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Data-Driven Waste Management in Smart Cities: Predicting, Preventing, and Processing
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Author(s): Sudipta Dhar (Brainware University, India), Shivangi Kashyap (Brainware University, India)and Pravin Kumar (Brainware University, India)
Copyright: 2026
Pages: 28
Source title:
Empowering Resilient Communities Through Climate Action, Renewable Energy, and Waste Management
Source Author(s)/Editor(s): Seda H. Bostancı (Tekirdağ Namık Kemal University, Turkey), Seda Yıldırım (Tekirdağ Namık Kemal University, Turkey)and Valentin Vasilev (Higher School of Security an Economics, Bulgaria)
DOI: 10.4018/979-8-3373-0862-3.ch011
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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.
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