A Framework for Automated Waste Classification System using Machine Learning and Deep Learning Techniques

The expansion of cities, businesses, and other sectors has made garbage management and disposal a top priority for preserving a clean and healthy environment. According to projections, India generates over 36.5 million tons of trash per year. Waste management is a labor-intensive process that must be managed economically as well as using effective procedures and techniques. Conventional waste management systems frequently suffer from ineffective waste classification and processing, which pollutes the environment and consumes resources. Therefore, it is crucial to separate waste and recycle various waste types. Vehicle route plans, communication between entities, waste collection, and local waste segregation are all part of the waste management system. An automated framework for automatic waste segregation and management systems that uses machine learning and deep learning techniques is addressed in the proposed work. The suggested model uses Convolutional Neural networks (CNN) for feature extraction, Region-based CNN( RCNN) for object identification and Random Forest(RF) for final classification.