Remote LED lighting method and system based on internet of things

Abstract

The application relates to the technical field of lighting systems, and provides a remote LED lighting method and system based on the Internet of Things. Initial parameters of a lighting system are acquired through the Internet of Things, a multi-dimensional lighting function is generated based on initial LED parameters of a lighting node and neighbor nodes corresponding to an LED device, LED parameters of the lighting node and the neighbor nodes at a current moment are input into the lighting function to determine state variables of the lighting node at a next moment, the state variables are dynamically modulated according to power parameters and the LED parameters to determine a signal frequency of a current signal passing through the LED device, and the LED device is controlled to perform lighting based on the state variables and the signal frequency. By determining the multi-dimensional lighting function, the state variables and the modulation current signal frequency are dynamically predicted, the adaptability and flexibility of lighting are improved, the light-emitting efficiency of the lighting system is enhanced, and energy consumption is reduced.

Description

Technical Field

[0001] This application relates to the field of lighting system technology, and more specifically, to a remote LED lighting method and system based on the Internet of Things. Background Technology

[0002] With the rise of smart cities, lighting systems, as a crucial component of urban infrastructure, are also evolving towards intelligence and networking. IoT-based remote LED lighting methods enable remote monitoring and management of lighting systems, improving the intelligence level of urban lighting. LED lighting has higher energy efficiency than traditional lighting, and IoT-based remote control technology can further achieve on-demand lighting, avoiding energy waste caused by excessive lighting, thereby meeting the needs of energy conservation and emission reduction.

[0003] The IoT-based remote LED lighting system involves multiple components and has a relatively complex system architecture. Traditional lighting systems lack intelligent control, resulting in low control precision and flexibility for LED lighting systems. 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 partially solve the problem of low control accuracy and flexibility of LED lighting systems.

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

[0006] According to one aspect of this application, a remote LED lighting method based on the Internet of Things (IoT) is provided, comprising: acquiring initial parameters of a lighting system via the IoT, the initial parameters including initial LED parameters of an LED device in the lighting system and power parameters of the lighting system; generating a multi-dimensional lighting function based on the initial LED parameters of the lighting node corresponding to the LED device and its neighboring nodes; inputting the LED parameters of the lighting node and its neighboring nodes at the current moment into the lighting function to determine the state variable of the lighting node at the next moment; dynamically modulating the current signal output by the power supply according to the power 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 variable and the signal frequency.

[0007] In this application, based on the aforementioned scheme, obtaining the initial parameters of the lighting system through the Internet of Things includes: constructing an Internet of Things based on the lighting system, wherein the Internet of Things includes a sensing 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 aforementioned scheme, the step of generating a multi-dimensional lighting function based on the initial LED parameters of the lighting node and neighboring 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 neighboring nodes of the lighting node based on the location information; obtaining the initial LED parameters of the lighting node and its neighboring 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 aforementioned scheme, the step of inputting the LED parameters of the lighting node and its neighboring 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 parameters, color temperature parameters, and energy efficiency parameters of the lighting node at the current moment, as well as the brightness parameters of the neighboring nodes of the lighting node at the current moment, into the lighting function for solving to determine the state variables of the lighting node at the next moment.

[0010] In this application, based on the aforementioned scheme, the step of 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; and 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 aforementioned scheme, controlling the LED device for illumination based on the state variable and the signal frequency includes: parsing the state variable based on a preset mapping relationship to generate control parameters; generating control instructions according to the control parameters and the signal frequency, and sending the control instructions to the LED driver module; the driver module compiles the control instructions into a drive signal to control the LED device for illumination through the drive signal.

[0012] In this application, based on the aforementioned scheme, after controlling the LED device for lighting based on the state variable and the signal frequency, the method further includes: acquiring the operating parameters of the LED during the lighting process, statistically analyzing the operating parameters, generating statistical charts, and displaying them on the control terminal; and issuing a reminder on the control terminal when a fault is detected based on the operating parameters.

[0013] According to one aspect of this application, an Internet of Things (IoT) based remote LED lighting system is provided, comprising:

[0014] The acquisition unit is used to acquire 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 parameters of the lighting system.

[0015] The target unit is used to generate a multi-dimensional lighting function based on the initial LED parameters of the lighting node and neighboring nodes corresponding to the LED device.

[0016] The variable unit is used to input the LED parameters of the lighting node and its neighboring nodes at the current time into the lighting function to determine the state variables of the lighting node at the next time.

[0017] A modulation unit is used to dynamically modulate the current signal output by the power supply according to the power supply parameters and the LED parameters, and determine the signal frequency of the current signal passing through the LED device.

[0018] A lighting unit is used to control the LED device to provide illumination based on the state variable and the signal frequency.

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

[0020] According to one aspect of this application, an electronic device is provided, comprising: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the IoT-based remote LED lighting method as described in the above embodiments.

[0021] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the IoT-based remote LED lighting method provided in the various alternative implementations described above.

[0022] This application's technical solution acquires initial parameters of a lighting system via the Internet of Things (IoT). These initial parameters include the initial LED parameters of the LED devices in the lighting system and the power parameters of the lighting system. Based on the initial LED parameters of the lighting nodes corresponding to the LED devices and their neighboring nodes, a multi-dimensional lighting function is generated. The LED parameters of the lighting nodes and their neighboring nodes at the current moment are input into the lighting function to determine the state variables of the lighting nodes at the next moment. According to the power 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 devices. The LED devices are controlled to provide illumination based on the state variables and the signal frequency. By accurately acquiring initial parameters through the IoT, determining a multi-dimensional lighting function based on the parameters of the lighting nodes and their neighboring nodes, dynamically predicting the state variables and modulating the current signal frequency, and making precise control decisions based on real-time lighting conditions, the adaptability and flexibility of the lighting are improved, the luminous efficiency of the lighting system is enhanced, and energy consumption is reduced.

[0023] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0024] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0025] Figure 1 The flowchart illustrating an embodiment of the Internet of Things-based remote LED lighting method is shown schematically.

[0026] Figure 2 A flowchart illustrating the generation of an illumination function is shown in one embodiment of this application.

[0027] Figure 3 The illustration shows a schematic diagram of an IoT-based remote LED lighting system in one embodiment of this application.

[0028] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown. Detailed Implementation

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

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

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

[0032] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0033] The implementation details of the technical solution of this application are described below:

[0034] Figure 1 A flowchart illustrating an embodiment of an IoT-based remote LED lighting method according to this application is shown. (Refer to...) Figure 1 As shown, this IoT-based remote LED lighting method includes at least steps S110 to S150, which are detailed below:

[0035] In step S110, 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 parameters of the lighting system.

[0036] In this embodiment, the host computer or control terminal connects to the lighting system via IoT technology and sends instructions to obtain the initial parameters of the lighting system. These initial parameters include the initial LED parameters of the LED devices in the lighting system and the power parameters of the lighting system. Specifically, the initial LED parameters of the LED devices are first identified and collected, including color temperature parameters to understand the color characteristics of the LED devices, energy efficiency parameters to evaluate the energy efficiency level of the LED lamps, and so on. Simultaneously, the power parameters of the lighting system, such as current intensity, are obtained to comprehensively understand the power supply status. The acquisition of these parameters provides basic data support for subsequent lighting system control and optimization.

[0037] In one embodiment of this application, obtaining the initial parameters of the lighting system via the Internet of Things includes:

[0038] The Internet of Things (IoT) is built based on a lighting system, and the IoT includes a sensing 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 IoT technology, lighting systems are gradually becoming intelligent. To manage and optimize lighting systems more efficiently, accurately obtaining their initial parameters is crucial. First, an IoT architecture comprising a perception layer, network layer, platform layer, and application layer needs to be constructed. Specifically, the perception layer, composed of various sensors and smart devices, is responsible for real-time data collection from the lighting system; the network layer handles data transmission, employing wireless or wired communication methods to ensure data real-time performance and reliability; the platform layer processes, stores, and analyzes data, providing support for the application layer; and the application layer implements intelligent control, monitoring, and optimization functions for the lighting system.

[0041] The Internet of Things (IoT) acquires initial LED parameters of LED devices in the lighting system in real time. These initial parameters include color temperature, brightness, and energy efficiency. Color temperature describes the color characteristics of the LED device, such as warm or cool light. Energy efficiency parameters reflect the energy efficiency level of the LED luminaire, such as luminous efficacy and power factor. Power supply parameters include current intensity, which indicates the magnitude of the current supplied by the power source and has a significant impact on the stability and lifespan of the LED luminaire.

[0042] The above process, by constructing a multi-layered Internet of Things (IoT) architecture, makes the acquisition and transmission of initial parameters more efficient and stable. Sensors in the perception layer can directly acquire various physical quantities of the lighting system, such as brightness, color temperature, current, and voltage, and transmit the data to the platform layer for processing and storage via the network layer. This layered architecture improves the system's scalability and compatibility, facilitating subsequent functional expansion and upgrades. Simultaneously, acquiring initial parameters through the IoT avoids the tediousness and errors of manual data collection, improving data accuracy and real-time performance.

[0043] Optionally, the acquired initial parameters can be preprocessed, such as denoising and normalization, to improve 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 (IoT) technology, it enables comprehensive and accurate acquisition of the initial parameters of the lighting system, providing a solid foundation for subsequent intelligent control and optimization, and realizing intelligent management and optimization of the lighting system.

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

[0046] In this embodiment, after obtaining the initial LED parameters, the correlation and mutual influence between these parameters are analyzed to uncover multi-dimensional features that reflect the relationship between lighting nodes and their neighboring nodes. Based on these features, a multi-dimensional lighting function is constructed. This function takes the initial LED parameters as input and outputs a quantitative index describing the lighting effect between the lighting node and its neighboring nodes at the next moment. During the construction process, the function can be optimized and adjusted to improve its accuracy and generalization ability, thereby enabling more precise simulation and prediction of the lighting system's behavior.

[0047] like Figure 2 As shown, in one embodiment of this application, a multi-dimensional lighting function is generated based on the initial LED parameters of the lighting node corresponding to the LED device and its neighboring nodes, including:

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

[0049] The neighboring nodes of the lighting node are determined based on the location information;

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

[0051] In this embodiment, an Internet of Things (IoT) technology is used to establish a connection with the lighting system and send instructions to obtain the total number of all lighting nodes in the system and their respective location information. The location data of each lighting node is then recorded and stored to ensure data integrity and accuracy.

[0052] It should be noted that the lighting nodes in this embodiment include various LED devices in the lighting system, such as streetlights in a street lighting system.

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

[0054] The initial LED parameters of each lighting node and its neighboring 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, which are used to comprehensively describe the performance and status of the lighting system.

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

[0056]

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

[0058] in, as well as This represents the increments in three dimensions: brightness, color temperature, and energy efficiency. By inputting initial LED parameters, the increments in different dimensions at the next moment can be determined based on these initial parameters, thus determining the data values ​​for each dimension at the next moment.

[0059] The above process, by obtaining the total number and location information of lighting nodes, determines the set of neighboring nodes, providing a spatial foundation for constructing a multi-dimensional lighting function. Different lighting nodes in different locations will influence each other; by considering the states of neighboring nodes, the overall behavior of the lighting system can be described more accurately.

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

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

[0062] In this embodiment, the LED parameters of the lighting node and its neighboring nodes at the current moment are obtained. These LED parameters are then organized according to a predetermined format and order and passed as input data to the lighting function. The lighting function is invoked, 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 dynamic prediction and adjustment of the lighting process. By continuously updating the state variables, the system can make corresponding decisions based on the real-time lighting conditions, improving the adaptability and flexibility of the lighting.

[0063] In this embodiment, the brightness parameter x of the illumination node at the current time t is... i (t), color temperature parameter y i (t) and energy efficiency parameter z i (t), and the brightness parameter x of the neighboring nodes of the lighting node at the current time. j (t), and a fixed parameter set {σ,ρ,β,k}, are input into the lighting function for solving to determine the increment of the lighting node at the next time step. Then, the state variable {x} is determined based on the vector sum between the increment and the LED parameters. i (t+Δt),y i (t+Δt),z i (t+Δt)}.

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

[0065] For example, in the above process, the brightness parameter x of the illumination node at the next moment is determined by the illumination function. i (t+Δt) can be directly mapped to the LED control signal for real-time adjustment of lighting parameters. For example, in a smart street light system, the amplitude of the brightness parameter can be converted into the duty cycle of pulse width modulation (PWM) to control the LED drive current, achieving dynamic brightness adjustment. For example, x i The range ∈ [0,10] corresponds to a duty cycle brightness range of 0% to 100%.

[0066] For example, in the above process, the color temperature parameter y of the illumination node at the next moment is determined by the illumination function. i (t+Δt) reflects the intermediate state of nonlinear coupling within the system, enhancing the complexity of the control signal and its anti-interference capability. For example, in smart home lighting, the color temperature parameter can be mapped to a color temperature adjustment coefficient, combined with the brightness parameter to achieve a smooth transition between warm and cool light. For example, y i The color temperature range corresponding to [-2,2] is 2700K to 6500K.

[0067] For example, in the above process, the energy efficiency parameter and color temperature parameter z of the lighting node at the next moment are determined by the lighting function. i (t+Δt), characterizing the system's energy dissipation and long-term stability, is used to optimize LED efficiency and thermal management. For example, in industrial lighting, the color temperature parameter can be correlated with the LED's real-time energy efficiency ratio (unit: lumens per watt lm / W), allowing for feedback-based current adjustment to reduce power consumption. Example value: z i =25 corresponds to an energy efficiency of 180lm / W.

[0068] The above process inputs the LED parameters of the lighting node and its neighboring nodes at the current moment into the lighting function, and determines the state variables for the next moment by solving the function, thus realizing the dynamic simulation and prediction of the lighting process. This dynamic adjustment mechanism enables the lighting system to respond to changes in the environment in real time, providing more intelligent lighting services. For example, during the day, when 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, the current signal output by the power supply is dynamically modulated according to the power supply parameters and the LED parameters to determine the signal frequency of the current signal passing through the LED device.

[0070] In this embodiment, the current signal output by the power supply is dynamically modulated in real time based on the acquired power supply parameters and LED parameters. The optimal signal frequency for the current signal to pass through the LED is determined to ensure that the LED lamp can operate in its optimal state, guaranteeing the performance of color temperature and energy efficiency parameters, achieving efficient and stable lighting effects, and optimizing energy utilization.

[0071] In one embodiment of this application, the current signal output by the power supply is dynamically modulated based on the power supply parameters and the LED parameters to determine the signal frequency of the current signal passing through the LED device, including:

[0072] The time-domain distribution of the current signal is determined based on the pulse period of the current signal in the power supply parameters.

[0073] Based on 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 one embodiment of this application, the time-domain distribution of the current signal is determined based on the pulse period of the current signal in the power supply parameters as follows:

[0075]

[0076] Where sech(·) represents the hyperbolic secant function, t represents time, nT represents the start 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] Subsequently, based on 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 of the current signal passing through the LED device. g (t) is:

[0078]

[0079] Where, 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 pi, c represents the speed of light, and α represents the piezoelectric coupling coefficient, which 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 an inherent periodic structural parameter of the photonic crystal when no external modulation is applied, representing the spacing between adjacent dielectric layers or the repetition distance of periodic units in the photonic crystal. A suitable lattice period can enhance the photon localization effect, improve the LED light extraction efficiency, and greatly benefit the system's spectral performance, response speed, and energy efficiency.

[0081] Through the above calculations, the signal frequency changes with Λ0, forming a dynamic split. For example, when Λ0 increases, the signal frequency shifts to lower frequencies, and vice versa. Dynamic tuning optimizes the photon localization effect, improving the light extraction efficiency of the LED.

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

[0083] The above process dynamically modulates the current signal based on power supply and 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, dynamic modulation of the current signal can improve the luminous efficiency and stability of the LED. Different signal frequencies affect the emission wavelength and intensity of the LED. By dynamically adjusting the signal frequency, the LED can emit appropriate light or maintain optimal luminous state under different operating conditions, thus improving its luminous efficiency and stability. Simultaneously, a reasonable signal frequency can reduce LED power consumption and extend its lifespan. In low-light conditions, the signal frequency can be reduced to decrease energy consumption.

[0084] In step S150, the LED device is controlled to provide illumination based on the state variable and the signal frequency.

[0085] In this embodiment, the state variables include the desired lighting characteristics of the lighting node at the next moment, such as brightness adjustment value and color change; the signal frequency determines the rate at which the current signal passes through the LED. The state variables and signal frequency are converted into specific control commands and transmitted to the LED driver module via the Internet of Things (IoT) communication protocol. The driver module adjusts the LED's current, voltage, and other parameters according to the state variables in the commands to achieve the desired lighting effects such as brightness and color. Simultaneously, the driver module precisely controls the on / off state 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 status of the LEDs can be monitored in real time, and the status variables and signal frequencies can be dynamically adjusted according to the difference between the actual lighting effect and the desired state to achieve more precise and stable lighting control.

[0087] In one embodiment of this application, controlling the LED device to provide illumination based on the state variable and the signal frequency includes:

[0088] Based on a preset mapping relationship, the state variables are parsed to generate control parameters;

[0089] A control command is generated based on the control parameters and the signal frequency, and the control command is sent to the LED driver module.

[0090] The drive module compiles the control instructions into drive signals to control the LED device for lighting.

[0091] In this embodiment, the state variables calculated through the illumination function are analyzed. These state variables contain multiple dimensions, such as brightness and color temperature. These parameters collectively describe the illumination state that the LED should present in the next moment. The state variables are mapped to the control parameters of the LED, that is, the abstract state variables are converted into instructions or signals that the LED driving module can understand, such as the duty cycle of the pulse width modulation signal and the current intensity.

[0092] For example, the brightness parameter x i The duty cycle C mapped to the pulse width modulation signal is:

[0093]

[0094] Where k1 is a parameter that adjusts the steepness of the curve, x i,0 This is the baseline 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 the duty cycle can also transition smoothly when the brightness parameter changes, thereby guaranteeing a smooth transition of lighting brightness and improving the stability of the lighting effect.

[0095] Next, based on the signal frequency calculated by the dynamic modulation function, the input signal frequency of the LED driver module is adjusted. The signal frequency determines the LED's switching frequency, thus affecting its illumination stability and energy efficiency. When adjusting the signal frequency, the frequency value is kept within the specifications of the LED driver module and the LED device to avoid damaging the equipment or affecting the lighting effect.

[0096] The parsed control layer parameters and calculated signal frequency are combined to generate control commands, which are then configured into the LED driver module. The internal registers of the driver are written to set parameters such as the PWM signal duty cycle and current limit. After configuration, the lighting process is initiated. The LED driver module generates corresponding drive signals based on the received control commands, controlling the LED device to emit light. The LED emits light according to the drive signals generated by the driver, thus achieving 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 the control. The LED driver module generates control commands to control the LED device for lighting, thus realizing precise control of the lighting system.

[0098] Simultaneously, the operating status of the LEDs can be continuously monitored, including parameters such as illuminance, color temperature, and color saturation. This can be achieved by reading signals fed back from the LED driver module or by using additional sensors. If the monitored LED operating status deviates from expectations, the computer will promptly adjust the control parameters or take other measures to ensure the normal operation of the lighting system and optimal lighting effects.

[0099] In one embodiment of this application, after controlling the LED device to provide illumination based on the state variable and the signal frequency, the method further includes:

[0100] The operating parameters of the LED during the lighting process are obtained, the operating parameters are statistically analyzed, statistical charts are generated, and the results are displayed on the control terminal.

[0101] When a fault is detected based on the operating parameters, an alert is issued on the control terminal.

[0102] In this embodiment, the system is connected to the LED lighting system via various sensor interfaces, including current sensors, voltage sensors, temperature sensors, and light intensity sensors. These sensors collect real-time operating parameters of the LED, such as operating current, voltage, temperature, and emitted light intensity. The analog signals collected by the sensors are converted into digital signals and transmitted to the IoT data acquisition module via a communication protocol.

[0103] After receiving these digital signals, the data acquisition module performs statistical analysis on the acquired operating parameters. For example, it calculates the average, maximum, and minimum values ​​of current and voltage over a period of time, counts the number of times the temperature exceeds the normal range, and analyzes fluctuations in light intensity. After completing the statistical analysis, it generates corresponding charts and graphs based on the results, such as line graphs showing current changes over time and bar charts comparing light intensity at different time points. Finally, these charts and graphs are transmitted to the control terminal via network protocols or a local interface and displayed on the terminal's screen, allowing users to intuitively understand the LED's operating status.

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

[0105] The collected working parameters are compared and analyzed in real time with these thresholds and rules. When a working parameter is detected to exceed the threshold or violate the fault judgment rules, it is determined that a fault has occurred and the fault reminder mechanism is triggered.

[0106] Optionally, a fault report can be generated based on the detection results. The report includes information such as the time of the fault, the parameters involved, the specific values ​​of the parameters, the fault type, and possible causes of the fault. The fault report and alert information are then sent to the control terminal. After receiving this information, the control terminal will display a prominent alert window on its screen, issuing an alarm to the user through text, sound, flashing icons, etc.

[0107] Optionally, depending on the severity of the fault, the system can automatically send SMS or email notifications to relevant maintenance personnel to ensure that the fault can be handled in a timely manner and to guarantee the normal operation of the LED lighting system.

[0108] The above process acquires the operating parameters of the LED during the lighting process, generates statistical charts and displays them on the control terminal, and provides fault alerts, making it convenient for users to understand the operating status of the lighting system in real time, promptly identify and solve problems, and improve the reliability and maintainability of the lighting system.

[0109] This application's technical solution acquires initial parameters of a lighting system via the Internet of Things (IoT). These initial parameters include the initial LED parameters of the LED devices in the lighting system and the power parameters of the lighting system. Based on the initial LED parameters of the lighting nodes corresponding to the LED devices and their neighboring nodes, a multi-dimensional lighting function is generated. The LED parameters of the lighting nodes and their neighboring nodes at the current moment are input into the lighting function to determine the state variables of the lighting nodes at the next moment. According to the power 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 devices. The LED devices are controlled to provide illumination based on the state variables and the signal frequency. By accurately acquiring initial parameters through the IoT, determining a multi-dimensional lighting function based on the parameters of the lighting nodes and their neighboring nodes, dynamically predicting the state variables and modulating the current signal frequency, and making corresponding decisions based on real-time lighting conditions, the adaptability and flexibility of the lighting are improved, the luminous efficiency of the lighting system is enhanced, and energy consumption is reduced.

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

[0111] Figure 3 A block diagram of an IoT-based remote LED lighting system according to an embodiment of this application is shown.

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

[0113] The acquisition unit 310 is used to acquire 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 parameters of the lighting system.

[0114] The target unit 320 is used to generate a multi-dimensional lighting function based on the initial LED parameters of the lighting node and neighboring nodes corresponding to the LED device.

[0115] Variable unit 330 is used to input the LED parameters of the lighting node and its neighboring nodes at the current time into the lighting function to determine the state variables of the lighting node at the next time.

[0116] The modulation unit 340 is used to dynamically modulate the current signal output by the power supply according to the power supply parameters and the LED parameters, and determine the signal frequency of the current signal passing through the LED device.

[0117] The lighting unit 350 is used to control the LED device to provide illumination based on the state variable and the signal frequency.

[0118] In this application, based on the aforementioned scheme, obtaining the initial parameters of the lighting system through the Internet of Things includes: constructing an Internet of Things based on the lighting system, wherein the Internet of Things includes a sensing 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.

[0119] In this application, based on the aforementioned scheme, the step of generating a multi-dimensional lighting function based on the initial LED parameters of the lighting node and neighboring 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 neighboring nodes of the lighting node based on the location information; obtaining the initial LED parameters of the lighting node and its neighboring 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 aforementioned scheme, the step of inputting the LED parameters of the lighting node and its neighboring 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 parameters, color temperature parameters, and energy efficiency parameters of the lighting node at the current moment, as well as the brightness parameters of the neighboring nodes of the lighting node at the current moment, into the lighting function for solving to determine the state variables of the lighting node at the next moment.

[0121] In this application, based on the aforementioned scheme, the step of 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; and 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 aforementioned scheme, controlling the LED device for illumination based on the state variable and the signal frequency includes: parsing the state variable based on a preset mapping relationship to generate control parameters; generating control instructions according to the control parameters and the signal frequency, and sending the control instructions to the LED driver module; the driver module compiles the control instructions into a drive signal to control the LED device for illumination through the drive signal.

[0123] In this application, based on the aforementioned scheme, after controlling the LED device for lighting based on the state variable and the signal frequency, the method further includes: acquiring the operating parameters of the LED during the lighting process, statistically analyzing the operating parameters, generating statistical charts, and displaying them on the control terminal; and issuing a reminder on the control terminal when a fault is detected based on the operating parameters.

[0124] This application's technical solution acquires initial parameters of a lighting system via the Internet of Things (IoT). These initial parameters include the initial LED parameters of the LED devices in the lighting system and the power parameters of the lighting system. Based on the initial LED parameters of the lighting nodes corresponding to the LED devices and their neighboring nodes, a multi-dimensional lighting function is generated. The LED parameters of the lighting nodes and their neighboring nodes at the current moment are input into the lighting function to determine the state variables of the lighting nodes at the next moment. According to the power 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 devices. The LED devices are controlled to provide illumination based on the state variables and the signal frequency. By accurately acquiring initial parameters through the IoT, determining a multi-dimensional lighting function based on the parameters of the lighting nodes and their neighboring nodes, dynamically predicting the state variables and modulating the current signal frequency, and making corresponding decisions based on real-time lighting conditions, the adaptability and flexibility of the lighting are improved, the luminous efficiency of the lighting system is enhanced, and energy consumption is reduced.

[0125] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present 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 impose any limitations on the function and scope of use 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 based on a program stored in a read-only memory 402 or a program loaded from a storage section 408 into a random access memory 403, such as executing the IoT-based remote LED lighting method described in the above embodiment. The random access memory 403 also stores various programs and data required for system operation. The central processing unit 401, the read-only memory 402, and the random access memory 403 are interconnected via a bus 404. An 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, mouse, etc.; an output section 407 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, 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, 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 disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 410 as needed so that computer programs read from it can be installed into the storage section 408 as needed.

[0129] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 409, and / or installed from removable medium 411. When the computer program is executed by central processing unit 401, it performs various functions defined in the system of this application.

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

[0131] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0132] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0133] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various alternative implementations described above.

[0134] In another aspect, this application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to implement the IoT-based remote LED lighting method described in the above embodiments.

[0135] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above 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 above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this 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, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the method according to the embodiments of this application.

[0137] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

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

Claims

1. A remote LED lighting method based on Internet of Things, characterized in that, The method comprises the following steps: obtaining initial parameters of a lighting system through an Internet of Things, wherein the initial parameters comprise 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 and neighbor nodes corresponding to the LED devices; inputting the LED parameters of the lighting nodes and their neighbor nodes at a current time into the lighting function to determine state variables of the lighting nodes at a next time; dynamically modulating a current signal output by a power supply based on the power supply parameters and the LED parameters to determine a signal frequency of the current signal passing through the LED devices; controlling the LED devices to illuminate based on the state variables and the signal frequency; wherein the step of generating a multi-dimensional lighting function based on the initial LED parameters of the lighting nodes and neighbor nodes corresponding to the LED devices comprises the following steps: obtaining the total number and position information of the lighting nodes in the lighting system through the Internet of Things; determining the neighbor nodes of the lighting nodes based on the position information; obtaining the initial LED parameters of the lighting nodes and their neighbor nodes, and generating a multi-dimensional lighting function based on the increments of the initial LED parameters in the three dimensions of brightness, color temperature and energy efficiency, in combination with the total number; wherein the step of dynamically modulating a current signal output by a power supply based on the power supply parameters and the LED parameters to determine a signal frequency of the current signal passing through the LED devices comprises the following steps: determining a time domain profile of the current signal based on a pulse period of the current signal in the power supply parameter S is: wherein, denotes the hyperbolic secant function, t denotes time, nT denotes the start time of the n modulation period; T denotes the pulse period of the current signal in the power supply parameter, denotes the modulation pulse width; determining a signal frequency of a current signal output by the power supply through the LED device based on the time domain distribution and an initial lattice period in the LED parameters is: wherein denotes the signal frequency of the current signal passing through the LED device at time t, denotes the initial lattice period, denotes the circle ratio, denotes the speed of light, denotes the piezoelectric coupling coefficient; wherein the step of controlling the LED devices to illuminate based on the state variables and the signal frequency comprises the following steps: controlling the LED devices to illuminate based on the state variables and the signal frequency, which comprises the following steps: analyzing the state variables based on a preset mapping relationship to generate control parameters; generating control instructions based on the control parameters and the signal frequency, and sending the control instructions to a driving module of the LED; the driving module compiles the control instructions into driving signals to control the LED devices to illuminate through the driving signals.

2. The IoT based remote LED lighting method as claimed in claim 1 wherein, The step of obtaining initial parameters of a lighting system through an Internet of Things comprises the following steps: constructing an Internet of Things based on the lighting system, wherein the Internet of Things comprises 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 IoT based remote LED lighting method as claimed in claim 1 wherein, The step of inputting the LED parameters of the lighting nodes and their neighbor nodes at a current time into the lighting function to determine state variables of the lighting nodes at a next time comprises the following steps: inputting the brightness parameters, color temperature parameters and energy efficiency parameters of the lighting nodes at a current time, and the brightness parameters of the neighbor nodes of the lighting nodes at a current time into the lighting function to solve and determine the state variables of the lighting nodes at a next time.

4. The Internet of Things based remote LED lighting method according to any one of claims 1-3, characterized in that, After the step of controlling the LED devices to illuminate based on the state variables and the signal frequency, the method further comprises the following steps: obtaining working parameters of the LED in the lighting process; statistically analyzing the working parameters to generate statistical charts and displaying the statistical charts on a control terminal.

5. A remote LED lighting system based on Internet of Things characterized in that, The method comprises the following steps: An acquisition unit is configured to acquire initial parameters of a lighting system through an Internet of Things, the initial parameters including initial LED parameters of LED devices in the lighting system and power supply parameters of the lighting system; A target unit is configured to generate a multi-dimensional lighting function based on initial LED parameters of a lighting node corresponding to the LED devices and neighbor nodes; A variable unit is configured to input LED parameters of the lighting node and the neighbor nodes at a current time into the lighting function to determine a state variable of the lighting node at a next time; A modulation unit is 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 of the current signal passing through the LED devices; A lighting unit is configured to control the LED devices to perform lighting based on the state variable and the signal frequency; The generation of the multi-dimensional lighting function based on the initial LED parameters of the lighting node corresponding to the LED devices and the neighbor nodes includes: acquiring a 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; acquiring initial LED parameters of the lighting nodes and the neighbor nodes, and generating a multi-dimensional lighting function based on increments corresponding to the initial LED parameters in three dimensions of brightness, color temperature and energy efficiency, and the total number; The dynamic modulation of 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 devices includes: determining a time domain profile of the current signal based on a pulse period of the current signal in the power supply parameter S is: wherein, denotes the hyperbolic secant function, t denotes time, nT denotes the start time of the n modulation period; T denotes the pulse period of the current signal in the power supply parameter, denotes the modulation pulse width; determining a signal frequency of a current signal output by the power supply through the LED device based on the time domain distribution and an initial lattice period in the LED parameters is: wherein, denotes the signal frequency of the current signal passing through the LED device at time t, denotes the initial lattice period, denotes the circle constant, denotes the speed of light, denotes the piezoelectric coupling coefficient; The control of the LED devices to perform lighting based on the state variable and the signal frequency includes: The control of the LED devices to perform lighting based on the state variable and the signal frequency includes: analyzing the state variable based on a preset mapping relationship to generate a control parameter; generating a control instruction according to the control parameter and the signal frequency, and sending the control instruction to a driving module of the LED; The driving module compiles the control instruction into a driving signal to control the LED devices to perform lighting through the driving signal.

6. The Internet of Things based remote LED lighting system as claimed in claim 5, wherein, The acquisition of the initial parameters of the lighting system through the Internet of Things includes: constructing an Internet of Things based on a lighting system, the Internet of Things including 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.

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