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This article provides a comprehensive review of existing research on machine learning, deep learning, and IoT-based models for smart e-waste management. The main objectives are to support research, facilitate other researchers in finding relevant studies, and propose future research areas within this domain. Additionally, it offers stakeholders, organizations, and government bodies valuable insights into smart e-waste management based on research-driven knowledge of implementation strategies. The review results indicate that the most frequently studied areas are motives, critical success factors, implementation status, and benefits. Each of these areas would benefit from further exploration.
Oise et al. (Mon,) studied this question.