AI and Sustainable Transformations

1. Auflage 2025
ISBN: 978-1-041-07928-6
Verlag: CRC Press

Buch, Englisch, 342 Seiten, Format (B × H): 174 mm x 246 mm

AI and Sustainable Transformations presents cutting-edge research and insights into the role of Artificial Intelligence (AI) and emerging technologies in driving human-centered innovation and sustainable transformation across various industries.

With an emphasis on aligning technological advancements with sustainable practices, this book explores applications of AI in manufacturing, healthcare and the food industry, it delves into critical themes such as Internet of Things-enabled smart manufacturing, blockchain for secure industrial ecosystems, emerging technologies for sustainable futures, intelligent healthcare systems, AI for sustainable and healthcare supply chains, and applications of AI in the food industry. Through in-depth case studies, technical analyses and alternative solutions, readers will gain a broad-based perspective on AI-driven human-centric development.

This is an essential resource for academics, researchers, professionals and policy makers who wish to leverage innovative strategies for a better tomorrow.

Zielgruppe

General, Postgraduate, and Professional Reference

Autoren/Hrsg.

Prakash, Gyan

Kaur, Amandeep

Fachgebiete

• Wirtschaftswissenschaften Volkswirtschaftslehre Internationale Wirtschaft Entwicklungsökonomie & Emerging Markets
• Naturwissenschaften Agrarwissenschaften Agrarwissenschaften Nachhaltige Landwirtschaft
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Gesundheitswirtschaft
• Geowissenschaften Umweltwissenschaften Nachhaltigkeit

Inhaltsverzeichnis

1. AI for sustainable human-centric solutions 2. Insights, ethics and frameworks in responsible AI

Über Autor(innen)

Gyan Prakash is a Professor, Operations and Technology Management; Dean, Planning and Development; and former Head, Department of Management Studies, at the ABV-Indian Institute of Information Technology and Management, Gwalior, India. Prof. Prakash was visiting Associate Professor at the Asian Institute of Technology Bangkok and Visiting Researcher at the Institute for Manufacturing, University of Cambridge. His research interests include the fields of supply chain management, information systems, operations and service management, including public management. He has published his research work in many prestigious journals, such as IEEE Transactions on Engineering Management, Supply Chain Management: An International Journal, Public Management Review, Production Planning and Control, International Journal of Pharmaceutical and Healthcare Marketing, Journal of Health Management, International Journal of Healthcare Management, The TQM Journal, Australian Journal of Maritime & Ocean Affairs, International Journal of Intelligent Enterprise, International Journal of Logistics Systems and Management, International Journal of Healthcare Quality Assurance, Journal of Advances in Management Research, IIMB Management Review, Productivity, Journal of Indian Business Research, IIM Kozhikode Society, and Management Review etc.

Amandeep Kaur, PhD, is an Assistant Professor in the Department of Management Studies at ABV-Indian Institute of Information Technology and Management (ABV-IIITM), Gwalior, India. Prior to joining ABV-IIITM, she served as Assistant Professor at Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, and the National Institute of Technology, Hamirpur. Her research interests lie at the intersection of Artificial Intelligence and Machine Learning in Healthcare, Operations Management, Quality of Service Management, Business Analytics, and Business Intelligence. She has contributed to various high-impact journals, including IEEE Transactions and other SCI-indexed publications, with her work reflecting a blend of technical innovation and practical application. Dr. Kaur continues to engage in interdisciplinary research and collaborative projects that aim to enhance data-driven decision-making across domains.