Real-Time Automated Waste Segregation System Using Machine Learning - AI System

A cutting-edge AI system designed for real-time automated waste segregation using advanced computer vision and deep learning techniques. The system identifies and categorizes six waste types such as Glass, Metal, Paper, Biodegradable, Plastic, and Cardboard with high accuracy, even in challenging environmental conditions. Built using YOLOv8, OpenCV, and PyTorch, the solution integrates a powerful data engine with Firebase to handle analytics, storage, and behavior tracking. This research-based system achieves up to 102 FPS on GPU hardware and establishes new benchmarks in accuracy, speed, and environmental adaptability for industrial waste management applications.