Adjustment control method of adaptive Internet of Things lighting system and AI control system

Abstract

The invention relates to the technical field of light adjustment and control, and discloses an adjustment and control method of a self-adaptive Internet of Things lighting system and an AI control system, environmental data and behavior data are acquired in real time through a sensing acquisition module, so that the brightness and color temperature of a lamp are adjusted to adapt to different use scenes and user requirements; the sensing processing module is used for processing the acquired environment data and behavior data; the AI decision module generates an AI control strategy according to the processed environment data and behavior data to obtain a control signal; the intelligent control module controls the lamp according to the control signal and adjusts the brightness and the color temperature of the lamp, the brightness and the color temperature of the lamp can be adjusted according to the environment state, the user mode and preference, and a more comfortable and healthy light environment is provided; and the feedback optimization module monitors the control effect, generates a feedback signal and optimizes the AI control strategy according to the feedback signal.

Description

Technical Field

[0001] The present invention relates to the technical field of lighting adjustment and control, and in particular to an adjustment and control method and an AI control system for an adaptive Internet of Things lighting system. Background Art

[0002] The research and development of adaptive IoT lighting systems currently focuses on how to improve the prediction accuracy and adaptive adjustment capabilities of lighting equipment in specific scenarios by aggregating prior adjustment events of different IoT scenarios, significantly improve lighting efficiency through adaptive adjustment, achieve energy conservation and emission reduction, and combine AI algorithms to achieve intelligent control and reduce the need for manual operation. However, most of them have not solved how to obtain and process environmental data and behavioral data in real time to generate AI control strategies, obtain control signals to control lamps, and monitor control effects to generate feedback signals to optimize AI control strategies.

[0003] For example, a Chinese patent application with publication number CN103731962A discloses an intelligent lighting system and an intelligent lighting adjustment method. The intelligent lighting system includes a control terminal, a signal receiving mechanism, a mechanical transmission mechanism, and a lighting mechanism; the control terminal signal is connected to the signal receiving mechanism, and the signal receiving mechanism is connected to the control mechanical transmission mechanism and the lighting mechanism to automatically adjust the lighting; the intelligent lighting adjustment method uses the above-mentioned intelligent lighting system to adjust the lighting by mechanical transmission. The intelligent lighting system and the intelligent lighting adjustment method can automatically adjust the lighting to a preset value to assist photography, reduce the difficulty of adjusting the lighting, and improve photography efficiency.

[0004] For example, a Chinese patent with the authorization announcement number CN108430132B discloses a lighting state adjustment controller, control system and control method. The controller includes a peak current comparator, a PWM controller, a power switch, a state detector and a state machine. The peak current comparator generates a PWM off signal according to the comparison result between the peak current sampling signal and the reference voltage. The PWM controller outputs a PWM control signal and a reference voltage under the control of the PWM off signal and the state control signal, wherein the state control signal controls the state of the PWM control signal. The state detector detects the state change of the PWM control signal or the equivalent signal of the PWM control signal, and outputs a state input signal. The state machine generates multiple states according to the state input signal, and outputs a state control signal reflecting the multiple states.

[0005] The above patents have the problem raised by this background technology: the above intelligent lighting system connects the signal receiving mechanism through the control terminal signal, and the signal receiving and transmitting mechanism connects the control mechanical transmission mechanism and the lighting mechanism to automatically adjust the lighting; the above lighting state adjustment controller generates a PWM shutdown signal according to the comparison result of the peak current sampling signal and the reference voltage through the peak current comparator, and the PWM controller outputs a PWM control signal and a reference voltage under the control of the PWM shutdown signal and the state control signal, wherein the state control signal controls the state of the PWM control signal, the state detector detects the state change of the PWM control signal or the equivalent signal of the PWM control signal, outputs a state input signal, and the state machine generates multiple states according to the state input signal, and outputs a state control signal reflecting multiple states. The above two patents do not solve the problem of how to obtain environmental data and behavior data in real time and process them to generate an AI control strategy, obtain a control signal to control the lamp, monitor the control effect and generate a feedback signal to optimize the AI ​​control strategy. To solve this problem, the present invention proposes an adjustment control method and an AI control system for an adaptive IoT lighting system. Summary of the invention

[0006] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0007] In view of the problems existing in the adjustment and control method and AI control system of the above-mentioned existing adaptive Internet of Things lighting system, the present invention is proposed.

[0008] Therefore, the object of the present invention is to provide an adjustment and control method and an AI control system for an adaptive Internet of Things lighting system.

[0009] In order to solve the above technical problems, the present invention provides an AI control system for an adaptive IoT lighting system: a sensor acquisition module, a sensor processing module, an AI decision module, an intelligent control module and a feedback optimization module;

[0010] The sensing acquisition module is used to acquire environmental data and behavioral data in real time;

[0011] The sensor processing module is used to process the acquired environmental data and behavior data;

[0012] The AI ​​decision module is used to generate an AI control strategy and obtain a control signal based on the processed environmental data and behavior data;

[0013] The intelligent control module is used to control the lamp according to the control signal and adjust the brightness and color temperature of the lamp;

[0014] The feedback optimization module is used to monitor the control effect, generate feedback signals, and optimize the AI ​​control strategy according to the feedback signals.

[0015] As a preferred solution of the AI ​​control system of the adaptive IoT lighting system of the present invention, wherein: the AI ​​control strategy includes environment adaptation logic and user adaptation logic;

[0016] The environmental adaptation logic includes calculating the comprehensive environment and judging the environmental state according to the processed environmental data, configuring the environmental base value, the environmental high value and the environmental extreme value, and if the comprehensive environment is less than or equal to the environmental base value, judging the environmental state to be state one;

[0017] If the comprehensive environment is greater than the environmental base value and the comprehensive environment is less than or equal to the environmental high value, the environmental state is determined to be state 2;

[0018] If the comprehensive environment is greater than the high value of the environment and the comprehensive environment is less than or equal to the extreme value of the environment, the environment state is determined to be state three;

[0019] If the comprehensive environment is greater than the environmental extreme value, the environmental state is determined to be state four.

[0020] As a preferred solution of the AI ​​control system of the adaptive IoT lighting system of the present invention, a control signal is obtained according to the environmental state, and the control signal includes controlling the brightness and color temperature of the lamp. The function expression of controlling the color temperature of the lamp is as follows:

[0021]

[0022] In the formula, c represents the color temperature of the lamp that needs to be adjusted according to the environmental conditions, c0 represents the color temperature of the current lamp, γ represents the environmental gain factor, s represents the comprehensive environment, e represents the natural constant, and β represents the attenuation adjustment factor.

[0023] As a preferred solution of the AI ​​control system of the adaptive IoT lighting system of the present invention, the user adaptation logic includes comprehensively judging the user mode by attention and satisfaction, configuring the attention base value, attention extreme value, satisfaction base value and satisfaction extreme value, and if the user's attention is at the attention extreme value and the user's satisfaction is at the satisfaction extreme value, the user mode is determined to be mode 1;

[0024] If the user's attention is at the extreme value and the user's satisfaction is at the base value, the user mode is determined to be mode 2;

[0025] If the user's attention is at the attention base value and the user's satisfaction is at the satisfaction extreme value, the user mode is determined to be mode three;

[0026] If the user's attention is at the attention base value and the user's satisfaction is at the satisfaction base value, the user mode is determined to be mode four.

[0027] As a preferred solution of the AI ​​control system of the adaptive IoT lighting system of the present invention, wherein: a control signal is obtained according to the user mode, and if the user mode is mode 1, the control signal is to increase the brightness and color temperature of the lamp;

[0028] If the user mode is mode 2, the control signal is to provide intelligent recommendation options for adjusting the brightness and color temperature of the lamp;

[0029] If the user mode is mode 3, the control signal is to control the brightness and color temperature of the lamp to remain unchanged;

[0030] If the user mode is mode 4, the control signal is to reduce the brightness and color temperature of the lamp.

[0031] As a preferred solution of the AI ​​control system of the adaptive IoT lighting system of the present invention, the logic of optimizing the AI ​​control strategy according to the feedback signal includes:

[0032] The brightness of the lamp is controlled by controlling the color temperature of the lamp. The new function expression for controlling the brightness of the lamp is as follows:

[0033]

[0034] Wherein, b' represents the brightness of the lamp to be adjusted according to the color temperature of the lamp, b0 represents the brightness of the current lamp, and cap represents the adjustment ratio threshold.

[0035] As a preferred solution of the AI ​​control system of the adaptive IoT lighting system of the present invention, the environmental data includes temperature, humidity and light intensity, and the behavioral data includes attention and satisfaction;

[0036] The specific steps to obtain environmental data and behavioral data in real time include:

[0037] Deploy sensor networks, obtain environmental data and behavioral data in real time through the sensor networks, dynamically adjust the data acquisition frequency according to changes in environmental data and behavioral data, configure the acquisition frequency base value and acquisition frequency extreme value, measure the changes in environmental data and behavioral data through the variance of environmental data and behavioral data, generate processing signals, and transmit the acquired environmental data and behavioral data to the sensor processing module for processing;

[0038] The function expression for dynamically adjusting the frequency of data acquisition is as follows:

[0039]

[0040] In the formula, f represents the adjusted data acquisition frequency, f min Indicates obtaining the frequency base value, f max represents the acquisition of frequency extreme value, e represents the natural constant, λ represents the speed adjustment parameter, v represents the variance of environmental data and behavioral data, and v max Represents the maximum variance of environmental and behavioral data.

[0041] The regulating and controlling method of the adaptive Internet of Things lighting system includes: S1, acquiring environmental data and behavioral data in real time;

[0042] S2, processing the acquired environmental data and behavioral data;

[0043] S3, generate AI control strategy based on the processed environmental data and behavior data to obtain control signals;

[0044] S4, controlling the lamp according to the control signal, and adjusting the brightness and color temperature of the lamp;

[0045] S5. Monitor the control effect, generate feedback signals, and optimize the AI ​​control strategy based on the feedback signals.

[0046] A computer device includes a memory for storing instructions; a processor for executing the instructions, so that the computer device executes a method for adjusting and controlling an adaptive Internet of Things lighting system.

[0047] A computer-readable storage medium stores a computer program, which, when executed, implements a method for regulating and controlling an adaptive Internet of Things lighting system.

[0048] Beneficial effects of the present invention: The present invention acquires environmental data and behavioral data in real time through the sensor acquisition module, so as to adjust the brightness and color temperature of the lamp to adapt to different usage scenarios and user needs; the sensor processing module processes the acquired environmental data and behavioral data; the AI ​​decision-making module generates an AI control strategy based on the processed environmental data and behavioral data, obtains a control signal, and generates an efficient AI control strategy based on the environmental data and behavioral data to reduce unnecessary energy consumption and achieve energy conservation and emission reduction; the intelligent control module controls the lamp according to the control signal and adjusts the brightness and color temperature of the lamp. It can adjust the brightness and color temperature of the lamp according to the environmental status, user mode and preference, and provide a more comfortable and healthy lighting environment; the feedback optimization module monitors the control effect, generates a feedback signal, and optimizes the AI ​​control strategy according to the feedback signal. Through continuous monitoring of environmental data and lamp performance, the system can monitor the control effect of the brightness and color temperature of the lamp in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0050] Figure 1 This is a system structure diagram of the AI ​​control system of the adaptive IoT lighting system of the present invention;

[0051] Figure 2 This is a flow chart of the data acquisition steps of the AI ​​control system of the adaptive IoT lighting system of the present invention;

[0052] Figure 3 It is an environmental adaptation logic diagram of the AI ​​control system of the adaptive IoT lighting system of the present invention;

[0053] Figure 4 The present invention is a method flow chart of the method for adjusting and controlling the adaptive Internet of Things lighting system. DETAILED DESCRIPTION

[0054] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0055] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention can also be implemented in other ways different from those described herein, and those skilled in the art can make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0056] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0057] Example 1

[0058] In this embodiment, a system structure diagram of the AI ​​control system of the adaptive IoT lighting system is provided, such as Figure 1 As shown, the AI ​​control system of the adaptive IoT lighting system includes a sensor acquisition module, a sensor processing module, an AI decision-making module, an intelligent control module and a feedback optimization module.

[0059] The sensor acquisition module is used to obtain environmental data and behavioral data in real time.

[0060] Environmental data includes temperature, humidity, and light intensity, and behavioral data includes attention and satisfaction.

[0061] The specific steps for obtaining environmental data and behavioral data in real time are as follows: Figure 2 As shown, including:

[0062] Deploy a sensor network, obtain environmental data and behavioral data in real time through the sensor network, dynamically adjust the data acquisition frequency according to the changes in environmental data and behavioral data, configure the acquisition frequency base value and acquisition frequency extreme value, measure the changes in environmental data and behavioral data through the variance of environmental data and behavioral data, generate processing signals, and transmit the acquired environmental data and behavioral data to the sensor processing module for processing.

[0063] The function expression for dynamically adjusting the frequency of data acquisition is as follows:

[0064]

[0065] In the formula, f represents the adjusted data acquisition frequency, f min Indicates obtaining the frequency base value, f max represents the acquisition of frequency extreme value, e represents the natural constant, λ represents the speed adjustment parameter, v represents the variance of environmental data and behavioral data, and v max Represents the maximum variance of environmental and behavioral data.

[0066] What needs to be explained is: the maximum variance v of environmental data and behavioral data max It is determined by historical data, and the variance of environmental data and behavioral data is compared with the maximum variance of environmental data and behavioral data to normalize the degree of change of environmental data and behavioral data, while the speed adjustment parameter λ is used to control the influence of normalized environmental data and behavioral data on the frequency of data acquisition.

[0067] The sensor network includes a temperature sensor, a humidity sensor, a photosensor and a camera, which respectively obtain the temperature, humidity and light intensity of the surrounding environment and the user's attention and satisfaction. The user's attention is determined by judging whether the user manually adjusts the brightness and color temperature of the lamp through the content captured by the camera. The user's satisfaction is determined by judging the user's emotional state through the content captured by the camera. The acquired environmental data and behavioral data are recorded in numbers. The acquisition frequency base value and the acquisition frequency extreme value are determined through historical data. When the variance of the environmental data and the behavioral data is large, the speed adjustment parameter is close to 0, and the data acquisition frequency is closer to the acquisition frequency extreme value. When the variance of the environmental data and the behavioral data is small, the speed adjustment parameter is close to 1, and the data acquisition frequency is closer to the acquisition frequency base value. According to the above steps, the data acquisition frequency can be increased when the environmental data and the behavioral data change drastically, and the data acquisition frequency can be reduced when the environmental data and the behavioral data change steadily, so as to balance the accuracy and system load.

[0068] The sensor processing module is used to process the acquired environmental data and behavior data.

[0069] After receiving the processing signal, the acquired environmental data and behavioral data are processed, including removing noise and erroneous data, standardizing the environmental data and behavioral data to ensure consistency, and using statistical methods to identify and eliminate outliers to improve the reliability of the environmental data and behavioral data. At the same time, key features are extracted from the environmental data and behavioral data, such as the peak, valley and average values ​​of the environmental data, and the frequency in the behavioral data. The key features in the environmental data and behavioral data are displayed in the form of charts through data visualization tools to help users intuitively understand environmental changes and user patterns.

[0070] The AI ​​decision-making module is used to generate AI control strategies and obtain control signals based on the processed environmental data and behavioral data.

[0071] AI control strategies include environment adaptation logic and user adaptation logic;

[0072] like Figure 3 As shown, the environmental adaptation logic includes calculating the comprehensive environment and judging the environmental state according to the processed environmental data, configuring the environmental base value, the environmental high value and the environmental extreme value. If the comprehensive environment is less than or equal to the environmental base value, the environmental state is determined to be state one;

[0073] If the comprehensive environment is greater than the environmental base value and the comprehensive environment is less than or equal to the environmental high value, the environmental state is determined to be state 2;

[0074] If the comprehensive environment is greater than the high value of the environment and the comprehensive environment is less than or equal to the extreme value of the environment, the environment state is determined to be state three;

[0075] If the comprehensive environment is greater than the environmental extreme value, the environmental state is determined to be state four.

[0076] The calculation formula for the comprehensive environment is as follows:

[0077] s=a1×ln(t)+a2×e h +a3×sin(l)+a4×t×ln(h)+a5;

[0078] Wherein, s represents the comprehensive environment, t represents temperature, h represents humidity, l represents light intensity, and a1 to a5 represent constant terms obtained by fitting environmental data.

[0079] It needs to be explained that standardization is performed before fitting the environmental data, and each variable is converted into a dimensionless form.

[0080] The environmental state is obtained by comparing the comprehensive environment with the environmental base value, the environmental high value and the environmental extreme value. For example, if the calculated comprehensive environment represents the season, then state one represents spring, state two represents summer, state three represents autumn, and state four represents winter. If the calculated comprehensive environment represents the weather, then state one is set to represent clear, state two represents cloudy, state three represents haze, and state four represents rainy. Corresponding to different environmental states, the lamps need to be adjusted to different color temperatures and brightness to meet the comfort needs of users in different seasons or weather.

[0081] The control signal is obtained according to the environmental state. The control signal includes the brightness and color temperature of the controlled lamp. The function expression of the color temperature of the controlled lamp is as follows:

[0082]

[0083] In the formula, c represents the color temperature of the lamp that needs to be adjusted according to the environmental conditions, c0 represents the color temperature of the current lamp, γ represents the environmental gain factor, s represents the comprehensive environment, e represents the natural constant, and β represents the attenuation adjustment factor.

[0084] It needs to be explained that the environmental gain factor γ is used to control the influence of the comprehensive environment on the color temperature of the lamp. The value range is between 0 and 1, indicating the relative size of the gain. γ of 0 means no gain, and γ of 1 means maximum gain. The attenuation adjustment factor β is used to control the rate of change of the influence of the comprehensive environment within different ranges. The value range is between -1 and 0. The smaller the β value, the faster the attenuation. When the value of the comprehensive environment is very large or very small, the adjustment effect of the color temperature of the lamp will not be too drastic, but will be manifested as a gradual and stable change.

[0085] The function expression for controlling the brightness of the lamp is as follows:

[0086] b = b0 + α × (l - b0);

[0087] Wherein, b represents the brightness of the lamp that needs to be adjusted according to the environmental conditions, b0 represents the brightness of the current lamp, and α represents the brightness adjustment factor.

[0088] It should be explained that the brightness adjustment factor α is used to control the weight of the difference between the light intensity and the brightness of the current lamp. When α=0.5, it means that the brightness of the current lamp will move closer to the middle value of the light intensity.

[0089] In specific applications, after obtaining different environmental states according to environmental data, if it is a season, then when the environmental state is in state one, that is, spring, the color temperature of the lamp is 5000K. The specific value needs to be carefully adjusted according to the actual environment and the expected atmosphere effect. Choosing the appropriate color temperature of the lamp can effectively improve the comfort and beauty of the outdoor space in spring; when the environmental state is in state two, that is, summer, the color temperature of the lamp is between 4000K and 5000K. The specific choice needs to be determined according to the actual environment and activity needs. Reasonable color temperature selection can not only provide sufficient lighting brightness, but also maintain visual comfort, adding a coolness and comfort to summer outdoor activities; when the environmental state is in state three, that is, autumn, the color temperature of the lamp is mainly concentrated between 2700K and 4000K. By choosing the appropriate color temperature, it can add warmth and comfort to autumn outdoor activities; when the environmental state is in state four, that is, winter, the color temperature of the lamp is mainly concentrated between 2700K and 4500K, which can give users a warm atmosphere.

[0090] If it is the weather, then when the environmental state is in state one, that is, sunny, the color temperature of the lamp is between 4300K ​​and 5500K, which can provide clearer and sharper lighting effects, restore the colors and details of the environment, and make the surrounding environment more clearly visible; when the environmental state is in state two, that is, cloudy, the color temperature of the lamp is between 2500K and 3500K, which can enhance the penetration of light, reduce glare, and improve visual comfort; when the environmental state is in state three, that is, haze, the color temperature of the lamp is between 3000K and 4000K, which can provide better penetration and reduce the degree of light absorption by particulate matter, thereby improving the lighting effect; when the environmental state is in state four, that is, rainy days, the color temperature of the lamp is between 2500K and 3000K, which can bring people a warm and relaxing feeling.

[0091] The user adaptation logic includes comprehensively judging the user mode through attention and satisfaction, configuring the attention base value, attention extreme value, satisfaction base value and satisfaction extreme value. If the user's attention is at the attention extreme value and the user's satisfaction is at the satisfaction extreme value, the user mode is determined to be mode 1;

[0092] If the user's attention is at the extreme value and the user's satisfaction is at the base value, the user mode is determined to be mode 2;

[0093] If the user's attention is at the attention base value and the user's satisfaction is at the satisfaction extreme value, the user mode is determined to be mode three;

[0094] If the user's attention is at the attention base value and the user's satisfaction is at the satisfaction base value, the user mode is determined to be mode four.

[0095] A control signal is obtained according to the user mode. If the user mode is mode 1, the control signal is to increase the brightness and color temperature of the lamp;

[0096] If the user mode is mode 2, the control signal is to provide intelligent recommendation options for adjusting the brightness and color temperature of the lamp;

[0097] If the user mode is mode 3, the control signal is to control the brightness and color temperature of the lamp to remain unchanged;

[0098] If the user mode is mode 4, the control signal is to reduce the brightness and color temperature of the lamp.

[0099] In specific applications, the frequency of the user manually adjusting the brightness and color temperature of the lamp is used to determine whether the user's attention is at the attention base value or the attention extreme value, and the user's satisfaction is determined by the user's emotional state. The user mode is then determined comprehensively based on the attention and satisfaction, and the corresponding control signal is obtained according to the corresponding mode. When the user is at the attention extreme value and the satisfaction extreme value at the same time, the user mode is determined to be mode one. At this time, the user frequently adjusts the brightness and color temperature of the lamp, and the user's emotional state shows satisfaction and comfort, indicating that the user may be in an office study mode that requires concentrated work or reading, and the brightness and color temperature of the lamp need to be increased; when the user is at the attention extreme value and the satisfaction base value at the same time, the user mode is determined to be mode two. At this time, the user frequently adjusts the brightness and color temperature of the lamp, but the user's emotional state If the user is dissatisfied or irritated, it means that the user may be in an environmental maladaptation mode, and it is necessary to provide a wider range of color temperature and brightness options, or to determine the user's preference settings based on historical data for recommendation; when the user is at both the attention base value and the satisfaction extreme value, the user mode is determined to be mode three. At this time, the user seldom adjusts the brightness and color temperature of the lamp, and the emotional state shows satisfaction and relaxation, which means that the user may be in leisure mode, and the current brightness and color temperature of the lamp should be kept unchanged to maintain the user's comfortable experience; when the user is at both the attention base value and the satisfaction base value, the user mode is determined to be mode four. At this time, the user seldom adjusts the brightness and color temperature of the lamp, and the emotional state shows dissatisfaction or fatigue, which means that the user may be in a fatigue mode that needs rest, and the brightness and color temperature of the lamp should be reduced to help the user relax and relieve fatigue.

[0100] At the same time, when the above user mode is in mode one or mode four, it is in special scenarios, including scenes of concentration and fatigue. At this time, the brightness and color temperature of the lamps are adjusted at the same time to adapt to the users, because the users have no time to operate and control the brightness and color temperature of the lamps. When the user mode is in mode two, the control system needs to provide a wider range of color temperature and brightness options, allowing users to independently control the brightness and color temperature of the lamps to meet their own needs.

[0101] The intelligent control module is used to control the lamps according to the control signals and adjust the brightness and color temperature of the lamps.

[0102] After receiving the control signal, the control signal is distinguished, whether it is obtained through the environmental state or through the user mode, and the relevant settings of the brightness and color temperature of the lamp included in the above-mentioned control signal are sent to the lamp, and the dimming function of the lamp is used to adjust the brightness to the required brightness, and the color temperature of the lamp is adjusted to the required color temperature value. At the same time, the user is provided with the option of independent adjustment, allowing the user to independently control the brightness and color temperature of the lamp, and let the user choose whether to adjust the brightness and color temperature of the lamp at the same time, or adjust one of the brightness and color temperature of the lamp separately.

[0103] The feedback optimization module is used to monitor the control effect, generate feedback signals, and optimize the AI ​​control strategy based on the feedback signals.

[0104] The logic for optimizing the AI ​​control strategy based on feedback signals includes:

[0105] The brightness of the lamp is controlled by controlling the color temperature of the lamp. The new function expression for controlling the brightness of the lamp is as follows:

[0106]

[0107] Wherein, b' represents the brightness of the lamp to be adjusted according to the color temperature of the lamp, and cap represents the adjustment ratio threshold.

[0108] It should be explained that the adjustment ratio threshold cap is the preset maximum adjustment ratio of the brightness, which is set to 3 here, which means that the brightness can be increased to 3 times the current brightness value at most.

[0109] Monitor the control effect and generate feedback signals. The feedback signals include good control effect and bad control effect. If the control effect is not good, it is necessary to comprehensively consider the environmental status and user mode. In the environmental status, the brightness of the lamp is adjusted by the color temperature of the lamp, so that the adjustment of the brightness of the lamp is also applicable to changes in weather or seasons, so that the change of the color temperature of the lamp can be more accurately reflected in the adjustment of the brightness of the lamp; and the optimization direction for obtaining the control signal according to the user mode is to introduce dynamic adjustment of time, allowing the control signal to be adjusted according to the user's long-term feedback and behavior pattern, and allowing the user to fine-tune the brightness and color temperature of the lamp according to personal preferences, providing more customized options, and judging the user's actual use scenario based on the user behavior captured by the camera, including work, entertainment and rest, etc., and further refining the adjustment of the brightness and color temperature of the lamp. Through the above optimization, the system can be more intelligent and meet user needs.

[0110] Example 2

[0111] In this embodiment, a method flow chart of a method for adjusting and controlling an adaptive IoT lighting system is provided, such as Figure 4 As shown, the adjustment and control method of the adaptive IoT lighting system includes:

[0112] S1. Obtain environmental data and behavioral data in real time.

[0113] S2. Process the acquired environmental data and behavioral data.

[0114] S3. Generate AI control strategy based on the processed environmental data and behavioral data to obtain control signals.

[0115] S4. Control the lamp according to the control signal and adjust the brightness and color temperature of the lamp.

[0116] S5. Monitor the control effect, generate feedback signals, and optimize the AI ​​control strategy based on the feedback signals.

[0117] For the specific content of the adjustment and control method of the adaptive IoT lighting system, please refer to the AI ​​control system of the adaptive IoT lighting system, which will not be repeated here.

[0118] Example 3

[0119] In this embodiment, a computer device is provided, including a memory and a processor, the memory is used to store instructions, and the processor is used to execute the instructions, so that the computer device executes the steps of implementing the above-mentioned adjustment and control method of the adaptive Internet of Things lighting system.

[0120] Example 4

[0121] In this embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed, the steps of the adjustment and control method of the above-mentioned adaptive Internet of Things lighting system are implemented.

[0122] The computer-readable storage medium includes: a U disk, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk or an optical disk, and other media for storing program codes.

[0123] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. AI control system for adaptive IoT lighting system, characterized by: include: Sensor acquisition module, sensor processing module, AI decision module, intelligent control module and feedback optimization module; The sensing acquisition module is used to acquire environmental data and behavioral data in real time; The sensor processing module is used to process the acquired environmental data and behavior data; The AI ​​decision module is used to generate an AI control strategy and obtain a control signal based on the processed environmental data and behavior data; The intelligent control module is used to control the lamp according to the control signal and adjust the brightness and color temperature of the lamp; The feedback optimization module is used to monitor the control effect, generate feedback signals, and optimize the AI ​​control strategy according to the feedback signals.

2. The AI ​​control system of the adaptive IoT lighting system according to claim 1, characterized in that: The AI ​​control strategy includes environment adaptation logic and user adaptation logic; The environmental adaptation logic includes calculating the comprehensive environment and judging the environmental state according to the processed environmental data, configuring the environmental base value, the environmental high value and the environmental extreme value, and if the comprehensive environment is less than or equal to the environmental base value, judging the environmental state to be state one; If the comprehensive environment is greater than the environmental base value and the comprehensive environment is less than or equal to the environmental high value, the environmental state is determined to be state 2; If the comprehensive environment is greater than the high value of the environment and the comprehensive environment is less than or equal to the extreme value of the environment, the environment state is determined to be state three; If the comprehensive environment is greater than the environmental extreme value, the environmental state is determined to be state four.

3. The AI ​​control system of the adaptive IoT lighting system as claimed in claim 2, characterized in that: A control signal is obtained according to the environmental state. The control signal includes the brightness and color temperature of the controlled lamp. The function expression of the color temperature of the controlled lamp is as follows: Where c represents the color temperature of the lamp that needs to be adjusted according to the environmental conditions, c0 represents the color temperature of the current lamp, γ represents the environmental gain factor, s represents the comprehensive environment, e represents the natural constant, and β represents the attenuation adjustment factor.

4. The AI ​​control system of the adaptive IoT lighting system as claimed in claim 3, characterized in that: The user adaptation logic includes comprehensively judging the user mode through attention and satisfaction, configuring the attention base value, attention extreme value, satisfaction base value and satisfaction extreme value, and if the user's attention is at the attention extreme value and the user's satisfaction is at the satisfaction extreme value, then the user mode is determined to be mode 1; If the user's attention is at the extreme value and the user's satisfaction is at the base value, the user mode is determined to be mode 2; If the user's attention is at the attention base value and the user's satisfaction is at the satisfaction extreme value, the user mode is determined to be mode three; If the user's attention is at the attention base value and the user's satisfaction is at the satisfaction base value, the user mode is determined to be mode four.

5. The AI ​​control system of the adaptive IoT lighting system as claimed in claim 4, characterized in that: Obtaining a control signal according to the user mode, if the user mode is mode 1, the control signal is to increase the brightness and color temperature of the lamp; If the user mode is mode 2, the control signal is to provide intelligent recommendation options for adjusting the brightness and color temperature of the lamp; If the user mode is mode 3, the control signal is to control the brightness and color temperature of the lamp to remain unchanged; If the user mode is mode 4, the control signal is to reduce the brightness and color temperature of the lamp.

6. The AI ​​control system of the adaptive IoT lighting system as claimed in claim 5, characterized in that: The logic of optimizing the AI ​​control strategy according to the feedback signal includes: The brightness of the lamp is controlled by controlling the color temperature of the lamp. The new function expression for controlling the brightness of the lamp is as follows: Wherein, b' represents the brightness of the lamp to be adjusted according to the color temperature of the lamp, b0 represents the brightness of the current lamp, and cap represents the adjustment ratio threshold.

7. The AI ​​control system of the adaptive IoT lighting system as claimed in claim 6, characterized in that: The environmental data include temperature, humidity and light intensity, and the behavioral data include attention and satisfaction; The specific steps to obtain environmental data and behavioral data in real time include: Deploy sensor networks, obtain environmental data and behavioral data in real time through the sensor networks, dynamically adjust the data acquisition frequency according to changes in environmental data and behavioral data, configure the acquisition frequency base value and acquisition frequency extreme value, measure the changes in environmental data and behavioral data through the variance of environmental data and behavioral data, generate processing signals, and transmit the acquired environmental data and behavioral data to the sensor processing module for processing; The function expression for dynamically adjusting the data acquisition frequency is as follows: In the formula, f represents the adjusted data acquisition frequency, f min Indicates obtaining the frequency base value, f max represents the acquisition of frequency extreme value, e represents the natural constant, λ represents the speed adjustment parameter, v represents the variance of environmental data and behavioral data, and v max Represents the maximum variance of environmental and behavioral data.

8. A method for regulating and controlling an adaptive IoT lighting system, implemented based on the AI ​​control system of the adaptive IoT lighting system according to any one of claims 1 to 7, characterized in that: include: S1, real-time acquisition of environmental data and behavioral data; S2, processing the acquired environmental data and behavioral data; S3, generate AI control strategy based on the processed environmental data and behavior data to obtain control signals; S4, controlling the lamp according to the control signal, and adjusting the brightness and color temperature of the lamp; S5. Monitor the control effect, generate feedback signals, and optimize the AI ​​control strategy based on the feedback signals.

9. A computer device, characterized in that: include: A memory for storing instructions; The processor is used to execute the instructions so that the computer device executes the adjustment and control method of the adaptive Internet of Things lighting system as claimed in claim 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, the adjustment and control method of the adaptive Internet of Things lighting system as claimed in claim 8 is implemented.

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