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.