Publication Date

1-1-2022

Document Type

Contribution to a Book

Publication Title

Machine Learning for Societal Improvement, Modernization, and Progress

Editor

Vishnu Pendyala

DOI

10.4018/978-1-6684-4045-2.ch001

First Page

1

Last Page

26

Abstract

Among the most pressing issues in the world today is the impact of globalization and energy consumption on the environment. Despite the growing regulatory framework to prevent ecological degradation, sustainability continues to be a problem. Machine learning can help with the transition toward a net-zero carbon society. Substantial work has been done in this direction. Changing electrical systems, transportation, buildings, industry, and land use are all necessary to reduce greenhouse gas emissions. Considering the carbon footprint aspect of sustainability, this chapter provides a detailed overview of how machine learning can be applied to forge a path to ecological sustainability in each of these areas. The chapter highlights how various machine learning algorithms are used to increase the use of renewable energy, efficient transportation, and waste management systems to reduce the carbon footprint. The authors summarize the findings from the current research literature and conclude by providing a few future directions.

Comments

This is the Version of Record, and has been used with the permission of IGI Global, under their Fair Use Policy.

Department

Applied Data Science

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