AUTOMATED GARBAGE SEPARATION USING AI BASED ROBOTIC ARM

Abstract

This paper aims to present an automated garbage separation system using a deep learning approach and integrating it with a robotic arm. The system is designed to separate different types of garbage, such as plastics, metals, and glass, based on images captured by sensors and analyzed using a deep learning model. The system is then integrated with a robotic arm that picks up and sorts the garbage based on the model's predictions. This system involves data collection, preprocessing, model building, training, testing, and deployment, as well as robotics engineering and sensor technology. The system has potential applications in waste management and recycling, including municipal waste management, recycling facilities, industrial waste management, landfills, and smart cities. It aims to improve the efficiency, accuracy, and safety of waste management systems and promote sustainability.