Remote regulation and control LED illumination system based on Internet of Things

Abstract

The invention discloses a remote regulation and control LED lighting system based on the Internet of Things, and relates to the technical field of LED lighting systems, comprising an LED lighting equipment module which comprises an efficient lamp, a microcontroller, an Internet of Things communication module, a remote control terminal module supporting multi-protocol and encryption, having Mesh networking, a multi-terminal control, having multiple functions and innovation formulas, and a sensor module; the intelligent LED lighting control system has the advantages that environment information is collected, the data management and analysis module stores and analyzes data, energy-saving management and the like are achieved, all the modules work cooperatively, and the functions of remote intelligent regulation and control, fault self-inspection, butt joint with other systems and the like of LED lighting are achieved. Through collaborative innovation of multiple modules, remote intelligent regulation and control of LED lighting are realized, the lighting quality and user experience are improved, energy is saved, consumption is reduced, the system has the functions of fault self-checking and alarming and the like, the reliability and compatibility of the system are improved, and the diversified requirements of modern lighting systems are met.

Description

Technical Field

[0001] The present invention relates to the technical field of LED lighting systems, and in particular to a remotely controlled LED lighting system based on the Internet of Things. Background Art

[0002] In today's society, lighting systems are an indispensable part of daily life and work, and their importance is self-evident. With the continuous advancement of technology and the improvement of people's quality of life, the requirements for lighting systems are becoming increasingly higher, and the limitations of traditional lighting systems are becoming increasingly prominent.

[0003] Traditional lighting systems primarily rely on simple circuit control, often relying on manual operation of switches to turn lamps on and off. This approach lacks flexibility and convenience. For example, in large commercial venues or office buildings, managers must manually operate switches in each area to control lighting. This is not only time-consuming and labor-intensive, but also difficult to achieve precise lighting control. When it comes to adjusting light brightness and color temperature based on time, scene, or activity, traditional lighting systems are often unable to meet diverse lighting needs.

[0004] Traditional lighting systems suffer from significant energy waste. Due to a lack of intelligent regulation, lighting cannot automatically adjust to ambient light levels and occupant activity. For example, even during the day when natural light is abundant, many indoor spaces remain permanently lit, resulting in unnecessary energy consumption. According to statistics, energy waste from traditional lighting systems in some public buildings can reach over 30% of total lighting energy consumption. Furthermore, the relatively low luminous efficiency of traditional lighting fixtures means that much of the electrical energy is converted into heat and wasted, further exacerbating energy consumption.

[0005] Traditional lighting systems also face significant limitations in terms of control. They lack remote control, creating significant inconvenience for scenarios requiring remote lighting management, such as remote monitoring in smart homes and lighting control in remote offices. Users cannot adjust lighting in real time after leaving a location, nor can they pre-set lighting settings based on actual needs. Furthermore, traditional lighting systems lack real-time monitoring and data analysis capabilities for lamp operating status. When a lamp malfunctions, manual inspections are often required to detect it, leading to delayed repairs, disrupting normal use, and increasing maintenance costs. Furthermore, the inability to collect and analyze data such as lamp energy consumption and usage time makes it difficult to optimize and improve the lighting system, hindering effective energy management and conservation.

[0006] With the rise and development of the Internet of Things (IoT) technology, its application in various fields has opened up possibilities for intelligent upgrades in lighting systems. IoT technology enables interconnection and information sharing between devices, making remote control, intelligent adjustment, and real-time monitoring of lighting equipment a reality. Furthermore, the continued maturity of LED lighting technology, with its advantages such as high luminous efficiency, long life, and strong adjustability, provides a strong hardware foundation for the development of intelligent lighting systems. However, effectively integrating IoT with LED lighting technology to build a comprehensive, high-performance, remotely controlled LED lighting system still faces numerous technical challenges and unmet needs. For example, ensuring the stable operation and compatibility of multiple communication protocols in diverse environments, implementing precise intelligent control algorithms to meet the personalized needs of diverse users, and ensuring secure data transmission and processing are key challenges. Therefore, developing an IoT-based remotely controlled LED lighting system that overcomes the shortcomings of traditional lighting systems and leverages the advantages of both IoT and LED technologies has become a crucial development direction and urgent need in the current lighting industry. Summary of the Invention

[0007] The present invention proposes a remote control LED lighting system based on the Internet of Things to solve the problems mentioned in the above-mentioned prior art.

[0008] In order to achieve the above objectives, the present invention adopts the following technical solution: a remote control LED lighting system based on the Internet of Things, comprising:

[0009] LED lighting modules consist of several LED lamps that utilize high-brightness, low-power LED chips with a luminous efficiency of no less than 100 lm / W, a color temperature adjustable between 2700K and 6500K, and a color rendering index of no less than 80. The lamps feature a robust heat dissipation structure to ensure the LED chip temperature does not exceed 70°C during extended operation, extending the lamp's lifespan. Each LED lamp has a built-in microcontroller that receives and executes control commands, enabling the lamp's on / off, dimming, and color-adjusting functions.

[0010] The IoT communication module is used to realize data communication between LED lighting equipment and remote control terminals. It supports multiple communication protocols, including but not limited to Wi-Fi, Bluetooth, ZigBee, and LoRa, to adapt to different application scenarios and network environments. In Wi-Fi communication mode, the operating frequency is 2.4GHz or 5GHz, and the signal strength is not less than -70dBm, ensuring stable data transmission. The effective transmission distance of Bluetooth communication is not less than 10 meters. ZigBee and LoRa are suitable for long-distance, low-power IoT applications, with transmission distances of up to 100 meters and more than 1000 meters respectively (depending on the specific environment). The module has data encryption and authentication functions, and uses the AES encryption algorithm to encrypt the transmitted data to prevent data from being stolen or tampered with, thereby ensuring communication security;

[0011] In Wi-Fi communication mode, signal strength decreases as the transmission distance increases and is also affected by obstacles and interference sources in the environment. The following formula is used to estimate the effective transmission distance d of Wi-Fi signals in actual environments: Wi-Fi :

[0012]

[0013] Among them, P t Is the Wi-Fi transmission power, unit: dBm. Common Wi-Fi devices generally have a transmission power of about 10-20dBm. Assume here that P t =15dBm; P r It is the minimum power threshold for the receiving end to receive the signal normally, unit: dBm, set P r =-70dBm, that is, stable transmission can be ensured when the signal strength is not less than -70dBm; L f is the free space propagation loss, unit: dB, calculated as L f =32.45+20lg(f)+20lg(d), where f is the operating frequency, unit: MHz. When the operating frequency is 2.4GHz, f=2400MHz. When the operating frequency is 5GHz, f=5000MHz. d is the transmission distance, unit: km.

[0014] The remote control terminal module includes a smartphone app, tablet app, and web control interface. Through these terminals, users can remotely monitor and manage LED lighting equipment in real time. The app and web interface are simple and intuitive, easy to use, and provide functions for lighting group management, timer setting, and scene mode switching. Users can group LED lights according to different needs and control each group of lights independently. The lighting group efficiency formula is introduced: Among them E group Indicates the lamp grouping efficiency, Neffective is the number of lamp groups actually used, N total is the total number of lamp groups, S satis It is the quantitative value of the user's satisfaction with the lighting grouping settings, ranging from 0 to 10, with 10 indicating very satisfied and S total is the maximum satisfaction value. Through this formula, we can evaluate the rationality and effectiveness of the lamp grouping scheme. When the value is close to 1, it means that the lamp grouping effect is good and can effectively meet user needs.

[0015] The timer switch function can set the switch schedule for multiple time periods with an accuracy of up to the minute. In order to better adapt to the user's living habits and energy-saving needs, we use an intelligent timing optimization formula to adjust the switch time: Where T new is the adjusted timer switch time, T current is the currently set timing time, ΔT is the time adjustment amplitude, and ω is a frequency parameter related to the number of days in a week. is the initial phase. This formula can dynamically adjust the timer on / off time according to the user's weekly routine.

[0016] Scene modes include but are not limited to reading mode, party mode, and sleep mode. Each mode corresponds to a different combination of light brightness and color temperature parameters. The scene comfort evaluation formula is introduced:

[0017] C scene =α×L brightness +β×C color +γ×P uniformity

[0018] Among them C scene Indicates the scene comfort, L brightness is the light brightness value, α is the brightness comfort weight coefficient, C color is the color temperature value, β is the color temperature comfort weight coefficient, P uniformity γ is the light uniformity indicator, ranging from 0 to 1, with 1 representing perfect uniformity. This formula allows for a quantitative assessment of the comfort level of each scene mode based on user preferences for different parameters and scenario requirements, allowing for continuous optimization of scene mode parameters to provide users with a more comfortable lighting experience.

[0019] The remote control terminal and the IoT communication module communicate via the Internet, with a data transmission response time of no more than 1 second, ensuring the timeliness and smoothness of user operations.

[0020] The sensor module integrates a variety of sensors to collect environmental information and provide a basis for lighting control. It includes a light intensity sensor with a measurement range of 0-10000 lux and an accuracy of ±5%, which can monitor the ambient light intensity in real time; a temperature sensor with a measurement range of -20℃-80℃ and an accuracy of ±0.5℃, which is used to detect the ambient temperature; a human infrared sensor with a detection distance of not less than 5 meters and an angle range of not less than 120°, which can sense the presence and activities of the human body. The sensor module transmits the collected data to the remote control terminal and LED lighting equipment module in real time through the Internet of Things communication module. The LED lighting equipment automatically adjusts the light brightness and color temperature parameters according to these environmental information to achieve intelligent lighting control. For example, when the light intensity sensor detects that the ambient light intensity is high, it automatically reduces the brightness of the LED lamp; when the human infrared sensor detects that someone enters the room, it automatically turns on the light, and automatically turns off the light after a delay after the person leaves. The delay time can be set within the range of 1-10 minutes;

[0021] The data management and analysis module, located on the cloud server, stores and processes operational data from the LED lighting system. This includes records of lamp on / off, dimming and color adjustment, energy consumption data, and environmental data. Utilizing big data storage technology, it can store at least one year of system operational data. Using data analysis algorithms, it mines and analyzes this data, providing users with energy consumption reports and lighting usage analysis services. Energy consumption reports allow users to understand lighting energy consumption over different time periods and areas, enabling them to implement energy-saving measures. Lighting usage analysis can recommend personalized lighting settings based on user operation records. Furthermore, the data management and analysis module predicts future lighting needs based on historical data and environmental trends, allowing for proactive adjustments to lighting strategies for energy-saving optimization and intelligent management. For example, by analyzing illumination data from the past week and user on / off times, it can predict optimal lighting brightness settings for different times of the day and automatically adjust the lighting before users use the system, improving the user experience while reducing energy consumption.

[0022] In intelligent lighting control, the following formula is used to automatically adjust the light brightness according to the light intensity:

[0023]

[0024] Among them L new is the adjusted light brightness, L current is the current light brightness, S current is the light intensity value detected by the current light sensor, S maxis the maximum measurement value of the light sensor, 10,000 lux, and k is the adjustment coefficient, which is set according to the actual scene and user needs, and the value range is generally between 0.1 and 0.5. The principle of this formula is to dynamically adjust the light brightness based on the ratio of the current light intensity to the maximum light intensity. When the ambient light is stronger, S current The larger the L new It will be reduced accordingly to keep the indoor lighting relatively stable and comfortable, achieving the purpose of energy saving and intelligent control.

[0025] When adjusting the color temperature of the light based on the temperature sensor data, the following formula is used:

[0026] C new =C base +m×(T current -T base )

[0027] Among them C new is the adjusted light color temperature value, C base is the initial basic color temperature value (such as the value preset according to the scene mode), T current is the ambient temperature value detected by the current temperature sensor, T base is the temperature reference value (which can be the average value of the indoor temperature, such as 25°C), and m is the color temperature adjustment coefficient, which is determined based on experiments and user experience, and is generally between 50-200 (unit: K / °C). This formula adjusts the light color temperature based on the difference between the ambient temperature and the reference temperature. When the ambient temperature is higher than the reference temperature, T current -T base >0, the color temperature of the light will decrease accordingly, C new <C base , creating a cool feeling; when the ambient temperature is lower than the reference temperature, the light color temperature will increase, C new >C base , creating a warm atmosphere and enhancing users' comfort and experience.

[0028] Furthermore, the LED lighting module also features fault detection and alarm functionality. When a lamp malfunctions, such as a damaged LED chip or a driver power failure, the microcontroller automatically detects the fault type and location and transmits this information to the remote control terminal and data management and analysis module via the IoT communication module. This information includes the fault code, time of occurrence, and lamp number, allowing users to promptly identify the fault and arrange repairs. Furthermore, the LED lamp can generate a local alarm by flashing its light or emitting a specific sound, alerting on-site personnel.

[0029] Furthermore, the IoT communication module supports mesh networking. When multiple LED lighting devices and sensors are distributed over a large area, mesh networking enables self-organizing, self-healing, multi-hop communication, improving network coverage and stability. In mesh networking mode, nodes in the network automatically select the optimal transmission path to ensure reliable data transmission. Even if a node fails, data can be forwarded by other nodes to reach its destination, enhancing the system's anti-interference capabilities and fault tolerance.

[0030] Furthermore, the remote control terminal module supports voice control. Users can operate the LED lighting equipment through voice commands, such as "Turn on the living room lights," "Dim the bedroom lights to 50%," or "Switch to reading mode." This voice control function utilizes advanced speech recognition technology with an accuracy rate of at least 95%. It can recognize multiple languages ​​and dialects, facilitating user convenience. Furthermore, the response time for voice commands is no more than 0.5 seconds, ensuring immediate and convenient operation.

[0031] Furthermore, the data management and analysis module is capable of interfacing with other intelligent device systems, such as smart home systems and intelligent building management systems. Through open API interfaces, data sharing and interactive control with other systems are possible. For example, after interfacing with a smart home system, when a user opens their door, not only can the lighting automatically turn on, but also the air conditioner, TV, and other smart devices, achieving intelligent scene linkage. Interfacing with an intelligent building management system can incorporate lighting system operating data into the building energy management system, providing data support for optimizing the building's overall energy consumption.

[0032] Furthermore, a method for remotely controlling an LED lighting system based on the Internet of Things includes the following steps:

[0033] S1. System Installation and Configuration: Install the LED lighting equipment in the desired location, ensuring that the fixtures are securely mounted and the electrical connections are correct. Install the sensor module to enable it to accurately collect environmental information. Configure the IoT communication module to establish communication connections with the LED lighting equipment, remote control terminal, and cloud server. Install the corresponding application on the remote control terminal or open the web control interface to register and log in as a user to complete the system initialization setup.

[0034] S2. Device grouping and scene mode settings: Through the remote control terminal, LED lighting devices can be grouped according to different areas or functions, for example, the living room lamps can be grouped together, and the bedroom lamps can be grouped together. Different scene modes can be set for each group. For example, in reading mode, the light brightness is set to 500 lux and the color temperature is set to 4000K; in party mode, the light brightness is set to 800 lux and the color temperature is set to 2700K. The color can be adjusted according to the atmosphere. Users can customize the parameters of the scene mode according to their preferences and actual needs.

[0035] S3. Remote control and real-time monitoring: users can remotely control the switching, dimming, and color adjustment functions of LED lighting equipment through smartphone applications, tablet applications, or web-based control interfaces. The working status of LED lamps and environmental information (illuminance, temperature, and whether there are people present) can be viewed in real time. When the lights need to be adjusted, the user sends a control instruction on the remote control terminal. The instruction is transmitted to the IoT communication module via the Internet, and then forwarded by the IoT communication module to the corresponding LED lighting equipment. The microcontroller of the LED lighting equipment receives the instruction and performs the corresponding operation to achieve remote control of the light. At the same time, the sensor module collects environmental information in real time and uploads the data to the cloud server and remote control terminal. Users can understand changes in the environment at any time.

[0036] S4, intelligent lighting control, based on the environmental information collected by the sensor module, the LED lighting equipment automatically adjusts intelligently. When the illuminance sensor detects a change in the ambient light intensity, the LED lamp automatically adjusts the brightness to maintain the comfort of the indoor lighting. When the human infrared sensor detects someone entering or leaving the room, it automatically controls the turning on and off of the lights. The ambient temperature data collected by the temperature sensor can be used to assist in adjusting the color temperature of the light. For example, when the temperature is high, the color temperature of the light can be appropriately lowered to give people a cool feeling; when the temperature is low, the color temperature of the light can be increased to create a warm atmosphere. The intelligent lighting control algorithm is optimized according to preset rules and user habits to continuously improve the accuracy and comfort of intelligent control;

[0037] S5. Data management and analysis: The data management and analysis module of the cloud server stores and analyzes the system operation data. Generate energy consumption reports regularly, count the lighting energy consumption in different time periods and different areas, and display them to users in the form of charts to help users understand energy consumption and discover energy-saving potential. Analyze the user's lighting usage habits, and provide users with personalized lighting suggestions and automatically optimized lighting strategies based on the user's daily operating patterns and environmental changes. For example, since the user usually spends time in the living room between 7 and 10 pm and prefers brighter lights, the system automatically adjusts the brightness of the living room lights to the brightness the user is accustomed to during this time period. At the same time, through the analysis of historical data and environmental trends, predict future lighting needs, adjust the working status of lighting equipment in advance, and achieve energy saving and intelligent management;

[0038] In energy consumption forecasting, the following time series forecasting formula is used:

[0039]

[0040] Among them E t+h is the predicted energy consumption value at time t+h, E t is the energy consumption value at the current moment, E t-i is the energy consumption value at the past i moments, p is the number of historical data time points considered, α and β are weighting coefficients for historical energy consumption data, determined based on the importance and timeliness of the data, and γ is the coefficient of influence of environmental factors (such as temperature and illuminance) on energy consumption, obtained through data analysis and is the comprehensive value of environmental factors at that moment (which can be a weighted sum of multiple environmental parameters). Using this formula, the system can more accurately predict lighting energy consumption over a period of time based on historical energy consumption data and current environmental conditions, providing a basis for formulating energy-saving measures.

[0041] S6. System Maintenance and Troubleshooting: Regularly inspect and maintain the LED lighting system, including cleaning lamps, calibrating sensors, and testing communication equipment. When the system detects a fault in an LED lighting device, it promptly obtains fault information through the remote control terminal and data management and analysis module. Based on the type and severity of the fault, appropriate maintenance personnel are assigned to perform repairs. For simple faults, such as a loose bulb, users can resolve them themselves by following the troubleshooting guide provided by the system. After repairs are completed, the device is tested to ensure it has returned to normal operation, and the repair record is uploaded to the cloud server for subsequent query and analysis.

[0042] Furthermore, during the system installation and configuration steps, the LED lighting equipment and sensors are calibrated to ensure the accuracy of their measurement data. The calibration process includes calibration of the light intensity sensor, temperature sensor, and human infrared sensor. Light intensity sensor calibration uses a standard light source for comparison and calibration, achieving an accuracy of ±3%. Temperature sensor calibration uses a high-precision thermometer as a reference, with a calibration error of no more than ±0.3°C. Human infrared sensor calibration involves testing and adjustment using simulated human movements to ensure detection accuracy and reliability.

[0043] Furthermore, in the intelligent lighting control step, an adaptive learning algorithm is used to optimize the intelligent lighting control strategy. The system continuously adjusts the light brightness and color temperature parameters based on actual user feedback and environmental changes. For example, if a user frequently manually adjusts the light brightness above the intelligent control setting, the system will gradually increase the default brightness value for that scenario to better meet the user's needs. Through continuous learning and optimization, the personalized and comfortable intelligent lighting control is enhanced.

[0044] Furthermore, during the data management and analysis steps, machine learning algorithms are used to analyze and predict energy consumption data. Regression analysis algorithms are used to build energy consumption models. Based on historical energy consumption data, environmental factors (such as season and weather), and lighting usage characteristics, future energy consumption trends are predicted. By proactively implementing energy-saving measures, such as adjusting lighting equipment operating hours and optimizing intelligent control strategies, effective energy management and conservation can be achieved.

[0045] Furthermore, during system maintenance and troubleshooting, a knowledge base for equipment failures is established. Common failure types, causes, and solutions are entered into the knowledge base. When a system failure occurs, the fault diagnosis algorithm compares the information with the knowledge base to quickly locate the cause and provide a solution. Furthermore, the knowledge base is regularly updated and optimized to improve the efficiency and accuracy of troubleshooting.

[0046] Compared with the existing technology, the beneficial effects of the present invention are:

[0047] This invention utilizes high-precision LED lighting modules to achieve efficient lighting, wide color temperature adjustment, and a high color rendering index, providing users with a high-quality lighting experience. The built-in microcontroller enables precise switching, dimming, and color adjustment to meet the needs of various scenarios.

[0048] The IoT communication module's support for multiple communication protocols and data encryption ensures stable system communication and data security. Whether it's Wi-Fi, Bluetooth, ZigBee, or LoRa, it can adapt to different environments and ensure reliable remote control. Furthermore, data encryption prevents data theft or tampering, protecting user privacy and system security.

[0049] The remote control terminal module's rich functionality significantly enhances user convenience. Features such as lamp group management, timer on / off settings, and scene mode switching allow users to easily customize their lighting solutions. Innovative lamp group efficiency formulas, intelligent timing optimization formulas, and scene comfort assessment formulas further optimize the user experience and enhance the intelligence of the lighting system.

[0050] The application of sensor modules enables intelligent lighting control. Light brightness and color temperature are automatically adjusted based on environmental information such as light intensity, temperature, and human activity, improving comfort and achieving energy savings. For example, brightness is automatically adjusted based on light intensity to avoid excessive light or dimming, while color temperature is adjusted based on temperature to create a more comfortable atmosphere.

[0051] The data management and analysis module plays a vital role. It can store and analyze large amounts of operational data, provide users with personalized lighting settings, predict lighting needs, and adjust strategies in advance, effectively reducing energy consumption while improving user experience.

[0052] Furthermore, the system's fault self-diagnosis and alarm functions, mesh networking, voice control, and integration with other intelligent device systems further enhance its reliability, scalability, and compatibility. This invention comprehensively improves the performance of LED lighting systems, providing users with a more intelligent, convenient, energy-efficient, and safe lighting solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is a schematic block diagram of a remote control LED lighting system based on the Internet of Things proposed by the present invention;

[0054] Figure 2 This is a schematic block diagram of a remote control LED lighting method based on the Internet of Things proposed by the present invention. DETAILED DESCRIPTION

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0056] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise" and "counterclockwise" indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore should not be understood as limiting the present invention.

[0057] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the said features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be a connection between the two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The present invention will be further described in detail below with reference to the accompanying drawings.

[0058] Reference Figure 1-2 : A remote control LED lighting system based on the Internet of Things, comprising:

[0059] LED lighting modules consist of several LED lamps that utilize high-brightness, low-power LED chips with a luminous efficiency of no less than 100 lm / W, a color temperature adjustable between 2700K and 6500K, and a color rendering index of no less than 80. The lamps feature a robust heat dissipation structure to ensure the LED chip temperature does not exceed 70°C during extended operation, extending the lamp's lifespan. Each LED lamp has a built-in microcontroller that receives and executes control commands, enabling the lamp's on / off, dimming, and color-adjusting functions.

[0060] The IoT communication module is used to realize data communication between LED lighting equipment and remote control terminals. It supports multiple communication protocols, including but not limited to Wi-Fi, Bluetooth, ZigBee, and LoRa, to adapt to different application scenarios and network environments. In Wi-Fi communication mode, the operating frequency is 2.4GHz or 5GHz, and the signal strength is not less than -70dBm, ensuring stable data transmission. The effective transmission distance of Bluetooth communication is not less than 10 meters. ZigBee and LoRa are suitable for long-distance, low-power IoT applications, with transmission distances of up to 100 meters and more than 1000 meters respectively (depending on the specific environment). The module has data encryption and authentication functions, and uses the AES encryption algorithm to encrypt the transmitted data to prevent data from being stolen or tampered with, thereby ensuring communication security;

[0061] In Wi-Fi communication mode, signal strength decreases as the transmission distance increases and is also affected by obstacles and interference sources in the environment. The following formula is used to estimate the effective transmission distance d of Wi-Fi signals in actual environments: Wi-Fi :

[0062]

[0063] Among them, P t Is the Wi-Fi transmission power, unit: dBm. Common Wi-Fi devices generally have a transmission power of about 10-20dBm. Assume here that P t =15dBm; P r It is the minimum power threshold for the receiving end to receive the signal normally, unit: dBm, set P r =-70dBm, that is, stable transmission can be ensured when the signal strength is not less than -70dBm; L f is the free space propagation loss, unit: dB, calculated as L f =32.45+20lg(f)+20lg(d), where f is the operating frequency, unit: MHz. When the operating frequency is 2.4GHz, f=2400MHz. When the operating frequency is 5GHz, f=5000MHz. d is the transmission distance, unit: km.

[0064] The remote control terminal module includes a smartphone app, tablet app, and web control interface. Through these terminals, users can remotely monitor and manage LED lighting equipment in real time. The app and web interface are simple and intuitive, easy to use, and provide functions for lighting group management, timer setting, and scene mode switching. Users can group LED lamps according to different needs and control each group of lamps independently. The lamp group efficiency formula is introduced: Among them E group Indicates the lamp grouping efficiency, Neffective is the number of lamp groups actually used, N total is the total number of lamp groups, S satis It is the quantitative value of the user's satisfaction with the lighting grouping settings, ranging from 0 to 10, with 10 indicating very satisfied and S total is the maximum satisfaction value. Through this formula, we can evaluate the rationality and effectiveness of the lamp grouping scheme. When the value is close to 1, it means that the lamp grouping effect is good and can effectively meet user needs.

[0065] The timer switch function can set the switch schedule for multiple time periods with an accuracy of up to the minute. In order to better adapt to the user's living habits and energy-saving needs, we use an intelligent timing optimization formula to adjust the switch time: Where T new is the adjusted timer switch time, T current is the currently set timing time, ΔT is the time adjustment amplitude, and ω is a frequency parameter related to the number of days in a week. is the initial phase. This formula can dynamically adjust the timer on / off time according to the user's weekly routine.

[0066] Scene modes include but are not limited to reading mode, party mode, and sleep mode. Each mode corresponds to a different combination of light brightness and color temperature parameters. The scene comfort evaluation formula is introduced:

[0067] C scene =α×L brightness +β×C color +γ×P uniformity

[0068] Among them C scene Indicates the scene comfort, L brightness is the light brightness value, α is the brightness comfort weight coefficient, C color is the color temperature value, β is the color temperature comfort weight coefficient, P uniformity It is the light uniformity index, with a value range of 0-1. 1表 indicates completely uniform, and γ is the uniformity comfort weighting coefficient. This formula allows for quantitative evaluation of scene mode comfort based on user preferences for different parameters and scenario requirements, thereby continuously optimizing scene mode parameter settings to provide users with a more comfortable lighting experience.

[0069] The remote control terminal and the IoT communication module communicate via the Internet, with a data transmission response time of no more than 1 second, ensuring the timeliness and smoothness of user operations.

[0070] The sensor module integrates a variety of sensors to collect environmental information and provide a basis for lighting control. It includes a light intensity sensor with a measurement range of 0-10000 lux and an accuracy of ±5%, which can monitor the ambient light intensity in real time; a temperature sensor with a measurement range of -20℃-80℃ and an accuracy of ±0.5℃, which is used to detect the ambient temperature; a human infrared sensor with a detection distance of not less than 5 meters and an angle range of not less than 120°, which can sense the presence and activities of the human body. The sensor module transmits the collected data to the remote control terminal and LED lighting equipment module in real time through the Internet of Things communication module. The LED lighting equipment automatically adjusts the light brightness and color temperature parameters according to these environmental information to achieve intelligent lighting control. For example, when the light intensity sensor detects that the ambient light intensity is high, it automatically reduces the brightness of the LED lamp; when the human infrared sensor detects that someone enters the room, it automatically turns on the light, and automatically turns off the light after a delay after the person leaves. The delay time can be set within the range of 1-10 minutes;

[0071] The data management and analysis module, located on the cloud server, stores and processes operational data from the LED lighting system. This includes records of lamp on / off, dimming and color adjustment, energy consumption data, and environmental data. Utilizing big data storage technology, it can store at least one year of system operational data. Using data analysis algorithms, it mines and analyzes this data, providing users with energy consumption reports and lighting usage analysis services. Energy consumption reports allow users to understand lighting energy consumption over different time periods and areas, enabling them to implement energy-saving measures. Lighting usage analysis can recommend personalized lighting settings based on user operation records. Furthermore, the data management and analysis module predicts future lighting needs based on historical data and environmental trends, allowing for proactive adjustments to lighting strategies for energy-saving optimization and intelligent management. For example, by analyzing illumination data from the past week and user on / off times, it can predict optimal lighting brightness settings for different times of the day and automatically adjust the lighting before users use the system, improving the user experience while reducing energy consumption.

[0072] In intelligent lighting control, the following formula is used to automatically adjust the light brightness according to the light intensity:

[0073]

[0074] Among them L new is the adjusted light brightness, L current is the current light brightness, S current is the light intensity value detected by the current light sensor, S maxis the maximum measurement value of the light sensor, 10,000 lux, and k is the adjustment coefficient, which is set according to the actual scene and user needs, and the value range is generally between 0.1 and 0.5. The principle of this formula is to dynamically adjust the light brightness based on the ratio of the current light intensity to the maximum light intensity. When the ambient light is stronger, S current The larger the L new It will be reduced accordingly to keep the indoor lighting relatively stable and comfortable, achieving the purpose of energy saving and intelligent control.

[0075] When adjusting the color temperature of the light based on the temperature sensor data, the following formula is used:

[0076] C new =C base +m×(T current -T base )

[0077] Among them C new is the adjusted light color temperature value, C base is the initial basic color temperature value (such as the value preset according to the scene mode), T current is the ambient temperature value detected by the current temperature sensor, T base is the temperature reference value (which can be the average value of the indoor temperature, such as 25°C), and m is the color temperature adjustment coefficient, which is determined based on experiments and user experience, and is generally between 50-200 (unit: K / °C). This formula adjusts the light color temperature based on the difference between the ambient temperature and the reference temperature. When the ambient temperature is higher than the reference temperature, T current -T base >0, the color temperature of the light will decrease accordingly, C new <C base , creating a cool feeling; when the ambient temperature is lower than the reference temperature, the light color temperature will increase, C new >C base , creating a warm atmosphere and enhancing users' comfort and experience.

[0078] In this invention, the LED lighting module also features fault detection and alarm functionality. When a lamp malfunctions, such as a damaged LED chip or a driver power failure, the microcontroller automatically detects the fault type and location and transmits this information to a remote control terminal and data management and analysis module via the IoT communication module. This information includes the fault code, time of occurrence, and lamp number, allowing users to promptly understand the fault and arrange repairs. Furthermore, the LED lamp can generate a local alarm by flashing lights or emitting a specific sound, alerting on-site personnel.

[0079] In this invention, the IoT communication module supports mesh networking. When multiple LED lighting devices and sensors are distributed over a large area, mesh networking can achieve self-organized, self-healing multi-hop communication, improving network coverage and stability. In mesh networking mode, nodes in the network automatically select the optimal transmission path to ensure reliable data transmission. Even if a node fails, data can still reach its destination through forwarding from other nodes, enhancing the system's anti-interference capabilities and fault tolerance.

[0080] In this invention, the remote control terminal module supports voice control. Users can operate the LED lighting equipment through voice commands, such as "Turn on the living room lights," "Dim the bedroom lights to 50%," and "Switch to reading mode." This voice control function utilizes advanced speech recognition technology with an accuracy rate of at least 95%. It can recognize multiple languages ​​and dialects, facilitating user convenience. Furthermore, the response time for voice commands is no more than 0.5 seconds, ensuring immediate and convenient operation.

[0081] In this invention, the data management and analysis module is capable of interfacing with other intelligent device systems, such as smart home systems and intelligent building management systems. Through open API interfaces, data sharing and interactive control with other systems are possible. For example, after interfacing with a smart home system, when a user opens their door, not only can the lighting automatically turn on, but also the air conditioner, television, and other smart devices, achieving intelligent scene linkage. Interfacing with an intelligent building management system can integrate lighting system operating data into the building energy management system, providing data support for optimizing the building's overall energy consumption.

[0082] In the present invention, a method for remotely controlling an LED lighting system based on the Internet of Things comprises the following steps:

[0083] S1. System Installation and Configuration: Install the LED lighting equipment in the desired location, ensuring that the fixtures are securely mounted and the electrical connections are correct. Install the sensor module to enable it to accurately collect environmental information. Configure the IoT communication module to establish communication connections with the LED lighting equipment, remote control terminal, and cloud server. Install the corresponding application on the remote control terminal or open the web control interface to register and log in as a user to complete the system initialization setup.

[0084] S2. Device grouping and scene mode settings: Through the remote control terminal, LED lighting devices can be grouped according to different areas or functions, for example, the living room lamps can be grouped together, and the bedroom lamps can be grouped together. Different scene modes can be set for each group. For example, in reading mode, the light brightness is set to 500 lux and the color temperature is set to 4000K; in party mode, the light brightness is set to 800 lux and the color temperature is set to 2700K. The color can be adjusted according to the atmosphere. Users can customize the parameters of the scene mode according to their preferences and actual needs.

[0085] S3. Remote control and real-time monitoring: users can remotely control the switching, dimming, and color adjustment functions of LED lighting equipment through smartphone applications, tablet applications, or web-based control interfaces. The working status of LED lamps and environmental information (illuminance, temperature, and whether there are people present) can be viewed in real time. When the lights need to be adjusted, the user sends a control instruction on the remote control terminal. The instruction is transmitted to the IoT communication module via the Internet, and then forwarded by the IoT communication module to the corresponding LED lighting equipment. The microcontroller of the LED lighting equipment receives the instruction and performs the corresponding operation to achieve remote control of the light. At the same time, the sensor module collects environmental information in real time and uploads the data to the cloud server and remote control terminal. Users can understand changes in the environment at any time.

[0086] S4, intelligent lighting control, based on the environmental information collected by the sensor module, the LED lighting equipment automatically adjusts intelligently. When the illuminance sensor detects a change in the ambient light intensity, the LED lamp automatically adjusts the brightness to maintain the comfort of the indoor lighting. When the human infrared sensor detects someone entering or leaving the room, it automatically controls the turning on and off of the lights. The ambient temperature data collected by the temperature sensor can be used to assist in adjusting the color temperature of the light. For example, when the temperature is high, the color temperature of the light can be appropriately lowered to give people a cool feeling; when the temperature is low, the color temperature of the light can be increased to create a warm atmosphere. The intelligent lighting control algorithm is optimized according to preset rules and user habits to continuously improve the accuracy and comfort of intelligent control;

[0087] S5. Data management and analysis: The data management and analysis module of the cloud server stores and analyzes the system operation data. Generate energy consumption reports regularly, count the lighting energy consumption in different time periods and different areas, and display them to users in the form of charts to help users understand energy consumption and discover energy-saving potential. Analyze the user's lighting usage habits, and provide users with personalized lighting suggestions and automatically optimized lighting strategies based on the user's daily operating patterns and environmental changes. For example, since the user usually spends time in the living room between 7 and 10 pm and prefers brighter lights, the system automatically adjusts the brightness of the living room lights to the brightness the user is accustomed to during this time period. At the same time, through the analysis of historical data and environmental trends, predict future lighting needs, adjust the working status of lighting equipment in advance, and achieve energy saving and intelligent management;

[0088] In energy consumption forecasting, the following time series forecasting formula is used:

[0089]

[0090] Among them E t+h is the predicted energy consumption value at time t+h, E t is the energy consumption value at the current moment, E t-i is the energy consumption value at the past i moments, p is the number of historical data time points considered, α and β are weighting coefficients for historical energy consumption data, determined based on the importance and timeliness of the data, and γ is the coefficient of influence of environmental factors (such as temperature and illuminance) on energy consumption, obtained through data analysis and is the comprehensive value of environmental factors at that moment (which can be a weighted sum of multiple environmental parameters). Using this formula, the system can more accurately predict lighting energy consumption over a period of time based on historical energy consumption data and current environmental conditions, providing a basis for formulating energy-saving measures.

[0091] S6. System Maintenance and Troubleshooting: Regularly inspect and maintain the LED lighting system, including cleaning lamps, calibrating sensors, and testing communication equipment. When the system detects a fault in an LED lighting device, it promptly obtains fault information through the remote control terminal and data management and analysis module. Based on the type and severity of the fault, appropriate maintenance personnel are assigned to perform repairs. For simple faults, such as a loose bulb, users can resolve them themselves by following the troubleshooting guide provided by the system. After repairs are completed, the device is tested to ensure it has returned to normal operation, and the repair record is uploaded to the cloud server for subsequent query and analysis.

[0092] In this invention, during the system installation and configuration steps, the LED lighting equipment and sensors are calibrated to ensure the accuracy of their measurement data. The calibration process includes calibration of the light intensity sensor, temperature sensor, and human infrared sensor. Light intensity sensor calibration uses a standard light source for comparison and calibration, achieving a calibration accuracy of ±3%. Temperature sensor calibration uses a high-precision thermometer as a reference, with a calibration error of no more than ±0.3°C. Human infrared sensor calibration is tested and adjusted by simulating human activity to ensure detection accuracy and reliability.

[0093] In this invention, an adaptive learning algorithm is used to optimize the intelligent lighting control strategy during the intelligent lighting control step. The system continuously adjusts the light brightness and color temperature parameters based on actual user feedback and environmental changes. For example, if a user frequently manually adjusts the light brightness above the intelligent control setting, the system will gradually increase the default brightness value for that scenario to better meet the user's needs. Through continuous learning and optimization, the personalized and comfortable intelligent lighting control is enhanced.

[0094] In this invention, during the data management and analysis steps, machine learning algorithms are used to analyze and predict energy consumption data. Regression analysis algorithms are used to build energy consumption models. Based on historical energy consumption data, environmental factors (such as season and weather), and lighting usage characteristics, future energy consumption trends are predicted. By proactively implementing energy-saving measures, such as adjusting lighting equipment operating hours and optimizing intelligent control strategies, effective energy management and conservation can be achieved.

[0095] In this invention, a knowledge base of equipment faults is established during system maintenance and troubleshooting. Common fault types, causes, and solutions are entered into the knowledge base. When a system fault occurs, a fault diagnosis algorithm compares the information with the knowledge base to quickly locate the cause and provide a corresponding solution. Furthermore, the knowledge base is regularly updated and optimized to improve the efficiency and accuracy of fault handling.

[0096] The above are only preferred specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field can replace or change the technical solution and inventive concept of the present invention within the technical scope disclosed by the present invention, and the replacement or change should be covered by the scope of protection of the present invention.

Claims

1. A remote control LED lighting system based on the Internet of Things, characterized in that: include: LED lighting equipment module, composed of a number of LED lamps, the luminous efficiency of the LED lamps is not less than 100lm / W, the color temperature is in the range of 2700K-6500K, and the color rendering index is not less than 80. Each LED lamp has a built-in microcontroller for receiving and executing control instructions to realize the switch, dimming and color adjustment functions of the lamp; The IoT communication module is used to realize data communication between LED lighting equipment and remote control terminals. It supports Wi-Fi, Bluetooth, ZigBee or LoRa communication protocols. The IoT communication module has data encryption and authentication functions. It uses the AES encryption algorithm to encrypt the transmitted data to prevent the data from being stolen or tampered with. In Wi-Fi communication mode, the signal strength decreases as the transmission distance increases. At the same time, it is affected by obstacles and interference sources in the environment. The following formula is used to estimate the effective transmission distance d of the Wi-Fi signal in the actual environment. Wi-Fi : Where P t is the Wi-Fi transmission power, unit: dBm, let P t =15dBm; P r It is the minimum power threshold for the receiving end to receive the signal normally, unit: dBm, set P r =-70dBm, L f is the free space propagation loss, unit: dB, calculated as L f =32.45+20lg(f)+20lg(d), where f is the operating frequency, unit: MHz, when the operating frequency is 2.4GHz, f=2400MHz, when the operating frequency is 5GHz, f=5000MHz, d is the transmission distance, unit: km; The remote control terminal module includes smartphone applications, tablet applications and web-based control interfaces, which are used to remotely monitor and manage LED lighting equipment in real time. It has the functions of lamp grouping management, timer switch setting, and scene mode switching. Users can group LED lamps according to different needs and independently control lamps in different groups. The lamp grouping efficiency formula is introduced: Where E group Indicates the lamp grouping efficiency, N effective is the number of lamp groups actually used, N total is the total number of lamp groups, S satis It is the quantitative value of the user's satisfaction with the lighting grouping settings, ranging from 0 to 10, with 10 indicating very satisfied and S total is the maximum satisfaction value. When the satisfaction value is close to 1, it means that the lighting grouping effect is better; The timed switch function uses an intelligent timing optimization formula to adjust the switch time, which is published as: Where T new is the adjusted timer switch time, T current is the currently set timing time, ΔT is the time adjustment amplitude, and ω is a frequency parameter related to the number of days in a week. is the initial phase; The scene modes include reading mode, party mode, and sleep mode. Each mode corresponds to a different combination of light brightness and color temperature parameters. The scene comfort evaluation formula is introduced: C scene =α×Lb rightness +β×C color +γ×P uniformity Among them C scene Indicates the scene comfort, L brightness is the light brightness value, α is the brightness comfort weight coefficient, C color is the color temperature value, β is the color temperature comfort weight coefficient, P uniformity It is the lighting uniformity index, with a value range of 0-1, 1 means completely uniform, and γ is the uniformity comfort weight coefficient; The sensor module integrates several sensors to collect environmental information and provide a basis for lighting control, including light intensity sensor, temperature sensor, and human infrared sensor. The sensor module transmits the collected data to the remote control terminal and LED lighting equipment module in real time through the Internet of Things communication module. The LED lighting equipment automatically adjusts the light brightness and color temperature parameters according to these environmental information to achieve intelligent lighting control. When the light intensity sensor detects that the ambient light intensity is high, the brightness of the LED lamp is automatically reduced; when the human infrared sensor detects that someone enters the room, the light is automatically turned on, and the light is automatically turned off after a delay after the person leaves. The delay time can be set within the range of 1-10 minutes; The data management and analysis module is located in the cloud server and is used to store and process the operating data of the LED lighting system, recommend personalized lighting settings for users, predict future lighting needs based on historical data and environmental change trends, adjust lighting strategies in advance, and achieve energy-saving optimization and intelligent management. By analyzing the illumination data of the past week and the user's light on and off time, it predicts the optimal light brightness settings for different time periods of the day, and automatically adjusts the lights before users use them, thereby improving user experience while reducing energy consumption; In intelligent lighting control, the following formula is used to automatically adjust the light brightness according to the light intensity: Where L new is the adjusted light brightness, L current is the current light brightness, S current is the light intensity value detected by the current light sensor, S max is the maximum measurement value of the light sensor, 10000 lux, and k is the adjustment factor. When the ambient light is stronger, S current The larger the L new will be reduced accordingly; When adjusting the color temperature of the light based on the temperature sensor data, the following formula is used: C new =C base +m×(T current -T base ) Among them C new is the adjusted light color temperature value, C base is the initial basic color temperature value, T current is the ambient temperature value detected by the current temperature sensor, T base is the temperature reference value, m is the color temperature adjustment coefficient. When the ambient temperature is higher than the reference temperature, T current -T base >0, the color temperature of the light will decrease accordingly, C new <C base , when the ambient temperature is lower than the reference temperature, the color temperature of the light will increase, C new >C base .

2. The remote control LED lighting system based on the Internet of Things according to claim 1 is characterized in that: The LED lighting equipment module also has fault self-detection and alarm functions. When a lamp fails, including LED chip damage and driving power failure, the microcontroller automatically detects the fault type and location, and sends the fault information to the remote control terminal and data management and analysis module through the Internet of Things communication module. The fault information includes the fault code, fault occurrence time and lamp number. The LED lamp will issue a local alarm by flashing lights or making specific sounds.

3. The remote control LED lighting system based on the Internet of Things according to claim 1 is characterized in that: The IoT communication module supports Mesh networking function. When LED lighting equipment and sensors are distributed in a large area, self-organizing and self-repairing multi-hop communication is realized through the Mesh network. In the Mesh networking mode, the nodes in the network automatically select the optimal transmission path.

4. The remote control LED lighting system based on the Internet of Things according to claim 1 is characterized in that: The remote control terminal module supports voice control function. Users can operate LED lighting equipment through voice commands, including "turn on the lights in the living room", "dim the bedroom lights to 50%", and "switch to reading mode". The voice control function adopts advanced iFlytek voice recognition technology with a recognition accuracy rate of no less than 95%. It can recognize multiple languages ​​and dialects, which is convenient for different users.

5. The remote control LED lighting system based on the Internet of Things according to claim 1 is characterized in that: The data management and analysis module has the ability to connect with other intelligent device systems, including smart home systems and smart building management systems. Through an open API interface, data sharing and interactive control with other systems can be achieved.

6. A method for remotely controlling an LED lighting system based on the Internet of Things using any one of claims 1 to 5, characterized in that: The following steps are involved: S1. System installation and configuration: install the LED lighting equipment at the required location, ensure that the lamps are firmly installed and the electrical connections are correct, install the sensor module so that it can accurately collect environmental information, configure the Internet of Things communication module so that it can establish communication connections with the LED lighting equipment, remote control terminal and cloud server, install the corresponding application on the remote control terminal or open the web control interface, perform user registration and login, and complete the initialization settings of the system; S2. Device grouping and scene mode setting: Through the remote control terminal, LED lighting devices are grouped according to different areas or functions. The lamps in the living room are grouped together, and the lamps in the bedroom are grouped together. Different scene modes are set for each group, including the reading mode, in which the light brightness is set to 500 lux and the color temperature is set to 4000K; the party mode, in which the light brightness is set to 800 lux and the color temperature is set to 2700K. The color is adjusted according to the atmosphere, and users can customize the parameters of the scene mode according to their preferences and actual needs. S3, remote control and real-time monitoring, users can remotely control the switch, dimming and color adjustment functions of LED lighting equipment through smartphone applications, tablet applications or web control interfaces, and view the working status and environmental information of LED lamps in real time. When the lights need to be adjusted, users send control instructions on the remote control terminal, which are transmitted to the IoT communication module through the Internet, and then forwarded to the corresponding LED lighting equipment by the IoT communication module. The microcontroller of the LED lighting equipment receives the instructions and performs the corresponding operations to realize remote control of the lights. The sensor module collects environmental information in real time and uploads the data to the cloud server and remote control terminal; S4, intelligent lighting control, according to the environmental information collected by the sensor module, the LED lighting equipment automatically adjusts intelligently. When the light intensity sensor detects a change in the ambient light intensity, the LED lamp automatically adjusts the brightness. When the human infrared sensor detects that someone enters or leaves the room, the light is automatically turned on and off. The ambient temperature data collected by the temperature sensor can be used to assist in adjusting the light color temperature. When the temperature is high, the light color temperature is appropriately reduced, and when the temperature is low, the light color temperature is increased; S5. Data management and analysis. The data management and analysis module of the cloud server stores and analyzes the system operation data, generates energy consumption reports, and counts the lighting energy consumption in different time periods and different areas. It is displayed to users in the form of charts and analyzes the user's lighting usage habits. According to the user's daily operation mode and environmental change rules, it provides users with personalized lighting suggestions and automatically optimized lighting strategies, including: automatically adjusting the brightness of the living room lights to the brightness that the user is accustomed to between 7pm and 10pm, predicting future lighting needs through analysis of historical data and environmental trends, and adjusting the working status of lighting equipment in advance to achieve energy saving and intelligent management; In energy consumption forecasting, the following time series forecasting formula is used: Where E t+h is the predicted energy consumption value at time t+h, E t is the energy consumption value at the current moment, E t-i is the energy consumption value at the past i moments, p is the number of historical data time points considered, α and β are weighted coefficients of historical energy consumption data, determined according to the importance and timeliness of the data, γ is the influence coefficient of environmental factors on energy consumption, and F t is the comprehensive value of environmental factors at the moment; S6. System maintenance and troubleshooting. Regularly inspect and maintain the LED lighting system, including cleaning of lamps, calibration of sensors, and testing of communication equipment. When the system detects a fault in the LED lighting equipment, it promptly obtains fault information through the remote control terminal and data management and analysis module, and arranges corresponding maintenance personnel to perform repairs based on the type and severity of the fault.

7. The method for remotely controlling an LED lighting system based on the Internet of Things according to claim 6, characterized in that: During the system installation and configuration steps, the LED lighting equipment and sensors are calibrated. The calibration process includes the calibration of the light intensity sensor, the temperature sensor and the human infrared sensor. The light intensity sensor calibration uses a standard light source for comparison and calibration, and the calibration accuracy reaches ±3%. The temperature sensor calibration uses a high-precision thermometer as a reference, and the calibration error does not exceed ±0.3℃. The human infrared sensor calibration is tested and adjusted by simulating human activities.

8. The method for remotely controlling an LED lighting system based on the Internet of Things according to claim 6, characterized in that: In the intelligent lighting control step, an adaptive learning algorithm is used to optimize the intelligent lighting control strategy. The system adjusts the light brightness and color temperature parameters according to the user's actual usage feedback and environmental changes.

9. The method for remotely controlling an LED lighting system based on the Internet of Things according to claim 6, characterized in that: In the data management and analysis step, machine learning algorithms are used to analyze and predict energy consumption data, and regression analysis algorithms are used to establish energy consumption models. Based on historical energy consumption data, environmental factors, and lighting usage characteristics, energy consumption trends in the future are predicted.

10. The method for remotely controlling an LED lighting system based on the Internet of Things according to claim 6, characterized in that: In the system maintenance and troubleshooting steps, an equipment fault knowledge model library is established, and common fault types, fault causes, and solution information are entered into the knowledge base. When a system fault occurs, the fault diagnosis algorithm is compared with the knowledge base to quickly locate the cause of the fault and provide a corresponding solution.

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