Artificial Intelligence in E-Waste Management: Enhancing Efficiency, Safety and Sustainability

The rapid growth of electronic waste (e-waste) presents pressing environmental and health challenges due to its toxic components and the difficulties in sorting and recycling its materials. Traditional methods for e-waste management are often labor-intensive, slow, and unable to cope with the increasing volume of waste. Artificial Intelligence (AI) offers a promising solution to these issues, enabling automation, efficiency, and enhanced precision in ewaste recycling processes. This paper explores the applications of AI, specifically machine learning, deep learning, and computer vision, in e-waste management. We review current developments, analyze case studies, and assess the role of AI in addressing e-waste challenges, improving resource recovery, and reducing ecological impact. Future directions and potential improvements for AI-driven e-waste management are also discussed. The matter presented in this article is the review of group of papers and is the summary of those papers which was submitted in the form of an assignment.