Data-Driven Waste Management in Smart Cities
Abstract
Smart cities are grappling with increasing urban waste management challenges in practical applications that can reduce processing, disposal, and environmental impacts. This chapter discusses urban waste management through the lens of a data-driven process that involves predictive analytics, preventive measures, and intelligent processing systems. Technologies include (but are not limited to) Internet of Things, Machine Learning, and Cloud Computing to optimize waste collection, reduce environmental impact, and improve energy efficiency. By utilizing real-time data, cities can act proactively by enhancing stakeholder engagement, optimizing routing for waste collection, delivering services on time, and making better decisions. This chapter also covers case studies, proposes a technological framework for smart waste management practices and systems, and looks at possibilities for future work and how to scale up practical applications, including integration into broader smart city governance.
Fields of Study & Subjects
Municipal Solid Waste Management
Food Waste Reduction and Sustainability
Smart Cities and Technologies
Publication details
- Journal / source
- Empowering Resilient Communities Through Climate Action, Renewable Energy, and Waste Management
- Publisher
- IGI Global Scientific Publishing
- Pages
- 247–274
- Publication date
- 18 February 2026
- Language
- NG
- Document type
- Book chapter