values ​​of the smart lamp within the control cycle.

[0019] In one embodiment of the present invention, the target brightness value includes a reference target brightness value; the target color temperature value includes a reference target color temperature value; and the method for determining the reference target brightness value and the reference target color temperature value includes the following steps:

[0020] Acquire user characteristic information of the user of the smart lamp;

[0021] Acquire a dimming parameter range for dimming control of the smart lamp, and arbitrarily select a first dimming parameter within the dimming parameter range;

[0022] Under the environmental characteristic parameters, dimming prediction is performed on the smart lamp based on the first dimming parameter to obtain a predicted brightness parameter and a predicted color temperature parameter; dimming control analysis is performed on the predicted brightness parameter and the predicted color temperature parameter according to the first dimming parameter to obtain a control delay parameter;

[0023] Under the environmental characteristic parameters, analog dimming control is performed based on the first dimming parameter, and the analog dimming control is corrected according to the control delay parameter to obtain analog brightness parameters and analog color temperature parameters;

[0024] Analyze and obtain a first comfort level of the first dimming parameter according to the simulated brightness parameter, the simulated color temperature parameter and the user characteristic information;

[0025] According to the first comfort level, continue to optimize the dimming parameters within the dimming parameter range to obtain optimal dimming parameters, and the brightness value and color temperature value corresponding to the optimal dimming parameters are configured as the reference target brightness value and the reference target color temperature value.

[0026] In one embodiment of the present invention, dimming prediction is performed on the smart lamp based on the first dimming parameter to obtain a predicted brightness parameter and a predicted color temperature parameter, including:

[0027] Obtain historical dimming data of the smart lamp of the same model;

[0028] Extracting a sample dimming parameter set, a sample environment characteristic parameter set, a sample brightness parameter set, and a sample color temperature parameter set from the historical dimming data;

[0029] Constructing a neural network model, and taking the sample dimming parameter set and the sample environment characteristic parameter set as input, and taking the sample brightness parameter set and the sample color temperature parameter set as output to train the neural network model to obtain a dimming predictor;

[0030] The first dimming parameter and the environmental characteristic parameter are input into the dimming predictor to obtain the predicted brightness parameter and the predicted color temperature parameter.

[0031] In one embodiment of the present invention, dimming control analysis is performed on the predicted brightness parameter and the predicted color temperature parameter according to the first dimming parameter to obtain a control delay parameter, including:

[0032] Obtain historical dimming data of the smart lamp of the same model;

[0033] Extracting a sample dimming parameter set and a sample control delay parameter set from the historical dimming data;

[0034] Constructing a network analysis model, and using the sample dimming parameter set as input and the sample control delay parameter set as output to train the network analysis model to obtain a dimming control analyzer;

[0035] The first dimming parameter is input into the dimming control analyzer to obtain the control delay parameter.

[0036] In one embodiment of the present invention, according to the first comfort level, continuing to optimize the dimming parameters within the dimming parameter range to obtain optimal dimming parameters, and setting the optimal dimming parameters to the reference target brightness value and the reference target color temperature value, including:

[0037] Randomly selecting a second dimming parameter within the dimming parameter range, and calculating and obtaining a second comfort level;

[0038] Compare the second comfort level with the first comfort level. If the second comfort level is greater than the first comfort level, use the second dimming parameter as the optimal dimming parameter. If the second comfort level is less than or equal to the first comfort level, use the first dimming parameter as the optimal dimming parameter. Iterate in this way until the iteration condition is met to obtain the optimal dimming parameter.

[0039] In a second aspect, in order to solve the above-mentioned technical problem, the present invention provides a smart lamp, which operates and controls dimming based on the whole-house smart lighting adjustment method.

[0040] The above technical solution of the present invention has the following beneficial effects compared with the prior art:

[0041] The whole-house intelligent lighting adjustment method and the smart lamp described in the present invention, if the current lights-off time T1 is greater than the reference lights-off time T, the lighting parameters of the smart lamp in the previous lighting-on state at the same time point are used as the initial dimming parameters; if the current lights-off time T1 is less than or equal to the reference lights-off time T, the lighting parameters of the smart lamp at the previous lights-off state are used as the initial dimming parameters, so as to dynamically adjust the initial dimming value according to the actual usage of the user, thereby significantly reducing the dimming time to dim to the target light and accelerating the dimming response speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below according to specific embodiments of the present invention in conjunction with the accompanying drawings, wherein:

[0043] Figure 1 This is a flow chart of the whole-house intelligent lighting adjustment method in a preferred embodiment of the present invention;

[0044] Figure 2 Flow chart of a method for determining target brightness value and target color temperature value in a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0045] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention. Embodiment 1

[0046] An embodiment of the present invention discloses a whole-house intelligent lighting adjustment method, by executing the lighting adjustment method to control the operation of intelligent lights, wherein the intelligent lights can continuously adjust the brightness and color temperature within a certain range.

[0047] Specifically, the brightness of an LED lamp is proportional to the current passing through it, that is, the greater the current, the higher the brightness; the smaller the current, the lower the brightness; brightness adjustment is achieved by changing the current flowing through the LED lamp beads. Smart lights usually use PWM (pulse width modulation) technology to accurately control the current, thereby achieving the purpose of smoothly adjusting the brightness.

[0048] Color temperature adjustment refers to the "temperature" of the light emitted by the LED lamp, which actually refers to the color of the light; the unit of color temperature is Kelvin K, the lower the value, the more yellow the light is; the higher the value, the more blue the light is. The smart lamp is equipped with multiple LED lamp beads with different color temperatures (such as warm white and cool white), and the required color temperature is mixed by adjusting the brightness ratio of each lamp bead to achieve color temperature adjustment; for example, increasing the proportion of warm white LEDs can make the overall light warmer, and vice versa.

[0049] The smart lamp includes a light-emitting module composed of multiple LED lamp beads, a controller and a memory, and dynamically adjusts the dimming parameters of the smart lamp according to the user's usage requirements and the ambient light information collected in real time.

[0050] Specifically, refer to Figure 1 As shown, an embodiment of the present invention discloses a whole-house intelligent light adjustment method for intelligent light adjustment, and the intelligent light performs light adjustment according to a dimming strategy. The method includes obtaining a set reference light-off time T of the intelligent light; wherein the reference light-off time is a preset time interval between the last light-off time and the next light-on time; obtaining the current light-off time T1 of the intelligent light, and comparing the current light-off time T1 with the reference light-off time T: if , then the next time the smart light is turned on is based on the first light parameter; wherein the first light parameter is the light parameter of the smart light when it was turned off last time; if , the next time the smart light is turned on is executed according to the second lighting parameter; wherein the second lighting parameter is the lighting parameter of the smart light when it was turned on at the same time point last time; wherein the lighting parameter includes a brightness parameter and a color temperature parameter.

[0051] The whole-house intelligent lighting adjustment method described in the present invention, if the current lights-off time T1 is greater than the reference lights-off time T, the lighting parameters of the smart light in the previous lighting-on state at the same time point are used as the initial dimming parameters; if the current lights-off time T1 is less than or equal to the reference lights-off time T, the lighting parameters of the smart light when the lights were previously turned off are used as the initial dimming parameters, so as to dynamically adjust the initial dimming value according to the actual usage of the user, thereby significantly reducing the dimming time to dim to the target light and accelerating the dimming response speed.

[0052] In specific application scenarios, the smart light memorizes or stores a target dimming strategy. After turning on the light, the smart light is controlled to gradually dim to the target value (that is, the light with the best user adaptability or comfort) according to the target dimming strategy. Usually, the target dimming strategy includes an adjustment curve set according to the dimming initial value and the dimming target value and the amplitude of each adjustment (that is, the adjustment step). In the prior art, the smart light memorizes or stores a reset dimming parameter when it leaves the factory, and the reset dimming parameter is configured as the dimming initial value when the smart light is turned on each time. Although the factory-set reset dimming parameters have been debugged to a certain extent, they can produce a satisfactory dimming effect for most users, there are still significant problems: the user's lighting needs will change under the influence of various environmental factors such as different time periods and weather changes. For example, in order to facilitate the use of most users, the factory-set reset dimming parameters are usually set to the lowest brightness and color temperature. Except for turning on the light at noon on a sunny day, the adjustment time required to turn on the light in other time periods to achieve the user's optimal brightness and optimal color temperature requirements is relatively long, that is, to achieve the light that the user is most satisfied with, a longer dimming time is required, and the dimming response speed is slow.

[0053] The whole-house intelligent lighting adjustment method disclosed in an embodiment of the present invention, if the current light-off time T1 is greater than the reference light-off time T, the lighting parameters of the smart light in the previous light-on state at the same time point are used as the initial dimming parameters; if the current light-off time T1 is less than or equal to the reference light-off time T, the lighting parameters of the smart light when it was turned off last time are used as the initial dimming parameters. In specific application scenarios, the reference lights-off time T is pre-set according to actual needs. For example, the reference lights-off time is set to 2 hours. When the lights-off time is within 2 hours, the lighting parameters at the last time the lights were turned off are used as the initial dimming parameters when the lights are turned on next time; for example, if the lights are turned off at 7:20 in the morning and turned on before 9:20 in the morning of the same day, the lighting parameters at 7:20 are used as the initial dimming parameters; if the lights are turned on for more than 2 hours, the lighting parameters of the last time the lights were turned on at the same time are used as the initial dimming parameters when the lights are turned on next time; for example, if the lights are turned off at 7:20 in the morning on November 2, 2024, and turned on at 14:20 on November 2, 2024, the lighting parameters at 14:20 on November 1, 2024 are used as the initial dimming parameters. Of course, if the lights are in the off state at 14:20 on November 1, 2024, the search will continue until the lighting parameters of the lights in the on state at 14:20 on the most recent day are used as the initial dimming parameters. In this way, the initial dimming parameters obtained are closest to the target optimal light, thereby significantly reducing the dimming time to the target light and accelerating the dimming response speed.

[0054] Furthermore, after the smart lamp executes the first lighting parameter or the second lighting parameter to turn on the lamp, it also includes executing dimming according to a dimming strategy; the dimming strategy is determined according to a target brightness value and a target color temperature value of a user of the smart lamp.

[0055] Specifically, determining the dimming strategy includes obtaining environmental characteristic parameters of the installation area where the smart lamp is located; wherein the environmental characteristic parameters include ambient light brightness value and ambient light color temperature value; determining a brightness adjustment strategy based on the ambient light brightness value and the target brightness value; determining a color temperature adjustment strategy based on the ambient light color temperature value and the target color temperature value; determining the dimming strategy based on the brightness adjustment strategy and the color temperature adjustment strategy.

[0056] Among them, the brightness adjustment strategy is determined according to the ambient light brightness value and the target brightness value, including applying the ambient light brightness value and the target brightness value as PID control parameters, iteratively calculating all brightness values ​​of the smart lamp within the control cycle, and determining the brightness adjustment strategy according to all brightness values ​​of the smart lamp within the control cycle.

[0057] A color temperature adjustment strategy is determined according to the ambient light color temperature value and the target color temperature value, including applying the ambient light color temperature value and the target color temperature value as PID control parameters, iteratively calculating all color temperature values ​​of the smart lamp within a control cycle, and determining the color temperature adjustment strategy according to all color temperature values ​​of the smart lamp within the control cycle.

[0058] By using the ambient light brightness value and target brightness value, ambient light color temperature value and target color temperature value as PID (proportional-integral-differential) control parameters, the smart light control system can accurately calculate the brightness and color temperature values ​​within each control cycle, thereby achieving precise control of the smart light and ensuring that the final lighting effect is very close to the target value set by the user. At the same time, the smart light is allowed to dynamically adjust the brightness and color temperature according to the changes in the actual ambient light, which means that in different time periods or environmental conditions (such as day and night, sunny or cloudy), the smart light can optimize its lighting effect so that the user always feels the best lighting environment. Among them, PID control has good stability and robustness, and can effectively cope with various interferences and uncertainties. Even in the case of large changes in ambient light or other external interferences, the smart light can still maintain stable performance to ensure that the lighting effect is not affected.

[0059] In the traditional use of smart lights, users are allowed to set target parameters in a personalized way, such as target brightness value and target color temperature value. However, users do not have a clear understanding of the specific values ​​of brightness value and color temperature value and the optimal lighting environment that suits them. In other words, users do not know what the most suitable brightness value and color temperature value are. Therefore, even if users are allowed to set target parameters in a personalized way, it is difficult to achieve the most ideal lighting effect.

[0060] To solve the above problems, refer to Figure 2 As shown, the embodiment of the present invention further includes that the target brightness value includes a reference target brightness value; the target color temperature value includes a reference target color temperature value; wherein the reference target brightness value and the reference target color temperature value are pre-set when the smart lamp leaves the factory, and are used for fine-tuning with the reference target brightness value and the reference target color temperature value as initial parameters during the first use until the target brightness value and the target color temperature value that meet the optimal lighting environment are obtained; thereby, it is convenient for users to quickly set the optimal target dimming parameters.

[0061] The reference target brightness value and the reference target color temperature value are determined according to the following method:

[0062] Step S100, obtaining user characteristic information of the user of the smart light;

[0063] In specific application scenarios, user characteristic information includes user age, health status, house structure, family members, etc. The collector is configured on the smart light and obtained through user input during initial use.

[0064] Step S200, obtaining a dimming parameter range for dimming control of the smart lamp, and arbitrarily selecting a first dimming parameter within the dimming parameter range;

[0065] In a specific application scenario, a dimming parameter range is obtained according to the factory performance of the smart lamp, where the dimming parameter range includes upper and lower limits of brightness adjustment and upper and lower limits of color temperature adjustment; a first dimming parameter is arbitrarily selected within the dimming parameter range, where the first dimming parameter emphasizes arbitrariness and randomness.

[0066] Step S300, under the environmental characteristic parameters, based on the first dimming parameter, the dimming prediction of the smart lamp is performed to obtain a predicted brightness parameter and a predicted color temperature parameter; and dimming control analysis is performed on the predicted brightness parameter and the predicted color temperature parameter according to the first dimming parameter to obtain a control delay parameter;

[0067] In a specific application scenario, the environmental characteristic parameters include the ambient light brightness value and the ambient light color temperature value; obtaining the predicted brightness parameter and the predicted color temperature parameter includes obtaining the historical dimming data of the smart lamp of the same model; extracting a sample dimming parameter set, a sample environmental characteristic parameter set, a sample brightness parameter set, and a sample color temperature parameter set from the historical dimming data; constructing a neural network model, and using the sample dimming parameter set and the sample environmental characteristic parameter set as input, and using the sample brightness parameter set and the sample color temperature parameter set as output to train the neural network model to obtain a dimming predictor; inputting the first dimming parameter and the environmental characteristic parameter into the dimming predictor to obtain the predicted brightness parameter and the predicted color temperature parameter. Through historical dimming data and environmental characteristics, smart lamps can tap into user preferences and habits and provide personalized lighting settings; deep learning methods fully consider the unique needs of users and increase comfort in use.

[0068] Obtaining the control delay parameter includes obtaining the historical dimming data of the smart lamp of the same model; extracting a sample dimming parameter set and a sample control delay parameter set from the historical dimming data; constructing a network analysis model, and using the sample dimming parameter set as input and the sample control delay parameter set as output to train the network analysis model to obtain a dimming control analyzer; inputting the first dimming parameter into the dimming control analyzer to obtain the control delay parameter. By analyzing the historical dimming data and the control delay parameter, the smart lamp can better understand the delay characteristics of its control system; by accurately predicting the delay, the smart lamp can react faster when adjusting the brightness and color temperature, thereby improving the overall control response capability. On the other hand, when adjusting the light, the user no longer needs to consider the delay effect of the dimming command too much, reducing the difficulty of the user's operation.

[0069] Step S400, performing analog dimming control based on the first dimming parameter under the environmental characteristic parameter, and obtaining an analog brightness parameter and an analog color temperature parameter after correcting the analog dimming control according to the control delay parameter;

[0070] In specific application scenarios, the dimming process of smart lights is simulated through simulation software, in which environmental characteristic parameters are taken into account during the simulation. During the simulation process, the changes in simulated brightness and simulated color temperature are monitored in real time. The control time is set and recorded during the simulation process, and the control time is corrected according to the control delay parameter. When the control time reaches the set corrected control time, the simulation control is stopped to obtain the simulated brightness parameter and simulated color temperature parameter. The simulation control time is corrected in combination with the control delay parameter, so that the final simulated brightness and simulated color temperature are closer to the actual needs of users, and the accuracy of the control effect is improved.

[0071] Step S500, analyzing and obtaining a first comfort level of the first dimming parameter according to the simulated brightness parameter, the simulated color temperature parameter and the user characteristic information;

[0072] In a specific application scenario, a sample brightness parameter set, a sample simulated color temperature parameter set, a sample user characteristic information set and a sample comfort set are obtained; a comfort analyzer is constructed using the sample brightness parameter set, the sample simulated color temperature parameter set and the sample user characteristic information set as input data and the sample comfort levels as output data; the simulated brightness parameters, simulated color temperature parameters and user characteristic information are input into the comfort analyzer to obtain a first comfort level.

[0073] Step S600: Continue to optimize the dimming parameters within the dimming parameter range according to the first comfort level to obtain optimal dimming parameters, and the brightness value and color temperature value corresponding to the optimal dimming parameters are configured as the reference target brightness value and the reference target color temperature value.

[0074] In a specific application scenario, a second dimming parameter is arbitrarily selected within the dimming parameter range, and a second comfort level is calculated; the second comfort level is compared with the first comfort level, and if the second comfort level is greater than the first comfort level, the second dimming parameter is used as the optimal dimming parameter; if the second comfort level is less than or equal to the first comfort level, the first dimming parameter is used as the optimal dimming parameter; and this is repeated until the iteration condition is met to obtain the optimal dimming parameter.

[0075] In the above, in the embodiment of the present invention, the brightness parameter and color temperature parameter of the smart lamp under the first dimming parameter are predicted according to the historical dimming data, and the control delay is obtained by analyzing the predicted brightness parameter and the predicted color temperature parameter in combination with the historical dimming data; at the same time, the brightness parameter and color temperature parameter of the smart lamp under the first dimming parameter are simulated by means of simulation software, and the simulation control time is corrected according to the obtained control delay parameter during the simulation process. Since the control delay of the smart lamp control system has been considered, the obtained simulated brightness parameter and simulated color temperature parameter can significantly improve the accuracy; then the first comfort degree is obtained according to the high-accuracy simulated brightness parameter and simulated color temperature parameter analysis, and the second comfort degree is obtained based on the same method, and the optimal dimming parameter obtained by continuous optimization within the dimming parameter range is used as the target brightness value and the target color temperature value. By comprehensively considering the user's characteristic information, the optimal comfort degree and the control delay of the smart lamp control system, the obtained target brightness value and target color temperature value have high accuracy and reference, and can be used directly by the user. Of course, if the user fails to achieve the optimal lighting state after use, it can be corrected and fine-tuned on this basis. Embodiment 2

[0076] The embodiment of the present invention discloses a smart lamp, which can achieve the technical effect described in the above embodiment by operating and controlling the dimming of the whole-house smart lighting adjustment method in the above embodiment, and will not be repeated here.

[0077] In summary, the whole-house intelligent lighting adjustment method and smart lamp described in the present invention, if the current lights-off time T1 is greater than the reference lights-off time T, then the lighting parameters of the smart lamp in the previous lighting-on state at the same time point are used as the initial dimming parameters; if the current lights-off time T1 is less than or equal to the reference lights-off time T, then the lighting parameters of the smart lamp at the previous lights-off state are used as the initial dimming parameters, so as to dynamically adjust the initial dimming value according to the actual usage of the user, thereby significantly reducing the dimming time to the target light and speeding up the dimming response speed.

[0078] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0079] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0080] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0081] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0082] Obviously, the above embodiments are merely examples for clear explanation and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived from these are still within the protection scope of the invention.

Claims

1. A whole-house intelligent lighting adjustment method, used for intelligent lamp adjustment, wherein the intelligent lamp performs lighting adjustment according to a dimming strategy, characterized in that: The method includes, Obtaining a set reference light-off duration T of the smart light; wherein the reference light-off duration is a preset time interval between the last light-off moment and the next light-on moment; Obtain the current light-off duration T1 of the smart light, and compare the current light-off duration T1 with the reference light-off duration T: like , then the next time the smart light is turned on is executed according to the first light parameter; wherein the first light parameter is the light parameter of the smart light when it was turned off last time; like , then the smart light is turned on for the next time according to the second light parameter; wherein the second light parameter is the light parameter of the smart light when it was turned on at the same time point last time; The lighting parameters include brightness parameters and color temperature parameters.

2. The whole-house intelligent lighting adjustment method according to claim 1 is characterized in that: After the smart lamp executes the first lighting parameter or the second lighting parameter to turn on the lamp, it also includes executing dimming according to a dimming strategy; the dimming strategy is determined according to the target brightness value and target color temperature value of the user of the smart lamp.

3. The whole-house intelligent lighting adjustment method according to claim 2 is characterized in that: Determining the dimming strategy includes, Acquire environmental characteristic parameters of the installation area of ​​the smart lamp; wherein the environmental characteristic parameters include an ambient light brightness value and an ambient light color temperature value; Determining a brightness adjustment strategy according to the ambient light brightness value and the target brightness value; Determining a color temperature adjustment strategy according to the ambient light color temperature value and the target color temperature value; The dimming strategy is determined according to the brightness adjustment strategy and the color temperature adjustment strategy.

4. The whole-house intelligent lighting adjustment method according to claim 3 is characterized in that: Determine a brightness adjustment strategy according to the ambient light brightness value and the target brightness value, including applying the ambient light brightness value and the target brightness value as PID control parameters, iteratively calculating all brightness values ​​of the smart lamp within a control cycle, and determining the brightness adjustment strategy according to all brightness values ​​of the smart lamp within the control cycle.

5. The whole-house intelligent lighting adjustment method according to claim 3 is characterized in that: A color temperature adjustment strategy is determined according to the ambient light color temperature value and the target color temperature value, including applying the ambient light color temperature value and the target color temperature value as PID control parameters, iteratively calculating all color temperature values ​​of the smart lamp within a control cycle, and determining the color temperature adjustment strategy according to all color temperature values ​​of the smart lamp within the control cycle.

6. The whole-house intelligent lighting adjustment method according to any one of claims 3 to 5, characterized in that: The target brightness value includes a reference target brightness value; the target color temperature value includes a reference target color temperature value; The method for determining the reference target brightness value and the reference target color temperature value comprises the following steps: Acquire user characteristic information of the user of the smart lamp; Acquire a dimming parameter range for dimming control of the smart lamp, and arbitrarily select a first dimming parameter within the dimming parameter range; Under the environmental characteristic parameters, dimming prediction is performed on the smart lamp based on the first dimming parameter to obtain a predicted brightness parameter and a predicted color temperature parameter; dimming control analysis is performed on the predicted brightness parameter and the predicted color temperature parameter according to the first dimming parameter to obtain a control delay parameter; Under the environmental characteristic parameters, analog dimming control is performed based on the first dimming parameter, and the analog dimming control is corrected according to the control delay parameter to obtain analog brightness parameters and analog color temperature parameters; Analyze and obtain a first comfort level of the first dimming parameter according to the simulated brightness parameter, the simulated color temperature parameter and the user characteristic information; According to the first comfort level, continue to optimize the dimming parameters within the dimming parameter range to obtain optimal dimming parameters, and the brightness value and color temperature value corresponding to the optimal dimming parameters are configured as the reference target brightness value and the reference target color temperature value.

7. The whole-house intelligent lighting adjustment method according to claim 6 is characterized in that: Performing dimming prediction on the smart lamp based on the first dimming parameter to obtain a predicted brightness parameter and a predicted color temperature parameter, including: Obtain historical dimming data of the smart lamp of the same model; Extracting a sample dimming parameter set, a sample environment characteristic parameter set, a sample brightness parameter set, and a sample color temperature parameter set from the historical dimming data; Constructing a neural network model, and taking the sample dimming parameter set and the sample environment characteristic parameter set as input, and taking the sample brightness parameter set and the sample color temperature parameter set as output to train the neural network model to obtain a dimming predictor; The first dimming parameter and the environmental characteristic parameter are input into the dimming predictor to obtain the predicted brightness parameter and the predicted color temperature parameter.

8. The whole-house intelligent lighting adjustment method according to claim 6 is characterized in that: Performing dimming control analysis on the predicted brightness parameter and the predicted color temperature parameter according to the first dimming parameter to obtain a control delay parameter, including: Obtain historical dimming data of the smart lamp of the same model; Extracting a sample dimming parameter set and a sample control delay parameter set from the historical dimming data; Constructing a network analysis model, and using the sample dimming parameter set as input and the sample control delay parameter set as output to train the network analysis model to obtain a dimming control analyzer; The first dimming parameter is input into the dimming control analyzer to obtain the control delay parameter.

9. The whole-house intelligent lighting adjustment method according to claim 6 is characterized in that: According to the first comfort level, continuing to optimize the dimming parameters within the dimming parameter range to obtain optimal dimming parameters, and setting the optimal dimming parameters to the reference target brightness value and the reference target color temperature value, including: Randomly selecting a second dimming parameter within the dimming parameter range, and calculating and obtaining a second comfort level; Compare the second comfort level with the first comfort level. If the second comfort level is greater than the first comfort level, use the second dimming parameter as the optimal dimming parameter. If the second comfort level is less than or equal to the first comfort level, use the first dimming parameter as the optimal dimming parameter. Iterate in this way until the iteration condition is met to obtain the optimal dimming parameter.

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