Design and Implementation of Edge Computing for Detection on Embedded Electromobility

Abstract

The proposed algorithm architecture of deep learning after darknet dropout are porting on embedded evaluation board with artificial intelligence board of Nvidia Jetson TX2. This article uses the post-training results to implement the actual road testing of edge computing. This design presents accurate identification of vehicles, front signal of traffic light status, road speed limit signs, and vehicle location for safe driving behavior modification system.