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The increasing waste volumes in African cities highlight the urgent need for innovative and sustainable waste management solutions to mitigate climate change, reduce health risks, and support urban development. Rapid urbanization has exacerbated these challenges, as existing waste management systems often suffer from inefficiencies, inadequate coverage, and environmental impacts such as pollution of aquatic ecosystems. This study systematically evaluates the challenges and opportunities of integrating smart waste management technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), and blockchain into waste collection and processing in African cities. Specifically, the research aims to assess the efficiency of smart waste management solutions in urban settings, identify barriers to implementing Centralized Smart Waste Management (CSWM) in African contexts, and propose a scalable framework tailored to the region's socio-economic and infrastructural conditions. Through a comprehensive review of contemporary waste management practices and global technological advancements, including case studies from South Korea and India, this study introduces a hypothetical CSWM framework. The proposed model integrates predictive waste volume sensing, real-time monitoring, and automated sorting and disposal systems to enhance operational efficiency, optimize resource utilization, and minimize environmental harm. While the CSWM framework offers economic, environmental, and social benefits, including enhanced resource recovery, job creation, and long-term cost savings, its implementation faces challenges such as infrastructure limitations, high costs, and the need for stakeholder engagement. Addressing these barriers requires collaborative efforts among governments, the private sector, and community organizations, alongside policy innovations such as tax incentives, regulatory reforms, and public-private partnerships. This study provides a structured roadmap for transitioning African cities toward efficient, resilient, and environmentally sustainable waste management systems by aligning technological advancements with sustainable policies and active stakeholder participation. • Proposes a centralized system integrating AI, IoT, and automation for efficient waste processing and resource recovery. • Promote recycling, reuse, and waste-to-energy solutions through supportive policies and incentives. • Promotes adaptable tech and community action for diverse urban and regional waste management challenges. • Offers actionable strategies to create cleaner, smarter, and more sustainable urban environments.
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Emmanuel O. Atofarati
University of South Africa
Victor O. Adogbeji
Babcock University
Christopher C. Enweremadu
University of South Africa
Utilities Policy
University of Johannesburg
Delta State Polytechnic Ogwashi-Uku
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Atofarati et al. (Thu,) studied this question.
synapsesocial.com/papers/6a006c8d2ff633f36577ef7f — DOI: https://doi.org/10.1016/j.jup.2025.101961
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