Harnessing Robotics for Sustainable Waste Management: Insights from the UK And African Cities
Waste management remains one of the most pressing global challenges, exacerbated by rapid urbanization, population growth, and limited infrastructure, particularly in developing regions such as Africa. This paper explores the role of robotics and artificial intelligence (AI) in advancing sustainable waste management, drawing comparative insights from the United Kingdom (UK) and African cities. It examines how robotics technologies are transforming waste management systems, with a particular focus on waste sorting, collection optimization, and recycling efforts. In the UK, robotics applications have contributed to nuclear waste management and construction and demolition waste sorting, demonstrating the potential of automation in waste reduction. In African cities, emerging trends such as AI-powered mobile apps and smart bins offer scalable solutions tailored to the region’s unique challenges, including rapid urbanization and resource constraints. Through a review of policies, technological innovations, and challenges in both contexts, this paper identifies strategies for integrating robotics into waste management. It underscores the importance of collaboration between governments, technology companies, and communities, and highlights capacity-building initiatives that can help African cities effectively adopt robotic technologies. The study offers recommendations for African cities, advocating for scalable, cost-effective solutions and emphasizing the need for public awareness and local expertise. Ultimately, this paper demonstrates how leveraging robotics can contribute to more sustainable waste management practices, improving environmental health and supporting sustainable urban development across diverse global contexts.
Authors
- Anya Adebayo Anya
Publication Details
- Journal
- Journal of Advanced Research and Multidisciplinary Studies
- Published
- 2025-01-10
- DOI
- https://doi.org/10.52589/jarms-4oe4aqvw
- Citations
- 1
- Primary Topic
- Healthcare and Environmental Waste Management
- Type
- article
- Field-Weighted Citation Impact
- 1.88