Water Trash Detection System: An Innovative Approach to Monitoring Aquatic Pollution

Abstract

Abstract: Water pollution, particularly from non-biodegradable waste such as plastics, is one of the most pressing environmental issues facing aquatic ecosystems today. This paper presents an innovative solution for detecting and classifying waste in water bodies using machine learning techniques, specifically You Only Look Once (YOLO) and Convolutional Neural Networks (CNNs). The Water Trash Detection System (WTDS) can process both static images and real-time video streams to efficiently detect various types of aquatic trash, including plastic bottles, bags, and fishing debris. The system generates detailed reports on detected waste, providing environmental organizations and researchers with actionable data for monitoring and cleaning polluted water bodies. The combination of YOLO for real-time object detection and CNNs for waste classification allows the WTDS to deliver high accuracy and real-time processing, which is essential for effective environmental management.