Sustainable Development and Computing—An Introduction

Abstract

Computational Sustainability is the computer scientific branch of the interdisciplinary field of sustainability research, an applied science about the research in sustainable solutions and their implementation. This introductory chapter describes the origins and the development of common and current sustainability goals and the development of sustainability science as separate field of research. It points out the relevance of Computer Science in many fields and gives an overview of the state of the art research in Computational Sustainability as well as about the content of this edited volume and about the case studies that are addressed in subsequent chapters.

Tackling Climate Change with Machine Learning

“…9 In (future) low-carbon systems with a high reliance on variable resources, much of this buffer may need to be provided by energy storage technologies such as batteries ( §2.3), pumped hydro, or power-to-gas [28]. 10 However, managing such highly variable systems is complex, and system operators may be unable to transition towards this low-carbon future without improvements in key technologies [31]. ML can both reduce emissions from today's standby generators and enable the transition to carbon-free systems by helping improve necessary technologies (namely forecasting, scheduling, and control) and by helping create advanced electricity markets that accommodate both variable electricity and flexible demand.…”

“…movement (e.g. [8][9][10][11][12]). Faghmous and Kumar presented an overview of climate change problems from the perspective of big data [13], and Kaack recently presented an overview of ML applications to climate mitigation [14].…”

A Qualitative Study on the United States Internet of Energy: A Step Towards Computational Sustainability

“…The Multiple regression analysis, leveraging the weighted least-squares estimation for each of the factor variables based on the statistical relationship between total load and factors' influence, is the most common technique for load forecasting. References [92]- [94] suggested the fundamental model for the multiple regression analysis as shown in (3).…”

“…Computational Sustainability, a massively interdisciplinary field of study, lies in the intersection of the multiple domains, such as applied mathematics, statistics, computer and information science, electrical and electronic engineering, economics, environmental science, operational research, and policymaking [1], [2]. The overarching goal of this field of study is leveraging the knowledge of these multiple domains to meet the essentials and demands of the current generation without compromising the future generation's potentiality to confront their known needs and prosper [3]- [5]. Computational Sustainability joins the movement of sustainable development through developing data-driven and The associate editor coordinating the review of this manuscript and approving it for publication was Muhammad Maaz Rehan .…”

Tackling Climate Change with Machine Learning

“…See the AI for social good movement (e.g.,[71,323]), ML for the developing world[163], the computational sustainability movement (e.g.,[184,296,297,401,471], the American Meteorological Society's Committee on AI Applications to Environmental Science, and the field of Climate Informatics (www.climateinformatics.org. )[548], as well as the relevant survey papers[231,251,403].…”