ABSTRACT
In order to maximize waste segregation and recycling procedures, creative solutions are required for waste management and environmental sustainability, which are two urgent global issues. The design and deployment of an AI-powered automated robot that cleans the environment and separates waste using wireless sensor networks (WSNs) is presented in this paper. To enable effective waste material detection, collection, and sorting, the suggested system combines cutting-edge AI algorithms, robotic mechanisms, and sensor networks. The robot accurately classifies waste by separating recyclable elements including plastics, metals, and organic waste using machine vision and near-infrared (NIR)/visible (VIS) optical sensor technology. The technology maximizes operational efficiency and adjusts to changing environmental circumstances by utilizing real-time wireless communication. To compare the system's performance with conventional manual sorting techniques, key performance metrics such as sorting accuracy, processing speed, and energy usage were assessed. The findings of the research show that sorting accuracy and operational cost-effectiveness have significantly improved, underscoring the potential of automated waste management systems to help create a more sustainable and cleaner environment. The benefits of combining AI with robotics and WSNs in trash management are highlighted in this paper, offering a scalable and financially feasible solution for businesses and governments looking to improve environmental sustainability while cutting down on operational inefficiencies and human labour.
