株式会社極東書店トップ商品一覧Data-Driven Sustainability: Harnessing Technology for A Greener Future and Environmental Resilience.

商品詳細

Data-Driven Sustainability: Harnessing Technology for A Greener Future and Environmental Resilience.

Data-Driven Sustainability: Harnessing Technology for A Greener Future and Environmental Resilience.

・ISBN 978-3-032-13411-0 hard EUR 159.99

¥42,764.- (税込) (※)価格はご注文時の参考価格となります。
納品価格につきましては書籍の入荷時点で確定となります。
版元の原価改定、外国為替の変動等により異なる場合がございますので、予めご了承下さい。

お気に入り
著者・編者Singh, Rubee / Filho, Walter Leal / Kumar, Vikas (eds.),
シリーズ (World Sustainability Series)
出版社 (Springer Nature Switzerland AG, SZ)
出版年月2026
ページ数456 pp.
言語ENG
ニュース番号<A05-5347>

解説

This book provides a timely and insightful exploration of how emerging digital technologies can be leveraged to achieve sustainability and build environmental resilience in the face of escalating global challenges. It offers readers a practical and theoretical foundation for understanding data-driven sustainability, a concept that refers to the integration of advanced data tools-such as artificial intelligence, big data analytics, Internet of Things (IoT), and blockchain-into environmental planning, policy, and operations. With climate change, biodiversity loss, pollution, and resource scarcity accelerating at an alarming pace, traditional approaches to sustainability are proving inadequate. The need for real-time data, predictive analytics, intelligent automation, and transparent monitoring has never been more urgent. This book addresses that critical need by illustrating how data-centric technologies can help bridge the gap between sustainability ambitions and tangible action. It explores how big data can transform environmental intelligence, enabling governments, businesses, and communities to track environmental performance in real time, anticipate risks, and intervene proactively. Artificial intelligence is examined as a powerful tool for optimizing resource use, modeling climate scenarios, enabling smart agriculture, and enhancing energy efficiency through learning algorithms and pattern recognition.