Green Artificial Intelligence and Industrial Applications (G-AIIA) (eBook, PDF)

Redaktion: Nayak, Sarat Chandra; Favorskaya, Margarita; Cho, Sung-Bae; Dehuri, Satchidananda

• Format: PDF

Produktbeschreibung

This proceeding book explores emerging field of Green AI, which emphasizes innovations to make AI more environmentally sustainable. Green AI seeks to mitigate the environmental impact of AI technologies by streamlining algorithms, enhancing hardware efficiency, and adopting eco-friendly data management practices-all while maintaining the high performance that modern AI systems promise. It addresses the challenges and opportunities associated with reducing AI's energy consumption, lowering carbon emissions, and promoting ethical and responsible AI practices. The book insights into the development of energy-efficient algorithms by design (Green-in-AI) as well as algorithms specifically created to tackle environmental challenges (Green-by-AI). It highlights the potential of Green AI in fostering a more sustainable technological future, which inspires researchers, engineers, and innovators to pursue ideas and solutions that balance technological advancement with environmental stewardship.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 416
• Erscheinungstermin: 1. Oktober 2025
• Englisch
• ISBN-13: 9783031998829
• Artikelnr.: 75561889

Inhaltsangabe

Unveiling the Unexpected Links Between Low-Cost Transactions and Taxi Usage.- A Case Study Predicting the Type of Intrusion Attack Using Deep Learning Algorithms.- A Comparative Study of Temperature Prediction Using Deep Learning Models.- Wind Speed Prediction using Deep Learning.