Waste Analytics, Carbon Mapping & Predictive Models in Era of Sustainability

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R. Felista Sugirtha Lizy, Ir. Bambang Sugiyono Agus Purwono

2026 World Sustainability Series Vol. Part F1465 Book chapter Cited by 0 SDG 12SDG 17 Quartile

Abstract

The problem of garbage and the carbon effect have been a significant problem in the high urbanization and industrialization world today that needs to be regulated and minimised to promote sustainability and environmental sustainability. The chapter presents an analytical model founded on data that combines waste analytics, carbon mapping, and predictive modeling so as to initiate effective and intelligent environmental management systems. Waste data can be turned into informative data to be used by policymakers and urban planners by using the tools of Artificial Intelligence (AI), Internet of Things (IoT), Geographic Information Systems (GIS), and machine learning. Carbon mapping gives a graphical insight on the hots spot areas of emissions and predictive models project future waste and patterns of carbon, which can be used to act proactively in terms of recovery of resources and reduction of emissions. The chapter also examines the case-based implementation, frameworks of analysis, and policy implications to show how the technologies that utilize data can be used to develop low-carbon, sustainable and resilient communities. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Affiliations

A.P.C. Mahalaxmi College for Women, Tamil Nadu, Thoothukudi, India; Mechanical Engineering Department, State Polytechnic of Malang, Malang, Indonesia

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