Paper
9 April 2024 Smart street lights based on artificial intelligence
Xiaoge Tang, Yang Yu, Ziyan Tang, Tonghui Qu, Yixian Feng, Shi He, Fan Yang, Chang Chen
Author Affiliations +
Abstract
In real life, high-pressure sodium lamps are still the main products of road lighting in China, but LED street lights replace traditional street lights faster and faster. Through experiments, we have designed and developed an energy-saving and environmentally friendly street lamp suitable for haze weather, and its light has high penetration in bad weather environments such as smog[1], which can effectively solve the problems of weak penetration, large system power consumption and backward control mode of existing street lamps in haze weather. The street lamp combines the Internet of Things, artificial intelligence and other technologies to make the urban road lighting project more intelligent, environmentally friendly and energy-saving, and reduces the complexity and engineering cost of the entire lighting project through standardized technical interfaces.New energy smart street lamp can realize refined artificial intelligence light distribution and adjust color temperature according to the flow of people, traffic and weather changes, which controls the LED brightness by applying PWM signals, completes the dimming of the LED without changing the color, and uses PWM switch dimming to adjust the on-time ratio of the cool white LED array and the warm white LED array, and intelligently adjusts the color temperature of the road surface suitable for observing smog weather[2]. Compared with the traditional high-voltage sodium lamp, supercapacitors are used instead of traditional batteries, thereby improving power density, prolonging life, and expanding the operating temperature range, while using DC-DC conversion circuits to realize the maximum power point tracking (MPPT) algorithm, so that the photovoltaic array always outputs the maximum power, charges the supercapacitor, and improves the charging efficiency. At the same time, the street lamp realizes efficient management of street lamps and reduces maintenance costs according to remote fault feedback and other functions.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Xiaoge Tang, Yang Yu, Ziyan Tang, Tonghui Qu, Yixian Feng, Shi He, Fan Yang, and Chang Chen "Smart street lights based on artificial intelligence", Proc. SPIE 12989, Third International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2023), 1298919 (9 April 2024); https://doi.org/10.1117/12.3023876
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KEYWORDS
Lamps

Light emitting diodes

Solar cells

Air contamination

Batteries

Control systems

Fiber optic gyroscopes

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