A linkage lighting control method, system, device and medium based on multiple devices

Abstract

The present invention discloses a linkage lighting control method, system, device and medium based on multiple devices, which relates to the field of lighting control technology, including obtaining lighting space information based on lighting places, collecting ambient light intensity and personnel action information in the lighting space by deploying sensors, and obtaining user-set lighting information; calculating lighting control brightness based on ambient light intensity and user-set lighting information, optimizing the lighting spectrum by adjusting the spectral power distribution of the lighting light source, and forming a lighting control scheme based on the lighting control brightness and the lighting spectrum; constructing a personnel action prediction model to predict user actions, generating a lighting control scheme at the lighting space position according to the predicted user actions, and applying the personnel action prediction model after further optimization through a reinforcement learning algorithm. The present invention realizes the optimization of lighting light efficiency ratio, improves lighting efficiency, and effectively improves the flexibility and real-time performance of lighting control.

Description

Technical Field

[0001] The present invention relates to the field of lighting control technology, and in particular to a method, system, device and medium for linkage lighting control based on multiple devices. Background Art

[0002] With the rapid development of smart home technology, multi-device based intelligent lighting control systems have become an important part of modern life. In recent years, intelligent lighting systems have undergone a transformation from single control to multi-device linkage. Initially, intelligent lighting systems mainly relied on simple sensors and timing control to achieve basic lighting management, but with the development of artificial intelligence and Internet of Things technologies, more and more intelligent lighting systems have begun to support dynamic adjustment based on environmental conditions and user needs. Modern intelligent lighting can not only automatically adjust the brightness according to the ambient light intensity, time period, etc., but also achieve smarter and more sophisticated control by integrating multiple sensors (such as motion sensors, temperature and humidity sensors, spectrum sensors, etc.).

[0003] However, the existing lighting control technology still has shortcomings. Its lighting brightness and spectral distribution optimization problems often lack refined control, the lighting effect often fails to achieve the best light efficiency and comfort, and there is a lack of precise control over the spectral power distribution of the light source, which affects the overall lighting quality and energy efficiency. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a linkage lighting control method, system, device and medium based on multiple devices to solve the problem that the prior art lighting brightness and spectral distribution optimization problems often lack refined control and lack precise control of the spectral power distribution of the light source.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a linkage lighting control method based on multiple devices, which comprises:

[0008] Obtain lighting space information based on lighting locations, collect ambient light intensity and personnel movement information in the lighting space by deploying sensors, and obtain user-set lighting information;

[0009] Calculate the lighting control brightness based on the ambient light intensity and the user-set lighting information, optimize the lighting spectrum by adjusting the spectral power distribution of the lighting source, and form a lighting control plan based on the lighting control brightness and lighting spectrum;

[0010] Construct a personnel action prediction model to predict user actions, generate a lighting space control plan based on the predicted user actions at the lighting space location, and further optimize the personnel action prediction model through a reinforcement learning algorithm before applying it;

[0011] Display the applied lighting control scheme and store it in the lighting control database;

[0012] The lighting control scheme based on lighting control brightness and lighting spectrum refers to taking the ground center of the lighting space as the measurement point, defining the ground normal vector plane, calculating the angle between the lighting source and the measurement point, calculating the luminous flux of each lighting source by multiplying the brightness and the angle, and calculating the wavelength. Spectral efficiency under , calculate the radiant flux based on the spectral efficiency and wavelength of each lighting source;

[0013] The adjustment wavelength range of each lighting source is randomly generated to form a genetic individual and a genetic population, constraints are set for each genetic individual, fitness is defined according to luminous flux and radiant flux, the individuals in the genetic population are iterated through a genetic algorithm to obtain the optimal individual, and the wavelength adjustment range of each lighting source in the optimal individual is extracted to form a lighting spectrum to form a lighting control scheme;

[0014] The lighting control scheme includes a lighting light control scheme and a lighting space control scheme.

[0015] As a preferred solution of the linkage lighting control method based on multiple devices described in the present invention, wherein: the lighting control brightness is calculated based on the ambient light intensity and the user-set lighting information, and the lighting spectrum is optimized by adjusting the spectral power distribution of the lighting light source, and the lighting control scheme is formed based on the lighting control brightness and the lighting spectrum, which means setting the lighting intensity information from the user-set lighting information, calculating the set lighting intensity and ambient light intensity The difference between the two gets the lighting control brightness , if the lighting controls the brightness If it is less than or equal to 0, the lighting will not be turned on, otherwise the lighting will be turned on;

[0016] Synchronously obtain the number, position and power of lighting sources in the lighting space, calculate the angle between the lighting source and the measurement point, and calculate the luminous flux of each lighting source by multiplying the brightness and the angle :

[0017]

[0018] in is the angle between the ith illumination source and the measurement point, is the brightness of the i-th light source;

[0019] Determine the optical function V according to the CIE standard, and use the optical function V to calculate the wavelength Spectral efficiency under :

[0020]

[0021] in The wavelength of the illumination light source is The light source efficiency under The wavelength The value of the optical function under ;

[0022] Calculate the radiant flux of each illumination source based on its wavelength :

[0023]

[0024] in is the wavelength range of the illumination source, The radiation spectrum at wavelength The value of

[0025] Randomly generate the adjustment wavelength range of each lighting source, form all lighting sources in the lighting space into genetic individuals and integrate all genetic individuals to form a genetic population;

[0026] Constraints are set for each genetic individual based on the measured point brightness and CIEDE2000 color difference:

[0027]

[0028] Where n is the number of light sources in the lighting space, is the power of the i-th lighting source, is the distance between the ith illumination source and the measurement point, is the color difference, is the color difference threshold, , as well as is the value of the wavelength-adjusted illumination source in the CIE 1976 color space, , b and c are the values ​​of the initial illumination source in the CIE 1976 color space;

[0029] Through the genetic algorithm, individuals in the genetic population are iterated, the ratio of luminous flux to radiation flux is calculated as the light efficiency ratio, the light efficiency ratios of all light sources in the genetic individual are added as the fitness of the genetic individual, and the genetic individual with the highest fitness that meets the constraints is selected for crossover mutation until the fitness converges and stops, and the genetic individual with the highest fitness that meets the constraints in the iterative genetic population is selected as the optimal individual, the wavelength adjustment range of each lighting source in the optimal individual is extracted to form a lighting spectrum, and the lighting control brightness and lighting spectrum form a lighting light control plan.

[0030] As a preferred solution of the multi-device linkage lighting control method described in the present invention, wherein: the construction of a personnel action prediction model to predict user actions, and generating an optimized lighting space control solution at a lighting space position according to the predicted user actions refers to constructing a personnel action prediction model based on an LSTM network, training the personnel action prediction model based on personnel action information, and predicting future personnel actions based on the trained model, and judging the future user's lighting space position according to future personnel actions and lighting space information;

[0031] The time when the user moves to the lighting space position is set as the lighting space control plan generation time. If the user moves to a new lighting space, the lighting equipment of the original lighting space is turned off when the user moves to the new lighting space, and the lighting equipment of the new lighting space is enabled to apply the lighting space control plan.

[0032] As a preferred solution of the multi-device linkage lighting control method described in the present invention, the further optimization of the personnel motion prediction model through the reinforcement learning algorithm and then applying it refers to using the Q-learning reinforcement learning algorithm to set a reward mechanism to regularly further optimize the personnel motion prediction model and verify the accuracy of the optimized model, and apply the personnel motion prediction model after passing the accuracy test.

[0033] As a preferred solution of the multi-device linkage lighting control method described in the present invention, wherein: the acquisition of lighting space information based on lighting places, and collecting ambient light intensity and human movements in the lighting space by deploying sensors, and obtaining user-set lighting information refers to acquiring lighting space information based on lighting place queries, deploying ambient light sensors and motion sensors in the lighting space to collect ambient light intensity and human movements, and obtaining user-set lighting information through users, and connecting all sensors through a low-latency communication network to form a sensor network.

[0034] As a preferred solution of the multi-device linkage lighting control method described in the present invention, wherein: the display of the applied lighting control scheme refers to displaying the lighting control scheme generated for each lighting space, and synchronously displaying the lighting control scheme replacement record after the user leaves the lighting space.

[0035] As a preferred solution of the multi-device linkage lighting control method described in the present invention, the storage in the lighting control database refers to storing the lighting control plan and replacement records in the lighting control database, the database adds timestamp and location information to the stored data, and uploads it to the cloud for backup.

[0036] In a second aspect, the present invention provides a multi-device linkage lighting control system, comprising:

[0037] A data collection module is used to collect lighting space information, ambient light intensity, personnel movement information, and user-set lighting information;

[0038] The linkage control module is used to calculate the lighting control brightness according to the lighting space information and the ambient light intensity, and to optimize the lighting control scheme by adjusting the spectral power distribution of the lighting source;

[0039] The prediction optimization module is used to build a personnel motion prediction model to predict personnel motion, and use the reinforcement learning algorithm to optimize the personnel motion prediction model for application;

[0040] The display and storage module is used to display and record the user's lighting control plan and store it in the database.

[0041] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the multi-device linkage lighting control method as described in the first aspect of the present invention is implemented.

[0042] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the multi-device linkage lighting control method as described in the first aspect of the present invention is implemented.

[0043] The beneficial effects of the present invention are as follows: the present invention calculates the lighting control intensity by collecting lighting space information and ambient light intensity, and optimizes the lighting spectrum by adjusting the spectral power distribution of multiple lighting light sources, thereby optimizing the lighting light efficiency ratio and improving the lighting efficiency. Moreover, the present invention predicts user actions by constructing a prediction model, thereby effectively improving the flexibility and real-time performance of lighting control. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0045] Figure 1 This is a flow chart of the multi-device linked lighting control method in Example 1.

[0046] Figure 2 This is a structural diagram of the multi-device linkage lighting control system in Example 1. DETAILED DESCRIPTION

[0047] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0048] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0049] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0050] Example 1, reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, and provides a linkage lighting control method based on multiple devices, comprising the following steps:

[0051] S1. Obtain lighting space information based on the lighting location, collect ambient light intensity and personnel movement information in the lighting space by deploying sensors, and obtain user-set lighting information;

[0052] Specifically, obtaining lighting space information based on lighting places, collecting ambient light intensity and human movements in the lighting space by deploying sensors, and obtaining user-set lighting information refers to obtaining lighting space information based on lighting place queries, deploying ambient light sensors and motion sensors in the lighting space to collect ambient light intensity and human movements, and obtaining user-set lighting information through users, and connecting all sensors through a low-latency communication network to form a sensor network.

[0053] By querying the lighting space information, the system can accurately grasp the specific configuration of each lighting location. This information provides a basis for subsequent intelligent adjustment. Ambient light sensors and motion sensors are deployed and connected through a low-latency communication network to form a sensor network for real-time data collection and transmission. The deployment of this sensor network helps to optimize lighting control in multiple dimensions. The sensor network enables the lighting system to perceive and adapt to changes in the environment and user behavior in real time, greatly improving the response speed and efficiency of the system. The use of low-latency communication networks effectively solves the control lag problem caused by sensor data transmission delays in existing technologies. In intelligent lighting systems, the rapid transmission of sensor data is crucial. Through low-latency network connections, the system can respond quickly and adjust the lighting intensity or color temperature when the user enters or leaves the room or the ambient light intensity changes.

[0054] S2. Calculate the lighting control brightness based on the ambient light intensity and the user-set lighting information, optimize the lighting spectrum by adjusting the spectral power distribution of the lighting light source, and form a lighting control plan based on the lighting control brightness and the lighting spectrum;

[0055] Specifically, the lighting control brightness is calculated based on the ambient light intensity and the user-set lighting information, and the lighting spectrum is optimized by adjusting the spectral power distribution of the lighting source. The lighting control scheme is formed based on the lighting control brightness and the lighting spectrum, which means setting the lighting intensity information from the user-set lighting information, and calculating the set lighting intensity. and ambient light intensity The difference between the two gets the lighting control brightness , if the lighting controls the brightness If it is less than or equal to 0, the lighting will not be turned on, otherwise the lighting will be turned on;

[0056] The ground center of the lighting space is used as the measurement point, the ground normal vector plane is defined, the number, position and power of the lighting sources in the lighting space are obtained synchronously, the angle between the lighting source and the measurement point is calculated, and the luminous flux of each lighting source is calculated by multiplying the brightness and the angle. :

[0057]

[0058] in is the angle between the ith illumination source and the measurement point, is the brightness of the i-th light source;

[0059] Determine the optical function V according to the CIE standard, and use the optical function V to calculate the wavelength Spectral efficiency under :

[0060]

[0061] in The wavelength of the illumination light source is The light source efficiency under the condition can be obtained through experiments. The wavelength The photopic function value under , is given by the International Illumination Commission standard;

[0062] Calculate the radiant flux of each illumination source based on its wavelength :

[0063]

[0064] in is the wavelength range of the illumination source, The radiation spectrum at wavelength The value of is obtained by measuring with a spectrum analyzer;

[0065] Randomly generate the adjustment wavelength range of each lighting source, form all lighting sources in the lighting space into genetic individuals and integrate all genetic individuals to form a genetic population;

[0066] Constraints are set for each genetic individual based on the measured point brightness and CIEDE2000 color difference:

[0067]

[0068] Where n is the number of light sources in the lighting space, is the power of the i-th lighting source, is the distance between the ith illumination source and the measurement point, is the color difference, is the color difference threshold, , as well as is the value of the wavelength-adjusted illumination source in the CIE 1976 color space, , b and c are the values ​​of the initial illumination source in the CIE 1976 color space;

[0069] The individuals in the genetic population are iterated through a genetic algorithm, and the ratio of luminous flux to radiant flux is calculated as the light efficiency ratio. The light efficiency ratios of all light sources in the genetic individual are added as the fitness of the genetic individual. The genetic individual with the highest fitness and satisfying the constraints is selected for crossover mutation, and the process stops after the fitness converges. The genetic individual with the highest fitness and satisfying the constraints in the iterative genetic population is selected as the optimal individual. The wavelength adjustment range of each lighting source in the optimal individual is extracted to form a lighting spectrum, and the lighting control brightness and the lighting spectrum are formed into a lighting control scheme.

[0070] By calculating the lighting control brightness and setting the switching conditions, the lighting system can be intelligently controlled according to the real-time ambient light intensity and the lighting requirements set by the user. This not only improves the intelligence level of the system, but also effectively avoids energy waste. This process realizes dynamic lighting control, significantly improves energy efficiency, and enhances the adaptability of the system. By adjusting the spectral power distribution of the lighting source, the system can more finely control the color and light effect of the light source output and optimize the light efficiency ratio. This optimization method is more advantageous than the traditional lighting system with fixed spectral distribution, because it not only improves the lighting efficiency, but also improves the adaptability of the light source in different scenes. By introducing genetic algorithms to optimize the lighting source, the present invention can intelligently select the optimal lighting source configuration to achieve the best lighting effect and energy efficiency. The system can simulate multiple lighting schemes to find the most energy-saving solution that meets user needs, further improving the intelligence and optimization capabilities of the system. By combining CIEDE2000 color difference and CIE By calculating the 1976 color space, the system can accurately adjust the color temperature and color output of the lighting source, which not only ensures the comfort and naturalness of the lighting effect, but also meets the personalized needs of users. The system can automatically adjust the color temperature according to the user's environmental needs and visual preferences to avoid discomfort or visual fatigue caused by excessive color difference, thereby improving the overall visual comfort and light efficiency ratio. This method makes lighting control more precise and humane.

[0071] S3, constructing a personnel action prediction model to predict user actions, generating a lighting control scheme at the lighting space location based on the predicted user actions, and further optimizing the personnel action prediction model through a reinforcement learning algorithm for application;

[0072] Specifically, constructing a personnel action prediction model to predict user actions, and generating an optimized lighting control scheme at a lighting space position according to the predicted user actions refers to constructing a personnel action prediction model based on an LSTM network, training the personnel action prediction model based on personnel action information, wherein the personnel action refers to a position change, and predicting future personnel actions based on the trained model, and determining the future user's lighting space position according to the future personnel actions and lighting space information;

[0073] The time when the user moves to the lighting space position is set as the lighting space control plan generation time. If the user moves to a new lighting space, the lighting equipment of the original lighting space is turned off when the user moves to the new lighting space, and the lighting equipment of the new lighting space is enabled to apply the lighting space control plan.

[0074] By introducing the LSTM network for predicting human motion, the common problems of delayed response and inaccurate adjustment in traditional intelligent lighting systems are solved. The application of the LSTM network enables the system to capture the long-term dependence and short-term behavioral changes of users in the lighting space, so as to more accurately predict the user's future activities. Through the training of the human motion prediction model, the system can accurately predict future actions based on the user's historical behavioral habits. Compared with the traditional sensor-based passive response method, this dynamic lighting control solution based on behavior prediction is more efficient and flexible. Before the user enters a room, the system can adjust the brightness of the room or turn on the lighting based on motion prediction, avoiding the need to start adjusting when the user arrives, thereby enhancing the user's comfort experience. Through accurate prediction and control, the system can maximize energy saving effects. By automatically turning off the lighting equipment in the original lighting space and enabling the lighting in the new area when the user moves, the system can ensure efficient use of lighting and effectively avoid energy waste.

[0075] Furthermore, further optimizing the personnel motion prediction model through the reinforcement learning algorithm and then applying it means using the Q-learning reinforcement learning algorithm to set a reward mechanism to periodically further optimize the personnel motion prediction model and verify the accuracy of the optimized model, and applying the personnel motion prediction model after passing the accuracy test.

[0076] The application of the Q-learning algorithm in the present invention solves the problem of poor adaptability to dynamic environments in traditional prediction methods. By continuously interacting with the environment and adjusting strategies based on feedback, the Q-learning algorithm enables the personnel action prediction model to adapt to real-time changes in user behavior. By setting a reward mechanism, the system can ensure that the personnel action prediction model develops in a more accurate direction in each iteration. The reward mechanism will encourage the model to select the optimal behavior path in the prediction. This mechanism enables the model to gradually adjust and improve the prediction accuracy from continuous feedback. The accuracy verification of the optimized model ensures that its accuracy and stability meet expectations before the prediction model is applied. Through regular verification, the system can promptly discover potential problems in the model and make adjustments. This feedback mechanism ensures the efficient operation of the lighting control system, especially when the ambient lighting conditions change greatly or the user behavior is more complex. The optimized prediction model can provide an accurate lighting control solution to ensure that the system can accurately adjust the parameters such as the switch and brightness of the lighting equipment to meet the needs under different environmental conditions.

[0077] S4, displaying the applied lighting control solution and storing it in the lighting control database;

[0078] Specifically, displaying the applied lighting control scheme refers to displaying the lighting control scheme generated for each lighting space, and synchronously displaying the lighting control scheme replacement record after the user leaves the lighting space.

[0079] Furthermore, storing in a lighting control database means storing the lighting control plan and the replacement record in the lighting control database, the database adds a timestamp and location information to the stored data, and uploads it to the cloud for backup.

[0080] This embodiment also provides a multi-device linkage lighting control system, including:

[0081] A data collection module is used to collect lighting space information, ambient light intensity, personnel movement information, and user-set lighting information;

[0082] The linkage control module is used to calculate the lighting control brightness according to the lighting space information and the ambient light intensity, and to optimize and form a lighting control scheme by adjusting the spectral power distribution of the lighting source;

[0083] The prediction optimization module is used to build a personnel motion prediction model to predict personnel motion, and use the reinforcement learning algorithm to optimize the personnel motion prediction model for application;

[0084] The display and storage module is used to display and record the user's lighting control plan and store it in the database.

[0085] This embodiment also provides a computer device, which is suitable for the case of a linkage lighting control method based on multiple devices, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the linkage lighting control method based on multiple devices as proposed in the above embodiment.

[0086] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0087] The present embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for realizing linkage lighting control based on multiple devices as proposed in the above embodiment is implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0088] In summary, the present invention calculates the lighting control intensity by collecting lighting space information and ambient light intensity, and optimizes the lighting spectrum by adjusting the spectral power distribution of multiple lighting light sources, thereby optimizing the lighting light efficiency ratio and improving the lighting efficiency. Moreover, by constructing a prediction model to predict user actions, the flexibility and real-time performance of lighting control are effectively improved.

[0089] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A linkage lighting control method based on multiple devices, characterized in that: include, Obtain lighting space information based on lighting locations, collect ambient light intensity and personnel movement information in the lighting space by deploying sensors, and obtain user-set lighting information; Calculate the lighting control brightness based on the ambient light intensity and the user-set lighting information, specifically including setting the lighting intensity information from the user-set lighting information, and calculating the set lighting intensity and ambient light intensity The difference between the two gets the lighting control brightness , if the lighting controls the brightness If it is less than or equal to 0, the lighting will not be turned on, otherwise the lighting will be turned on; Synchronously obtain the number, position and power of lighting sources in the lighting space, calculate the angle between the lighting source and the measurement point, and calculate the luminous flux of each lighting source by multiplying the brightness and the angle : in is the angle between the ith illumination source and the measurement point, is the brightness of the i-th light source; Determine the optical function V according to the CIE standard, and use the optical function V to calculate the wavelength Spectral efficiency under : in The wavelength of the illumination light source is The light source efficiency under The wavelength The value of the optical function under ; Calculate the radiant flux of each illumination source based on its wavelength : in is the wavelength range of the illumination source, The radiation spectrum at wavelength The value of Optimize the lighting spectrum by adjusting the spectral power distribution of the lighting source, and form a lighting control scheme based on lighting control brightness and lighting spectrum; Construct a personnel action prediction model to predict user actions, generate a lighting space control plan based on the predicted user actions at the lighting space location, and further optimize the personnel action prediction model through a reinforcement learning algorithm before applying it; Display the applied lighting control scheme and store it in the lighting control database; The lighting control scheme based on lighting control brightness and lighting spectrum refers to taking the ground center of the lighting space as the measurement point, defining the ground normal vector plane, calculating the angle between the lighting source and the measurement point, calculating the luminous flux of each lighting source by multiplying the brightness and the angle, and calculating the wavelength. Spectral efficiency under , calculate the radiant flux based on the spectral efficiency and wavelength of each lighting source; The adjustment wavelength range of each lighting source is randomly generated to form a genetic individual and a genetic population, constraints are set for each genetic individual, fitness is defined according to luminous flux and radiant flux, the individuals in the genetic population are iterated through a genetic algorithm to obtain the optimal individual, and the wavelength adjustment range of each lighting source in the optimal individual is extracted to form a lighting spectrum to form a lighting control scheme; The lighting control scheme includes a lighting light control scheme and a lighting space control scheme.

2. The method for controlling lighting based on linkage of multiple devices according to claim 1, characterized in that: The lighting spectrum is optimized by adjusting the spectral power distribution of the lighting light source, and the lighting light control scheme is formed based on the lighting control brightness and the lighting spectrum, which means randomly generating an adjustment wavelength range for each lighting light source, forming all lighting light sources in the lighting space into genetic individuals, and integrating all genetic individuals to form a genetic population; Constraints are set for each genetic individual based on the measured point brightness and CIEDE2000 color difference: Where n is the number of light sources in the lighting space, is the power of the i-th lighting source, is the distance between the ith illumination source and the measurement point, is the color difference, is the color difference threshold, , as well as is the value of the wavelength-adjusted illumination source in the CIE 1976 color space, , b and c are the values ​​of the initial illumination source in the CIE 1976 color space; Through the genetic algorithm, individuals in the genetic population are iterated, the ratio of luminous flux to radiation flux is calculated as the light efficiency ratio, the light efficiency ratios of all light sources in the genetic individual are added as the fitness of the genetic individual, and the genetic individual with the highest fitness that meets the constraints is selected for crossover mutation until the fitness converges and stops, and the genetic individual with the highest fitness that meets the constraints in the iterative genetic population is selected as the optimal individual, the wavelength adjustment range of each lighting source in the optimal individual is extracted to form a lighting spectrum, and the lighting control brightness and lighting spectrum form a lighting light control plan.

3. The method for controlling lighting based on linkage of multiple devices as claimed in claim 2, characterized in that: The constructing of the personnel action prediction model to predict the user action, and generating the lighting space control scheme at the lighting space position according to the predicted user action refers to constructing the personnel action prediction model based on the LSTM network, training the personnel action prediction model based on the personnel action information, predicting the future personnel action based on the trained model, and judging the future user's lighting space position according to the future personnel action and lighting space information; The time when the user moves to the lighting space position is set as the lighting space control plan generation time. If the user moves to a new lighting space, the lighting equipment of the original lighting space is turned off when the user moves to the new lighting space, and the lighting equipment of the new lighting space is enabled to apply the lighting space control plan.

4. The method for controlling lighting based on linkage of multiple devices as claimed in claim 3, characterized in that: The further optimization of the personnel motion prediction model through the reinforcement learning algorithm and then applying it refers to using the Q-learning reinforcement learning algorithm to set a reward mechanism to regularly further optimize the personnel motion prediction model and verify the accuracy of the optimized model, and applying the personnel motion prediction model after passing the accuracy test.

5. The method for controlling lighting based on linkage of multiple devices as claimed in claim 4, characterized in that: The obtaining of lighting space information based on lighting places, collecting ambient light intensity and personnel movement information in the lighting space by deploying sensors, and obtaining user-set lighting information refers to obtaining lighting space information based on lighting place queries, deploying ambient light sensors and motion sensors in the lighting space to collect ambient light intensity and personnel movement, obtaining user-set lighting information through users, and connecting all sensors through a low-latency communication network to form a sensor network.

6. The method for controlling lighting based on linkage of multiple devices as claimed in claim 5, characterized in that: The display of the applied lighting control scheme refers to displaying the lighting control scheme generated for each lighting space, and synchronously displaying the lighting control scheme replacement record after the user leaves the lighting space.

7. The method for controlling lighting based on linkage of multiple devices as claimed in claim 6, characterized in that: The storing in the lighting control database refers to storing the lighting control plan and the replacement record in the lighting control database, the database adds a timestamp and location information to the stored data, and uploads it to the cloud for backup.

8. A multi-device linkage lighting control system, based on the multi-device linkage lighting control method according to any one of claims 1 to 7, characterized in that: include, A data collection module is used to collect lighting space information, ambient light intensity, personnel movement information, and user-set lighting information; The linkage control module is used to calculate the lighting control brightness according to the lighting space information and the ambient light intensity, and to optimize the lighting control scheme by adjusting the spectral power distribution of the lighting source; The prediction optimization module is used to build a personnel motion prediction model to predict personnel motion, and use the reinforcement learning algorithm to optimize the personnel motion prediction model for application; The display and storage module is used to display and record the user's lighting control plan and store it in the database.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the multi-device linkage lighting control method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the multi-device linkage lighting control method according to any one of claims 1 to 7 are implemented.

Images