IoT-Based Smart Waste Management Using YOLO Computer Vision for Automatic Waste Segregation

Abstract

Improper waste disposal is a major environmental problem because dry, wet, and metal waste are frequently mixed together. Traditional sensor-based waste segregation systems can work effectively when waste items are placed individually, but their performance can be limited when different types of waste are mixed. This research proposes an IoT-Based Smart Waste Management System using YOLO Computer Vision for automatic waste segregation. A camera is used to capture waste images and the YOLOv8 model is used to identify and classify waste. The proposed system integrates Computer Vision with an IoT-based hardware prototype consisting of Arduino UNO, IR sensor, Raindrop moisture sensor, servo motor, stepper motor, and ESP8266 Wi-Fi module. The detected waste category is used to control the segregation mechanism. The research evaluates the proposed system using Computer Vision and system-level performance metrics. The objective is to improve the accuracy, speed, and automation of waste segregation while reducing dependence on manual sorting.