Edge Camera based Dynamic Lighting Control System for Smart Streetlights

Abstract

In this paper, we propose a novel dynamic lighting control system for smart streetlights using an edge camera which detects objects for itself using a light weight deep neural network at local. The proposed system consists of an edge camera, a light control unit, and a control server. The proposed system dynamically adjusts the brightness of a dimming module based on event messages from the edge camera. The proposed system maintains low brightness when there are no pedestrians and switches to high brightness when pedestrians appear. And when a pedestrian leaves the service radius, it returns to low brightness. We designed the protocol between the edge camera and the light control unit, and developed the pedestrian detector using a lightweight deep neural network, which provides real-time processing and the high detection accuracy.