EcoScan - Smart Waste Classification using Computer Vision and Deep Learning

Automated classification of solid waste is essential for improving environmental sustainability and reducing health risks associated with manual sorting. This paper presents the design and implementation of a computer vision-based waste classification system leveraging deep learning techniques to accurately categorize various types of waste. The system utilizes Convolutional Neural Networks to extract and analyse image features, enabling efficient multi-class classification across diverse waste categories. Integrated into a user-friendly web application, the solution supports real-time image upload and provides automated predictions with confidence scores. The proposed approach demonstrates significant potential to enhance waste segregation processes by reducing human intervention and improving sorting accuracy. Future work will focus on optimizing model architectures and expanding deployment for practical applications in smart waste management.