Assessing the Implementation of Artificial Intelligence-Based Systems for Sustainable Solid Waste Management in Selected Countries in Asia, Europe and North America: A Systematic Review

Vollständiger Abstract

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The efficient management of solid waste remains a persistent challenge worldwide, particularly in developing countries, due to increasing waste generation driven by rapid population growth and urbanisation. Artificial Intelligence (AI) has emerged as a transformative approach to improving solid waste management (SWM) by enhancing waste collection, sorting, recycling, and resource recovery processes. Several countries have integrated AI into their SWM systems; however, the extent of AI-driven automation across the SWM value chain remains insufficiently understood. This study examines the implementation of AI-powered systems across various areas of SWM in ten selected countries to identify progress, benefits, challenges, and opportunities for advancing sustainable SWM practices. A systematic literature review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 268 studies published between 2005 and 2025 were identified and analysed. The findings indicate that the selected countries have made significant progress in adopting AI-powered systems across different areas of the SWM value chain, contributing to improved efficiency, resource recovery, and sustainability. However, challenges related to data availability and quality, privacy, cost, infrastructure, and ethical considerations remain. Addressing these challenges requires collaboration among governments, waste management agencies, technology providers, private companies, and researchers. The study provides best-practice insights and recommendations for leveraging AI to optimise resource efficiency and support improved economic, environmental, and social outcomes in sustainable solid waste management.