Intelligent adjustment method and system based on intelligent lamp

Abstract

The invention provides an intelligent adjustment method and system based on an intelligent lamp. The method comprises the steps that light brightness information in a house is detected; determining whether target light-emitting equipment exists or not according to the brightness of the indoor light-emitting equipment; when the target light-emitting equipment 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 equipment; 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 adjusting instruction according to the to-be-adjusted area and the indoor total brightness; sending the lamp brightness adjusting instruction to a target intelligent lamp in the to-be-adjusted area; higher accuracy and flexibility are achieved, a more comfortable and energy-saving lighting environment can be provided, and the lighting experience of a user is improved.

Description

Technical Field

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

[0002] With the continuous development of smart home technology, the lighting system plays an increasingly important role in family life. Traditional lighting systems can no longer meet the needs of modern families, and smart lighting systems have emerged. Smart lighting systems can detect the brightness of indoor and outdoor light through sensors, and automatically adjust the brightness of lamps based on this information, thereby providing a more comfortable and energy-saving lighting environment. At the same time, the application of computer control systems is also becoming more and more widespread, which can achieve refined control of home appliances.

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

[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 the brightness of the indoor environment, while ignoring the impact of the outdoor environment on the indoor light. For example, when the outdoor light is very bright, even if the indoor light is very dim, the existing system may adjust the brightness of the lamp very low, thus affecting the user's visual experience. Secondly, existing systems also have problems when dealing with different types of light-emitting devices. For example, for devices such as televisions and projectors, existing systems usually only adjust the brightness of lamps according to the brightness of the indoor environment, while ignoring the brightness requirements of these devices themselves. This may result in insufficient indoor light when playing film and television programs, affecting the viewing experience. Finally, existing systems also have certain limitations when generating brightness adjustment strategies. They usually only generate adjustment strategies based on preset algorithms and thresholds, without considering the specific conditions of the specific area to be adjusted and the target brightness. This may lead to inaccurate adjustment results and affect the user's lighting experience. Summary of the invention

[0005] In view of the above problems, the present application is proposed to provide an intelligent adjustment method based on an intelligent lamp and a system thereof to overcome the above problems or at least partially solve the above problems, including: An intelligent adjustment method based on an intelligent lamp, the method comprising: 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 there is a target light-emitting device according to the brightness of the indoor light-emitting device; When the target light-emitting device exists, the total indoor brightness is determined according to the outdoor environment brightness, the indoor environment brightness and the light brightness corresponding to the target light-emitting device; Determining the area to be adjusted in the house according to the total indoor brightness, the outdoor environment brightness and the indoor environment brightness; Generate a lamp brightness adjustment instruction according to the area to be adjusted and the total indoor brightness; The lamp brightness adjustment instruction is sent to the target smart lamp in the area to be adjusted.

[0006] Furthermore, the area inside the house is divided into several areas, and several light intensity sensors are arranged in each area; the step of detecting the light brightness information inside the house, wherein the light brightness information includes the outdoor environment brightness, the indoor environment brightness and the brightness of at least one indoor lighting device, comprises: Acquire sensor information of all the light intensity sensors in each area of ​​the house; The light brightness information is determined according to the sensor information and a preset time period.

[0007] Furthermore, the step of determining the light brightness information based on the sensor information and a preset time period includes: Acquire illumination information acquired by the sensor information collection; Determining the type of illumination information according to the illumination information and a preset illumination analysis model, wherein the type of illumination information includes natural light and device light; Determining a light brightness level of the device light according to the device light and the preset light analysis model, wherein the light brightness level includes high brightness, medium brightness and low brightness; The light brightness information is determined according to the device light having the high brightness and the medium brightness and the natural light.

[0008] Furthermore, the step of determining whether there is a target light-emitting device according to the brightness of the indoor light-emitting device includes: Performing ambient light correction processing on the brightness of a plurality of the indoor light-emitting devices to generate brightness information of a target indoor light-emitting device; Determine whether the target light-emitting device exists according to the brightness information of the target indoor light-emitting device and a preset brightness threshold.

[0009] Furthermore, the step of performing ambient light correction processing on the brightness of a plurality of indoor light-emitting devices to generate brightness information of a target indoor light-emitting device includes: Performing wavelet transform processing on the brightness of the indoor lighting device to generate a plurality of frequency bands; wherein the number of decomposition layers in each of the frequency bands includes at least four layers, and the wavelet basis function of each layer is dbN; Performing filtering processing on a plurality of said frequency bands to generate corrected brightness information; Determining characteristic information according to the corrected light information, wherein the characteristic information includes intensity characteristics, frequency characteristics, direction characteristics and color characteristics; Determine a target indoor light-emitting device in the corrected light information according to the intensity feature, the frequency feature, the direction feature, the color feature and a preset light information recognition model; The brightness information of the target indoor light-emitting device is generated according to the target indoor light-emitting device.

[0010] Furthermore, the step of determining the area to be adjusted in the house according to the total indoor brightness, the outdoor environment brightness and the indoor environment brightness includes: Performing vector machine processing and screening according to the outdoor environment brightness, the indoor environment brightness and the indoor total brightness to obtain an initial adjustment area; Acquire first real-time brightness information of the initial adjustment area; Performing matching processing according to the real-time brightness information and the total indoor brightness to determine the matching degree; When the matching degree is greater than a preset difference threshold, the target matching degree of the real-time brightness information is marked as significantly different; The initial adjustment area corresponding to the real-time brightness information is determined as the area to be adjusted according to the target matching degree.

[0011] Furthermore, the step of generating a lamp brightness adjustment instruction according to the area to be adjusted and the total indoor brightness includes: Acquire second real-time brightness information of the area to be adjusted; Perform matching analysis and calculation based on the second real-time brightness information and the total brightness of the room to generate a difference between the second real-time brightness information and the total brightness of the room; Determining whether the difference is within a preset allowable range; 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 mismatched; Determine a brightness adjustment strategy according to the brightness relationship and the second real-time brightness information, wherein the brightness adjustment strategy includes adjusting the light source power of all devices in the area to be adjusted corresponding to the second real-time brightness information, changing the light source type of all devices in the area to be adjusted corresponding to the second real-time brightness information, adjusting the light source angle of all devices in the area to be adjusted corresponding to the second real-time brightness information, and prompt information for reminding the user that the light source is not a lamp; The lamp brightness adjustment instruction is generated according to the brightness adjustment strategy.

[0012] The present application also discloses an intelligent adjustment system based on intelligent lamps, the system comprising: A detection module, used to detect 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; A first determination module, used to determine whether there is a target light-emitting device according to the brightness of the indoor light-emitting device; A second determination module is used to determine the total indoor brightness according to the outdoor environment brightness, the indoor environment brightness and the light brightness corresponding to the target light-emitting device when the target light-emitting device exists; A third determination module is used to determine the area to be adjusted in the house according to the total indoor brightness, the outdoor environment brightness and the indoor environment brightness; A generating module, used for generating a lamp brightness adjustment instruction according to the area to be adjusted and the total indoor brightness; The sending module is used to send the lamp brightness adjustment instruction to the target smart lamp in the area to be adjusted.

[0013] The present application also discloses a computer device, including a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, the steps of the intelligent adjustment method based on the intelligent lamp are implemented as described above.

[0014] The present application also discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the intelligent adjustment method based on the intelligent lamp are implemented as described above.

[0015] This application has the following advantages: In the embodiments of the present application, compared with the existing systems in the prior art, which usually only focus on the brightness of the indoor environment, they ignore the impact of the outdoor environment on the indoor light. For example, when the outdoor light is very bright, even if the indoor light is very dim, the existing system may adjust the brightness of the lamp very low, thereby affecting the user's visual experience. Secondly, the existing system also has problems when 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 brightness of the indoor environment, while ignoring the brightness requirements of these devices themselves. This may result in insufficient indoor light when playing film and television programs, affecting the viewing experience. Finally, the existing system also has certain limitations when generating brightness adjustment strategies. They usually only generate adjustment strategies based on preset algorithms and thresholds, without considering the specific conditions of the specific area to be adjusted and the target brightness. This may lead to inaccurate adjustment results and affect the user's lighting experience. The present application provides a solution for an intelligent adjustment method based on smart lamps, specifically: an intelligent adjustment method based on smart lamps, the method comprising: detecting the light brightness information in the house, wherein the light brightness information includes the outdoor environment brightness, the indoor environment brightness and at least one indoor light-emitting device brightness; determining whether there is a target light-emitting device according to the brightness of the indoor light-emitting device; when the target light-emitting device exists, determining the total indoor brightness according to the outdoor environment brightness, the indoor environment brightness and the light brightness corresponding to the target light-emitting device; determining the area to be adjusted in the house according to the total indoor brightness, the outdoor environment brightness and the indoor environment brightness; generating a lamp brightness adjustment instruction according to the area to be adjusted and the total indoor brightness; and sending the lamp brightness adjustment instruction to the target smart lamp in the area to be adjusted. By determining the area to be adjusted in the house according to the total indoor brightness, the outdoor environment brightness and the indoor environment brightness; and generating a lamp brightness adjustment instruction according to the area to be adjusted and the total indoor brightness, the existing system usually only focuses on the brightness of the indoor environment, but ignores the impact of the outdoor environment on the indoor light. For example, when the outdoor light is very bright, even if the indoor light is very dim, the existing system may adjust the brightness of the lamps very low, thus affecting the user's visual experience. Secondly, the existing systems also have problems when dealing with different types of light-emitting devices. For example, for devices such as televisions and projectors, the existing systems usually only adjust the brightness of the lamps according to the indoor ambient brightness, while ignoring the brightness requirements of these devices themselves. This may result in insufficient indoor light when playing film and television programs, affecting the viewing experience. Finally, the existing systems also have certain limitations when generating brightness adjustment strategies. They usually only generate adjustment strategies based on preset algorithms and thresholds, without considering the specific conditions of the specific area to be adjusted and the target brightness.This may lead to inaccurate adjustment results and affect the user's lighting experience. The brightness of smart lamps can be adjusted more accurately to provide a more comfortable and energy-saving lighting environment; it can be adjusted for different types of light-emitting devices, so that smart lamps can match the brightness of the light-emitting devices, thereby enhancing the user's viewing experience; improve the accuracy of the adjustment results; with higher accuracy and flexibility, it can provide a more comfortable and energy-saving lighting environment, and enhance the user's lighting experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solution of the present application, the drawings required for use in the description of the present application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0017] Figure 1 This is a flowchart of a smart adjustment method based on a smart lamp provided in an embodiment of the present application; Figure 2 This is a structural block diagram of an intelligent adjustment system based on intelligent lamps provided in one embodiment of the present application; Figure 3 It is a structural schematic diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the objects, features and advantages of the present application more obvious and understandable, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0019] Reference Figure 1 , showing a flowchart of a smart adjustment method based on a smart lamp provided in an embodiment of the present application; The method comprises: S110, 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; S120, determining whether there is a target light-emitting device according to the brightness of the indoor light-emitting device; S130, when the target light-emitting device exists, determining the total indoor brightness according to the outdoor environment brightness, the indoor environment brightness and the light brightness corresponding to the target light-emitting device; S140, determining the area to be adjusted in the house according to the total indoor brightness, the outdoor environment brightness and the indoor environment brightness; S150, generating a lamp brightness adjustment instruction according to the area to be adjusted and the total indoor brightness; S160: Send the lamp brightness adjustment instruction to the target smart lamp in the area to be adjusted.

[0020] In the embodiments of the present application, compared with the existing systems in the prior art, which usually only focus on the brightness of the indoor environment, they ignore the impact of the outdoor environment on the indoor light. For example, when the outdoor light is very bright, even if the indoor light is very dim, the existing system may adjust the brightness of the lamp very low, thereby affecting the user's visual experience. Secondly, the existing system also has problems when 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 brightness of the indoor environment, while ignoring the brightness requirements of these devices themselves. This may result in insufficient indoor light when playing film and television programs, affecting the viewing experience. Finally, the existing system also has certain limitations when generating brightness adjustment strategies. They usually only generate adjustment strategies based on preset algorithms and thresholds, without considering the specific conditions of the specific area to be adjusted and the target brightness. This may lead to inaccurate adjustment results and affect the user's lighting experience. The present application provides a solution for an intelligent adjustment method based on smart lamps, specifically: an intelligent adjustment method based on smart lamps, the method comprising: detecting the light brightness information in the house, wherein the light brightness information includes the outdoor environment brightness, the indoor environment brightness and at least one indoor light-emitting device brightness; determining whether there is a target light-emitting device according to the brightness of the indoor light-emitting device; when the target light-emitting device exists, determining the total indoor brightness according to the outdoor environment brightness, the indoor environment brightness and the light brightness corresponding to the target light-emitting device; determining the area to be adjusted in the house according to the total indoor brightness, the outdoor environment brightness and the indoor environment brightness; generating a lamp brightness adjustment instruction according to the area to be adjusted and the total indoor brightness; and sending the lamp brightness adjustment instruction to the target smart lamp in the area to be adjusted. By determining the area to be adjusted in the house according to the total indoor brightness, the outdoor environment brightness and the indoor environment brightness; and generating a lamp brightness adjustment instruction according to the area to be adjusted and the total indoor brightness, the existing system usually only focuses on the brightness of the indoor environment, but ignores the impact of the outdoor environment on the indoor light. For example, when the outdoor light is very bright, even if the indoor light is very dim, the existing system may adjust the brightness of the lamps very low, thus affecting the user's visual experience. Secondly, the existing systems also have problems when dealing with different types of light-emitting devices. For example, for devices such as televisions and projectors, the existing systems usually only adjust the brightness of the lamps according to the indoor ambient brightness, while ignoring the brightness requirements of these devices themselves. This may result in insufficient indoor light when playing film and television programs, affecting the viewing experience. Finally, the existing systems also have certain limitations when generating brightness adjustment strategies. They usually only generate adjustment strategies based on preset algorithms and thresholds, without considering the specific conditions of the specific area to be adjusted and the target brightness.This may lead to inaccurate adjustment results and affect the user's lighting experience. The brightness of smart lamps can be adjusted more accurately to provide a more comfortable and energy-saving lighting environment; it can be adjusted for different types of light-emitting devices, so that smart lamps can match the brightness of the light-emitting devices, thereby enhancing the user's viewing experience; improve the accuracy of the adjustment results; with higher accuracy and flexibility, it can provide a more comfortable and energy-saving lighting environment, and enhance the user's lighting experience.

[0021] Next, an intelligent adjustment method based on an intelligent lamp in this exemplary embodiment will be further described.

[0022] As described in step S110, the light brightness information in the house is detected, wherein the light brightness information includes the outdoor environment brightness, the indoor environment brightness and at least one item of indoor light-emitting device brightness.

[0023] In an embodiment of the present invention, the specific process of detecting the light brightness information in the house in step S110 can be further explained in combination with the following description, wherein the light brightness information includes the outdoor environment brightness, the indoor environment brightness and the brightness of at least one indoor lighting device.

[0024] As described in the following steps, S210, obtaining sensor information of all the light intensity sensors in each area of ​​the house; S220: Determine the light brightness information according to the sensor information and a preset time period.

[0025] It should be noted that the area inside 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 the usage scenario time set in advance by the user, that is, the light brightness information is determined only within the set time.

[0026] As an example, outdoor environment brightness, indoor environment brightness, and brightness of several indoor light-emitting devices are obtained by sensors arranged at different locations of a house. For example, an outdoor environment brightness sensor may be arranged near a window of a house, an indoor environment brightness sensor may be arranged in the center of a house, and an indoor light-emitting device brightness sensor may be arranged near each light-emitting device.

[0027] In a specific implementation, the measurement range of the brightness sensor can be from 0 to 200,000 lux, and the accuracy can reach ±5%.

[0028] As described in step S220, the light brightness information is determined according to the sensor information and a preset time period.

[0029] 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 can be further explained in combination with the following description.

[0030] As described in the following steps, S310, obtaining illumination information acquired by the sensor information collection; S320, determining the type of illumination information according to the illumination information and a preset illumination analysis model, wherein the type of illumination information includes natural light and device light; S330, determining a light brightness level of the device light according to the device light and the preset light analysis model, wherein the light brightness level includes high brightness, medium brightness and low brightness; S340: Determine the light brightness information according to the device light having the high brightness and the medium brightness and the natural light.

[0031] It should be noted that high brightness includes display devices such as TVs, monitors, and projectors; stage lighting equipment such as stage lights and follow-up lights; and lighting equipment such as billboards and neon lights. Medium brightness includes daily lighting equipment such as desk lamps, work lamps, and ceiling lamps; mobile devices such as laptops and tablets; and shooting 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.

[0032] As an example, the preset illumination analysis model uses an image recognition algorithm based on deep learning. The specific parameters are that the training data set is 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 the learning rate set to 0.001.

[0033] 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.

[0034] As described in step S120, whether there is a target light-emitting device is determined according to the brightness of the indoor light-emitting device.

[0035] In an embodiment of the present invention, the specific process of determining whether there is a target light-emitting device according to the brightness of the indoor light-emitting device in step S120 can be further explained in combination with the following description.

[0036] As described in the following steps, S410, performing ambient light correction processing on the brightness of a plurality of indoor light-emitting devices to generate brightness information of a target indoor light-emitting device; S420: Determine whether the target light-emitting device exists according to the brightness information of the target indoor light-emitting device and a preset brightness threshold.

[0037] It should be noted that, by presetting the brightness threshold, it can be determined whether there is a target light-emitting device among the brightness of several indoor light-emitting devices.

[0038] As an example, when the light brightness of a certain device exceeds a preset brightness threshold, the device can be determined to be a target light-emitting device.

[0039] In a specific implementation, the preset brightness threshold may be set to 100 lux. When the light brightness of a device exceeds 100 lux, the device may be determined to be a target light-emitting device.

[0040] As described in step S420, it is determined whether a target light-emitting device exists according to the brightness information of the target indoor light-emitting device and the preset brightness threshold.

[0041] In an embodiment of the present invention, the specific process of determining whether there is a target light-emitting device according to the brightness information of the target indoor light-emitting device and the preset brightness threshold in step S420 can be further explained in combination with the following description.

[0042] As described in the following steps, S510, performing wavelet transform processing on the brightness of the indoor lighting device to generate a plurality of frequency bands; wherein the number of decomposition layers in each of the frequency bands includes at least four layers, and the wavelet basis function of each layer is dbN; S520, performing filtering processing on the plurality of frequency bands to generate corrected light information; S530, determining characteristic information according to the corrected light information, wherein the characteristic information includes intensity characteristics, frequency characteristics, direction characteristics, and color characteristics; S540, determining a target indoor light-emitting device in the corrected light information according to the intensity feature, the frequency feature, the direction feature, the color feature, and a preset light information recognition model; S550: Generate brightness information of the target indoor light-emitting device according to the target indoor light-emitting device.

[0043] It should be noted that the wavelet transform algorithm is used for the brightness of indoor lighting equipment. The specific parameters are that the number of decomposition layers is 4, the wavelet basis function of each layer is dbN, and N is the number of decomposition layers.

[0044] As an example, through wavelet transform, the brightness of indoor lighting equipment is decomposed into multiple frequency bands, which are filtered separately to remove the interference of ambient light and obtain corrected light information; various characteristics of light information, such as intensity, frequency, direction, color, etc., are comprehensively utilized to further accurately determine the specific source of the corrected light information; the basic principle of the preset light information recognition model is to detect brightness changes in the image, and identify and extract light areas based on these changes; the light areas in the image are enhanced through preprocessing steps, such as contrast adjustment and edge detection, and clustering algorithms and edge detection algorithms are used to identify and extract these light areas, such as clustering algorithms and edge detection algorithms; 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.

[0045] In a specific implementation, it also includes detection and compensation of ambient light, using an ambient light sensor, model TSL2561, to monitor changes in ambient light in real time. Through an adaptive algorithm, filter parameters or compensation values ​​are dynamically adjusted to adapt to different ambient light conditions. The adaptive algorithm adjusts the ambient light intensity, filter parameters, and compensation values.

[0046] As described in step S130, the area to be adjusted in the house is determined according to the total indoor brightness, the outdoor environment brightness and the indoor environment brightness.

[0047] In an embodiment of the present invention, the specific process of determining the area to be adjusted in the house according to the total indoor brightness, the outdoor environment brightness and the indoor environment brightness in step S130 can be further explained in combination with the following description.

[0048] As described in the following steps, S610, performing vector machine processing and screening according to the outdoor environment brightness, the indoor environment brightness and the indoor total brightness to obtain an initial adjustment area; S620, obtaining first real-time brightness information of the initial adjustment area; S630, performing matching processing according to the real-time brightness information and the total indoor brightness to determine the matching degree; S640: When the matching degree is greater than a preset difference threshold, marking the target matching degree of the real-time brightness information as having a significant difference; S650: Determine, according to the target matching degree, the initial adjustment area corresponding to the real-time brightness information as the area to be adjusted.

[0049] It should be noted that further matching analysis is required after obtaining the initial adjustment area. The real-time brightness information is matched with the target brightness information to determine whether the real-time brightness meets the target brightness requirement. Matching analysis can use difference method, ratio method, fuzzy matching and other methods.

[0050] It should be noted that the three vectors of outdoor environment brightness, indoor environment brightness and indoor total brightness are normalized so that their value range is between 0 and 1; if there are missing values ​​or outliers 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 outliers, the three data of outdoor environment brightness, indoor environment brightness and indoor total brightness are used as features. In an implementation case, other relevant features, such as time, weather conditions, etc., can also be selected according to actual conditions; a training data set is used to train a vector machine model, which can be linear regression or ridge regression in an implementation case, so as to obtain a vector machine model; a validation data set is used in combination with evaluation indicators to evaluate the performance of the model, wherein the evaluation indicators include mean square error or root mean square error; using the trained vector machine model, a new outdoor environment brightness, a new indoor environment brightness and a new indoor total brightness are input to obtain a predicted indoor brightness value; an initial adjustment area is screened out according to the predicted indoor brightness value. In a specific implementation, a brightness threshold can be preset, and an area with a predicted indoor brightness value greater than the preset brightness threshold is used as the initial adjustment area.

[0051] 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 allowable range; the installation position of the target light-emitting device can be obtained through GPS positioning, and its viewing angle can be obtained through measurement, so as to determine the range of lamps that need to be adjusted.

[0052] In a specific implementation, when the target light-emitting device is a television or a projector, the area to be adjusted is determined based on the outdoor ambient brightness, the indoor ambient brightness, and the total indoor brightness; the range of lamps that need to be adjusted can be determined based on the installation position and viewing angle of the target light-emitting device to determine the area to be adjusted.

[0053] As described in step S140, a lamp brightness adjustment instruction is generated according to the area to be adjusted and the total indoor brightness.

[0054] In an embodiment of the present invention, the specific process of generating the lamp brightness adjustment instruction according to the area to be adjusted and the total indoor brightness in step S140 can be further explained in combination with the following description.

[0055] As described in the following steps, S710, obtaining second real-time brightness information of the area to be adjusted; S720, performing matching analysis and calculation according to the second real-time brightness information and the total brightness of the room to generate a difference between the second real-time brightness information and the total brightness of the room; S730, determining whether the difference is within a preset allowable range; 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 mismatched; S750, determining a brightness adjustment strategy based on the brightness relationship and the second real-time brightness information, wherein the brightness adjustment strategy includes adjusting the light source power of all devices in the area to be adjusted corresponding to the second real-time brightness information, replacing the light source type of all devices in the area to be adjusted corresponding to the second real-time brightness information, adjusting the light source angle of all devices in the area to be adjusted corresponding to the second real-time brightness information, and prompt information for reminding the user that the light source is not a lamp; S760: Generate the lamp brightness adjustment instruction according to the brightness adjustment strategy.

[0056] It should be noted that the brightness adjustment strategy is generated based on the area to be adjusted and the total indoor brightness; the corresponding brightness adjustment amplitude and time can be generated based on the difference between the total indoor brightness and the brightness of the area to be adjusted. The generated brightness adjustment command is sent to the target smart lamp in the area to be adjusted; the smart lamp can automatically adjust its own brightness according to the received brightness adjustment command to achieve the preset target brightness.

[0057] As an example, the total indoor brightness can be calculated by the outdoor environment brightness, the indoor environment brightness and the luminous brightness corresponding to the target light-emitting device. The brightness of the area to be adjusted can be obtained by measuring with a sensor, thereby generating the corresponding brightness adjustment amplitude and time; then, the brightness adjustment strategy is determined in combination with the situation of the area to be adjusted, and the brightness adjustment strategy includes adjusting one or more of the light source power, light source type, light source angle and reminder information; then, the determined brightness adjustment strategy is used to generate a brightness adjustment instruction, and the corresponding brightness adjustment instruction is sent to the target smart lamp in the area to be adjusted, wherein the first adjustment instruction is sent to the target smart lamp; the target smart lamp receives the adjustment strategy through the Wi-Fi network, and automatically adjusts its own brightness according to the adjustment strategy; the second adjustment instruction is sent to the user's mobile terminal to prompt the user which other light sources other than lamps exist.

[0058] In a specific implementation, a corresponding adjustment strategy is generated according to the difference between the real-time brightness information and the total indoor brightness; if the adjustment strategy is to adjust the power of the light source, the adjustment range is 10%; then a judgment is made based on the real-time brightness information and the total indoor brightness; when the real-time brightness information is lower than the total indoor brightness, the adjustment strategy may be to increase the power of the light source or turn on an additional light source; when the real-time brightness information is higher than the total indoor brightness, the adjustment strategy may be to reduce the power of the light source or turn off some of the light sources; the generated adjustment strategy is sent to the corresponding control unit to control the power of the light source or other related parameters, so as to achieve brightness adjustment of the target area; and during the adjustment process, the real-time brightness information of the target area can be continuously monitored, and the adjustment strategy can be appropriately adjusted according to the feedback results to ensure that the brightness of the target area 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 specific circumstances, so as to provide a more comfortable and personalized lighting environment.

[0059] Embodiment 1 The technical solution of the present application can realize that when a user uses a display device such as a projector or a TV, the user no longer needs to turn on or off the lamps by himself during use. The technical solution of the present application can adaptively adjust the lamps to a brightness that matches the display device, thereby providing better visual effects and lighting environment.

[0060] The technical solution of this application can be applied to various projector usage scenarios such as education, entertainment, and conferences; in the field of education, teachers can optimize the classroom environment and improve students' learning efficiency by automatically adjusting the brightness of lamps; in the field of entertainment, audiences can get a better viewing experience by automatically adjusting the brightness of lamps; in the field of conferences, speakers can ensure the clarity and readability of the speech content by automatically adjusting the brightness of lamps. In addition, since this technical solution can realize automatic adjustment of lamp brightness, it can also be widely used in smart homes, smart offices, and other fields. For example, in smart homes, users can realize automatic adjustment of lamp brightness through smart control devices, thereby improving the convenience and comfort of family life. In smart offices, employees can realize automatic adjustment of lamp brightness through smart control devices, thereby improving work efficiency and comfort.

[0061] Smart lamps can be turned on and off through smart control chips; users can input their preferences, such as brightness level, color, etc., through remote controls or other control devices, and the smart control chip can adjust the brightness of the lamp according to the lamp brightness adjustment instructions; the lamp brightness adjustment instructions can be sent to the remote control of the smart lamp to achieve remote control of the smart lamp through the remote control; smart lamps can also be remotely controlled to turn on and off, and adjust the brightness of the lamps through mobile phones, tablets or other mobile devices; smart lamps include smart LED bulbs, smart light strips, smart switches and smart desk lamps. When a lamp brightness adjustment instruction is received, the smart control chip combines the current brightness of the corresponding smart lamp and the lamp brightness adjustment instruction to adjust the brightness of the lamp. The target brightness in the instruction is used to adjust the brightness of the smart lamp. For example, when the current brightness is greater than the target brightness, the current brightness of the smart lamp is lowered; or when the current brightness is lower than the target brightness, it is determined whether to make adjustments based on the brightness of the surrounding environment of the smart lamp. If the current brightness of the smart lamp is consistent with the brightness of the surrounding environment, no adjustment is required. If the current brightness of the smart lamp is significantly different from the brightness of the surrounding environment, the current brightness of the smart lamp 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, and send the corresponding lamp brightness adjustment instruction to the mobile device, so as to adjust the brightness of the light-emitting devices in the smart home field through the mobile device.

[0062] As for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0063] Reference Figure 2 , shows a structural block diagram of an intelligent adjustment system based on intelligent lamps provided in an embodiment of the present application; An intelligent adjustment system based on intelligent lamps, the system comprising: The detection module 210 is used to detect the light brightness information in the house, wherein the light brightness information includes the outdoor environment brightness, the indoor environment brightness and at least one indoor light-emitting device brightness; A first determination module 220, configured to determine whether there is a target light emitting device according to the brightness of the indoor light emitting device; A second determination module 230 is used to determine the total indoor brightness according to the outdoor environment brightness, the indoor environment brightness and the light brightness corresponding to the target light-emitting device when the target light-emitting device exists; A third determination module 240 is used to determine the area to be adjusted in the house according to the total indoor brightness, the outdoor environment brightness and the indoor environment brightness; A generating module 250, configured to generate a lamp brightness adjustment instruction according to the area to be adjusted and the total indoor brightness; The sending module 260 is used to send the lamp brightness adjustment instruction to the target smart lamp in the area to be adjusted.

[0064] In one embodiment of the present invention, the detection module 210 includes: A first acquisition submodule is used to acquire sensor information of all the light intensity sensors in each area of ​​the house; The first determination submodule is used to determine the light brightness information according to the sensor information and a preset time period.

[0065] In one embodiment of the present invention, the first determining submodule includes: A first acquisition unit, used to acquire the illumination information acquired by the sensor information collection; A first determining unit, configured to determine a type of illumination information according to the illumination information and a preset illumination analysis model, wherein the type of illumination information includes natural light and device light; a second determining unit, configured to determine a light brightness level of the device light according to the device light and the preset illumination analysis model, wherein the light brightness level includes high brightness, medium brightness and low brightness; A third determining unit is used to determine the light brightness information according to the device light with the high brightness and the medium brightness and the natural light.

[0066] In one embodiment of the present invention, the first determining module 220 includes: A first generating submodule is used to perform ambient light correction processing on the brightness of a plurality of indoor light-emitting devices to generate brightness information of a target indoor light-emitting device; The second determination submodule is used to determine whether the target light-emitting device exists according to the brightness information of the target indoor light-emitting device and a preset brightness threshold.

[0067] In one embodiment of the present invention, the first generating submodule includes: A first generating unit is used to perform wavelet transform processing on the brightness of the indoor lighting device to generate a plurality of frequency bands; wherein the number of decomposition layers in each of the frequency bands includes at least four layers, and the wavelet basis function of each layer is dbN; A second generating unit, configured to perform filtering processing on a plurality of the frequency bands to generate corrected brightness information; a fourth determining unit, configured to determine characteristic information according to the corrected light information, wherein the characteristic information includes intensity characteristics, frequency characteristics, direction characteristics, and color characteristics; A fifth determination unit, configured to determine a target indoor light-emitting device in the corrected light information according to the intensity feature, the frequency feature, the direction feature, the color feature, and a preset light information recognition model; The third generating unit is configured to generate brightness information of the target indoor light-emitting device according to the target indoor light-emitting device.

[0068] In one embodiment of the present invention, the third determining module 240 includes: A first screening submodule is used to perform vector machine processing and screening according to the outdoor environment brightness, the indoor environment brightness and the indoor total brightness to obtain an initial adjustment area; A second acquisition submodule is used to acquire first real-time brightness information of the initial adjustment area; A third determination submodule is used to perform matching processing according to the real-time brightness information and the total indoor brightness to determine the matching degree; A first marking submodule, for marking the target matching degree of the real-time brightness information as being significantly different when the matching degree is greater than a preset difference threshold; The fourth determination submodule is used to determine, according to the target matching degree, that the initial adjustment area corresponding to the real-time brightness information is the area to be adjusted.

[0069] In one embodiment of the present invention, the generating module 250 includes: A third acquisition submodule is used to acquire second real-time brightness information of the area to be adjusted; A second generating submodule, configured to perform matching analysis and calculation based 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; A fifth determination submodule, used to determine whether the difference is within a preset allowable range; a sixth determination submodule, configured to determine that the brightness relationship between the second real-time brightness information and the total indoor brightness is mismatched when the difference is not within the preset allowable range; A third generating submodule is used to determine a brightness adjustment strategy according to the brightness relationship and the second real-time brightness information, wherein the brightness adjustment strategy includes adjusting the light source power of all devices in the area to be adjusted corresponding to the second real-time brightness information, replacing the light source type of all devices in the area to be adjusted corresponding to the second real-time brightness information, adjusting the light source angle of all devices in the area to be adjusted corresponding to the second real-time brightness information, and prompt information for reminding the user that the light source is not a lamp; The fourth generating submodule is used to generate the lamp brightness adjustment instruction according to the brightness adjustment strategy.

[0070] Reference Figure 3 , shows a computer device of the present invention based on the intelligent adjustment method of intelligent lamps, which may specifically include the following: The computer device 12 is in the form of a general-purpose computing device, and the components of the computer device 12 may 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).

[0071] The bus 18 represents one or more of several types of bus 18 structures, including a memory bus 18 or memory controller, a peripheral bus 18, an accelerated graphics port, a processor, or a local bus 18 using any of a variety of bus 18 architectures. These architectures include, by way of example, but are not limited to, an Industry Standard Architecture (ISA) bus 18, a Micro Channel Architecture (MAC) bus 18, an Enhanced ISA bus 18, an Audio Video Electronics Standards Association (VESA) local bus 18, and a Peripheral Component Interconnect (PCI) bus 18.

[0072] The computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0073] System memory 28 may 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 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be used to read and write to non-removable, non-volatile magnetic media (commonly referred to as a hard drive). Although Figure 3 Not shown in the figure, a disk drive for reading and writing a removable non-volatile disk (such as a floppy disk) and an optical disk drive for reading and writing a removable non-volatile optical disk (such as a CD-ROM, a DVD-ROM or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory may include at least one program product having a set (e.g., at least one) of program modules 42, which are configured to perform the functions of various embodiments of the present invention.

[0074] A program / utility 40 having a set (at least one) of program modules 42 may be stored in, for example, a memory, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules 42, and program data, each of which or some combination may include an implementation of a network environment. The program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0075] The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, cameras, etc.), one or more devices that enable a user to interact with the computer device 12, and / or any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 22. Furthermore, the computer device 12 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network (e.g., the Internet)) via a network adapter 20. As shown, the network adapter 20 communicates with other modules of the computer device 12 via a bus 18. It should be understood that although Figure 3 Not shown, other hardware and / or software modules may be used in conjunction with the computer device 12, including but not limited to: microcode, device drivers, redundant processing units 16, external disk drive arrays, RAID systems, tape drives, and data backup storage systems 34, etc.

[0076] The processing unit 16 executes various functional applications and data processing by running the programs stored in the system memory 28, for example, implementing an intelligent adjustment method based on an intelligent lamp provided in an embodiment of the present invention.

[0077] That is, when the processing unit 16 executes the program, it realizes: detecting the light brightness information in the house, wherein the light brightness information includes the outdoor environment brightness, the indoor environment brightness and at least one indoor light-emitting device brightness; determining whether there is a target light-emitting device based on the brightness of the indoor light-emitting device; when the target light-emitting device exists, determining the total indoor brightness based on the outdoor environment brightness, the indoor environment brightness and the light brightness corresponding to the target light-emitting device; determining the area to be adjusted in the house based on the total indoor brightness, the outdoor environment brightness and the indoor environment brightness; generating a lamp brightness adjustment instruction based on the area to be adjusted and the total indoor brightness; and sending the lamp brightness adjustment instruction to the target smart lamp in the area to be adjusted.

[0078] In an embodiment of the present invention, the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, an intelligent adjustment method based on an intelligent lamp as provided in all embodiments of the present application is implemented: That is, when the program is executed by the processor, it is implemented as follows: detecting the light brightness information in the house, wherein the light brightness information includes the outdoor environment brightness, the indoor environment brightness and the brightness of at least one indoor light-emitting device; determining whether there is a target light-emitting device based on the brightness of the indoor light-emitting device; when the target light-emitting device exists, determining the total indoor brightness based on the outdoor environment brightness, the indoor environment brightness and the light brightness corresponding to the target light-emitting device; determining the area to be adjusted in the house based on the total indoor brightness, the outdoor environment brightness and the indoor environment brightness; generating a lamp brightness adjustment instruction based on the area to be adjusted and the total indoor brightness; and sending the lamp brightness adjustment instruction to the target smart lamp in the area to be adjusted.

[0079] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, device or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device or device.

[0080] Computer-readable signal media may include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0081] The computer program code for performing the operation of the present invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as C or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, 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 can be connected to an external computer (for example, using an Internet service provider to connect through the Internet). The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the various embodiments can be referred to each other.

[0082] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present application.

[0083] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms include, contain or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, an element defined by the sentence includes a... does not exclude the existence of other identical elements in the process, method, article or terminal device including the element.

[0084] The above is a detailed introduction to the intelligent adjustment method and system based on intelligent lamps provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. An intelligent adjustment method based on intelligent lamps, characterized in that: The method comprises: 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 there is a target light-emitting device according to the brightness of the indoor light-emitting device; When the target light-emitting device exists, the total indoor brightness is determined according to the outdoor environment brightness, the indoor environment brightness and the light brightness corresponding to the target light-emitting device; Determining the area to be adjusted in the house according to the total indoor brightness, the outdoor environment brightness and the indoor environment brightness; Generate a lamp brightness adjustment instruction according to the area to be adjusted and the total indoor brightness; The lamp brightness adjustment instruction is sent to the target smart lamp in the area to be adjusted.

2. The method according to claim 1, characterized in that: The area in the house is divided into several areas, and several light intensity sensors are arranged in each area; the step of detecting the light brightness information in the house, wherein the light brightness information includes the outdoor environment brightness, the indoor environment brightness and the brightness of at least one indoor lighting device, comprises: Acquire sensor information of all the light intensity sensors in each area of ​​the house; The light brightness information is determined according to the sensor information and a preset time period.

3. The method according to claim 2, characterized in that The step of determining the light brightness information according to the sensor information and a preset time period includes: Acquire illumination information acquired by the sensor information collection; Determining the type of illumination information according to the illumination information and a preset illumination analysis model, wherein the type of illumination information includes natural light and device light; Determining a light brightness level of the device light according to the device light and the preset light analysis model, wherein the light brightness level includes high brightness, medium brightness and low brightness; The light brightness information is determined according to the device light having the high brightness and the medium brightness and the natural light.

4. The method according to claim 1, characterized in that The step of determining whether a target light-emitting device exists according to the brightness of the indoor light-emitting device comprises: Performing ambient light correction processing on the brightness of a plurality of the indoor light-emitting devices to generate brightness information of a target indoor light-emitting device; Determine whether the target light-emitting device exists according to the brightness information of the target indoor light-emitting device and a preset brightness threshold.

5. The method according to claim 4, characterized in that The step of performing ambient light correction processing on the brightness of a plurality of indoor light-emitting devices to generate brightness information of a target indoor light-emitting device comprises: Performing wavelet transform processing on the brightness of the indoor lighting device to generate a plurality of frequency bands; wherein the number of decomposition layers in each of the frequency bands includes at least four layers, and the wavelet basis function of each layer is dbN; Performing filtering processing on a plurality of said frequency bands to generate corrected brightness information; Determining characteristic information according to the corrected light information, wherein the characteristic information includes intensity characteristics, frequency characteristics, direction characteristics and color characteristics; Determine a target indoor light-emitting device in the corrected light information according to the intensity feature, the frequency feature, the direction feature, the color feature and a preset light information recognition model; The brightness information of the target indoor light-emitting device is generated according to the target indoor light-emitting device.

6. The method according to claim 1, characterized in that The step of determining the area to be adjusted in the house according to the total indoor brightness, the outdoor environment brightness and the indoor environment brightness comprises: Performing vector machine processing and screening according to the outdoor environment brightness, the indoor environment brightness and the indoor total brightness to obtain an initial adjustment area; Acquire first real-time brightness information of the initial adjustment area; Performing matching processing according to the real-time brightness information and the total indoor brightness to determine the matching degree; When the matching degree is greater than a preset difference threshold, the target matching degree of the real-time brightness information is marked as significantly different; The initial adjustment area corresponding to the real-time brightness information is determined as the area to be adjusted according to the target matching degree.

7. The method according to claim 1, characterized in that The step of generating a lamp brightness adjustment instruction according to the area to be adjusted and the total indoor brightness includes: Acquire second real-time brightness information of the area to be adjusted; Perform matching analysis and calculation based on the second real-time brightness information and the total brightness of the room to generate a difference between the second real-time brightness information and the total brightness of the room; Determining whether the difference is within a preset allowable range; 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 mismatched; Determine a brightness adjustment strategy according to the brightness relationship and the second real-time brightness information, wherein the brightness adjustment strategy includes adjusting the light source power of all devices in the area to be adjusted corresponding to the second real-time brightness information, changing the light source type of all devices in the area to be adjusted corresponding to the second real-time brightness information, adjusting the light source angle of all devices in the area to be adjusted corresponding to the second real-time brightness information, and prompt information for reminding the user that the light source is not a lamp; The lamp brightness adjustment instruction is generated according to the brightness adjustment strategy.

8. An intelligent adjustment system based on intelligent lamps, characterized in that: The system comprises: A detection module, used to detect 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; A first determination module, used to determine whether there is a target light-emitting device according to the brightness of the indoor light-emitting device; A second determination module is used to determine the total indoor brightness according to the outdoor environment brightness, the indoor environment brightness and the light brightness corresponding to the target light-emitting device when the target light-emitting device exists; A third determination module is used to determine the area to be adjusted in the house according to the total indoor brightness, the outdoor environment brightness and the indoor environment brightness; A generating module, used for generating a lamp brightness adjustment instruction according to the area to be adjusted and the total indoor brightness; The sending module is used to send the lamp brightness adjustment instruction to the target smart lamp in the area to be adjusted.

9. A computer device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program implements the method according to any one of claims 1 to 7 when executed by the processor.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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