Design and Implementation of an IoT and ML-based Smart Waste Management System

This paper discusses the impact of population growth and increased consumption on waste production, highlighting the challenges of managing waste efficiently. It proposes an IoT-based smart bin system that uses a deep learning model and vision sensors to classify waste into five categories: paper, plastic, metal, cigarettes, and organic waste, achieving 96% accuracy. The system segregates waste into appropriate bins, monitors bin conditions such as toxic gas levels and temperature, and includes fire-extinguishing capabilities. Additionally, a web interface provides real-time data from the sensors, aiming to streamline the recycling process and enhance waste management sustainability.