Intelligent adjustment method and system based on intelligent lamp

Abstract

The application provides a smart adjustment method and system based on a smart lamp, the method comprising: detecting indoor light brightness information; determining whether a target light emitting device exists according to the indoor light emitting device brightness; when the target light emitting device exists, determining indoor total brightness according to the outdoor environment brightness, the indoor environment brightness and the light emitting brightness corresponding to the target light emitting device; determining a to-be-adjusted area in the house according to the indoor total brightness, the outdoor environment brightness and the indoor environment brightness; generating a lamp brightness adjustment instruction according to the to-be-adjusted area and the indoor total brightness; and sending the lamp brightness adjustment instruction to a target smart lamp in the to-be-adjusted area. The application has higher accuracy and flexibility, can provide a more comfortable and energy-saving lighting environment, and improves the lighting experience of users.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of lighting systems, and in particular to an intelligent adjustment method based on intelligent lamps and a system thereof. BACKGROUND

[0002] With the continuous development of smart home technology, the role of lighting systems in family life is becoming increasingly important. Traditional lighting systems have been unable to meet the needs of modern families, and intelligent lighting systems have emerged. Intelligent lighting systems can detect indoor and outdoor light brightness through sensors and automatically adjust the brightness of lamps according to this information, thereby providing a more comfortable and energy-saving lighting environment. At the same time, the application of computer control systems is also increasingly widespread, enabling fine control of home devices.

[0003] Existing intelligent lighting systems usually use photosensitive sensors to detect indoor and outdoor light brightness. These sensors transmit the detected data to the control system, which adjusts the brightness of the lamps according to pre-set algorithms and thresholds. In addition, some high-end intelligent lighting systems can also automatically adjust the brightness of the lamps according to the habits and usage scenarios of users.

[0004] Although existing intelligent lighting systems can already achieve basic automatic adjustment functions, they still have some problems when dealing with complex lighting scenarios. First, existing systems usually only focus on indoor environmental brightness, ignoring the impact of outdoor environments on indoor light. For example, in the case of very bright outdoor light, even if the indoor light is very dark, the existing system may still adjust the brightness of the lamps to be very low, thereby affecting the user's visual experience. Second, existing systems also have problems when dealing with different types of lighting devices. For example, for devices such as televisions and projectors, existing systems usually only adjust the brightness of the lamps according to indoor environmental brightness, ignoring the brightness needs of these devices themselves. This may cause insufficient indoor light when playing video programs, affecting the viewing experience. Finally, existing systems also have certain limitations when generating brightness adjustment strategies. They usually only generate adjustment strategies according to pre-set algorithms and thresholds, without considering the specific circumstances of the specific areas to be adjusted and the target brightness. This may result in inaccurate adjustment results, affecting the user's lighting experience. SUMMARY

[0005] In view of the problems described above, the present application is proposed to provide an intelligent adjustment method based on intelligent lamps and a system thereof that overcomes the problems or at least partially solves the problems, comprising:

[0006] An intelligent adjustment method based on intelligent lamps, the method comprising:

[0007] detecting light intensity information in the house, wherein the light intensity information comprises outdoor environment brightness, indoor environment brightness, and at least one indoor light emitting device brightness;

[0008] determining whether a target light emitting device exists according to the indoor light emitting device brightness;

[0009] when the target light emitting device exists, determining indoor total brightness according to the outdoor environment brightness, the indoor environment brightness, and light emitting brightness corresponding to the target light emitting device;

[0010] determining a region to be adjusted in the house according to the indoor total brightness, the outdoor environment brightness, and the indoor environment brightness;

[0011] generating a lamp brightness adjustment instruction according to the region to be adjusted and the indoor total brightness;

[0012] sending the lamp brightness adjustment instruction to a target intelligent lamp in the region to be adjusted.

[0013] Further, the region in the house is divided into a plurality of regions, and a plurality of light intensity sensors are arranged in each region; the step of detecting light intensity information in the house, wherein the light intensity information comprises outdoor environment brightness, indoor environment brightness, and at least one indoor light emitting device brightness, comprises:

[0014] obtaining sensor information of all the light intensity sensors in each region in the house;

[0015] determining the light intensity information according to the sensor information and a preset time period.

[0016] Further, the step of determining the light intensity information according to the sensor information and a preset time period comprises:

[0017] obtaining light information collected by the sensor information;

[0018] determining a light information type according to the light information and a preset light analysis model, wherein the light information type comprises natural light and device light;

[0019] determining light intensity levels of the device light according to the device light and the preset light analysis model, wherein the light intensity levels comprise high brightness, medium brightness, and low brightness;

[0020] determining the light intensity information according to the device light with the high brightness and the medium brightness and the natural light.

[0021] Further, the step of determining whether the target light emitting device exists according to the indoor light emitting device brightness includes:

[0022] The indoor light emitting device brightness is subjected to ambient light correction processing to generate target indoor light emitting device brightness information;

[0023] The target light emitting device is determined to exist according to the target indoor light emitting device brightness information and a preset brightness threshold.

[0024] Further, the step of subjecting the indoor light emitting device brightness to ambient light correction processing to generate target indoor light emitting device brightness information includes:

[0025] The indoor light emitting device brightness is subjected to wavelet transform processing to generate a plurality of frequency bands; wherein the decomposition layers in each frequency band include at least four layers, and the wavelet basis function of each layer is dbN;

[0026] The plurality of frequency bands are subjected to filtering processing to generate correction light information;

[0027] The feature information is determined according to the correction light information, wherein the feature information includes intensity feature, frequency feature, direction feature, and color feature;

[0028] The target indoor light emitting device is determined in the correction light information according to the intensity feature, the frequency feature, the direction feature, the color feature, and a preset light information recognition model;

[0029] The target indoor light emitting device brightness information is generated according to the target indoor light emitting device.

[0030] Further, the step of determining the to-be-adjusted area in the house according to the indoor total brightness, the outdoor environment brightness, and the indoor environment brightness includes:

[0031] The initial adjustment area is obtained by vector machine processing according to the outdoor environment brightness, the indoor environment brightness, and the indoor total brightness;

[0032] The first real-time brightness information of the initial adjustment area is obtained;

[0033] The matching degree is determined by matching processing according to the real-time brightness information and the indoor total brightness;

[0034] When the matching degree is greater than a preset difference threshold, the target matching degree of the real-time brightness information is marked as obvious difference;

[0035] The initial adjustment area corresponding to the real-time brightness information is determined to be the to-be-adjusted area according to the target matching degree.

[0036] Further, the step of generating the lamp brightness adjustment instruction according to the to-be-adjusted area and the indoor total brightness comprises:

[0037] obtaining second real-time brightness information of the to-be-adjusted area;

[0038] performing matching analysis and calculation according to the second real-time brightness information and the indoor total brightness to generate a difference between the second real-time brightness information and the indoor total brightness;

[0039] determining whether the difference is within a preset allowable range;

[0040] when the difference is not within the preset allowable range, determining that a brightness relationship between the second real-time brightness information and the indoor total brightness is mismatched;

[0041] determining a brightness adjustment strategy according to the brightness relationship and the second real-time brightness information, wherein the brightness adjustment strategy comprises adjusting power of all device light sources in the to-be-adjusted area corresponding to the second real-time brightness information, replacing light source types of all devices in the to-be-adjusted area corresponding to the second real-time brightness information, adjusting light source angles of all devices in the to-be-adjusted area corresponding to the second real-time brightness information, and prompt information for reminding a user of non-lamp light sources;

[0042] generating the lamp brightness adjustment instruction according to the brightness adjustment strategy.

[0043] The application further discloses an intelligent adjustment system based on an intelligent lamp, which comprises:

[0044] a detection module configured to detect light brightness information in a house, wherein the light brightness information comprises outdoor environment brightness, indoor environment brightness, and at least one item of indoor light-emitting device brightness;

[0045] a first determination module configured to determine whether there is a target light-emitting device according to the indoor light-emitting device brightness;

[0046] a second determination module configured to, when there is the target light-emitting device, determine indoor total brightness according to the outdoor environment brightness, the indoor environment brightness, and light-emitting brightness corresponding to the target light-emitting device;

[0047] a third determination module configured to determine a to-be-adjusted area in the house according to the indoor total brightness, the outdoor environment brightness, and the indoor environment brightness;

[0048] a generation module configured to generate a lamp brightness adjustment instruction according to the to-be-adjusted area and the indoor total brightness;

[0049] The sending module is configured to send the lamp brightness adjustment instruction to a target smart lamp in the region to be adjusted.

[0050] The application further discloses a computer device, which comprises a processor, a memory, and a computer program stored in the memory and capable of running on the processor, and the computer program implements the steps of the smart adjustment method based on the smart lamp when executed by the processor.

[0051] The application further discloses a computer readable storage medium, which stores a computer program, and the computer program implements the steps of the smart adjustment method based on the smart lamp when executed by a processor.

[0052] The application has the following advantages:

[0053] In the embodiments of the present application, the existing system in the prior art usually only focuses on the brightness of the indoor environment, ignoring the influence of the outdoor environment on the indoor light. For example, in the case of very bright outdoor light, even if the indoor light is very dark, the existing system may adjust the brightness of the lamp to a very low level, thereby affecting the user's visual experience. Secondly, the existing system also has problems in dealing with different types of light emitting devices. For example, for devices such as televisions and projectors, the existing system usually only adjusts the brightness of the lamp according to the indoor environment brightness, ignoring the brightness demand of these devices themselves. This may cause insufficient indoor light when playing video programs, affecting the viewing experience. Finally, the existing system also has certain limitations in generating brightness adjustment strategies. They usually only generate adjustment strategies according to preset algorithms and thresholds, without considering the specific circumstances of the specific adjustment area and target brightness. This may result in inaccurate adjustment results, affecting the user's lighting experience. The present application provides a solution based on an intelligent adjustment method of intelligent lamps, specifically: an intelligent adjustment method based on intelligent lamps, the method comprising: detecting the light brightness information in the house, wherein the light brightness information includes outdoor environment brightness, indoor environment brightness, and at least one indoor light emitting device brightness; determining whether there is a target light emitting device according to the indoor light emitting device brightness; when there is the target light emitting device, determining the indoor total brightness according to the outdoor environment brightness, the indoor environment brightness, and the light emitting brightness corresponding to the target light emitting device; determining the adjustment area in the house according to the indoor total brightness, the outdoor environment brightness, and the indoor environment brightness; generating a lamp brightness adjustment instruction according to the adjustment area and the indoor total brightness; and sending the lamp brightness adjustment instruction to the target intelligent lamp in the adjustment area. By determining the adjustment area in the house according to the indoor total brightness, the outdoor environment brightness, and the indoor environment brightness, and generating a lamp brightness adjustment instruction according to the adjustment area and the indoor total brightness, the present application solves the problem that the existing system in the prior art usually only focuses on the brightness of the indoor environment, ignoring the influence of the outdoor environment on the indoor light. For example, in the case of very bright outdoor light, even if the indoor light is very dark, the existing system may adjust the brightness of the lamp to a very low level, thereby affecting the user's visual experience. Secondly, the existing system also has problems in dealing with different types of light emitting devices. For example, for devices such as televisions and projectors, the existing system usually only adjusts the brightness of the lamp according to the indoor environment brightness, ignoring the brightness demand of these devices themselves. This may cause insufficient indoor light when playing video programs, affecting the viewing experience. Finally, the existing system also has certain limitations in generating brightness adjustment strategies. They usually only generate adjustment strategies according to preset algorithms and thresholds, without considering the specific circumstances of the specific adjustment area and target brightness.This can cause the adjustment result to be inaccurate, affecting the user's lighting experience, and can more accurately adjust the brightness of the smart lamp, providing a more comfortable and energy-saving lighting environment; can adjust for different types of light emitting devices, so that the smart lamp can match the light brightness of the light emitting device, thereby improving the user's viewing experience; improve the accuracy of the adjustment result; have higher accuracy and flexibility, can provide a more comfortable and energy-saving lighting environment, and improve the effect of the user's lighting experience. BRIEF DESCRIPTION OF DRAWINGS

[0054] In order to more clearly illustrate the technical solutions of the present application, the following will briefly introduce the drawings needed to be used in the description of the present application. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0055] Figure 1 is a step flow chart of a smart adjustment method based on a smart lamp provided by an embodiment of the present application;

[0056] Figure 2 is a structural block diagram of a smart adjustment system based on a smart lamp provided by an embodiment of the present application;

[0057] Figure 3 is a structural schematic diagram of a computer device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0058] In order to make the purposes, features and advantages of the present application more obvious and easy to understand, the following will further describe the present application in combination with the drawings and specific embodiments. Obviously, the described embodiments are some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0059] Referring to Figure 1 , a step flow chart of a smart adjustment method based on a smart lamp provided by an embodiment of the present application is shown;

[0060] The method comprises:

[0061] S110, detecting light brightness information in the house, wherein the light brightness information comprises outdoor environment brightness, indoor environment brightness and at least one indoor light emitting device brightness;

[0062] S120, determining whether there is a target light emitting device according to the indoor light emitting device brightness;

[0063] S130, when the target light emitting device exists, then according to the outdoor environment brightness, the indoor environment brightness and the light emitting brightness corresponding to the target light emitting device, determine the indoor total brightness;

[0064] S140, according to the indoor total brightness, the outdoor environment brightness and the indoor environment brightness, determine the to-be-adjusted area in the house;

[0065] S150, according to the to-be-adjusted area and the indoor total brightness, generate a lamp brightness adjustment instruction;

[0066] S160, send the lamp brightness adjustment instruction to the target intelligent lamp in the to-be-adjusted area.

[0067] In the embodiments of the present application, the existing system in the prior art usually only focuses on the brightness of the indoor environment, ignoring the influence of the outdoor environment on the indoor light. For example, in the case of very bright outdoor light, even if the indoor light is very dark, the existing system may adjust the brightness of the lamp to a very low level, thereby affecting the user's visual experience. Secondly, the existing system also has problems in dealing with different types of light emitting devices. For example, for devices such as televisions and projectors, the existing system usually only adjusts the brightness of the lamp according to the indoor environment brightness, ignoring the brightness requirements of these devices themselves. This may cause insufficient indoor light when playing video programs, affecting the viewing experience. Finally, the existing system also has certain limitations in generating brightness adjustment strategies. They usually only generate adjustment strategies according to preset algorithms and thresholds, without considering the specific circumstances of the specific adjustment area and target brightness. This may result in inaccurate adjustment results, affecting the user's lighting experience. The present application provides a solution based on an intelligent adjustment method of intelligent lamps, specifically: an intelligent adjustment method based on intelligent lamps, the method comprising: detecting the light brightness information in the house, wherein the light brightness information includes outdoor environment brightness, indoor environment brightness, and at least one indoor light emitting device brightness; determining whether there is a target light emitting device according to the indoor light emitting device brightness; when there is the target light emitting device, determining the indoor total brightness according to the outdoor environment brightness, the indoor environment brightness, and the light emitting brightness corresponding to the target light emitting device; determining the adjustment area in the house according to the indoor total brightness, the outdoor environment brightness, and the indoor environment brightness; generating a lamp brightness adjustment instruction according to the adjustment area and the indoor total brightness; and sending the lamp brightness adjustment instruction to the target intelligent lamp in the adjustment area. By determining the adjustment area in the house according to the indoor total brightness, the outdoor environment brightness, and the indoor environment brightness, and generating a lamp brightness adjustment instruction according to the adjustment area and the indoor total brightness, the present application solves the problem that the existing system in the prior art usually only focuses on the brightness of the indoor environment, ignoring the influence of the outdoor environment on the indoor light. For example, in the case of very bright outdoor light, even if the indoor light is very dark, the existing system may adjust the brightness of the lamp to a very low level, thereby affecting the user's visual experience. Secondly, the existing system also has problems in dealing with different types of light emitting devices. For example, for devices such as televisions and projectors, the existing system usually only adjusts the brightness of the lamp according to the indoor environment brightness, ignoring the brightness requirements of these devices themselves. This may cause insufficient indoor light when playing video programs, affecting the viewing experience. Finally, the existing system also has certain limitations in generating brightness adjustment strategies. They usually only generate adjustment strategies according to preset algorithms and thresholds, without considering the specific circumstances of the specific adjustment area and target brightness.This can cause the adjustment result to be inaccurate, affecting the user's lighting experience, and can more accurately adjust the brightness of the smart lamp, providing a more comfortable and energy-saving lighting environment; can adjust for different types of light emitting devices, so that the smart lamp can match the light brightness of the light emitting device, thereby improving the user's viewing experience; improve the accuracy of the adjustment result; have higher accuracy and flexibility, can provide a more comfortable and energy-saving lighting environment, and improve the effect of the user's lighting experience.

[0068] In the following, a smart adjustment method based on a smart lamp in the present exemplary embodiment will be further described.

[0069] As described in step S110, the light brightness information in the house is detected, wherein the light brightness information includes outdoor environment brightness, indoor environment brightness, and at least one indoor light emitting device brightness.

[0070] In an embodiment of the present application, the detection of the light brightness information in the house described in step S110 can be further described in combination with the following description, which describes the specific process of the light brightness information including outdoor environment brightness, indoor environment brightness, and at least one indoor light emitting device brightness.

[0071] As described in the following steps,

[0072] S210, acquiring sensor information of all light intensity sensors in each area in the house;

[0073] S220, determining the light brightness information according to the sensor information and a preset time period.

[0074] It should be noted that the area in the house is divided into several areas, and several light intensity sensors are arranged in each area; the light intensity sensor is a brightness sensor; the preset time period is a use scenario time set by the user, i.e., the light brightness information is determined only within the set time.

[0075] As an example, the outdoor environment brightness, indoor environment brightness, and several indoor light emitting device brightnesses are obtained by sensors arranged at different positions in the house. For example, the outdoor environment brightness sensor can be arranged near the window of the house, the indoor environment brightness sensor can be arranged in the center of the house, and the indoor light emitting device brightness sensor can be arranged near each light emitting device.

[0076] In a specific implementation, the measurement range of the brightness sensor can be from 0 to 200000 lux, and the accuracy can reach ±5%.

[0077] As described in step S220, the light brightness information is determined according to the sensor information and a preset time period.

[0078] In an embodiment of the present invention, the specific process of determining the light brightness information according to the sensor information and the preset time period in step S220 may be further explained in combination with the following description.

[0079] As described in the following steps,

[0080] S310, obtaining illumination information acquired by the sensor information collection;

[0081] S320: Determine the type of illumination information according to the illumination information and a preset illumination analysis model, wherein the illumination information type includes natural light and device light;

[0082] S330, determining a brightness level of the device light according to the device light and the preset illumination analysis model, wherein the brightness level includes high brightness, medium brightness, and low brightness;

[0083] S340: Determine the light brightness information according to the device light having the high brightness and the medium brightness and the natural light.

[0084] It should be noted that high brightness includes display devices such as televisions, monitors, and projectors; stage lighting equipment such as stage lights and follow spots; and lighting equipment such as billboards and neon signs. Medium brightness includes everyday lighting equipment such as desk lamps, work lamps, and ceiling lamps; mobile devices such as laptops and tablets; and recording equipment such as cameras and camcorders. Low brightness includes small mobile devices such as mobile phones and watches; low-power devices such as e-book readers and tablets; and low-power devices such as remote controls and sensors.

[0085] As an example, the preset lighting analysis model uses a deep learning-based image recognition algorithm. The specific parameters are: a training dataset of 5,000 light source images, including 2,000 white light source images, 1,500 red light source images, 1,000 blue light source images, and 500 green light source images. The model architecture is ResNet50, and the Adam optimizer is used during training, with a learning rate set to 0.001.

[0086] In a specific implementation, the illumination information is identified and classified, and then the illumination information of the target is screened, and the illumination information that meets the requirements is used as the usable light brightness information.

[0087] As described in step S120, whether a target light-emitting device exists is determined based on the brightness of the indoor light-emitting device.

[0088] In an embodiment of the present invention, the specific process of determining whether a target light-emitting device exists according to the brightness of the indoor light-emitting device in step S120 may be further explained in combination with the following description.

[0089] As described in the following steps,

[0090] S410, performing ambient light correction processing on the luminance of the indoor light emitting devices to generate target indoor light emitting device luminance information;

[0091] S420, determining whether the target light emitting device exists according to the target indoor light emitting device luminance information and a preset luminance threshold.

[0092] It should be noted that the preset luminance threshold can be used to determine whether the luminance of the indoor light emitting devices includes the target light emitting device.

[0093] As an example, when the luminance of the light of a certain device exceeds the preset luminance threshold, it can be determined that the device is the target light emitting device.

[0094] In a specific implementation, the preset luminance threshold can be set to 100 lux, and when the luminance of the light of a certain device exceeds 100 lux, it can be determined that the device is the target light emitting device.

[0095] As described in step S420, whether the target light emitting device exists is determined according to the target indoor light emitting device luminance information and the preset luminance threshold.

[0096] In an embodiment of the present application, the specific process of determining whether the target light emitting device exists according to the target indoor light emitting device luminance information and the preset luminance threshold described in step S420 can be further described as follows.

[0097] As described in the following steps,

[0098] S510, performing wavelet transform processing on the luminance of the indoor light emitting devices to generate a plurality of frequency bands; wherein the number of decomposition layers in each frequency band includes at least four layers, and the wavelet basis function of each layer is dbN;

[0099] S520, performing filtering processing on the plurality of frequency bands to generate corrected light brightness information;

[0100] S530, determining feature information according to the corrected light brightness information, wherein the feature information includes intensity feature, frequency feature, direction feature, and color feature;

[0101] S540, determining the target indoor light emitting device in the corrected light brightness information according to the intensity feature, the frequency feature, the direction feature, the color feature, and a preset light information recognition model;

[0102] S550, generating the target indoor light emitting device luminance information according to the target indoor light emitting device.

[0103] It should be noted that the wavelet transform algorithm is used for the indoor light emitting device brightness, and specific parameters are that the decomposition layer number is 4, and the wavelet base function of each layer is dbN, N is the decomposition layer number.

[0104] As an example, through wavelet transform, the indoor light emitting device brightness is decomposed into multiple frequency bands, and filtering processing is performed respectively to remove the interference of ambient light to obtain corrected light information; various features of the light information are comprehensively utilized, such as intensity, frequency, direction, color and the like to further accurately judge the specific source of the corrected light information; the basic principle of the preset light information recognition model is to detect the brightness change in the image, and to recognize and extract the light area based on the change; the light area in the image is enhanced through a preprocessing step, such as contrast adjustment and edge detection, and the light area is recognized and extracted through a clustering algorithm and an edge detection algorithm; in another example, the preset light information recognition model can also be a convolutional neural network (CNN) deep learning model or a recurrent neural network (RNN) deep learning model.

[0105] In a specific implementation, detection and compensation of ambient light are further included, an ambient light sensor is used, and the model is TSL2561, which monitors the change of ambient light in real time. Through an adaptive algorithm, the filtering parameter or the compensation value is dynamically adjusted to adapt to different ambient light conditions. The ambient light intensity, the filtering parameter and the compensation value are adjusted by the adaptive algorithm.

[0106] As described in step S130, the to-be-adjusted area in the house is determined according to the indoor total brightness, the outdoor environment brightness and the indoor environment brightness.

[0107] In an embodiment of the present application, the specific process of determining the to-be-adjusted area in the house according to the indoor total brightness, the outdoor environment brightness and the indoor environment brightness in step S130 can be further described in combination with the following description.

[0108] As described in the following steps,

[0109] S610, vector machine processing is performed according to the outdoor environment brightness, the indoor environment brightness and the indoor total brightness to obtain an initial adjustment area;

[0110] S620, first real-time brightness information of the initial adjustment area is obtained;

[0111] S630, matching processing is performed according to the real-time brightness information and the indoor total brightness to determine a matching degree;

[0112] S640, when the matching degree is greater than a preset difference threshold, the target matching degree of the real-time brightness information is marked as obvious difference;

[0113] S650, determining, according to the target matching degree, that the initial adjustment region corresponding to the real-time brightness information is the to-be-adjusted region.

[0114] It should be noted that after obtaining the initial adjustment region, further matching analysis is required. The real-time brightness information is matched with the target brightness information to determine whether the real-time brightness meets the target brightness requirement. The matching analysis can use difference method, proportion method, fuzzy matching, etc.

[0115] It should be noted that the outdoor environment brightness, indoor environment brightness and indoor total brightness are normalized to have a value range of 0 to 1; if there are missing values or abnormal values in the three data of outdoor environment brightness, indoor environment brightness and indoor total brightness, they need to be filled or deleted respectively; after ensuring that there are no missing values or abnormal values, the three data of outdoor environment brightness, indoor environment brightness and indoor total brightness are used as features, and in an embodiment, other related features such as time and weather conditions can also be selected according to actual conditions; a vector machine model is trained using a training data set, which can be linear regression or ridge regression in an embodiment, so as to obtain the vector machine model; the performance of the model is evaluated using a validation data set combined with evaluation indicators, including mean square error or root mean square error; the trained vector machine model is used to input new outdoor environment brightness, new indoor environment brightness and new indoor total brightness to obtain the predicted indoor brightness value; the initial adjustment region is selected according to the predicted indoor brightness value, and in a specific implementation, a preset brightness threshold can be set, and the region with a predicted indoor brightness value greater than the preset brightness threshold is set as the initial adjustment region.

[0116] As an example, the difference method is used, that is, the difference between the real-time brightness information and the target brightness information is calculated, and it is determined whether the difference is within the allowed range; the installation position of the target light emitting device can be obtained by GPS positioning, and the viewing angle can be obtained by measurement, so as to determine the range of lamps and lanterns that need to be adjusted.

[0117] In a specific implementation, when the target light emitting device is a television or a projector, the to-be-adjusted region is determined according to the outdoor environment brightness, the indoor environment brightness and the indoor total brightness; the range of lamps and lanterns that need to be adjusted can be determined according to the installation position and the viewing angle of the target light emitting device, so as to determine the to-be-adjusted region.

[0118] As described in step S140, the lamp brightness adjustment instruction is generated according to the to-be-adjusted region and the indoor total brightness.

[0119] In an embodiment of the present application, the specific process of generating the lamp brightness adjustment instruction according to the to-be-adjusted region and the indoor total brightness described in step S140 can be further explained in combination with the following description.

[0120] As described in the following steps,

[0121] S710, acquiring second real-time brightness information of the to-be-adjusted area;

[0122] S720, performing matching analysis and calculation on the second real-time brightness information and the total indoor brightness to generate a difference between the second real-time brightness information and the total indoor brightness;

[0123] S730, determining whether the difference is within a preset allowable range;

[0124] S740, when the difference is not within the preset allowable range, determining that the brightness relationship between the second real-time brightness information and the total indoor brightness is not matched;

[0125] S750, determining a brightness adjustment strategy according to the brightness relationship and the second real-time brightness information, wherein the brightness adjustment strategy includes adjusting power of all device light sources in the to-be-adjusted area corresponding to the second real-time brightness information, replacing light source types of all devices in the to-be-adjusted area corresponding to the second real-time brightness information, adjusting light source angles of all devices in the to-be-adjusted area corresponding to the second real-time brightness information, and prompt information for reminding a user of non-lamp light sources;

[0126] S760, generating the lamp brightness adjustment instruction according to the brightness adjustment strategy.

[0127] It should be noted that the brightness adjustment strategy is generated according to the to-be-adjusted area and the total indoor brightness; the corresponding brightness adjustment amplitude and time can be generated according to the brightness difference between the total indoor brightness and the to-be-adjusted area. The generated brightness adjustment instruction is sent to the target smart lamp in the to-be-adjusted area; the smart lamp can automatically adjust its brightness according to the received brightness adjustment instruction to achieve the preset target brightness.

[0128] As an example, the total indoor brightness can be calculated by the outdoor environment brightness, the indoor environment brightness and the light emitting brightness corresponding to the target light emitting device, the brightness of the region to be adjusted can be obtained by sensor measurement, thereby generating the corresponding brightness adjustment amplitude and time; combined with the situation of the region to be adjusted to determine the brightness adjustment strategy, the brightness adjustment strategy includes one or more of adjusting the light source power, the light source type, the light source angle and the reminder information; then generate the brightness adjustment instruction according to the determined brightness adjustment strategy, and send the corresponding brightness adjustment instruction to the target intelligent lamp in the region to be adjusted, wherein the first adjustment instruction is sent to the target intelligent lamp; the target intelligent lamp receives the adjustment strategy through the Wi-Fi network, and automatically adjusts the brightness of itself according to the adjustment strategy; the second adjustment instruction is sent to the user's mobile terminal, which is used to prompt the user which non-lamp emitting light source still exists.

[0129] In a specific implementation, according to the difference between the real-time brightness information and the total indoor brightness, the corresponding adjustment strategy is generated; if the adjustment strategy is to adjust the power of the light source, the adjustment amplitude is 10%; then the real-time brightness information and the total indoor brightness are judged; when the real-time brightness information is lower than the total indoor brightness, the adjustment strategy can be to increase the power of the light source or turn on additional light sources; when the real-time brightness information is higher than the total indoor brightness, the adjustment strategy can be to reduce the power of the light source or turn off part of the light source; the generated adjustment strategy is sent to the corresponding control unit to control the power of the light source or other related parameters, thereby realizing the brightness adjustment of the target region; and during the adjustment process, the real-time brightness information of the target region can also be continuously monitored, and the adjustment strategy can be adjusted according to the feedback result to ensure that the brightness of the target region is stable at the set value; by comprehensively considering the outdoor environment brightness, the indoor environment brightness and the total indoor brightness, different types of light emitting devices are identified, and accurate brightness adjustment strategies are generated according to the specific situation, thereby providing a more comfortable and personalized lighting environment.

[0130] Embodiment one

[0131] Through the technical solution of the present application, the user no longer needs to manually turn off or turn on the lamp during the use of the display device such as the projector or the television, and the lamp can be automatically adjusted to match the brightness of the display device through the technical solution of the present application, so as to bring better visual effect and lighting environment.

[0132] The technical solution of the present application can be applied in various projector use scenarios such as education, entertainment, and conference. In the field of education, teachers can optimize the classroom environment by automatically adjusting the brightness of the lamps and lanterns, thereby improving the learning efficiency of students. In the field of entertainment, the audience can obtain a better viewing experience by automatically adjusting the brightness of the lamps and lanterns. In the field of conference, the speaker can ensure the clarity and readability of the speech content by automatically adjusting the brightness of the lamps and lanterns. In addition, since the technical solution can realize automatic adjustment of the brightness of the lamps and lanterns, it can also be widely applied in the fields of smart home and smart office. For example, in the smart home, users can realize automatic adjustment of the brightness of the lamps and lanterns through smart control devices, thereby improving the convenience and comfort of family life. In the smart office, employees can realize automatic adjustment of the brightness of the lamps and lanterns through smart control devices, thereby improving work efficiency and comfort.

[0133] The control opening and control closing of the smart lamps and lanterns are realized through the smart control chip. The user can input his / her preferences such as brightness level, color, etc. through the remote controller or other control devices, and the smart control chip can adjust the brightness of the lamps and lanterns according to the lamp brightness adjustment instruction. The lamp brightness adjustment instruction can be sent to the remote controller of the smart lamps and lanterns, and the remote control of the smart lamps and lanterns is realized through the remote controller. The smart lamps and lanterns can also be remotely controlled by the mobile phone, tablet computer or other mobile devices to open and close, and to adjust the brightness. The smart lamps and lanterns include smart LED bulbs, smart lamp strips, smart switches and smart table lamps. When receiving the lamp brightness adjustment instruction, the smart control chip adjusts the brightness of the smart lamps and lanterns in combination with the current brightness of the corresponding smart lamps and lanterns and the target brightness in the lamp brightness adjustment instruction. For example, if the current brightness is greater than the target brightness, the current brightness of the smart lamps and lanterns is lowered. Or if the current brightness is lower than the target brightness, whether to make an adjustment is determined in combination with the ambient brightness of the smart lamps and lanterns. For example, if the current brightness of the smart lamps and lanterns is consistent with the ambient brightness, no adjustment is needed. If the current brightness of the smart lamps and lanterns is obviously conspicuous compared with the ambient brightness, the current brightness of the smart lamps and lanterns is lowered. The present application can also adjust the brightness of other light emitting devices such as displays, computer tablets, mobile phones and other mobile devices. The corresponding lamp brightness adjustment instruction is sent to the mobile device end, and the brightness of the light emitting devices in the smart home field is adjusted through the mobile device end.

[0134] For the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts are referred to the part of the method embodiment.

[0135] Reference Figure 2 , a structural block diagram of a smart adjustment system based on smart lamps and lanterns provided by an embodiment of the present application is shown;

[0136] An intelligent adjustment system based on intelligent lamps, the system comprising:

[0137] A detection module 210 is configured to detect light intensity information in a house, wherein the light intensity information comprises outdoor environment brightness, indoor environment brightness, and at least one indoor light emitting device brightness;

[0138] A first determination module 220 is configured to determine whether there is a target light emitting device according to the indoor light emitting device brightness;

[0139] A second determination module 230 is configured to determine indoor total brightness according to the outdoor environment brightness, the indoor environment brightness, and the light emitting brightness corresponding to the target light emitting device when the target light emitting device exists;

[0140] A third determination module 240 is configured to determine a region to be adjusted in the house according to the indoor total brightness, the outdoor environment brightness, and the indoor environment brightness;

[0141] A generation module 250 is configured to generate a lamp brightness adjustment instruction according to the region to be adjusted and the indoor total brightness;

[0142] A sending module 260 is configured to send the lamp brightness adjustment instruction to a target intelligent lamp in the region to be adjusted.

[0143] In an embodiment of the present application, the detection module 210 comprises:

[0144] A first acquisition sub-module is configured to acquire sensor information of all light intensity sensors in each region in the house;

[0145] A first determination sub-module is configured to determine the light intensity information according to the sensor information and a preset time period.

[0146] In an embodiment of the present application, the first determination sub-module comprises:

[0147] A first acquisition unit is configured to acquire light information collected by the sensor information;

[0148] A first determination unit is configured to determine a light information type according to the light information and a preset light analysis model, wherein the light information type comprises natural light and device light;

[0149] A second determination unit is configured to determine a light intensity level of the device light according to the device light and the preset light analysis model, wherein the light intensity level comprises high brightness, medium brightness, and low brightness;

[0150] The third determining unit is configured to determine the light intensity information according to the device light with the high intensity and the medium intensity and the natural light.

[0151] In an embodiment of the present application, the first determining module 220 comprises:

[0152] The first generating submodule is configured to perform ambient light correction processing on the indoor light emitting device intensities to generate target indoor light emitting device intensity information.

[0153] The second determining submodule is configured to determine whether the target light emitting device exists according to the target indoor light emitting device intensity information and a preset intensity threshold.

[0154] In an embodiment of the present application, the first generating submodule comprises:

[0155] The first generating unit is configured to perform wavelet transform processing on the indoor light emitting device intensities to generate a plurality of frequency bands, wherein the decomposition layers in each of the frequency bands comprise at least four layers, and the wavelet base function of each layer is dbN.

[0156] The second generating unit is configured to perform filtering processing on the plurality of frequency bands to generate correction light information.

[0157] The fourth determining unit is configured to determine feature information according to the correction light information, wherein the feature information comprises intensity feature, frequency feature, direction feature and color feature.

[0158] The fifth determining unit is configured to determine a target indoor light emitting device in the correction light information according to the intensity feature, the frequency feature, the direction feature, the color feature and a preset light information recognition model.

[0159] The third generating unit is configured to generate the target indoor light emitting device intensity information according to the target indoor light emitting device.

[0160] In an embodiment of the present application, the third determining module 240 comprises:

[0161] The first screening submodule is configured to perform vector machine processing on the outdoor environment intensity, the indoor environment intensity and the indoor total intensity to screen an initial adjustment region.

[0162] The second acquiring submodule is configured to acquire first real-time intensity information of the initial adjustment region.

[0163] The third determining submodule is configured to determine a matching degree by performing matching processing on the real-time intensity information and the indoor total intensity.

[0164] The first marking sub-module is configured to mark the target matching degree of the real-time brightness information as obvious difference when the matching degree is greater than the preset difference threshold.

[0165] The fourth determining sub-module is configured to determine the initial adjustment region corresponding to the real-time brightness information as the to-be-adjusted region according to the target matching degree.

[0166] In an embodiment of the present application, the generating module 250 comprises:

[0167] The third acquiring sub-module is configured to acquire second real-time brightness information of the to-be-adjusted region.

[0168] The second generating sub-module is configured to generate a difference value between the second real-time brightness information and the total indoor brightness according to matching analysis and calculation of the second real-time brightness information and the total indoor brightness.

[0169] The fifth determining sub-module is configured to determine whether the difference value is within a preset allowable range.

[0170] The sixth determining sub-module is configured to determine that the brightness relationship between the second real-time brightness information and the total indoor brightness is not matched when the difference value is not within the preset allowable range.

[0171] The third generating sub-module is configured to determine a brightness adjustment strategy according to the brightness relationship and the second real-time brightness information, wherein the brightness adjustment strategy comprises adjusting power of all device light sources in the to-be-adjusted region corresponding to the second real-time brightness information, replacing a light source type of all devices in the to-be-adjusted region corresponding to the second real-time brightness information, adjusting a light source angle of all devices in the to-be-adjusted region corresponding to the second real-time brightness information, and prompting information for reminding a user of a non-lamp light source.

[0172] The fourth generating sub-module is configured to generate the lamp brightness adjustment instruction according to the brightness adjustment strategy.

[0173] Referring to Figure 3 , a computer device of an intelligent adjustment method based on an intelligent lamp is shown, and specifically can comprise the following:

[0174] The computer device 12 is in the form of a general-purpose computing device, and components of the computer device 12 can include but are not limited to one or more processors or processing units 16, a system memory 28, and a bus 18 connecting different system components (including the system memory 28 and the processing unit 16).

[0175] Bus 18 represents one or more of several types of bus structures, including a memory bus 18 or memory controller, a peripheral bus 18, a graphics acceleration port, a processor or local bus using any of a variety of bus architectures including the Industrial Standard Architecture (ISA), Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

[0176] Computer device 12 typically includes a variety of computer system readable media. Such media can be any available media that is located either internally or externally to computer device 12, including both volatile and nonvolatile media, removable and non-removable media.

[0177] System memory 28 can include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. Computer device 12 can further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 can be provided for reading from and writing to a non-removable, non-volatile magnetic media (typically called a "hard drive"). Figure 3 Although not shown, a magnetic disk drive for reading from and writing to a removable, non-volatile magnetic media (e.g., a floppy disk), and an optical disk drive for reading from or writing to a removable, non-volatile optical disk (e.g., a CD-ROM, DVD-ROM or other optical media) can be provided. In such instances, each can be connected to bus 18 by one or more data media interfaces. The drives and their associated computer system storage media, can provide non-volatile storage of computer code in a machine readable

[0178] Program / utility 40, having a set of programs / modules 42, can be stored in, for example, memory (ROM, RAM, or the like) and implemented by computer device 12. Each of the programs / modules 42 maybe implemented in, for example, an operating system, one or more applications, other program modules 42 and program data, and each can include an implementation of a networking environment. Generally, programs / modules 42 can execute functions and / or methods of embodiments of the present application.

[0179] Computer device 12 can also communicate with one or more external devices 14 such as a keyboard, a pointing device, a display 24, a camera, etc.; can communicate with one or more devices that enable a user to interact with computer device 12; and / or can communicate with any devices (such as a network card, a modem, etc.) that enable computer device 12 to communicate with one or more other computing devices. Such communication can occur via Input / Output (I / O) interface(s) 22. Still yet, computer device 12 can communicate with one or more networks, such as a local area network (LAN), a general wide area network (WAN), and / or a public network (e.g., the Internet) via network adapter 20. As depicted, network adapter 20 communicates with the other components of computer device 12 via bus 18. It should be appreciated that although not shown, other hardware and / or software modules could be used in conjunction with computer device 12. Examples, include, but are not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems 34, etc. Figure 3

[0180] Processing unit 16 can execute instructions stored in system memory 28 to perform various functions and data processing, such as implementing a smart adjustment method based on smart lamps according to embodiments of the present application.

[0181] That is, when the above processing unit 16 executes the above program, it implements: detecting light intensity information in a house, wherein the light intensity information includes outdoor environment brightness, indoor environment brightness, and at least one indoor light emitting device brightness; determining whether there is a target light emitting device according to the indoor light emitting device brightness; when there is the target light emitting device, then determining indoor total brightness according to the outdoor environment brightness, the indoor environment brightness, and the light emitting brightness corresponding to the target light emitting device; determining a to-be-adjusted area in the house according to the indoor total brightness, the outdoor environment brightness, and the indoor environment brightness; generating a lamp brightness adjustment instruction according to the to-be-adjusted area and the indoor total brightness; and sending the lamp brightness adjustment instruction to a target smart lamp in the to-be-adjusted area.

[0182] In embodiments of the present application, the present application also provides a computer readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a smart adjustment method based on smart lamps according to all embodiments of the present application:

[0183] ​That is, the program, when executed by a processor, implements: detecting light brightness information in a house, wherein the light brightness information includes outdoor environment brightness, indoor environment brightness, and at least one indoor light emitting device brightness; determining whether a target light emitting device exists according to the indoor light emitting device brightness; when the target light emitting device exists, determining indoor total brightness according to the outdoor environment brightness, the indoor environment brightness, and light emitting brightness corresponding to the target light emitting device; determining a to-be-adjusted area in the house according to the indoor total brightness, the outdoor environment brightness, and the indoor environment brightness; generating a lamp brightness adjustment instruction according to the to-be-adjusted area and the indoor total brightness; and sending the lamp brightness adjustment instruction to a target intelligent lamp in the to-be-adjusted area.

[0184] Any combination of one or more computer readable medium can be employed. The computer readable medium can be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium include: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, the computer readable storage medium can be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0185] A computer readable signal medium can include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal can take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium can be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0186] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). The embodiments of the present application described above are illustrative examples and not limiting. Numerous modifications and adaptations thereof will be apparent to those skilled in the art without departing from the spirit and scope of the application.

[0187] Although the preferred embodiments of the application have been described, those skilled in the art will recognize that many modifications and variations of the preferred embodiments could be made without departing from the spirit or scope of the application. Accordingly, it is intended that there be included within the scope of the application, all such modifications and variations as would be apparent to those skilled in the art upon reading the foregoing disclosure. It is intended to be covered by the following claims.

[0188] Finally, it should be noted that the terms "first" and "second" and the like are used merely to distinguish one element from another, and do not necessarily indicate a physical or chronological priority of one element over another. Furthermore, the terms "comprise", "include", "contain" or "encompass", and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises, includes, contains or encompasses one list of features is not required to also include the other elements not expressly listed, or to also exclude additional elements that are inherent in such process, method, article, or apparatus. The term "comprising" includes the terms "consisting of" and "consisting essentially of".

[0189] The above provides a kind of smart adjustment method and system based on intelligent lamp based on the principle and implementation mode of the application described in detail in the application, the principle and implementation mode of the application are described in this paper by specific examples, the above description of the embodiment is only for helping to understand the method and its core idea of the application;For those skilled in the art, according to the idea of the application, there will be changes in specific implementation mode and application range, and the above description of the specification should not be understood as limiting the application.

Claims

1. A smart adjustment method based on a smart lamp, characterized in that, The method comprises: detecting light intensity information in a house, wherein the light intensity information comprises outdoor environment brightness, indoor environment brightness, and brightness of at least one indoor light emitting device; determining whether a target light emitting device exists according to the brightness of the indoor light emitting device; performing ambient light correction processing on the brightness of the indoor light emitting device to generate target indoor light emitting device brightness information; performing wavelet transform processing on the brightness of the indoor light emitting device to generate a plurality of frequency bands; wherein the number of decomposition layers in each frequency band comprises at least four layers, and the wavelet basis function of each layer is dbN; performing filtering processing on the plurality of frequency bands to generate corrected light brightness information; determining feature information according to the corrected light brightness information, wherein the feature information comprises intensity feature, frequency feature, direction feature, and color feature; determining a target indoor light emitting device in the corrected light brightness information according to the intensity feature, the frequency feature, the direction feature, the color feature, and a preset light information recognition model; generating the target indoor light emitting device brightness information according to the target indoor light emitting device; and determining whether the target light emitting device exists according to the target indoor light emitting device brightness information and a preset brightness threshold; when the target light emitting device exists, determining indoor total brightness according to the outdoor environment brightness, the indoor environment brightness, and the light emitting brightness corresponding to the target light emitting device; determining a region to be adjusted in the house according to the indoor total brightness, the outdoor environment brightness, and the indoor environment brightness; generating a lamp brightness adjustment instruction according to the region to be adjusted and the indoor total brightness; sending the lamp brightness adjustment instruction to a target intelligent lamp in the region to be adjusted.

2. The method of claim 1, wherein, The house is divided into a plurality of regions, and a plurality of light intensity sensors are arranged in each region; the step of detecting light intensity information in a house, wherein the light intensity information comprises outdoor environment brightness, indoor environment brightness, and brightness of at least one indoor light emitting device, comprises: obtaining sensor information of all light intensity sensors in each region in the house; determining the light intensity information according to the sensor information and a preset time period.

3. The method of claim 2, wherein, The step of determining the light intensity information according to the sensor information and a preset time period comprises: obtaining light information collected by the sensor information; determining a light information type according to the light information and a preset light analysis model, wherein the light information type comprises natural light and device light; determining light intensity levels of the device light according to the device light and the preset light analysis model, wherein the light intensity levels comprise high brightness, medium brightness, and low brightness; determining the light intensity information according to the device light with the high brightness and the medium brightness, and the natural light.

4. The method of claim 1, wherein, The step of determining a region to be adjusted in the house according to the indoor total brightness, the outdoor environment brightness, and the indoor environment brightness comprises: performing vector machine processing on the outdoor environment brightness, the indoor environment brightness, and the indoor total brightness to obtain an initial adjustment region; Obtaining first real-time brightness information of an initial adjustment area; Performing matching processing according to the real-time brightness information and the total indoor brightness to determine a matching degree; When the matching degree is greater than a preset difference threshold, marking that a target matching degree of the real-time brightness information is obviously different; According to the target matching degree, determining that the initial adjustment area corresponding to the real-time brightness information is the to-be-adjusted area.

5. The method of claim 1, wherein, The step of generating a lamp brightness adjustment instruction according to the to-be-adjusted area and the total indoor brightness comprises: Obtaining second real-time brightness information of the to-be-adjusted area; Performing matching analysis and calculation according to the second real-time brightness information and the total indoor brightness to generate a difference value between the second real-time brightness information and the total indoor brightness; Determining whether the difference value is within a preset allowable range; When the difference value is not within the preset allowable range, determining that a brightness relationship between the second real-time brightness information and the total indoor brightness is not matched; According to the brightness relationship and the second real-time brightness information, determining a brightness adjustment strategy, wherein the brightness adjustment strategy comprises adjusting power of all device light sources in the to-be-adjusted area corresponding to the second real-time brightness information, replacing light source types of all devices in the to-be-adjusted area corresponding to the second real-time brightness information, adjusting light source angles of all devices in the to-be-adjusted area corresponding to the second real-time brightness information, and prompt information for reminding a user of non-lamp light sources; Generating the lamp brightness adjustment instruction according to the brightness adjustment strategy.

6. A smart regulation system based on smart light fixtures, characterized in that, The system comprises: A detection module configured to detect light brightness information in a house, wherein the light brightness information comprises outdoor environment brightness, indoor environment brightness, and at least one indoor light emitting device brightness; A first determination module configured to determine whether there is a target light emitting device according to the indoor light emitting device brightness, perform ambient light correction processing on a plurality of the indoor light emitting device brightnesses to generate target indoor light emitting device brightness information, perform wavelet transform processing on the indoor light emitting device brightnesses to generate a plurality of frequency bands, wherein each of the frequency bands comprises at least four layers of decomposition, and each layer of wavelet base function is dbN, perform filtering processing on the plurality of frequency bands to generate corrected light brightness information, determine feature information according to the corrected light brightness information, wherein the feature information comprises intensity feature, frequency feature, direction feature, and color feature, determine a target indoor light emitting device in the corrected light brightness information according to the intensity feature, the frequency feature, the direction feature, the color feature, and a preset light information recognition model, generate the target indoor light emitting device brightness information according to the target indoor light emitting device, and determine whether there is the target light emitting device according to the target indoor light emitting device brightness information and a preset brightness threshold; A second determination module configured to, when there is the target light emitting device, determine a total indoor brightness according to the outdoor environment brightness, the indoor environment brightness, and light emitting brightness corresponding to the target light emitting device. a third determining module, configured to determine a to-be-adjusted area in the house according to the total indoor brightness, the outdoor environment brightness and the indoor environment brightness; a generating module, configured to generate a lamp brightness adjustment instruction according to the to-be-adjusted area and the total indoor brightness; a sending module, configured to send the lamp brightness adjustment instruction to a target intelligent lamp in the to-be-adjusted area.

7. A computer device, comprising: A computer program product, comprising a processor, a memory, and a computer program stored on the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, A computer program product, comprising a processor, a memory, and a computer program stored on the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the method according to any one of claims 1 to 5. A computer program product, comprising a processor, a memory, and a computer program stored on the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the method according to any one of claims 1 to 5.

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