Remote LED lighting method and system based on Internet of Things

Abstract

The invention relates to the technical field of lighting systems, and provides a remote LED lighting method and system based on the Internet of Things. Obtaining an initial parameter of a lighting system through the Internet of Things, and generating a multi-dimensional lighting function based on the initial LED parameters of the lighting node and the neighbor node corresponding to the LED equipment; inputting the LED parameters of the illumination node and the neighbor node thereof at the current moment into an illumination function, and determining the state variable of the illumination node at the next moment; dynamically modulating a state variable according to the power supply parameter and the LED parameter, and determining the signal frequency of a current signal passing through the LED equipment; and controlling the LED equipment to illuminate based on the state variable and the signal frequency. By determining the multi-dimensional illumination function, dynamically predicting the state variable and modulating the current signal frequency, the adaptability and flexibility of illumination are improved, the luminous efficiency of the illumination system is enhanced, and the energy consumption is reduced.

Description

Technical Field

[0001] This application relates to the technical field of lighting systems, and more particularly, to a remote LED lighting method and system based on the Internet of Things. Background Art

[0002] With the rise of smart cities, the lighting system, as an important part of urban infrastructure, is also developing towards intelligence and networking. The remote LED lighting method based on the Internet of Things can achieve remote monitoring and management of the lighting system, improving the intelligent level of urban lighting. LED lighting has higher energy efficiency compared to traditional lighting, and the remote control technology based on the Internet of Things can further achieve lighting on demand, avoiding energy waste caused by over-illumination, thus meeting the requirements of energy conservation and consumption reduction.

[0003] The remote LED lighting system based on the Internet of Things involves multiple components, and the system architecture is relatively complex. The traditional lighting system lacks intelligent control, and the control accuracy and flexibility of the LED lighting system are relatively low. Summary of the Invention

[0004] This application provides a remote LED lighting method and system based on the Internet of Things, which can at least to some extent solve the problem of relatively low control accuracy and flexibility of the LED lighting system.

[0005] Other features and advantages of this application will become apparent through the following detailed description, or be learned in part through the practice of this application.

[0006] According to one aspect of this application, a remote LED lighting method based on the Internet of Things is provided, including: obtaining the initial parameters of the lighting system through the Internet of Things, where the initial parameters include the initial LED parameters of the LED devices in the lighting system and the power supply parameters of the lighting system; generating a multi-dimensional lighting function based on the initial LED parameters of the lighting nodes and neighbor nodes corresponding to the LED devices; inputting the LED parameters of the lighting node and its neighbor nodes at the current moment into the lighting function to determine the state variables of the lighting node at the next moment; dynamically modulating the current signal output by the power supply according to the power supply parameters and the LED parameters to determine the signal frequency of the current signal passing through the LED device; and controlling the LED device to perform lighting based on the state variables and the signal frequency.

[0007] In this application, based on the foregoing solution, the obtaining the initial parameters of the lighting system through the Internet of Things includes: constructing the Internet of Things based on the lighting system, where the Internet of Things includes a perception layer, a network layer, a platform layer, and an application layer; and obtaining the initial parameters of the lighting system based on the Internet of Things.

[0008] In this application, based on the foregoing solution, generating a multi-dimensional lighting function based on the initial LED parameters of the lighting nodes and neighbor nodes corresponding to the LED device includes: obtaining the total number and location information of the lighting nodes in the lighting system through the Internet of Things; determining the neighbor nodes of the lighting nodes according to the location information; obtaining the initial LED parameters of the lighting nodes and their neighbor nodes, and generating a multi-dimensional lighting function based on the initial LED parameters and the total number.

[0009] In this application, based on the foregoing solution, inputting the LED parameters of the lighting nodes and their neighbor nodes at the current moment into the lighting function to determine the state variables of the lighting nodes at the next moment includes: inputting the brightness parameter, color temperature parameter, and energy efficiency parameter of the lighting nodes at the current moment, and the brightness parameter of the neighbor nodes of the lighting nodes at the current moment, into the lighting function for solution to determine the state variables of the lighting nodes at the next moment.

[0010] In this application, based on the foregoing solution, dynamically modulating the current signal output by the power supply according to the power supply parameters and the LED parameters to determine the signal frequency of the current signal passing through the LED device includes: determining the time-domain distribution of the current signal according to the pulse period of the current signal in the power supply parameters; dynamically modulating the current signal output by the power supply according to the time-domain distribution and the initial lattice period in the LED parameters to determine the signal frequency of the current signal passing through the LED device.

[0011] In this application, based on the foregoing solution, controlling the LED device to perform lighting based on the state variables and the signal frequency includes: parsing the state variables based on a preset mapping relationship to generate control parameters; generating a control instruction according to the control parameters and the signal frequency, and sending the control instruction to the driving module of the LED; the driving module compiles the control instruction into a driving signal to control the LED device to perform lighting through the driving signal.

[0012] In this application, based on the foregoing solution, after controlling the LED device to perform lighting based on the state variables and the signal frequency, it further includes: obtaining the working parameters of the LED during the lighting process, statistically analyzing the working parameters to generate a statistical chart, and displaying the statistical chart on a control terminal; when a fault is detected based on the working parameters, giving a reminder on the control terminal.

[0013] According to one aspect of this application, there is provided a remote LED lighting system based on the Internet of Things, including:

[0014] An acquisition unit, configured to acquire initial parameters of a lighting system through the Internet of Things, where the initial parameters include initial LED parameters of LED devices in the lighting system and power supply parameters of the lighting system;

[0015] A target unit, configured to generate a multi-dimensional lighting function based on initial LED parameters of a lighting node corresponding to the LED device and neighbor nodes;

[0016] A variable unit, configured to input LED parameters of the lighting node and its neighbor nodes at the current moment into the lighting function to determine state variables of the lighting node at the next moment;

[0017] A modulation unit, configured to dynamically modulate a current signal output by a power supply according to the power supply parameters and the LED parameters to determine a signal frequency at which the current signal passes through the LED device;

[0018] A lighting unit, configured to control the LED device to perform lighting based on the state variables and the signal frequency.

[0019] According to one aspect of the present application, there is provided a computer-readable medium having a computer program stored thereon, and when the computer program is executed by a processor, it implements the remote LED lighting method based on the Internet of Things as described in the above embodiments.

[0020] According to one aspect of the present application, there is provided an electronic device, including: one or more processors; a storage device configured to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the remote LED lighting method based on the Internet of Things as described in the above embodiments.

[0021] According to one aspect of the present application, there is provided a computer program product or a computer program, the computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the remote LED lighting method based on the Internet of Things provided in the above various optional implementation manners.

[0022] The technical solution of this application obtains the initial parameters of the lighting system through the Internet of Things. The initial parameters include the initial LED parameters of the LED devices in the lighting system and the power supply parameters of the lighting system. Based on the initial LED parameters of the lighting nodes corresponding to the LED devices and their neighbor nodes, a multi-dimensional lighting function is generated. The LED parameters of the lighting node and its neighbor nodes at the current moment are input into the lighting function to determine the state variables of the lighting node at the next moment. According to the power supply parameters and the LED parameters, the current signal output by the power supply is dynamically modulated to determine the signal frequency of the current signal passing through the LED device. The LED device is controlled to perform lighting based on the state variables and the signal frequency. By accurately obtaining the initial parameters through the Internet of Things, a multi-dimensional lighting function is determined based on the parameters of the lighting nodes and their neighbor nodes, the state variables and the modulation current signal frequency are dynamically predicted, and accurate control decisions are made according to the real-time lighting conditions, improving the adaptability and flexibility of lighting, enhancing the luminous efficiency of the lighting system and reducing energy consumption.

[0023] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit this application. Brief Description of the Drawings

[0024] The drawings here are incorporated into the specification and form a part of this specification, showing the embodiments consistent with this application, and are used together with the specification to explain the principles of this application. Obviously, the drawings in the following description are only some embodiments of this application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0025] Figure 1 Schematically shows the flowchart of a remote LED lighting method based on the Internet of Things in an embodiment of this application.

[0026] Figure 2 Schematically shows the flowchart of generating a lighting function in an embodiment of this application.

[0027] Figure 3 Schematically shows the schematic diagram of a remote LED lighting system based on the Internet of Things in an embodiment of this application.

[0028] Figure 4 Shows the structural schematic diagram of a computer system of an electronic device suitable for implementing the embodiments of this application. Detailed Description of the Embodiments

[0029] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more complete and comprehensive, and will fully convey the concept of the example embodiments to those skilled in the art.

[0030] In addition, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of the embodiments of this application. However, those skilled in the art will realize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be used. In other cases, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of this application.

[0031] The block diagrams shown in the drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0032] The flowcharts shown in the drawings are merely illustrative and do not necessarily include all the content and operations / steps, nor do they necessarily need to be executed in the order described. For example, some operations / steps can be decomposed, while some operations / steps can be combined or partially combined, so the actual execution order may change according to the actual situation.

[0033] The implementation details of the technical solutions of this application are elaborated in detail below:

[0034] Figure 1 A flowchart of a remote LED lighting method based on the Internet of Things according to an embodiment of this application is shown. Referring to Figure 1 as shown, the remote LED lighting method based on the Internet of Things at least includes steps S110 to S150, which are introduced in detail as follows:

[0035] In step S110, initial parameters of the lighting system are obtained through the Internet of Things, and the initial parameters include the initial LED parameters of the LED devices in the lighting system and the power supply parameters of the lighting system.

[0036] In this embodiment, the host computer or the control terminal is connected to the lighting system through the Internet of Things technology and sends instructions to obtain the initial parameters of the lighting system. The initial parameters in this embodiment include the initial LED parameters of the LED devices in the lighting system and the power supply parameters of the lighting system. Specifically, first identify and collect the initial LED parameters of the LED devices, including the color temperature parameter to understand the color characteristics of the LED devices, the energy efficiency parameter to evaluate the energy efficiency level of the LED lamps, and so on. At the same time, obtain the power supply parameters of the lighting system, such as the current intensity, to comprehensively master the power supply situation. The acquisition of these parameters provides basic data support for the subsequent control and optimization of the lighting system.

[0037] In an embodiment of the present application, the initial parameters of the lighting system are obtained through the Internet of Things, including:

[0038] An Internet of Things is constructed based on the lighting system, and the Internet of Things includes a perception layer, a network layer, a platform layer, and an application layer;

[0039] The initial parameters of the lighting system are obtained based on the Internet of Things.

[0040] With the rapid development of the Internet of Things technology, the lighting system is gradually becoming intelligent. In order to manage and optimize the lighting system more efficiently, it is crucial to accurately obtain its initial parameters. First, construct an Internet of Things architecture including a perception layer, a network layer, a platform layer, and an application layer. Specifically, the perception layer consists of various sensors and intelligent devices and is responsible for collecting data of the lighting system in real time; the network layer is responsible for data transmission and uses wireless or wired communication methods to ensure the real-time and reliability of the data; the platform layer performs data processing, storage, and analysis and provides support for the application layer; the application layer realizes functions such as intelligent control, monitoring, and optimization of the lighting system.

[0041] The initial LED parameters of the LED devices in the lighting system are obtained in real time through the Internet of Things. Among them, the initial LED parameters include color temperature parameters, brightness parameters, energy efficiency parameters, and so on. Among them, the color temperature parameter is used to describe the color characteristics of the LED devices, such as warm light, cold light, etc., and the energy efficiency parameter is used to reflect the energy efficiency level of the LED lamps, such as luminous efficacy, power factor, etc. The power supply parameters include the current intensity, which is used to represent the magnitude of the current provided by the power supply and has an important impact on the stability and lifespan of the LED lamps.

[0042] The above process makes the acquisition and transmission of initial parameters more efficient and stable by constructing an Internet of Things with a multi-layer structure. The sensors in the perception layer can directly obtain various physical quantities of the lighting system, such as brightness, color temperature, current, and voltage, and transmit the data to the platform layer through the network layer for processing and storage. This layered architecture improves the scalability and compatibility of the system, facilitating subsequent function expansion and upgrade. At the same time, obtaining initial parameters through the Internet of Things avoids the tediousness and errors of manual data collection, improving the accuracy and real-time nature of the data.

[0043] Optionally, the obtained initial parameters can also be preprocessed, such as denoising, normalization, etc., to improve the data quality.

[0044] This embodiment can be widely applied to various lighting systems such as commercial buildings, residential communities, or public places. Through Internet of Things technology, it realizes the comprehensive and accurate acquisition of the initial parameters of the lighting system, providing a solid foundation for subsequent intelligent control and optimization, and realizing the intelligent management and optimization of the lighting system.

[0045] In step S120, based on the initial LED parameters of the lighting node corresponding to the LED device and its neighbor nodes, a multi-dimensional lighting function is generated.

[0046] In this embodiment, after obtaining the initial LED parameters, the correlation and mutual influence between the initial LED parameters are analyzed, and multi-dimensional features that can reflect the relationship between the lighting node and its neighbor nodes are mined. Based on these features, a multi-dimensional lighting function is constructed. This lighting function takes the initial LED parameters as input and can output a quantitative index describing the lighting effect between the lighting node and its neighbor nodes at the next moment. During the construction process, the function can also be optimized and adjusted to improve its accuracy and generalization ability, so as to more accurately simulate and predict the behavior of the lighting system.

[0047] As Figure 2 shown, in an embodiment of the present application, generating a multi-dimensional lighting function based on the initial LED parameters of the lighting node corresponding to the LED device and its neighbor nodes includes:

[0048] Obtaining the total number and location information of the lighting nodes in the lighting system through the Internet of Things;

[0049] Determining the neighbor nodes of the lighting node according to the location information;

[0050] Obtaining the initial LED parameters of the lighting node and its neighbor nodes, and generating a multi-dimensional lighting function based on the initial LED parameters and the total number.

[0051] In this embodiment, through the Internet of Things technology, a connection is established with the lighting system, and instructions are sent to obtain the total number of all lighting nodes in the lighting system and their respective location information. Then, the location data of each lighting node is recorded and stored to ensure the integrity and accuracy of the data.

[0052] It should be noted that the lighting nodes in this embodiment include various LED devices in the lighting system. For example, the street lights in the street lighting system.

[0053] After obtaining the location information of the lighting nodes, this information is used for spatial analysis. By calculating the distances between the nodes, the adjacent nodes of each lighting node are identified, providing support for subsequent local lighting control and coordination.

[0054] The initial LED parameters between each lighting node and its neighbor nodes are obtained. Based on the obtained initial LED parameters, a multi-dimensional lighting function is generated. In this embodiment, the lighting function includes multiple dimensions such as brightness, color temperature, and energy efficiency, and is used to comprehensively describe the performance and state of the lighting system.

[0055] Specifically, based on the initial LED parameters between the lighting node and its neighbor nodes, the multi-dimensional lighting function RK(i,j) corresponding to this moment is determined as:

[0056]

[0057] where i, j represent the identifiers of the lighting node and its neighbor nodes, N represents the number of lighting nodes in the lighting system, t represents time, k represents the network coupling strength, which is used to control the feedback strength of the state difference between nodes; x i and x j represent the brightness parameters between the lighting node and its neighbor nodes, y i represents the color temperature parameter of the lighting node, z i represents the energy efficiency parameter of the lighting node; σ represents the brightness factor, ρ represents the color temperature factor, β represents the energy efficiency factor. Exemplarily, in this embodiment, σ = 10, ρ = 28, and β = 8 / 3 can be taken.

[0058] where and represent the increments corresponding to the three dimensions of brightness, color temperature, and energy efficiency respectively. When the initial LED parameters are input, based on the initial LED parameters, the increments of different dimensions at the next moment can be determined, and then the data values of different dimensions at the next moment can be determined.

[0059] The above process, by obtaining the total number and location information of lighting nodes, determines the set of neighbor nodes, providing a basis for the spatial dimension in constructing a multi-dimensional lighting function. Different lighting nodes at different positions affect each other. By considering the states of neighbor nodes, the overall behavior of the lighting system can be described more accurately.

[0060] Meanwhile, determining the lighting function based on the initial LED parameters can comprehensively consider multiple factors such as brightness, color temperature, and energy efficiency, making the lighting effect more personalized. For example, in a meeting room, the brightness and color temperature of the lighting can be adjusted according to different meeting scenarios to improve the efficiency and comfort of the meeting.

[0061] In step S130, the LED parameters of the lighting node and its neighbor nodes at the current moment are input into the lighting function to determine the state variables of the lighting node at the next moment.

[0062] In this embodiment, the LED parameters of the lighting node and its neighbor nodes at the current moment are obtained, sorted in a predetermined format and order, and used as input data to be passed to the lighting function. The lighting function is called and the LED parameters are input into the function. By processing and calculating these input parameters, the state variables of the lighting node at the next moment are obtained. These state variables include the brightness adjustment value or color temperature change parameter of the lighting node at the next moment, etc., realizing the dynamic prediction and adjustment of the lighting process. By continuously updating the state variables, the system can make corresponding decisions according to the real-time lighting situation, improving the adaptability and flexibility of the lighting.

[0063] In this embodiment, the brightness parameter x i (t), color temperature parameter y i (t), and energy efficiency parameter z i (t) of the lighting node at the current moment t, the brightness parameter x j (t) of the neighbor nodes of the lighting node at the current moment, and the fixed parameter set {σ, ρ, β, k} are input into the lighting function for solution to determine the increment of the lighting node at the next moment. Then, according to the vector sum between the increment and the LED parameters, the state variables {x i (t + Δt), y i (t + Δt), z i (t + Δt)} are determined.

[0064] Among them, Δt represents the time step, which is used to balance accuracy and computational efficiency. x i (t + Δt), y i (t + Δt), and z i (t + Δt) respectively represent the brightness parameter, color temperature parameter, and energy efficiency parameter of the lighting node at the next moment.

[0065] Exemplarily, in the above process, the brightness parameter x of the lighting node at the next moment is determined through the lighting function i (t + Δt), which can be directly mapped to the control signal of the LED for real-time adjustment of lighting parameters. For example, in an intelligent street lamp system, the amplitude of the brightness parameter can be converted into the duty cycle of pulse width modulation to control the LED drive current and achieve dynamic brightness adjustment. For example, x i ∈[0, 10] corresponds to the duty cycle brightness range of 0% to 100%.

[0066] Exemplarily, in the above process, the color temperature parameter y of the lighting node at the next moment is determined through the lighting function i (t + Δt), which reflects the intermediate state of the internal non-linear coupling of the system and enhances the complexity and anti-interference ability of the control signal. For example, in smart home lighting, the color temperature parameter can be mapped to the adjustment coefficient of the color temperature, and combined with the brightness parameter to achieve a smooth transition between warm and cold lights. For example, y i ∈[-2, 2] corresponds to the color temperature range of 2700K to 6500K.

[0067] Exemplarily, in the above process, the energy efficiency parameter color temperature parameter z of the lighting node at the next moment is determined through the lighting function i (t + Δt), which characterizes the energy dissipation and long-term stability of the system and is used to optimize the working efficiency and thermal management of the LED. For example, in industrial lighting, the color temperature parameter can be associated with the real-time energy efficiency ratio of the LED (unit: lumens per watt lm / W), and the current is adjusted through feedback to reduce power consumption. For example, example value: z i = 25 corresponds to an energy efficiency of 180 lm / W.

[0068] In the above process, the LED parameters of the lighting node and its neighbor nodes at the current moment are input into the lighting function, and the state variables at the next moment are determined by solving, realizing the dynamic simulation and prediction of the lighting process. This dynamic adjustment mechanism enables the lighting system to respond to environmental changes in real time and provide more intelligent lighting services. For example, during the day, when the outdoor light is strong, the system can automatically reduce the brightness of indoor lighting; at night, when people are active, the system can increase the brightness of lighting to meet people's various needs.

[0069] In step S140, according to the power supply parameters and the LED parameters, the current signal output by the power supply is dynamically modulated to determine the signal frequency of the current signal passing through the LED device.

[0070] In this embodiment, based on the obtained power supply parameters and LED parameters, the current signal output by the power supply is modulated in real time and dynamically. The optimal signal frequency for the current signal to pass through the LED is determined to ensure that the LED lamp can operate in an optimal state, guarantee the manifestation of color temperature parameters and energy efficiency parameters, achieve an efficient and stable lighting effect, and simultaneously optimize the energy utilization rate.

[0071] In an embodiment of the present application, according to the power supply parameters and the LED parameters, the current signal output by the power supply is dynamically modulated, and the signal frequency of the current signal passing through the LED device is determined, including:

[0072] According to the pulse period of the current signal in the power supply parameters, the time domain distribution of the current signal is determined;

[0073] According to the time domain distribution and the initial lattice period in the LED parameters, the current signal output by the power supply is dynamically modulated to determine the signal frequency of the current signal passing through the LED device.

[0074] In an embodiment of the present application, according to the pulse period of the current signal in the power supply parameters, the time domain distribution of the current signal is determined as:

[0075]

[0076] Among them, sech(·) represents the hyperbolic secant function, t represents time, nT represents the starting time of the nth modulation period; T represents the pulse period of the current signal in the power supply parameters, and τ represents the modulation pulse width.

[0077] After that, according to the time domain distribution and the initial lattice period in the LED parameters, the current signal output by the power supply is dynamically modulated to determine the signal frequency ω g (t) is:

[0078]

[0079] Among them, ω g (t) represents the signal frequency of the current signal passing through the LED device at time t, Λ0 represents the initial lattice period, π represents the pi, c represents the speed of light, α represents the piezoelectric coupling coefficient, and α can be taken as α = 0.15 to achieve dynamic tuning of the signal frequency.

[0080] It should be noted that in this embodiment, the initial lattice period Λ0 is the inherent periodic structure parameter of the photonic crystal when no external modulation is applied, representing the spacing between adjacent dielectric layers in the photonic crystal or the repetition distance of the periodic unit. A suitable lattice period can enhance the photon localization effect, improve the LED light extraction efficiency, and be very helpful for the spectral performance, response speed and energy efficiency of the system.

[0081] Through the above operations, the signal frequency changes with Λ0, forming a dynamic splitting. For example, when Λ0 increases, the signal frequency moves towards the low frequency, and vice versa towards the high frequency. The photon localization effect is optimized through dynamic tuning, improving the light extraction efficiency of the LED.

[0082] It should be noted that in this embodiment, the initial lattice period Λ0 is the inherent periodic structure parameter of the photonic crystal when no external modulation is applied, representing the spacing between adjacent dielectric layers in the photonic crystal or the repetition distance of the periodic unit. A suitable lattice period can enhance the photon localization effect, improve the light extraction efficiency of the LED, and is very helpful for the spectral performance, response speed, and energy efficiency of the system.

[0083] In the above process, the current signal is dynamically modulated according to the power supply parameters and the LED parameters to determine the signal frequency. By considering the pulse period of the current signal in the power supply parameters and the initial lattice period in the LED parameters, the current signal is dynamically modulated, which can improve the luminous efficiency and stability of the LED. Different signal frequencies will affect the emission wavelength and intensity of the LED. By dynamically adjusting the signal frequency, the LED can emit appropriate light or maintain the best luminous state under different working conditions, improving the luminous efficiency and stability of the LED. At the same time, a reasonable signal frequency can reduce the power consumption of the LED and extend its service life. In the case of low light requirements, the signal frequency can be reduced to reduce energy consumption.

[0084] In step S150, based on the state variable and the signal frequency, control the LED device to perform lighting.

[0085] In this embodiment, the state variable includes the expected lighting characteristics of the lighting node at the next moment, such as the brightness adjustment value, color change, etc.; the signal frequency determines the rate at which the current signal passes through the LED. Convert the state variable and the signal frequency into specific control instructions and transmit them to the driving module of the LED through the communication protocol of the Internet of Things. The driving module adjusts parameters such as the current and voltage of the LED according to the state variable in the instruction to achieve the desired lighting effects such as brightness and color. At the same time, the driving module accurately controls the on and off of the current signal according to the signal frequency to ensure that the LED emits light at a stable frequency.

[0086] Throughout the process, the lighting state of the LED can also be monitored in real time, and the state variable and the signal frequency are dynamically adjusted according to the difference between the actual lighting effect and the expected state to achieve more accurate and stable lighting control.

[0087] In an embodiment of the present application, controlling the LED device to perform lighting based on the state variable and the signal frequency includes:

[0088] Parse the state variable based on a preset mapping relationship to generate a control parameter;

[0089] Generate a control instruction according to the control parameter and the signal frequency, and send the control instruction to the driving module of the LED;

[0090] The driving module compiles the control instruction into a driving signal to control the LED device to perform lighting through the driving signal.

[0091] In this embodiment, the state variable calculated by the lighting function is parsed. The state variable includes multiple dimensions, such as brightness, color temperature, etc. These parameters together describe the lighting state that the LED should present at the next moment. Map the state variable to the control parameter of the LED, that is, convert the abstract state variable into an instruction or signal that the driving module of the LED can understand, such as the duty cycle of the pulse width modulation signal, current intensity, etc.

[0092] Exemplarily, map the brightness parameter x i to the duty cycle C of the pulse width modulation signal as:

[0093]

[0094] where k1 is a parameter for adjusting the steepness of the curve, and x i,0 is the reference value of the brightness parameter of lighting node i, and exp(·) represents the exponential operation of the natural constant. By using a mapping function to smoothly map the light intensity to the duty cycle, it is ensured that when the brightness parameter changes, the duty cycle can also transition smoothly to ensure the smooth transition of the lighting brightness and improve the stability of the lighting effect.

[0095] After that, adjust the input signal frequency of the driving module of the LED according to the signal frequency calculated by the dynamic modulation function. The signal frequency determines the switching frequency of the LED, which in turn affects the lighting stability and energy efficiency of the LED. When adjusting the signal frequency, the frequency value is within the specifications of the driving module of the LED and the LED device to avoid damaging the device or affecting the lighting effect.

[0096] Combine the parsed control layer parameters and the calculated signal frequency to generate a control instruction, and configure the control instruction into the driving module of the LED. Complete the write operation of the internal register of the driver to set parameters such as the duty cycle of the PWM signal and current limit. After the configuration is completed, start the lighting process. The driving module of the LED will generate a corresponding driving signal according to the received control instruction to control the LED device to perform lighting, and the LED emits light according to the driving signal generated by the driver to achieve the lighting function.

[0097] In the above process, the preset mapping relationship accurately converts the state variables into control parameters, ensuring the accuracy and stability of control. The control instructions are generated by the driving module of the LED to control the LED device for lighting, achieving precise control of the lighting system.

[0098] Meanwhile, the working state of the LED can be continuously monitored, including parameters such as light intensity, color temperature, and color saturation. This can be achieved by reading the signals fed back by the driving module of the LED or using additional sensors. If it is detected that the working state of the LED does not match the expectation, the computer will promptly adjust the control parameters or take other measures to ensure the normal operation of the lighting system and the best lighting effect.

[0099] In an embodiment of the present application, after controlling the LED device for lighting based on the state variable and the signal frequency, it further includes:

[0100] Obtaining the working parameters of the LED during the lighting process, statistically analyzing the working parameters, generating statistical charts, and displaying them on the control terminal;

[0101] When a fault is detected based on the working parameters, a reminder is given in the control terminal.

[0102] In this embodiment, it is connected to the LED lighting system through various sensor interfaces. These sensors include current sensors, voltage sensors, temperature sensors, and light intensity sensors, etc. They collect working parameters such as the working current, voltage, temperature, and emitted light intensity of the LED in real time. The analog signals collected by the sensors will be converted into digital signals and transmitted to the data acquisition module of the Internet of Things through a communication protocol.

[0103] After the data acquisition module receives these digital signals, it statistically analyzes the collected working parameters. For example, calculating the average value, maximum value, and minimum value of the current and voltage over a period of time, counting the number of times the temperature exceeds the normal range, and analyzing the fluctuation of the light intensity, etc. After completing the statistics, corresponding statistical charts are generated according to the statistical results, such as a line chart showing the change of current over time, a bar chart comparing the light intensity in different time periods, etc. Finally, these statistical charts are transmitted to the control terminal through a network protocol or a local interface and displayed on the display interface of the control terminal, facilitating the user to intuitively understand the working state of the LED.

[0104] In addition, during the process of collecting the working parameters, fault detection based on the working parameters is simultaneously carried out. Parameter thresholds and fault judgment rules are preset. These parameter thresholds and fault judgment rules are determined according to the characteristics of the LED and actual working experience, such as the normal range of current, the fluctuation threshold of voltage, the upper limit of temperature, etc.

[0105] Compare and analyze the collected working parameters with these thresholds and rules in real time. When it is detected that a certain working parameter exceeds the threshold or violates the fault judgment rule, it is determined that a fault has occurred, and the fault reminder mechanism is triggered.

[0106] Optionally, a fault report can also be generated according to the detection result. The report includes information such as the time of fault occurrence, the parameters involved, the specific values of the parameters, the fault type, and the possible causes of the fault. Then, the fault report and reminder information are sent to the control terminal. After receiving this information, the control terminal pops up a prominent reminder window on its display interface, sending an alarm to the user in the form of text, sound, flashing icons, etc.

[0107] Optionally, according to the severity of the fault, text messages or email notifications can also be automatically sent to relevant maintenance personnel to ensure that the fault can be processed in a timely manner and the normal operation of the LED lighting system is guaranteed.

[0108] The above process obtains the working parameters of the LED during the lighting process, generates statistical charts and displays them on the control terminal, and gives fault reminders, facilitating users to understand the operating status of the lighting system in real time, discover and solve problems in a timely manner, and improving the reliability and maintainability of the lighting system.

[0109] In the technical solution of this application, the initial parameters of the lighting system are obtained through the Internet of Things. The initial parameters include the initial LED parameters of the LED devices in the lighting system and the power supply parameters of the lighting system. Based on the initial LED parameters of the lighting nodes corresponding to the LED devices and the neighbor nodes, a multi-dimensional lighting function is generated. The LED parameters of the lighting node and its neighbor nodes at the current moment are input into the lighting function to determine the state variables of the lighting node at the next moment. According to the power supply parameters and the LED parameters, the current signal output by the power supply is dynamically modulated to determine the signal frequency of the current signal passing through the LED device. Based on the state variables and the signal frequency, the LED device is controlled to perform lighting. By accurately obtaining the initial parameters through the Internet of Things, determining a multi-dimensional lighting function based on the parameters of the lighting node and its neighbor nodes, dynamically predicting the state variables and modulating the current signal frequency, and making corresponding decisions according to the real-time lighting situation, the adaptability and flexibility of lighting are improved, the luminous efficiency of the lighting system is enhanced, and the energy consumption is reduced.

[0110] The following describes an apparatus embodiment of the present application, which can be used to execute the IoT-based remote LED lighting method in the above embodiments of the present application. It can be understood that the apparatus can be a computer program (including program code) running in a computer device. For example, the apparatus is an application software; the apparatus can be used to execute the corresponding steps in the method provided in the embodiments of the present application. For details not disclosed in the apparatus embodiments of the present application, please refer to the embodiments of the above IoT-based remote LED lighting method of the present application.

[0111] Figure 3 FIG. shows a block diagram of an IoT-based remote LED lighting system according to an embodiment of the present application.

[0112] Referring to Figure 3 As shown, an IoT-based remote LED lighting system according to an embodiment of the present application includes:

[0113] An acquisition unit 310, configured to acquire initial parameters of the lighting system through the IoT, where the initial parameters include initial LED parameters of LED devices in the lighting system and power supply parameters of the lighting system;

[0114] A target unit 320, configured to generate a multi-dimensional lighting function based on the initial LED parameters of the lighting nodes and neighbor nodes corresponding to the LED devices;

[0115] A variable unit 330, configured to input the LED parameters of the lighting node and its neighbor nodes at the current moment into the lighting function to determine the state variables of the lighting node at the next moment;

[0116] A modulation unit 340, configured to dynamically modulate the current signal output by the power supply according to the power supply parameters and the LED parameters to determine the signal frequency of the current signal passing through the LED device;

[0117] A lighting unit 350, configured to control the LED device to perform lighting based on the state variables and the signal frequency.

[0118] In the present application, based on the foregoing solution, the acquiring the initial parameters of the lighting system through the IoT includes: constructing an IoT based on the lighting system, where the IoT includes a perception layer, a network layer, a platform layer, and an application layer; acquiring the initial parameters of the lighting system based on the IoT.

[0119] In this application, based on the foregoing solution, generating a multi-dimensional lighting function based on the initial LED parameters of the lighting nodes and neighbor nodes corresponding to the LED device includes: obtaining the total number and location information of the lighting nodes in the lighting system through the Internet of Things; determining the neighbor nodes of the lighting nodes according to the location information; obtaining the initial LED parameters of the lighting nodes and their neighbor nodes, and generating a multi-dimensional lighting function based on the initial LED parameters and the total number.

[0120] In this application, based on the foregoing solution, inputting the LED parameters of the lighting nodes and their neighbor nodes at the current moment into the lighting function to determine the state variables of the lighting nodes at the next moment includes: inputting the brightness parameter, color temperature parameter, and energy efficiency parameter of the lighting nodes at the current moment, and the brightness parameter of the neighbor nodes of the lighting nodes at the current moment into the lighting function for solution to determine the state variables of the lighting nodes at the next moment.

[0121] In this application, based on the foregoing solution, dynamically modulating the current signal output by the power supply according to the power supply parameters and the LED parameters to determine the signal frequency of the current signal passing through the LED device includes: determining the time-domain distribution of the current signal according to the pulse period of the current signal in the power supply parameters; dynamically modulating the current signal output by the power supply according to the time-domain distribution and the initial lattice period in the LED parameters to determine the signal frequency of the current signal passing through the LED device.

[0122] In this application, based on the foregoing solution, controlling the LED device to perform lighting based on the state variables and the signal frequency includes: parsing the state variables based on a preset mapping relationship to generate control parameters; generating a control instruction according to the control parameters and the signal frequency, and sending the control instruction to the driving module of the LED; the driving module compiles the control instruction into a driving signal to control the LED device to perform lighting through the driving signal.

[0123] In this application, after controlling the LED device to perform lighting based on the state variables and the signal frequency, it further includes: obtaining the working parameters of the LED during the lighting process, statistically analyzing the working parameters to generate a statistical chart, and displaying the statistical chart on the control terminal; when a fault is detected based on the working parameters, giving a reminder on the control terminal.

[0124] The technical solution of this application obtains the initial parameters of the lighting system through the Internet of Things. The initial parameters include the initial LED parameters of the LED devices in the lighting system and the power supply parameters of the lighting system. Based on the initial LED parameters of the lighting nodes corresponding to the LED devices and their neighbor nodes, a multi-dimensional lighting function is generated. The LED parameters of the lighting node and its neighbor nodes at the current moment are input into the lighting function to determine the state variables of the lighting node at the next moment. According to the power supply parameters and the LED parameters, the current signal output by the power supply is dynamically modulated to determine the signal frequency of the current signal passing through the LED device. The LED device is controlled to perform lighting based on the state variables and the signal frequency. By accurately obtaining the initial parameters through the Internet of Things, a multi-dimensional lighting function is determined based on the parameters of the lighting node and its neighbor nodes, the state variables and the modulation current signal frequency are dynamically predicted, and corresponding decisions are made according to the real-time lighting situation, improving the adaptability and flexibility of lighting, enhancing the luminous efficiency of the lighting system and reducing energy consumption.

[0125] Figure 4 The schematic structural diagram of a computer system of an electronic device suitable for implementing the embodiments of this application is shown.

[0126] It should be noted that the computer system of the electronic device in this embodiment is only an example and should not bring any limitations to the functions and usage scopes of the embodiments of this application.

[0127] In this embodiment, the computer system includes a central processing unit 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory 402 or the program loaded from the storage part 408 into the random access memory 403, such as executing the remote LED lighting method based on the Internet of Things described in the above embodiments. In the random access memory 403, various programs and data required for system operation are also stored. The central processing unit 401, the read-only memory 402, and the random access memory 403 are connected to each other through a bus 404. The input / output interface 405 is also connected to the bus 404.

[0128] The following components are connected to the input / output interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the input / output interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed so that a computer program read from it can be installed into the storage section 408 as needed.

[0129] Specifically, according to an embodiment of the present application, the processes described above with reference to the flowchart can be implemented as computer software programs. For example, an embodiment of the present application includes a computer program product that includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for performing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication section 409, and / or installed from the removable medium 411. When the computer program is executed by the central processing unit 401, various functions defined in the system of the present application are executed.

[0130] It should be noted that the computer-readable medium shown in the embodiments of the present application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of a computer-readable storage medium can include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable computer program is carried. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, and this computer-readable medium can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0131] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. Among them, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code, and the above module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0132] The units involved in the embodiments of the present application can be implemented in software or in hardware, and the described units can also be provided in a processor. Among them, the names of these units do not, in some cases, constitute a limitation on the unit itself.

[0133] According to one aspect of the present application, there is provided a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the methods provided in the above various optional implementation manners.

[0134] As another aspect, the present application further provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or may exist alone without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method for remote LED lighting based on the Internet of Things described in the above embodiments.

[0135] It should be noted that although several modules or units of a device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more of the above-described modules or units can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0136] Through the description of the above embodiments, those skilled in the art can easily understand that the example embodiments described herein can be implemented in software or in a manner combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (such as a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.

[0137] After considering the specification and practicing the disclosed embodiments herein, those skilled in the art will readily conceive of other embodiments of the present application. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include common general knowledge or conventional technical means in the technical field not disclosed in the present application.

[0138] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A remote LED lighting method based on the Internet of Things, characterized in that, Comprising: Obtaining initial parameters of the lighting system through the Internet of Things, where the initial parameters include initial LED parameters of LED devices in the lighting system and power supply parameters of the lighting system; Generating a multi-dimensional lighting function based on the initial LED parameters of the lighting nodes corresponding to the LED devices and their neighbor nodes; Inputting the LED parameters of the lighting node and its neighbor nodes at the current moment into the lighting function to determine the state variables of the lighting node at the next moment; Dynamically modulating the current signal output by the power supply according to the power supply parameters and the LED parameters to determine the signal frequency of the current signal passing through the LED device; Controlling the LED device to perform lighting based on the state variables and the signal frequency.

2. The remote LED lighting method based on the Internet of Things according to claim 1, characterized in that The obtaining the initial parameters of the lighting system through the Internet of Things includes: Constructing the Internet of Things based on the lighting system, where the Internet of Things includes a perception layer, a network layer, a platform layer, and an application layer; Obtaining the initial parameters of the lighting system based on the Internet of Things.

3. The remote LED lighting method based on the Internet of Things according to claim 1, characterized in that, The generating a multi-dimensional lighting function based on the initial LED parameters of the lighting nodes corresponding to the LED devices and their neighbor nodes includes: Obtaining the total number and location information of the lighting nodes in the lighting system through the Internet of Things; Determining the neighbor nodes of the lighting nodes according to the location information; Obtaining the initial LED parameters of the lighting nodes and their neighbor nodes, and generating a multi-dimensional lighting function based on the initial LED parameters and the total number.

4. The remote LED lighting method based on the Internet of Things according to claim 1, characterized in that The inputting the LED parameters of the lighting node and its neighbor nodes at the current moment into the lighting function to determine the state variables of the lighting node at the next moment includes: Inputting the brightness parameter, color temperature parameter, and energy efficiency parameter of the lighting node at the current moment, and the brightness parameter of the neighbor nodes of the lighting node at the current moment into the lighting function for solution to determine the state variables of the lighting node at the next moment.

5. The remote LED lighting method based on the Internet of Things according to claim 1, characterized in that The dynamically modulating the current signal output by the power supply according to the power supply parameters and the LED parameters to determine the signal frequency of the current signal passing through the LED device includes: Determining the time-domain distribution of the current signal according to the pulse period of the current signal in the power supply parameters; Dynamically modulating the current signal output by the power supply according to the time-domain distribution and the initial lattice period in the LED parameters to determine the signal frequency of the current signal passing through the LED device.

6. The remote LED lighting method based on the Internet of Things according to claim 1, characterized in that The controlling the LED device to perform lighting based on the state variables and the signal frequency includes: Analyzing the state variables based on a preset mapping relationship to generate control parameters; Generating a control instruction according to the control parameters and the signal frequency, and sending the control instruction to the driving module of the LED; The driving module compiles the control instruction into a driving signal to control the LED device to perform lighting through the driving signal.

7. The remote LED lighting method based on the Internet of Things according to any one of claims 1-6, characterized in that, After the controlling the LED device to perform lighting based on the state variables and the signal frequency, it further includes: Obtaining the working parameters of the LED during the lighting process; Statistically analyzing the working parameters to generate a statistical chart and displaying it on the control terminal.

8. A remote LED lighting system based on the Internet of Things, characterized in that, Comprising: An acquisition unit for acquiring initial parameters of a lighting system through the Internet of Things, where the initial parameters include initial LED parameters of LED devices in the lighting system and power supply parameters of the lighting system; A target unit for generating a multi-dimensional lighting function based on the initial LED parameters of the lighting nodes corresponding to the LED devices and their neighbor nodes; A variable unit for inputting the LED parameters of the lighting node and its neighbor nodes at the current moment into the lighting function to determine the state variables of the lighting node at the next moment; A modulation unit for dynamically modulating the current signal output by the power supply according to the power supply parameters and the LED parameters to determine the signal frequency of the current signal passing through the LED device; A lighting unit for controlling the LED device to perform lighting based on the state variables and the signal frequency; 9. The remote LED lighting system based on the Internet of Things according to claim 8, characterized in that The acquisition of the initial parameters of the lighting system through the Internet of Things includes: Constructing the Internet of Things based on the lighting system, where the Internet of Things includes a perception layer, a network layer, a platform layer, and an application layer; Acquiring the initial parameters of the lighting system based on the Internet of Things; 10. The remote LED lighting system based on the Internet of Things according to claim 8, characterized in that, The generation of the multi-dimensional lighting function based on the initial LED parameters of the lighting nodes corresponding to the LED devices and their neighbor nodes includes: Acquiring the total number and location information of the lighting nodes in the lighting system through the Internet of Things; Determining the neighbor nodes of the lighting node according to the location information; Acquiring the initial LED parameters of the lighting node and its neighbor nodes, and generating a multi-dimensional lighting function based on the initial LED parameters and the total number.

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