Lighting control method, device and system based on edge computing

Abstract

The present invention provides a lighting control method, device and system based on edge computing, the method comprising: obtaining historical behavior data of a user and historical data of light intensity in a target area; generating a first control scheme for a target light source system based on the historical behavior data and the historical data of light intensity; controlling the target light source system based on the first control scheme; wherein the historical behavior data includes historical control behavior data of the user on the target light source system and historical activity behavior data of the user in the target area; the target light source system is used for lighting the target area. The lighting control method, device and system based on edge computing provided by the present invention can perform lighting control more intelligently, reduce manual operations of the user, improve user experience and comfort, avoid the situation where the user forgets to turn off the light source system, and reduce energy waste.

Description

Technical Field

[0001] The present invention relates to the field of smart home technologies, and in particular to a lighting control method, device and system based on edge computing. Background Art

[0002] Smart home is based on the house as a platform, using integrated wiring technology, network communication technology, security technology, automatic control technology and audio and video technology to integrate facilities related to home life and build an efficient management system for residential facilities and family schedule affairs, thereby improving home safety, convenience, comfort and artistry, and achieving an environmentally friendly and energy-saving living environment. As an important part of smart home, intelligent lighting control is attracting more and more attention.

[0003] Existing edge computing-based lighting control methods mainly rely on the user's manual control of the light source system and / or the shading system. However, in real life, the user's manual control of the light source system and / or the shading system is cumbersome, the user experience is poor, and it is easy for the user to forget to turn off the light source system, resulting in energy waste. Therefore, how to control lighting more intelligently and more environmentally friendly is a technical problem that needs to be solved in this field. Summary of the invention

[0004] The present invention provides a lighting control method, device and system based on edge computing, which are used to solve the defect that it is difficult to perform lighting control in an intelligent and environmentally friendly manner in the prior art, and to achieve more intelligent and environmentally friendly lighting control.

[0005] The present invention provides a lighting control method based on edge computing, comprising:

[0006] Obtain historical behavior data of users and historical data of light intensity in the target area;

[0007] Generate a first control scheme for the target light source system based on the historical behavior data and the historical data of light intensity;

[0008] Based on the first control scheme, controlling the target light source system;

[0009] The historical behavior data includes the historical control behavior data of the user on the target light source system and the historical activity behavior data of the user in the target area; the target light source system is used for lighting the target area.

[0010] According to a lighting control method based on edge computing provided by the present invention, when the historical behavior data also includes the historical control behavior data of the user on the target shading system, after acquiring the historical behavior data of the user and the historical data of the light intensity in the target area, the method further includes:

[0011] generating a second control scheme for the target shading system based on the historical behavior data and the historical data of light intensity;

[0012] Based on the second control scheme, controlling the target shading system;

[0013] Wherein, the target shading system is used for shading the target area.

[0014] According to a lighting control method based on edge computing provided by the present invention, after controlling the target light source system based on the first control scheme, the method further includes:

[0015] Acquiring first control behavior data of a user on the target light source system;

[0016] Based on the first control behavior data, the first control scheme is updated.

[0017] According to a lighting control method based on edge computing provided by the present invention, after controlling the target shading system based on the second control scheme, the method further includes:

[0018] Acquiring second control behavior data of the user on the target shading system;

[0019] Based on the second control behavior data, the second control scheme is updated.

[0020] According to a lighting control method based on edge computing provided by the present invention, historical activity behavior data of users in the target area is obtained, including:

[0021] Obtain historical video stream data in the target area;

[0022] Performing frame extraction processing on the historical video stream data to obtain a historical image set of the target area;

[0023] Image recognition is performed on the historical image set based on deep learning technology, and the historical activity behavior data is obtained based on the image recognition results.

[0024] According to a lighting control method based on edge computing provided by the present invention, the first control scheme of the target light source system is generated based on the historical behavior data and the historical data of the light intensity, including:

[0025] Inputting the historical behavior data and the historical data of light intensity into a lighting control model to obtain the first control scheme output by the lighting control model;

[0026] Among them, the lighting control model is obtained after training based on sample historical data of light intensity in the sample area, sample historical behavior data of sample users and the first sample control scheme of the sample area; the sample historical behavior data includes the historical control behavior data of the sample user on the sample light source system and the historical activity behavior data of the sample user in the sample area; the sample light source system is used for lighting the sample area.

[0027] According to a lighting control method based on edge computing provided by the present invention, the target shading system is controlled based on the second control scheme, including:

[0028] Inputting the historical behavior data and the historical data of light intensity into the lighting control model to obtain the second control scheme output by the lighting control model;

[0029] The sample historical behavior data of the sample user also includes the sample user's historical control behavior data on the sample shading system; the sample shading system is used for shading the sample area.

[0030] The present invention also provides a lighting control device based on edge computing, comprising:

[0031] A data acquisition module, used to acquire historical behavior data of users and historical data of light intensity in a target area;

[0032] A scheme generating module, used for generating a first control scheme for a target light source system based on the historical behavior data and the historical data of light intensity;

[0033] A lighting control module, configured to control the target light source system based on the first control scheme;

[0034] The historical behavior data includes the historical control behavior data of the user on the target light source system and the historical activity behavior data of the user in the target area; the target light source system is used for lighting the target area.

[0035] According to a lighting control device based on edge computing provided by the present invention, the lighting control device based on edge computing is an edge device.

[0036] The present invention also provides a lighting control system based on edge computing, comprising: a lighting control device based on edge computing and a light source system as described above.

[0037] According to the present invention, a lighting control system based on edge computing also includes: a shading system.

[0038] According to the present invention, a lighting control system based on edge computing further includes: an image sensor and a light intensity sensor;

[0039] The light intensity sensor is used to obtain historical data of light intensity in the target area;

[0040] The image sensor is used to obtain historical video stream data in the target area.

[0041] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the edge computing-based lighting control method as described above is implemented.

[0042] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the edge computing-based lighting control methods described above.

[0043] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned edge computing-based lighting control methods.

[0044] The lighting control method, device and system based on edge computing provided by the present invention generate a first control scheme for the target light source system based on the user's historical activity behavior data in the target area, the user's historical control behavior data on the target light source system, and the historical data of light intensity in the target area, and then control the target light source system based on the above-mentioned first control scheme. The target light source system is used for lighting the target area, and can perform lighting control more intelligently, reduce the user's manual operation, improve user experience and comfort, avoid the situation where the user forgets to turn off the light source system, and reduce energy waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 It is a flow chart of the lighting control method based on edge computing provided by the present invention;

[0047] Figure 2 It is a structural schematic diagram of a lighting control device based on edge computing provided by the present invention;

[0048] Figure 3It is a structural schematic diagram of a lighting control system based on edge computing provided by the present invention;

[0049] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] In the description of the invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0052] It should be noted that according to the definition of the China Edge Computing Industry Alliance, edge computing refers to an open platform that integrates network, computing storage, and application core capabilities at the edge of the network close to the source of objects or data, providing edge intelligent services nearby to meet the key needs of industry digitalization in agile connectivity, real-time business, data optimization, application intelligence security and privacy protection.

[0053] With the development of IoT technology, edge devices have also been more widely used in the field of smart home. Edge computing can include network-side edge computing and field-level edge computing. Edge computing in the smart home scenario is a type of field-level edge computing. Based on the communication, computing, and storage capabilities provided by edge devices, effective linkage between different smart home products can be achieved.

[0054] In a home wireless network, the home network host connects to the wireless access points (APs) distributed in each room of the house through network cables to manage the home wireless LAN coverage Wifi. Home edge devices, smart devices, and IoT sensors within the home range access the home wireless network through Wifi. Home edge devices can work independently without the Internet, and data collection and processing are all performed in the home edge computing host, which can protect user privacy from being leaked.

[0055] Figure 1Schematic diagram of the lighting control method based on edge computing provided by the present invention. Figure 1 The lighting control method based on edge computing of the present invention is described. Figure 1 As shown, the method includes: step 101, obtaining historical behavior data of the user and historical data of light intensity in the target area.

[0056] The historical behavior data includes the user's historical control behavior data on the target light source system and the user's historical activity behavior data in the target area; the target light source system is used for lighting the target area.

[0057] It should be noted that the executor of the embodiment of the present invention is a lighting control device based on edge computing, and the lighting control device based on edge computing may be an edge device.

[0058] Specifically, the target area is a control object of the edge computing-based lighting control method provided by the present invention. Based on the edge computing-based lighting control method provided by the present invention, the light intensity in the target area can be controlled.

[0059] It should be noted that the target area can be an indoor area or an outdoor area. The target light source system can provide lighting for the target area. The target light source system can be set in the target area or outside the target area.

[0060] Light sensors can be used to obtain historical data on light intensity in the target area. Historical user behavior data can be obtained in a variety of ways.

[0061] For example, based on a controller and a counter arranged in the target light source system, the user's historical control behavior on the target light source system can be recorded to obtain the user's historical control behavior data on the target light source system; wherein the above-mentioned historical control behavior data may include the type of control behavior of the user on the target light source system and the time when the above-mentioned behavior is performed; the type of the above-mentioned control behavior may include but is not limited to controlling the target light source system to turn on the lighting mode, controlling the target light source system to turn off the lighting mode, controlling the lighting mode of the target light source system to switch from the previous lighting mode to the current lighting mode, etc.

[0062] For another example, image sensors and deep learning technology can be used to obtain historical activity behavior data of users in the target area. The historical activity behavior data may include the type of activity behavior performed by the user and the start and end time of the activity; the type of activity behavior may include but is not limited to work, fitness, leisure, and sleep.

[0063] For another example, various types of sensors can be used to obtain the user's historical activity behavior data in the target area. For example, based on sensors installed near the desk in the target area, the user's work or study behavior can be monitored to obtain the time when the user starts working or studying, and the time when the user ends work or study as the user's historical activity behavior data in the target area.

[0064] It should be noted that the historical data of light intensity and the historical behavior data of users may be time series data. The number of users may be one or more.

[0065] It should be noted that the duration of the historical data of light intensity and the historical behavior data of the user can be determined based on prior knowledge. For example, the historical data of light intensity and the historical behavior data of the user in the target area in the past week can be obtained. In the embodiment of the present invention, the duration of the historical data of light intensity and the historical behavior data of the user is not specifically limited.

[0066] Step 102: Generate a first control solution for the target light source system based on the historical behavior data and the historical data of light intensity.

[0067] Specifically, after obtaining the user's historical behavior data and the historical data of light intensity in the target area, based on the above historical behavior data and the above historical data of light intensity, the user's behavior patterns, the user's control patterns of the target light source system, and the patterns of light intensity changes in the target area can be obtained.

[0068] Based on the user's behavioral patterns, the user's control patterns of the target light source system, and the patterns of light intensity changes in the target area, a first control scheme for the target light source system can be generated through numerical calculations, mathematical statistics, and the like.

[0069] Optionally, deep learning technology may be used to obtain a first control solution for the target light source system based on historical behavior data of the user and historical data of light intensity in the target area.

[0070] Optionally, the first control scheme may include control instructions for the target light source system and the time to execute the control instructions. For example, when the target light source system is a lighting lamp, and the lighting lamp includes three lighting modes, the first control scheme may include controlling the target light source system to start the first lighting mode at 6:00 a.m. every weekday, shutting down the target light source system at 8:00 a.m. every weekday, and starting the second lighting mode of the target light source system at 19:00 p.m. every weekend.

[0071] Step 103: Control the target light source system based on the first control solution.

[0072] Specifically, after the first control scheme of the target light source system is acquired, the target light source system may be controlled based on the first control scheme.

[0073] The embodiment of the present invention generates a first control scheme for the target light source system based on the user's historical activity behavior data in the target area, the user's historical control behavior data on the target light source system, and the historical data of light intensity in the target area, and then controls the target light source system based on the above first control scheme. The target light source system is used for lighting the target area, and can perform lighting control more intelligently, reduce the user's manual operation, improve user experience and comfort, avoid the situation where the user forgets to turn off the light source system, and reduce energy waste.

[0074] Based on the contents of the above embodiments, when the historical behavior data also includes the user's historical control behavior data of the target shading system, after obtaining the user's historical behavior data and the historical data of light intensity in the target area, it also includes: generating a second control scheme for the target shading system based on the historical behavior data and the historical data of light intensity.

[0075] Among them, the target shading system is used for shading the target area.

[0076] Specifically, the target shading system can provide shading for the target area, for example, the target shading system can be a controllable curtain or a controllable outdoor ceiling. The target shading system can be set in the target area or outside the target area.

[0077] The user's historical behavior data may also include the user's historical control behavior data on the target shading system.

[0078] The historical control behavior data of the user on the target shading system can be obtained in a variety of ways. For example, the historical control behavior of the user on the target shading system can be recorded based on the controller and counter set in the target shading system to obtain the historical control behavior data of the user on the target shading system; wherein the above historical control behavior data can include the type of control behavior of the user on the target shading system and the time when the above behavior is performed; the type of the above control behavior can include but is not limited to controlling the target shading system to start the shading mode, controlling the target shading system to turn off the shading mode, switching the shading mode of the target shading system from the previous shading mode to the current shading mode, etc.

[0079] Correspondingly, after obtaining the user's historical behavior data and the historical data of light intensity in the target area, based on the above historical behavior data and the above historical data of light intensity, in addition to obtaining the user's behavior patterns, the user's control patterns of the target light source system and the patterns of changes in light intensity in the target area, the user's control patterns of the target shading system can also be obtained.

[0080] Based on the user's behavioral patterns, the user's control patterns of the target light source system, the patterns of light intensity changes in the target area, and the user's control patterns of the target shading system, a second control scheme for the target shading system can be generated through numerical calculations, mathematical statistics, and the like.

[0081] Optionally, deep learning technology may be used to obtain a second control solution for the target light source system based on historical behavior data of the user and historical data of light intensity in the target area.

[0082] Optionally, the second control scheme may include control instructions for the target shading system and the time to execute the control instructions. For example, when the target shading system is a controllable curtain, the controllable curtain includes two layers of curtain fabric, the first layer of curtain fabric is light-transmissive, the second layer of curtain fabric is not light-transmissive, the first shading mode is that both layers of curtain fabric are in a closed state, and the second shading mode is that the first layer of curtain fabric is closed and the second layer of curtain fabric is opened, the second control scheme may include controlling the target shading system to switch from the first shading mode to the second shading mode at 6:00 a.m. every weekday, controlling the target shading system to turn off the shading mode at 8:00 a.m. every weekday, and controlling the target light source system to turn on the first shading mode at 19:00 p.m. every weekday.

[0083] Based on the second control scheme, the target shading system is controlled.

[0084] Specifically, after the second control scheme of the target shading system is acquired, the target shading system may be controlled based on the second control scheme.

[0085] The embodiment of the present invention generates a second control scheme for the target shading system based on the user's historical activity behavior data in the target area, the user's historical control behavior data of the target light source system, the historical data of the light intensity in the target area, and the user's historical control behavior data of the target shading system. Then, the target shading system is controlled based on the second control scheme. The target shading system is used for shading the target area, and the shading system can be controlled more intelligently, thereby enabling more flexible and diverse lighting control, reducing the user's manual operation, and improving user experience and comfort.

[0086] Based on the contents of the above embodiments, after controlling the target light source system based on the first control scheme, the method further includes: acquiring first control behavior data of the user on the target light source system.

[0087] Specifically, after the target light source system is controlled based on the first control scheme, if the user manually controls the target light source system, the control behavior data of the control behavior can be obtained as the first control behavior data.

[0088] It should be noted that the above manual control may be performed once or multiple times.

[0089] It should be noted that after the target light source system is controlled based on the above-mentioned first control scheme, if the duration between the moment when the user manually controls the target light source system and the moment when the target light source system was last automatically controlled is less than a first preset value, it can be said that the user believes that the last automatic control of the target light source system does not meet actual needs.

[0090] For example: based on the above-mentioned first control scheme, after the target light source system is controlled to start the lighting mode at the first moment, no other automatic control is performed on the target light source system. If the user manually controls the target light source system to turn off the lighting mode at the second moment, and the interval between the first moment and the second moment is less than 3 minutes, it can be said that the user believes that controlling the target light source system to start the lighting mode at the first moment does not meet actual needs.

[0091] After controlling the target light source system based on the above-mentioned first control scheme, if the duration between the moment when the user manually controls the target light source system and the moment when the target light source system was last automatically controlled is not less than a second preset value, it can be said that the user has a need to increase control over the target light source system at a second moment.

[0092] For example: based on the above-mentioned first control scheme, after the target light source system is controlled to turn off the lighting mode at the first moment, no other automatic control is performed on the target light source system. If the user manually controls the target light source system to start the lighting mode at the second moment, and the interval between the first moment and the second moment is not less than 1 hour, it can be said that the user believes that there is a need to control the target light source system to start the lighting mode at the second moment.

[0093] It should be noted that the first preset value and the second preset value can be determined according to actual conditions. In the embodiment of the present invention, there is no specific limitation on the specific values ​​of the first preset value and the second preset value.

[0094] It should be noted that the first control behavior data may be obtained in the same manner as obtaining the historical control behavior data of the user on the target light source system.

[0095] It should be noted that the duration of the first control behavior can be determined based on prior knowledge. For example, the first control behavior data of the user on the target light source system within 3 days after the first control scheme controls the target light source system can be obtained. In the embodiment of the present invention, the duration of the first control behavior data is not specifically limited.

[0096] Based on the first control action data, the first control scheme is updated.

[0097] Specifically, after obtaining the above-mentioned first control behavior data, the first control scheme can be updated by numerical calculation, mathematical statistics, etc. to obtain an updated first control scheme, and the target light source system can be controlled based on the updated first control scheme.

[0098] Optionally, when using deep learning technology to obtain the first control scheme for the target light source system, the above-mentioned first control behavior data can also be used to replace some data that are earlier in time in the historical control behavior data of the user for the target light source system, so as to update the historical control behavior data of the user for the target light source system, and based on the updated historical control behavior data of the user for the target light source system, deep learning technology can be used to update the first control scheme to obtain an updated first control scheme.

[0099] The embodiment of the present invention updates the first control scheme based on the first control behavior data of the target light source system after the user controls the target light source system based on the above-mentioned first control scheme. The first control scheme can be continuously updated based on the user's corrected behavior on the target light source system, so that more accurate and more in line with actual demand automatic lighting control can be performed based on the updated first control scheme.

[0100] Based on the contents of the above embodiments, after controlling the target shading system based on the second control scheme, the method further includes: obtaining second control behavior data of the user on the target shading system.

[0101] Specifically, after the target shading system is controlled based on the second control scheme, if the user manually controls the target shading system, the control behavior data of the control behavior is acquired as the second control behavior data.

[0102] It should be noted that the above manual control may be performed once or multiple times.

[0103] It should be noted that after the target shading system is controlled based on the above-mentioned second control scheme, if the duration between the moment when the user manually controls the target shading system and the moment when the target shading system was last automatically controlled is less than the third preset value, it can be said that the user believes that the last automatic control of the target shading system does not meet actual needs.

[0104] For example: based on the above-mentioned second control scheme, after the target shading system is controlled to turn on the shading mode at the third moment, no other automatic control is performed on the target shading system. If the user manually controls the target shading system to turn off the shading mode at the fourth moment, and the interval between the third moment and the fourth moment is less than 3 minutes, it can be said that the user believes that controlling the target shading system to turn on the shading mode at the third moment does not meet actual needs.

[0105] After the target shading system is controlled based on the above-mentioned second control scheme, if the duration between the moment when the user manually controls the target shading system and the moment when the target shading system was last automatically controlled is not less than the fourth preset value, it can be said that the user has a need to increase the control of the target shading system at the fourth moment.

[0106] For example: after controlling the target shading system to turn off the shading mode at the third moment based on the above-mentioned second control scheme, if the user manually controls the target shading system to start the shading mode at the fourth moment, and the interval between the third moment and the fourth moment is not less than 1 hour, it can be said that the user believes that there is a need to control the target shading system to start the shading mode at the fourth moment.

[0107] It should be noted that the third preset value and the fourth preset value can be determined according to actual conditions. In the embodiment of the present invention, the specific values ​​of the third preset value and the fourth preset value are not specifically limited.

[0108] It should be noted that the second control behavior data can be obtained in the same manner as obtaining the historical control behavior data of the user on the target shading system.

[0109] It should be noted that the duration of the second control behavior can be determined based on prior knowledge. For example, the second control behavior data of the user on the target light source system within 3 days after the second control scheme controls the target shading system can be obtained. In the embodiment of the present invention, the duration of the second control behavior data is not specifically limited.

[0110] Based on the second control action data, the second control method is updated.

[0111] Specifically, after obtaining the above-mentioned second control behavior data, the second control scheme can be updated through numerical calculation, mathematical statistics, etc. to obtain an updated second control scheme, and the target shading system can be controlled based on the updated second control scheme.

[0112] Optionally, when using deep learning technology to obtain a second control scheme for the target shading system, the above-mentioned second control behavior data can also be used to replace some data that are earlier in time in the historical control behavior data of the user for the target shading system, so as to update the historical control behavior data of the user for the target shading system, and based on the updated historical control behavior data of the user for the target light source system, deep learning technology can be used to update the second control scheme to obtain an updated second control scheme.

[0113] The embodiment of the present invention updates the second control scheme based on the second control behavior data of the target shading system after the user controls the target shading system based on the above-mentioned second control scheme. The second control scheme can be continuously updated based on the user's corrected behavior on the target shading system, so that more accurate and more in line with actual demand automatic lighting control can be performed based on the updated second control scheme.

[0114] Based on the contents of the above embodiments, obtaining historical activity behavior data of the user in the target area includes: obtaining historical video stream data in the target area.

[0115] Specifically, historical video stream data in the target area may be acquired based on an image sensor.

[0116] The historical video stream data is processed by frame extraction to obtain the historical image set of the target area.

[0117] Specifically, after acquiring the historical video stream data in the target area, frame extraction processing may be performed on the historical video stream data to obtain an original historical image set of the target area.

[0118] The original historical image set is subjected to image processing, and the original historical image set after image processing can be used as the historical image set of the target area.

[0119] Optionally, the image processing in the embodiment of the present invention may include but is not limited to image cropping and eliminating overly bright or overly dark images.

[0120] Based on deep learning technology, image recognition is performed on images in historical image collections, and historical activity behavior data is obtained based on the image recognition results.

[0121] Specifically, after obtaining a historical image set of the target area, image recognition can be performed on the images in the historical image set based on deep learning technology to obtain image recognition results of the images.

[0122] It should be noted that the above image recognition result may include human body instances in the image and the posture of each human body instance. The above image recognition result may also include large objects in the image.

[0123] After obtaining the above image recognition results, the historical activity behaviors of the user in the target area can be obtained based on the above image recognition results, and then the historical activity behavior data of the user in the target area can be obtained.

[0124] The embodiment of the present invention obtains a historical image set of the target area by performing frame extraction processing on the historical video stream data of the target area, performs image recognition on the images in the historical image set based on deep learning technology, and obtains the historical activity behavior data of the user in the target area based on the image recognition result, so as to obtain the historical activity behavior data of the user in the target area more accurately and efficiently.

[0125] Based on the contents of the above embodiments, based on the historical behavior data and the historical data of light intensity, a first control scheme for the target light source system is generated, including: inputting the historical behavior data and the historical data of light intensity into a lighting control model, and obtaining a first control scheme output by the lighting control model.

[0126] Among them, the lighting control model is obtained after training based on the sample historical data of light intensity in the sample area, the sample historical behavior data of the sample users and the first sample control scheme of the sample area; the sample historical behavior data of the sample users include the historical control behavior data of the sample users on the sample light source system and the historical activity behavior data of the sample users in the sample area; the sample light source system is used for lighting the sample area.

[0127] Specifically, the lighting control model can be trained using sample historical data of light intensity in the sample area, historical activity behavior data of sample users in the sample area, and historical control behavior data of sample users on the sample light source system as samples, and the first sample control scheme of the sample light source system as sample labels to obtain a trained lighting control model.

[0128] It should be noted that the first sample control scheme of the sample light source system can be pre-formulated based on prior knowledge, sample historical data of light intensity in the sample area, historical activity behavior data of sample users in the sample area, and historical control behavior data of sample users on the sample light source system.

[0129] After the trained lighting control model is obtained, the historical data of light intensity in the target area, the historical activity behavior data of users in the target area, and the historical control behavior data of users on the target light source system can be input into the trained lighting control model.

[0130] The trained lighting control model can generate and output a first control scheme for the target light source system based on historical data of light intensity in the target area, historical activity behavior data of users in the target area, and historical control behavior data of users on the target light source system.

[0131] Optionally, after obtaining the first control behavior data of the target light source system after the user controls the target light source system based on the above-mentioned first control scheme, the above-mentioned first control behavior data can also be used to replace some data that are earlier in time sequence in the historical control behavior data of the user on the target light source system, so as to update the historical control behavior data of the user on the target light source system and obtain the updated historical control behavior data of the user on the target light source system.

[0132] By inputting the updated historical control behavior data of the user on the target light source system, the historical data of the light intensity in the target area and the historical activity behavior data of the user in the target area into the above-mentioned trained lighting control model, an updated first control scheme output by the above-mentioned trained lighting control model can be obtained.

[0133] The embodiment of the present invention obtains a first control scheme for the target light source system output by the trained lighting control model by inputting the historical data of light intensity in the target area, the historical activity behavior data of the user in the target area, and the historical control behavior data of the user on the target light source system into the above-mentioned trained lighting control model. The first control scheme for the target light source system can be generated more accurately and efficiently based on the historical data of light intensity in the target area, the historical activity behavior data of the user in the target area, and the historical control behavior data of the user on the target light source system.

[0134] Based on the contents of the above embodiments, the target shading system is controlled based on the second control scheme, including: inputting historical behavior data and historical data of light intensity into a lighting control model, and obtaining a second control scheme output by the lighting control model.

[0135] Among them, the sample historical behavior data of the sample user also includes the sample user's historical control behavior data on the sample shading system; the sample shading system is used for shading the sample area.

[0136] Specifically, when the sample historical behavior data of the sample user also includes the sample user's historical control behavior data of the sample shading system, the lighting control model can be trained using the sample historical data of light intensity in the sample area, the sample user's historical activity behavior data in the sample area, the sample user's historical control behavior data of the sample light source system, and the sample user's historical control behavior data of the sample shading system as samples, and the second sample control scheme of the sample shading system as the sample label to obtain a trained lighting control model.

[0137] It should be noted that the second sample control scheme of the sample shading system can be pre-formulated based on prior knowledge, sample historical data of light intensity in the sample area, historical activity behavior data of sample users in the sample area, historical control behavior data of sample users on the sample light source system, and historical control behavior data of sample users on the sample shading system.

[0138] After obtaining the trained lighting control model, the historical data of light intensity in the target area, the historical activity behavior data of the user in the target area, the historical control behavior data of the user on the target light source system, and the historical control behavior of the user on the target shading system can be input into the above-mentioned trained lighting control model.

[0139] The above-mentioned trained lighting control model can generate and output a first control scheme for the target light source system and a second control scheme for the target shading system based on the historical data of light intensity in the target area, the historical activity behavior data of the user in the target area, the historical control behavior data of the user on the target light source system, and the historical control behavior of the user on the target shading system.

[0140] Optionally, after obtaining the second control behavior data of the target shading system after the user controls the target shading system based on the above-mentioned second control scheme, the above-mentioned second control behavior data can also be used to replace the part of the historical control behavior data of the user on the target shading system that is earlier in time sequence, and the historical control behavior data of the user on the target shading system is updated to obtain the updated historical control behavior data of the user on the target shading system.

[0141] By inputting the updated historical control behavior data of the user on the target light source system, the updated historical control behavior data of the user on the target shading system, the historical data of the light intensity in the target area, and the historical activity behavior data of the user in the target area into the above-mentioned trained lighting control model, an updated first control scheme and an updated second control scheme output by the above-mentioned trained lighting control model can be obtained.

[0142] The embodiment of the present invention obtains a first control scheme for the target light source system and a second control scheme for the target shading system output by the above-trained lighting control model by inputting historical data of light intensity in the target area, historical activity behavior data of the user in the target area, historical control behavior data of the user on the target light source system, and historical control behavior of the user on the target shading system into a trained lighting control model. The first control scheme for the target light source system and the second control scheme for the target shading system can be generated more accurately and efficiently based on the historical data of light intensity in the target area, historical activity behavior data of the user in the target area, historical control behavior data of the user on the target light source system, and historical control behavior of the user on the target shading system.

[0143] Figure 2 Schematic diagram of the structure of the lighting control device based on edge computing provided by the present invention. Figure 2 The lighting control device based on edge computing provided by the present invention is described. The lighting control device based on edge computing described below and the lighting control method based on edge computing provided by the present invention described above can be referred to each other. Figure 2 As shown, the device includes: a data acquisition module 201, a solution generation module 202 and a lighting control module 203.

[0144] The data acquisition module 201 is used to acquire the historical behavior data of the user and the historical data of the light intensity in the target area.

[0145] The solution generation module 202 is used to generate a first control solution for the target light source system based on the historical behavior data and the historical data of the light intensity.

[0146] The lighting control module 203 is used to control the target light source system based on the first control scheme.

[0147] The historical behavior data includes the user's historical control behavior data on the target light source system and the user's historical activity behavior data in the target area; the target light source system is used for lighting the target area.

[0148] Specifically, the data acquisition module 201, the solution generation module 202 and the lighting control module 203 are electrically connected.

[0149] The data acquisition module 201 can be used to acquire historical data of light intensity in a target area using a light sensor, and can also be used to acquire historical behavior data of a user in a variety of ways.

[0150] The solution generation module 202 can be used to obtain the user's behavior pattern, the user's control pattern of the target light source system, and the pattern of light intensity change in the target area based on the above historical behavior data and the above historical data of light intensity. Based on the user's behavior pattern, the user's control pattern of the target light source system, and the pattern of light intensity change in the target area, a first control solution for the target light source system can be generated by numerical calculation, mathematical statistics, etc.

[0151] The solution generation module 202 can also be used to obtain a first control solution for the target light source system based on the historical behavior data of the user and the historical data of the light intensity in the target area by using deep learning technology.

[0152] The lighting control module 203 may be used to control the target light source system based on the first control solution described above.

[0153] Based on the contents of the above embodiments, the lighting control device based on edge computing is an edge device.

[0154] Specifically, when the lighting control device based on edge computing is an edge device, the above-mentioned lighting control device based on edge computing can work independently on the Internet, and data collection and processing are all performed within the above-mentioned lighting control device based on edge computing, which can ensure that the user's privacy is not leaked.

[0155] Optionally, the scheme generation module 202 can also be used to generate a second control scheme for the target shading system based on historical behavior data and historical data of light intensity; based on the second control scheme, the target shading system is controlled; wherein the target shading system is used for shading the target area.

[0156] Optionally, the edge computing-based lighting control device may further include a solution updating module.

[0157] The scheme updating module may be used to obtain first control behavior data of a user on a target light source system; and update a first control scheme based on the first control behavior data.

[0158] The scheme updating module may also be used to obtain second control behavior data of the user on the target shading system; and update the second control scheme based on the second control behavior data.

[0159] Optionally, the data acquisition module 201 can be specifically used to acquire historical video stream data in the target area; perform frame extraction on the historical video stream data to acquire a historical image set of the target area; perform image recognition on the historical image set based on deep learning technology, and acquire historical activity behavior data based on the image recognition results.

[0160] Optionally, the solution generation module 202 can be specifically used to input historical behavior data and historical data of light intensity into a lighting control model to obtain a first control solution output by the lighting control model; wherein the lighting control model is obtained after training based on sample historical data of light intensity in the sample area, sample historical behavior data of sample users, and a first sample control solution for the sample area; the sample historical behavior data includes historical control behavior data of sample users on a sample light source system and historical activity behavior data of sample users in the sample area; the sample light source system is used for lighting the sample area.

[0161] Optionally, the solution generation module 202 can also be specifically used to input historical behavior data and historical data of light intensity into the lighting control model to obtain a second control solution output by the lighting control model; wherein the sample historical behavior data of the sample user also includes the historical control behavior data of the sample user on the sample shading system; the sample shading system is used for shading the sample area.

[0162] The edge computing-based lighting control device in the embodiment of the present invention generates a first control scheme for the target light source system based on the user's historical activity behavior data in the target area, the user's historical control behavior data on the target light source system, and the historical data of light intensity in the target area, and then controls the target light source system based on the above-mentioned first control scheme. The target light source system is used for lighting the target area, and can perform lighting control more intelligently, reduce the user's manual operation, improve user experience and comfort, avoid the situation where the user forgets to turn off the light source system, and reduce energy waste.

[0163] Figure 3 Schematic diagram of the lighting control system based on edge computing provided by the present invention. Figure 3 As shown, the system includes: a lighting control device and a light source system based on edge computing as described above.

[0164] Specifically, the edge computing-based lighting control system may include the above-mentioned edge computing-based lighting control device 301, a network switch 302, a wireless controller (AC) 303, a wireless access point (AP) 304, and a target light source system 306, etc.

[0165] The above-mentioned edge computing-based lighting control device 301, network switch 302 and wireless controller 303 can be installed in the information box 307 corresponding to the target area; the wireless access point 304 and the target light source system 305 can be set in the target area.

[0166] The target light source system 305 can be used to provide lighting for the target area. The target light source system 305 can include a controller 308 of the target light source system and a light source device 309. The controller 308 of the target light source system can control the light source.

[0167] The above-mentioned edge computing-based lighting control device 301, wireless controller 303 and wireless access point 304 are connected to the network switch through a network cable. The wireless controller 303 and the wireless access point 304 can complete the wireless network coverage in the target area.

[0168] The network switch 302 is used for network communication connection of LAN devices, and can realize access and mutual communication of LAN devices in the target area.

[0169] The wireless controller 303 can implement network management of the wireless access points 304 in the target area.

[0170] The wireless access point 304 can achieve wireless signal coverage in the target area.

[0171] The controller 308 of the target light source system can access the local area network in the target area through the wireless access point 304, and the controller 308 of the target light source system can be controlled by the user or the lighting control device 301 based on edge computing, thereby realizing the control of the light source device 309. The controller 308 of the target light source system can also transmit the status of the light source device 309 to the lighting control device 301 based on edge computing.

[0172] Based on the contents of the above embodiments, the lighting control system based on edge computing also includes: a shading system.

[0173] Specifically, the edge computing-based lighting control system may further include a target shading system 310 .

[0174] The target shading system 310 can be used to provide shading for the target area. The target shading system 310 can include a controller 311 of the target shading system and a shading device 312 , and the controller 311 of the target shading system can control the shading device 312 .

[0175] The controller 311 of the target shading system can access the local area network in the target area through the wireless access point 304, and the controller 311 of the target shading system can be controlled by the user or the lighting control device 301 based on edge computing, thereby realizing the control of the shading device 312. The controller 311 of the target shading system can also transmit the state of the shading device 312 to the lighting control device 301 based on edge computing.

[0176] Based on the contents of the above embodiments, the lighting control system based on edge computing further includes: an image sensor 313 and a light intensity sensor 314 .

[0177] The light intensity sensor 314 is used to obtain historical data of light intensity in the target area.

[0178] The image sensor 313 is used to obtain historical video stream data in the target area.

[0179] Specifically, the image sensor 313 can be set in the target area to obtain historical video stream data in the target area, and can access the local area network in the target area through the wireless access point 304 to transmit the collected historical video stream data to the above-mentioned edge computing-based lighting control device 301.

[0180] The light intensity sensor 314 can be set in the target area to obtain historical data of light intensity in the target area, and can access the local area network in the target area through the wireless access point 304 to transmit the collected historical data of light intensity to the above-mentioned edge computing-based lighting control device 301.

[0181] Optionally, the edge computing-based lighting control system in the embodiment of the present invention may further include a memory.

[0182] The memory can be used to store the above historical video stream data and the above historical data of light intensity. The above memory can also be used to store the above first control scheme and the second control scheme. The above memory can also be used to store the lighting control model built based on deep learning technology and related data.

[0183] In order to facilitate the understanding of the edge computing-based lighting control system provided by the present invention, the edge computing-based lighting control system provided by the present invention is illustrated by an example below.

[0184] After the image sensor 313 obtains the historical video stream data in the target area, the light intensity sensor 314 can obtain the historical data of the light intensity in the target area, the controller 308 of the target light source system obtains the historical control behavior data of the user on the target light source system, and the controller 311 of the target shading system obtains the historical control behavior data of the user on the target shading system 310, the image sensor 313, the light intensity sensor 314, the controller 308 of the target light source system, and the controller 311 of the target shading system can send the historical video stream data in the target area, the historical data of the light intensity in the target area, the historical control behavior data of the user on the target light source system, and the historical control behavior data of the user on the target shading system 310 to the lighting control device 301 based on edge computing. The lighting control device 301 based on edge computing can send the above data to the memory for storage.

[0185] The deep learning module in the edge computing-based lighting control device 301 can obtain the historical activity behavior data of the user in the target area based on the historical video stream data in the target area, and can send the above data to the memory for storage.

[0186] The solution generation module 202 in the edge computing-based lighting control device 301 can utilize deep learning technology to obtain a first control solution for the target light source system and a second control solution for the target shading system 310 based on the user's historical activity behavior data in the target area, the historical data of light intensity in the target area, the user's historical control behavior data of the target light source system, and the user's historical control behavior data of the target shading system 310.

[0187] The lighting control module 203 in the edge computing-based lighting control device 301 can send control instructions to the controller 308 of the target light source system based on the first control scheme to control the target light source system, and can also send control instructions to the controller 311 of the target shading system based on the second control scheme to control the target shading system 310.

[0188] The controller 308 of the target light source system can also obtain the first control behavior data of the target light source system after the user controls the target light source system based on the first control scheme, and transmit the first control behavior data to the lighting control device 301 based on edge computing.

[0189] The controller 311 of the target shading system can also obtain the second control behavior data of the target shading system 310 after the user controls the target shading system 310 based on the second control scheme, and transmit the second control behavior data to the lighting control device 301 based on edge computing.

[0190] The data update module in the edge computing-based lighting control device 301 can update the first control scheme based on the above-mentioned first control behavior data; and can also update the second control scheme based on the above-mentioned second control behavior data.

[0191] The lighting control system in the embodiment of the present invention generates a first control scheme for the target light source system based on the user's historical activity behavior data in the target area, the user's historical control behavior data on the target light source system, and the historical data of light intensity in the target area, and then controls the target light source system based on the above-mentioned first control scheme. The target light source system is used for lighting the target area, and can perform lighting control more intelligently, reduce the user's manual operation, improve user experience and comfort, avoid the situation where the user forgets to turn off the light source system, and reduce energy waste.

[0192] Figure 4 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430 and a communication bus 440, wherein the processor 410, the communication interface 420 and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the lighting control method based on edge computing, the method comprising: obtaining the historical behavior data of the user and the historical data of the light intensity in the target area; generating a first control scheme of the target light source system based on the historical behavior data and the historical data of the light intensity; controlling the target light source system based on the first control scheme; wherein the historical behavior data includes the historical control behavior data of the user on the target light source system and the historical activity behavior data of the user in the target area; the target light source system is used for lighting the target area.

[0193] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0194] On the other hand, the present invention also provides a computer program product, which includes a computer program, and the computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the edge computing-based lighting control method provided by the above-mentioned methods, and the method includes: obtaining the user's historical behavior data and the historical data of light intensity in the target area; based on the historical behavior data and the historical data of light intensity, generating a first control scheme for the target light source system; based on the first control scheme, controlling the target light source system; wherein the historical behavior data includes the user's historical control behavior data of the target light source system and the user's historical activity behavior data in the target area; the target light source system is used for lighting the target area.

[0195] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the edge computing-based lighting control method provided by the above-mentioned methods, the method comprising: obtaining historical behavior data of the user and historical data of light intensity in the target area; generating a first control scheme for the target light source system based on the historical behavior data and the historical data of light intensity; controlling the target light source system based on the first control scheme; wherein the historical behavior data includes historical control behavior data of the user on the target light source system and historical activity behavior data of the user in the target area; the target light source system is used for lighting the target area.

[0196] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0197] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0198] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A lighting control method based on edge computing, characterized in that: include: Obtain historical behavior data of users and historical data of light intensity in the target area; Generate a first control scheme for the target light source system based on the historical behavior data and the historical data of light intensity; Based on the first control scheme, controlling the target light source system; The historical behavior data includes the historical control behavior data of the user on the target light source system and the historical activity behavior data of the user in the target area; the target light source system is used for lighting the target area; In the case where the historical behavior data also includes the historical control behavior data of the user on the target shading system, after acquiring the historical behavior data of the user and the historical data of the light intensity in the target area, the method further includes: generating a second control scheme for the target shading system based on the historical behavior data and the historical data of light intensity; Based on the second control scheme, controlling the target shading system; Wherein, the target shading system is used for shading the target area; The target shading system is a controllable curtain, the controllable curtain includes two layers of curtain fabric, the first layer of curtain fabric is light-transmissive, and the second layer of curtain fabric is not light-transmissive, the first shading mode is that the two layers of curtain fabric are both in a closed state, and the second shading mode is that the first layer of curtain fabric is closed, and the second layer of curtain fabric is opened; The second control scheme includes controlling the target shading system to switch from the first shading mode to the second shading mode at 6 a.m. on each working day, controlling the target shading system to turn off the shading mode at 8 a.m. on each working day, and controlling the target shading system to turn on the first shading mode at 19 p.m. on each working day; The target light source system is a lighting lamp, and the lighting lamp includes three lighting modes. The first control scheme includes controlling the target light source system to start the first lighting mode at 6:00 a.m. every weekday, turning off the target light source system at 8:00 a.m. every weekday, and starting the second lighting mode of the target light source system at 19:00 p.m. every weekend; After the target light source system is controlled based on the first control scheme, it also includes: if the user manually controls the target light source system, and the time interval between the moment when the user manually controls the target light source system and the moment when the target light source system was last automatically controlled is less than a first preset value, it is determined that the last automatic control of the target light source system does not meet the user's needs; if the user manually controls the target light source system, and the time interval between the moment when the user manually controls the target light source system and the moment when the target light source system was last automatically controlled is not less than a second preset value, it is determined that the user has a need to increase the control of the target light source system at a second moment; After controlling the target shading system based on the second control scheme, it also includes: if the user manually controls the target shading system, and the duration between the moment when the user manually controls the target shading system and the moment when the target shading system was last automatically controlled is less than a third preset value, it is determined that the last automatic control of the target shading system does not meet user needs; if the user manually controls the target shading system, and the duration between the moment when the user manually controls the target shading system and the moment when the target shading system was last automatically controlled is not less than a fourth preset value, it is determined that the user has a need to increase control over the target shading system at the fourth moment.

2. The lighting control method based on edge computing according to claim 1, characterized in that: After the target light source system is controlled based on the first control scheme, the method further includes: Acquiring first control behavior data of a user on the target light source system; Based on the first control behavior data, the first control scheme is updated.

3. The lighting control method based on edge computing according to claim 1, characterized in that: After the target shading system is controlled based on the second control scheme, the method further includes: Acquiring second control behavior data of the user on the target shading system; Based on the second control behavior data, the second control scheme is updated.

4. The lighting control method based on edge computing according to any one of claims 1 to 3, characterized in that: Obtain the user's historical activity behavior data in the target area, including: Obtain historical video stream data in the target area; Performing frame extraction processing on the historical video stream data to obtain a historical image set of the target area; Image recognition is performed on the historical image set based on deep learning technology, and the historical activity behavior data is obtained based on the image recognition results.

5. The lighting control method based on edge computing according to claim 1, characterized in that: The generating a first control scheme for the target light source system based on the historical behavior data and the historical data of the light intensity includes: Inputting the historical behavior data and the historical data of light intensity into a lighting control model to obtain the first control scheme output by the lighting control model; Among them, the lighting control model is obtained after training based on sample historical data of light intensity in the sample area, sample historical behavior data of sample users and the first sample control scheme of the sample area; the sample historical behavior data includes the historical control behavior data of the sample user on the sample light source system and the historical activity behavior data of the sample user in the sample area; the sample light source system is used for lighting the sample area.

6. The lighting control method based on edge computing according to claim 5, characterized in that: The controlling of the target shading system based on the second control scheme includes: Inputting the historical behavior data and the historical data of light intensity into the lighting control model to obtain the second control scheme output by the lighting control model; The sample historical behavior data of the sample user also includes the sample user's historical control behavior data on the sample shading system; the sample shading system is used for shading the sample area.

7. A lighting control device based on edge computing, characterized in that: include; A data acquisition module, used to acquire historical behavior data of users and historical data of light intensity in a target area; A scheme generating module, used for generating a first control scheme for a target light source system based on the historical behavior data and the historical data of light intensity; A lighting control module, configured to control the target light source system based on the first control scheme; The historical behavior data includes the historical control behavior data of the user on the target light source system and the historical activity behavior data of the user in the target area; the target light source system is used for lighting the target area; In the case where the historical behavior data also includes the historical control behavior data of the user on the target shading system, after acquiring the historical behavior data of the user and the historical data of the light intensity in the target area, the method further includes: generating a second control scheme for the target shading system based on the historical behavior data and the historical data of light intensity; Based on the second control scheme, controlling the target shading system; Wherein, the target shading system is used for shading the target area; The target shading system is a controllable curtain, the controllable curtain includes two layers of curtain fabric, the first layer of curtain fabric is light-transmissive, and the second layer of curtain fabric is not light-transmissive, the first shading mode is that the two layers of curtain fabric are both in a closed state, and the second shading mode is that the first layer of curtain fabric is closed, and the second layer of curtain fabric is opened; The second control scheme includes controlling the target shading system to switch from the first shading mode to the second shading mode at 6 a.m. on each working day, controlling the target shading system to turn off the shading mode at 8 a.m. on each working day, and controlling the target shading system to turn on the first shading mode at 19 p.m. on each working day; The target light source system is a lighting lamp, and the lighting lamp includes three lighting modes. The first control scheme includes controlling the target light source system to start the first lighting mode at 6:00 a.m. every weekday, turning off the target light source system at 8:00 a.m. every weekday, and starting the second lighting mode of the target light source system at 19:00 p.m. every weekend; After the target light source system is controlled based on the first control scheme, it also includes: if the user manually controls the target light source system, and the time interval between the moment when the user manually controls the target light source system and the moment when the target light source system was last automatically controlled is less than a first preset value, it is determined that the last automatic control of the target light source system does not meet the user's needs; if the user manually controls the target light source system, and the time interval between the moment when the user manually controls the target light source system and the moment when the target light source system was last automatically controlled is not less than a second preset value, it is determined that the user has a need to increase the control of the target light source system at a second moment; After controlling the target shading system based on the second control scheme, it also includes: if the user manually controls the target shading system, and the duration between the moment when the user manually controls the target shading system and the moment when the target shading system was last automatically controlled is less than a third preset value, it is determined that the last automatic control of the target shading system does not meet user needs; if the user manually controls the target shading system, and the duration between the moment when the user manually controls the target shading system and the moment when the target shading system was last automatically controlled is not less than a fourth preset value, it is determined that the user has a need to increase control over the target shading system at the fourth moment.

8. The lighting control device based on edge computing according to claim 7, characterized in that: The edge computing-based lighting control device is an edge device.

9. A lighting control system based on edge computing, characterized in that: include: A lighting control device and light source system based on edge computing as described in claim 7 or 8.

10. The edge computing-based lighting control system according to claim 9, characterized in that: Also includes: Shading system.

11. The edge computing-based lighting control system according to claim 9 or 10, characterized in that: Also includes: Image sensors and light intensity sensors; The light intensity sensor is used to obtain historical data of light intensity in the target area; The image sensor is used to obtain historical video stream data in the target area.

12. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the edge computing-based lighting control method as described in any one of claims 1 to 6 is implemented.

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