Design and Implementation of Garbage Detection and Classification Using YOLOV–5

Abstract

Garbage management has become a global challenge. Talking about India, garbage management has greatly improved over the past few years as a result of various schemes proposed and initiatives undertaken by the government. However, to achieve efficient garbage management, garbage segregation is a crucial step, which is quite poor in India. Every year, we produce approximately 63 million (plus) metric tons of waste, out of which only 30% is properly segregated, and the remaining 70% is dumped in the ground. This paper proposes a design for the automated segregation of garbage and waste by using computer vision and the deep learning algorithm YOLOv5 to efficiently segregate the waste at the source itself.