Towards Sustainable Waste Management: Exploring Machine Learning and Deep Learning Solutions for Biodegradable and Non-Biodegradable Waste Identification

This study examines 20 research articles focused on AI-based waste management techniques, including machine learning, deep learning, and IoT sensors. Researchers aim to develop sustainable solutions for waste sorting and management. The articles highlight the significant role of deep learning and computer vision in waste classification, with a growing interest in recent years, particularly in 2022. These advanced technologies offer promising avenues for enhancing waste sorting accuracy, reducing manual labor reliance, and promoting recycling efforts. Moreover, the incorporation of IoT sensors plays a vital role in continuously monitoring waste levels and environmental parameters, thereby optimizing the entire waste collection and management workflow. These outcomes underscore the escalating adoption of sophisticated AI methodologies in waste management, suggesting a paradigm shift towards enhanced and environmentally conscious waste management practices. This research provides valuable insights for policymakers, waste management practitioners, and researchers seeking to address the challenges of waste management while promoting environmental sustainability.