Intelligent illumination automatic light turn-off control method based on light interference adaptive learning

Abstract

The invention relates to the technical field of intelligent lighting, in particular to an intelligent lighting automatic light turn-off control method based on light interference adaptive learning, which comprises the steps of initializing system parameters, collecting illumination data in real time, learning a light interference value, dynamically calculating a light turn-off threshold value, triggering light turn-off control and the like. By introducing a light interference adaptive learning and buffering mechanism, the stability and accuracy of the system in a complex illumination environment are remarkably improved, and misjudgment caused by illumination fluctuation or equipment interference is avoided. In addition, the system supports flexible adjustment of parameters, is suitable for various scene requirements, and achieves the purposes of energy conservation and consumption reduction by accurately controlling the lamp turning-on and turning-off time. The invention further provides a related control system, computer equipment and a storage medium.

Description

Technical Field

[0001] This invention relates to the field of intelligent lighting control technology, specifically to an intelligent lighting automatic shutdown control method based on light interference adaptive learning. Background Technology

[0002] In modern intelligent lighting systems, lighting control technology is increasingly widely used, including outdoor lighting, smart streetlights, and industrial park lighting. Traditional lighting control systems typically rely on fixed illuminance thresholds to control the switching on and off of lights. That is, lighting equipment is turned on when the ambient light intensity is below a preset threshold, and turned off when the ambient light intensity is above a preset threshold. While this method is simple and easy to implement, it has significant shortcomings in practical applications.

[0003] Because the light output of the lighting equipment itself can interfere with the light sensor, the illuminance value read by the sensor may not fully reflect the true ambient light intensity. This interference is particularly noticeable after the lights are turned on, causing the illuminance value collected by the sensor to include the light output component of the lights, leading to misjudgments. For example, after the lights are turned off, the sensor may re-trigger the lighting conditions due to rapid changes in illuminance values ​​within a short period, resulting in a "flickering" phenomenon or control confusion. In addition, natural fluctuations in ambient light, such as cloud cover blocking sunlight, can also cause fluctuations in illuminance values, further exacerbating system instability and the risk of malfunction.

[0004] Another limitation of existing technologies lies in their lack of dynamic adaptability. Traditional methods typically rely on fixed thresholds for control, failing to adjust the light-off threshold in real time according to environmental changes. This not only reduces system reliability but may also lead to increased energy consumption, contradicting the current trend of energy conservation and emission reduction. Therefore, there is an urgent need for an intelligent lighting control method that can dynamically adapt to environmental changes, suppress false judgments of light fluctuations, and is applicable to different geographical environments and luminaire types. Summary of the Invention

[0005] In view of this, the problem to be solved by the present invention is to provide an intelligent lighting automatic shutdown control method based on light interference adaptive learning. By analyzing the light change trend in real time and combining dynamic estimation of light interference value with an adaptive buffering strategy, a more reasonable shutdown threshold model is constructed, thereby achieving stable and accurate lighting control, avoiding misjudgments caused by equipment interference or light fluctuations, and improving the versatility and energy-saving effect of the system.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0007] A smart lighting automatic shut-off control method based on light interference adaptive learning includes the following steps:

[0008] S1. Initialize system parameters; wherein, the system parameters include the light-on threshold, the initial buffer value, and the factory-preset light-off threshold;

[0009] S2. Collect illumination data in real time and determine whether to trigger the lighting conditions based on the illumination intensity; if the current illumination intensity is lower than the lighting threshold, trigger the lighting equipment to turn on.

[0010] S3. After the lights are turned on, the system enters the light interference value learning stage, and extracts the light interference value by analyzing the stable trend of the illumination data;

[0011] S4. Dynamically calculate the light-off threshold based on the light interference value, and optimize the light-off conditions by combining a buffer mechanism;

[0012] S5. When the light intensity is higher than the dynamically calculated light-off threshold, the lighting equipment is triggered to turn off and re-enter the light monitoring state.

[0013] The specific process of initializing system parameters in S1 includes: setting the light-on threshold to an empirical value A, the initial buffer value to a fixed value B, and the factory-preset light-off threshold to an empirical value C; simultaneously, the system reserves a parameter adjustment interface for manual calibration based on actual scenario requirements. Optionally, S3 includes the following steps: continuously recording illumination data after the lights are turned on, and smoothing the data to eliminate short-term fluctuations; selecting the minimum illumination value during the data stabilization phase as the light interference value; comparing the light interference value with historical data, and if the deviation exceeds a preset range, recalculating and updating the light interference value.

[0014] The S4 includes the following steps: loading the light interference value and calculating the dynamic light-off threshold by combining the light-on threshold and the buffer value; if the ambient light intensity is close to the dynamic light-off threshold, extending the monitoring time to avoid malfunctions caused by light fluctuations; and updating the dynamic light-off threshold in real time to ensure that it matches the current environmental changes.

[0015] S5 includes the following steps: when the light intensity reaches the dynamic shutdown threshold, a shutdown command is triggered; after shutdown, the system re-enters the light monitoring state and updates the light interference value and dynamic shutdown threshold based on the new light data. Optionally, the light data acquisition module includes a high-sensitivity photoelectric sensor for real-time monitoring of ambient light intensity; simultaneously, the system has a built-in filtering algorithm to remove abnormal data points and improve data accuracy. Optionally, the buffering mechanism design includes: dynamically adjusting the buffer value according to the ambient light fluctuation amplitude; increasing the buffer value to enhance stability when the fluctuation amplitude is large; and decreasing the buffer value to improve response speed when the fluctuation amplitude is small.

[0016] The specific process of initializing system parameters in S1 includes:

[0017] Set the light-on threshold to empirical value A, the initial buffer value to fixed value B, and the factory-preset light-off threshold to empirical value C. The system also reserves a parameter adjustment interface for subsequent manual calibration.

[0018] S3 includes the following steps:

[0019] Continuously record the illumination data after the lights are turned on, and smooth the data to eliminate short-term fluctuations; select the minimum illumination value during the stable data period as the light interference value; compare the light interference value with historical data, and if the deviation exceeds the preset range, recalculate and update the light interference value.

[0020] S4 includes the following steps:

[0021] The system loads light interference values ​​and calculates dynamic light-off thresholds by combining them with the light-on threshold and buffer value; if the ambient light intensity is close to the dynamic light-off threshold, the monitoring time is extended; and the dynamic light-off threshold is updated in real time to match current environmental changes.

[0022] S5 includes the following steps:

[0023] When the light intensity reaches the dynamic light-off threshold, a light-off command is triggered; after the lights are turned off, the system re-enters the light monitoring state and updates the light interference value and dynamic light-off threshold according to the new light data.

[0024] The illumination data acquisition module includes a high-sensitivity photoelectric sensor for real-time monitoring of ambient light intensity, and a built-in filtering algorithm for removing abnormal data points.

[0025] The design of the buffering mechanism includes: dynamically adjusting the buffer value according to the fluctuation range of ambient light; increasing the buffer value when the fluctuation range is large, and decreasing the buffer value when the fluctuation range is small.

[0026] An intelligent lighting automatic shut-off control system based on light interference adaptive learning includes:

[0027] The system parameter initialization module is used to initialize the light-on threshold, initial buffer value, and factory-preset light-off threshold.

[0028] The illumination data acquisition module is used to collect ambient light intensity data in real time.

[0029] The light interference value learning module is used to extract stable values ​​of illumination data and calculate light interference values ​​after the lights are turned on.

[0030] The dynamic light-off threshold calculation module is used to calculate the dynamic light-off threshold by combining the light interference value, the light-on threshold, and the buffer value.

[0031] The lights-off control module is used to trigger the lighting equipment to turn off based on a dynamic lights-off threshold.

[0032] The illumination data acquisition module includes a high-sensitivity photoelectric sensor and a filtering algorithm unit, which are used to remove abnormal data points and improve data accuracy.

[0033] The light interference value learning module includes a data smoothing processing unit and a light interference value calculation unit, which are used to extract stable values ​​of illumination data and calculate light interference values.

[0034] The dynamic light-off threshold calculation module includes a buffer value adjustment unit and a dynamic threshold calculation unit, which are used to dynamically adjust the buffer value and calculate the dynamic light-off threshold according to the fluctuation range of ambient light.

[0035] A computer device includes: one or more processors; a memory; and one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the one or more processors, and the one or more application programs are configured to perform an intelligent lighting automatic shutdown control method based on light interference adaptive learning.

[0036] A computer-readable storage medium storing at least one instruction, at least one program, a code set, or an instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement an intelligent lighting automatic shut-off control method based on light interference adaptive learning.

[0037] The advantages and positive effects of this invention are:

[0038] 1. By learning light interference values ​​in real time and dynamically adjusting the light-off threshold, the accuracy and stability of the lighting control system are significantly improved, avoiding misjudgments caused by equipment light interference or light fluctuations.

[0039] 2. The introduction of a buffering mechanism effectively suppresses the impact of light fluctuations on the system, ensuring the smoothness and reliability of the light switching action and improving the user experience.

[0040] 3. The system is highly versatile and suitable for various complex lighting environments. It can flexibly adjust parameters according to different scenarios to meet the needs of different users.

[0041] 4. By precisely controlling the switching timing of lighting equipment, unnecessary energy consumption is reduced, achieving the goal of energy conservation and consumption reduction. Attached Figure Description

[0042] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0043] In the attached diagram:

[0044] Figure 1 The flowchart illustrates an intelligent lighting automatic shut-off control method based on light interference adaptive learning in one embodiment of the present invention.

[0045] Figure 2 A flowchart illustrating the S1 initialization of system parameters sub-step in one embodiment of the present invention is shown.

[0046] Figure 3 The flowchart illustrates the sub-step of S2 in one embodiment of the present invention, which involves real-time acquisition of illumination data and determination of the conditions for turning on the lights.

[0047] Figure 4 A flowchart illustrating the S3 optical interference value learning stage in one embodiment of the present invention is shown.

[0048] Figure 5 A flowchart illustrating the sub-step of S4 dynamically calculating the light-off threshold and optimizing the light-off conditions in one embodiment of the present invention is shown.

[0049] Figure 6 A schematic diagram of the structure of a computer device according to an embodiment of the present invention is shown. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] It should be noted that when a component is described as "fixed to" another component, it can be directly on the other component or may have a component in between. When a component is considered "connected to" another component, it can be directly connected to the other component or may have a component in between. When a component is considered "set on" another component, it can be directly set on the other component or may have a component in between. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0053] This invention provides an intelligent lighting automatic shut-off control method and related device based on light interference adaptive learning, the specific implementation of which is described in conjunction with the accompanying drawings. Figures 1 to 6 To provide a detailed description and facilitate understanding, the following will elaborate on each step, including system initialization, light data acquisition and processing, light interference value learning, dynamic light-off threshold calculation, and the specific implementation of light-off control. The operating principles and processes of each step will also be explained in detail in conjunction with actual application scenarios.

[0054] Firstly, as Figure 1 As shown, the core process of this invention includes five main steps:

[0055] The system consists of several steps: S1 initializing system parameters, S2 real-time acquisition of illumination data and determination of lighting conditions, S3 light interference value learning phase, S4 dynamic calculation of the lighting off threshold and optimization of lighting off conditions, and S5 triggering the lighting equipment to turn off. These steps together constitute a complete closed-loop control system capable of intelligent lighting management in complex lighting environments. In practice, the system uses a high-sensitivity photoelectric sensor to collect ambient light intensity data and employs a built-in filtering algorithm to eliminate abnormal data points, thereby ensuring the accuracy and reliability of the data. Simultaneously, the system incorporates a buffering mechanism to cope with the impact of illumination fluctuations, thereby improving the smoothness and stability of the light switching action.

[0056] Specifically, the implementation process for initializing system parameters for S1, such as... Figure 2 The operation details of this sub-step are shown in detail;

[0057] Upon system startup, key parameters need to be initialized, including the light-on threshold, initial buffer value, and factory-preset light-off threshold. The light-on threshold is set to an empirical value A, the initial buffer value is fixed at B, and the factory-preset light-off threshold is set to an empirical value C. These empirical values ​​are selected based on extensive experimental data and real-world scenario requirements, ensuring good performance in most situations. For example, in a typical indoor office environment, empirical value A is usually set to 100 lux, empirical value B to 10 lux, and empirical value C to 150 lux. Furthermore, the system provides a parameter adjustment interface, allowing users to manually calibrate these parameters according to actual usage scenarios. For instance, when applied to nighttime outdoor lighting, users can appropriately lower the light-on threshold to adapt to lower ambient brightness requirements. This flexibility makes the system widely applicable to various complex lighting environments.

[0058] After entering phase S2, the system's illumination data acquisition module begins to work, such as... Figure 3As shown, this module uses a high-sensitivity photoelectric sensor to monitor ambient light intensity in real time and transmits the collected data to the central processing unit for analysis. To eliminate the impact of short-term fluctuations on data accuracy, the system incorporates a filtering algorithm. This algorithm smooths the curve by performing a weighted average on continuously sampled data. For example, assuming the current sampling window contains the most recent 10 light intensity data points of 98 lux, 102 lux, 100 lux, 99 lux, 101 lux, 103 lux, 100 lux, 97 lux, 102 lux, and 101 lux, the effective light intensity after weighted averaging is 100.3 lux. Subsequently, the system compares this effective light intensity with the lighting threshold. If the current light intensity is lower than the lighting threshold, the circuit is triggered to turn on the lighting equipment. This real-time monitoring and rapid response mechanism ensures that the system can provide lighting services in a timely manner when the ambient brightness is insufficient, thereby improving the user experience.

[0059] After the lights are turned on, the system enters the S3 light interference value learning phase, such as... Figure 4 As shown, the goal of this stage is to extract light interference values ​​by analyzing the stable trend of illumination data. Specifically, the system continuously records illumination data after the lights are turned on and smooths this data to eliminate short-term fluctuations. For example, suppose that in the first 10 seconds after the lights are turned on, the system collects the following illumination intensity data: 100 lux, 105 lux, 102 lux, 103 lux, 101 lux, 104 lux, 102 lux, 103 lux, 101 lux, 100 lux; after performing a moving average on these data, the smoothed data sequence is: 102 lux, 102.5 lux, 102 lux, 102.3 lux, ... Next, the system selects the minimum illumination value during the data stabilization phase as the light interference value. In the example above, the data stabilization phase is from the 3rd to the 10th second, and the corresponding minimum illumination value is 101 lux. Therefore, the light interference value is determined to be 101 lux. In order to further improve the accuracy of the light interference value, the system will also compare it with historical data. If the deviation exceeds the preset range, such as ±5 lux, the light interference value will be recalculated and updated. This adaptive learning mechanism can effectively deal with the light interference problem in different environments and ensure that the system is always in the best working state.

[0060] After completing the learning of light interference values, the system enters the S4 stage of dynamically calculating the light-off threshold and optimizing the light-off conditions, such as... Figure 5As shown, at this stage, the system loads the light interference value and calculates the dynamic light-off threshold by combining the light-on threshold and the buffer value. The specific formula is as follows: Dynamic light-off threshold = Light interference value + Light-on threshold + Buffer value. For example, assuming the light interference value is 101 lux, the light-on threshold is 100 lux, and the buffer value is 10 lux, then the dynamic light-off threshold is 211 lux.

[0061] It's important to note that the buffer value is not fixed but dynamically adjusted based on fluctuations in ambient light intensity. When the fluctuation is large, the system increases the buffer value to enhance stability; when the fluctuation is small, the system decreases the buffer value to improve response speed. For example, if the fluctuation exceeds 20 lux, the buffer value may be adjusted to 15 lux; while if the fluctuation is less than 10 lux, the buffer value may be adjusted to 5 lux. Furthermore, if the ambient light intensity is close to the dynamic shutdown threshold, the system extends the monitoring time to avoid malfunctions caused by light fluctuations. For instance, when the light intensity reaches 95% of the dynamic shutdown threshold, the system will monitor for an additional 5 seconds to confirm whether the shutdown conditions are truly met. This dynamic adjustment and extended monitoring mechanism significantly improves the system's reliability and stability.

[0062] Finally, in stage S5, when the illuminance exceeds the dynamically calculated shutdown threshold, the system triggers a shutdown command and re-enters the illuminance monitoring state. Specifically, assuming the current illuminance is 215 lux and the dynamic shutdown threshold is 211 lux, the system immediately issues a shutdown signal to turn off the lighting equipment. After shutdown, the system re-enters the illuminance monitoring state and updates the light interference value and dynamic shutdown threshold based on the new illuminance data. For example, the next time the lights are turned on, the system may recalculate the light interference value to 103 lux based on the new illuminance data and adjust the dynamic shutdown threshold to 213 lux accordingly. This closed-loop control mechanism ensures that the system can continuously adapt to environmental changes, thereby maintaining efficient lighting management capabilities at all times.

[0063] In addition to the core processes described above, this invention also provides an intelligent automatic lighting shut-off control system based on adaptive learning of light interference. This system includes a system parameter initialization module, a light intensity data acquisition module, a light interference value learning module, a dynamic shut-off threshold calculation module, and a shut-off control module. These modules work collaboratively to achieve intelligent lighting control functions. For example, the system parameter initialization module is responsible for setting the lighting threshold, initial buffer value, and factory-preset shut-off threshold; the light intensity data acquisition module is responsible for collecting ambient light intensity data in real time; the light interference value learning module is responsible for extracting stable values ​​from the light intensity data and calculating the light interference value; the dynamic shut-off threshold calculation module is responsible for calculating the dynamic shut-off threshold by combining the light interference value, the lighting threshold, and the buffer value; and the shut-off control module is responsible for triggering the lighting equipment to shut down based on the dynamic shut-off threshold. The modules work closely together through efficient data communication and coordination mechanisms to ensure the stable operation of the entire system.

[0064] Furthermore, this invention also relates to a computer device and a computer-readable storage medium for executing the above-described intelligent lighting automatic shut-off control method based on adaptive learning of light interference, such as... Figure 6 As shown, the computer device includes one or more processors, memory, and one or more application programs. These application programs are stored in the memory and executed by the processor to implement all the steps of the above method. For example, the processor can complete tasks such as light data acquisition, light interference value learning, and dynamic light-off threshold calculation by calling program code in the memory. At the same time, the computer-readable storage medium stores at least one instruction, at least one program, code set, or instruction set, which are loaded and executed by the processor to implement the above method. For example, the storage medium may contain code segments for implementing filtering algorithms or logical instructions for dynamically adjusting buffer values. This hardware and software combined design not only improves the system's flexibility and scalability but also facilitates its deployment in different application scenarios.

[0065] In summary, this invention significantly improves the accuracy and stability of the lighting control system by learning light interference values ​​in real time and dynamically adjusting the light-off threshold. It avoids misjudgments caused by equipment light interference or light fluctuations. Simultaneously, the introduction of a buffering mechanism effectively suppresses the impact of light fluctuations on the system, ensuring the smoothness and reliability of light switching actions and enhancing the user experience. Furthermore, the system is highly versatile and suitable for various complex lighting environments, allowing for flexible parameter adjustments based on different scenarios to meet the needs of diverse users. By precisely controlling the switching timing of lighting equipment, unnecessary energy consumption is reduced, achieving the goal of energy saving and consumption reduction.

[0066] The embodiments of the present invention have been described in detail above, but the content described is only a preferred embodiment of the present invention and should not be considered as limiting the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of this patent.

Claims

1. A method for intelligent lighting automatic shut-off control based on light interference adaptive learning, characterized in that, Includes the following steps: S1. Initialize system parameters, wherein the system parameters include light-on threshold, initial buffer value and factory-preset light-off threshold; S2. Collect illumination data in real time and determine whether to trigger the lighting conditions based on the illumination intensity. If the current illumination intensity is lower than the lighting threshold, the lighting equipment will be turned on. S3. After the lights are turned on, the system enters the light interference value learning stage, and extracts the light interference value by analyzing the stable trend of the illumination data; S4. Dynamically calculate the light-off threshold based on the light interference value, and optimize the light-off conditions by combining a buffer mechanism; S5. When the light intensity is higher than the dynamically calculated light-off threshold, the lighting equipment is triggered to turn off and re-enter the light monitoring state.

2. The intelligent lighting automatic shut-off control method based on light interference adaptive learning according to claim 1, characterized in that, The specific process of initializing system parameters in S1 includes: Set the light-on threshold to an empirical value A, the initial buffer value to a fixed value B, and the factory-preset light-off threshold to an empirical value C. The system also reserves a parameter adjustment interface for subsequent manual calibration.

3. The intelligent lighting automatic shut-off control method based on light interference adaptive learning according to claim 1, characterized in that, S3 includes the following steps: Continuously record the illumination data after the lights are turned on, and smooth the data to eliminate short-term fluctuations; select the minimum illumination value during the stable data period as the light interference value; compare the light interference value with historical data, and if the deviation exceeds the preset range, recalculate and update the light interference value.

4. The intelligent lighting automatic shut-off control method based on light interference adaptive learning according to claim 1, characterized in that, S4 includes the following steps: The system loads light interference values ​​and calculates dynamic light-off thresholds by combining them with the light-on threshold and buffer value; if the ambient light intensity is close to the dynamic light-off threshold, the monitoring time is extended; and the dynamic light-off threshold is updated in real time to match current environmental changes.

5. The intelligent lighting automatic shut-off control method based on adaptive learning of light interference according to claim 1, characterized in that, S5 includes the following steps: When the light intensity reaches the dynamic light-off threshold, a light-off command is triggered; after the lights are turned off, the system re-enters the light monitoring state and updates the light interference value and dynamic light-off threshold according to the new light data.

6. The intelligent lighting automatic shut-off control method based on light interference adaptive learning according to claim 1, characterized in that, The illumination data acquisition module includes a high-sensitivity photoelectric sensor for real-time monitoring of ambient light intensity, and a built-in filtering algorithm for removing abnormal data points.

7. The intelligent lighting automatic shut-off control method based on light interference adaptive learning according to claim 1, characterized in that, The design of the buffering mechanism includes: dynamically adjusting the buffer value according to the fluctuation range of ambient light; increasing the buffer value when the fluctuation range is large, and decreasing the buffer value when the fluctuation range is small.

8. A smart lighting automatic shut-off control system based on light interference adaptive learning, characterized in that, include: The system parameter initialization module is used to initialize the light-on threshold, initial buffer value, and factory-preset light-off threshold. The illumination data acquisition module is used to collect ambient light intensity data in real time. The light interference value learning module is used to extract stable values ​​of illumination data and calculate light interference values ​​after the lights are turned on. The dynamic light-off threshold calculation module is used to calculate the dynamic light-off threshold by combining the light interference value, the light-on threshold, and the buffer value. The lights-off control module is used to trigger the lighting equipment to turn off based on a dynamic lights-off threshold. The illumination data acquisition module includes a high-sensitivity photoelectric sensor and a filtering algorithm unit, which are used to remove abnormal data points and improve data accuracy. The light interference value learning module includes a data smoothing processing unit and a light interference value calculation unit, which are used to extract stable values ​​of illumination data and calculate light interference values. The dynamic light-off threshold calculation module includes a buffer value adjustment unit and a dynamic threshold calculation unit, which are used to dynamically adjust the buffer value and calculate the dynamic light-off threshold according to the fluctuation range of ambient light.

9. A computer device, characterized in that, include: One or more processors; Memory; One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more applications being configured to perform the intelligent lighting automatic shut-off control method based on light interference adaptive learning according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The storage medium stores at least one instruction, at least one program, code set, or instruction set, wherein the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by a processor to implement the intelligent lighting automatic shut-off control method based on light interference adaptive learning according to any one of claims 1 to 7.

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