Advancing Disaster Management Through Federated Learning
A Comprehensive Guide
1st Edition
Published on 28. October 2025
Book
Paperback/Softback
482 pages
978-1-0364-6117-1 (ISBN)
Description
Effective disaster management in an age of more frequent and devastating calamities requires creative solutions. This book explores the revolutionary possibilities of Federated Learning (FL) in crisis management, providing an all-inclusive manual that connects theory with practice. Learn how FL can change the game for disaster response and recovery decision-making, resource allocation, predictive modeling, and information sharing. Readers in the fields of emergency response, governance, research, and technology will find this book's wealth of real-world case studies and examples to be an important resource. It shows how FL improves catastrophe readiness and response by letting strong models be built while data privacy is maintained across decentralized sources. With a comprehensive roadmap that includes enhancing early warning systems, optimizing resource distribution, and integrating cutting-edge technologies like IoT, blockchain, and advanced AI, this book provides a clear explanation of how to use FL to protect communities, infrastructure, and lives during disasters.
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Other editions
Additional editions
C. Kishor Kumar Reddy | Anindya Nag
Advancing Disaster Management Through Federated Learning
A Comprehensive Guide
Book
01/2025
Cambridge Scholars Publishing
€121.80
Shipment within 15-20 days
Persons
Dr C Kishor Kumar Reddy is currently working as an Associate Professor, Dept. of Computer Science and Engineering, Stanley College of Engineering and Technology for Women, Hyderabad, India. He has more than 10 years of research and teaching experience. He has published more than 50 research papers in national and international conferences, book chapters, and journals indexed by Scopus and others. He is an author for 2 textbooks and 7 co-edited books.
Anindya Nag obtained an MSc in Computer Science and Engineering from Khulna University in Khulna, Bangladesh, and a BTech in Computer Science and Engineering from Adamas University in Kolkata, India. He is currently a Lecturer in the Department of Computer Science and Engineering at the Northern University of Business and Technology in Khulna, Bangladesh. His research focuses on health informatics, medical Internet of Things, neuroscience, and machine learning. He serves as a reviewer for numerous prestigious journals and international conferences. He has authored and co-authored about 25 publications, including journal articles, conference papers, book chapters, and has co-edited two books.
Anindya Nag obtained an MSc in Computer Science and Engineering from Khulna University in Khulna, Bangladesh, and a BTech in Computer Science and Engineering from Adamas University in Kolkata, India. He is currently a Lecturer in the Department of Computer Science and Engineering at the Northern University of Business and Technology in Khulna, Bangladesh. His research focuses on health informatics, medical Internet of Things, neuroscience, and machine learning. He serves as a reviewer for numerous prestigious journals and international conferences. He has authored and co-authored about 25 publications, including journal articles, conference papers, book chapters, and has co-edited two books.