Intelligent Light Emitting Diode Flashing Supplementary Lighting Control Design and Its Big Data Illumination Analysis

Abstract

Considering the inherent advantages of the Light Emitting Diode (LED) in the field of illumination, this work designs an intelligent supplementary lighting system using LED as the light source. Combining microcontroller and electronic circuit theory, the circuit is built with the microcontroller PIC16F873 as the core control chip. The system utilizes an external 220 V AC-20 V DC conversion power supply, hence operating on a 20 V DC power source. The system consists of four hardware parts: the onboard power supply uses TI-produced TPS54331 as the control chip to achieve voltage conversion; the external signals (flashing and burst flashing signals) are isolated from the microcontroller through an optocoupler circuit; the PWM pulses output from the microcontroller’s RC1/CCP2 pins drive the corresponding switching tubes to achieve the flashing function; the flashing synchronization signal is output externally after optocoupler isolation, and its synchronous output with the flashing signal is achieved through an optocoupler after LED conduction; the circuit is established using TI-produced differential bus transceiver SN65LBC184D to convert the external 485 differential signal to the level signal required by the microcontroller. In the experiment, after completing the hardware design, connecting the LED panel, and debugging the test program, it is found that the designed lighting system has a good supplementary lighting effect. According to the PWM output waveform, the flashing effect meets the design expectations. The Hadoop big data computing platform is introduced. Simulation testing reveals that under no backlight conditions, the system achieves an illumination intensity of around 20 klx at a distance of about 10 meters. With backlight conditions, the system maintains an illumination intensity of around 1.5 klx at a distance of about 10 meters. Further calculations are performed to analyze the variation in foot traffic within the test area’s illumination over 24 hours. The total illumination intensity during different time intervals is compiled, confirming that the system can autonomously adjust the illumination intensity of the area based on changes in foot traffic.