Vai al contenuto principale della pagina

Integrating Cloud, Fog, and Edge Computing in Healthcare: Federated Learning and Blockchain Approaches : Harnessing Distributed Technologies for Enhanced Healthcare Delivery / / edited by Naween Kumar, Shailendra Pratap Singh, Balamurugan Balusamy, Prithi Samuel, Chander Prabha



(Visualizza in formato marc)    (Visualizza in BIBFRAME)

Autore: Kumar Naween Visualizza persona
Titolo: Integrating Cloud, Fog, and Edge Computing in Healthcare: Federated Learning and Blockchain Approaches : Harnessing Distributed Technologies for Enhanced Healthcare Delivery / / edited by Naween Kumar, Shailendra Pratap Singh, Balamurugan Balusamy, Prithi Samuel, Chander Prabha Visualizza cluster
Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026
Edizione: 1st ed. 2026.
Descrizione fisica: 1 online resource (492 pages)
Disciplina: 004.6782
Soggetto topico: Cloud computing
Medical care
Computer simulation
Cloud Computing
Health Care
Computer Modelling
Altri autori: KumarUthaya  
Nota di contenuto: Chapter 1: Introduction to Cloud, Fog, and Edge Computing in Healthcare -- Chapter 2: Addressing the Challenges in Federating Edge Resources -- Chapter 3: Integrating IoT + Fog + Cloud Infrastructures: System Modelling and Research Challenges -- Chapter 4: Blockchain and Federated Learning for the Management and Orchestration of Network Slices in 5G, Fog, Edge, and Clouds -- Chapter 5: Health Optimization Problems in Fog and Edge Computing with Machine Learning -- Chapter 6: A Lightweight AI-Enabled Container Middleware for Edge Cloud Architectures -- Chapter 7: Health Data Management in Fog Computing using Machine Learning -- Chapter 8: Predictive Analysis in Healthcare to Support Fog Application Deployment -- Chapter 9: Using Machine Learning for Protecting the Security and Privacy of Internet of Medical Things (IoMT) Systems -- Chapter 10: Fog Computing Realization for Healthcare-Based Big Data Analytics with Machine Learning -- Chapter 11: Exploiting Fog Computing and Federated Learning in Health Monitoring -- Chapter 12: Smart Surveillance Video Stream Processing at the Edge for Real-Time Patient Activity Tracking with Machine Learning -- Chapter 13: Fog Computing Model for Evolving Smart Healthcare Applications -- Chapter 14: Testing Perspectives of Fog-Based IoMT Applications with Federated Learning -- Chapter 15: Legal Aspects of Operating IoMT Applications in the Fog Computing.
Sommario/riassunto: This book discusses how Cloud, Fog, and Edge computing, alongside federated learning and blockchain, are revolutionizing healthcare systems by addressing the challenges of data management, privacy, and efficiency. Targeted at healthcare technology researchers, professionals, and advanced students, it explores how these technologies enhance patient care, data security, and organizational effectiveness. The book provides a detailed overview of how Cloud, Fog, and Edge computing work in healthcare, focusing on real-time data processing and secure data sharing. It covers integrating federated learning for privacy-preserving AI models, blockchain for ensuring data integrity, and the technical and regulatory challenges of implementing these systems in healthcare settings. Real-world case studies illustrate successful applications, while practical advice helps navigate common obstacles. A must-read for anyone involved in healthcare delivery, research, or policy, this book offers invaluable insights into the future of healthcare technology. It equips healthcare professionals and technologists with the knowledge to leverage these emerging tools to improve patient outcomes, safeguard electronic health records, and streamline healthcare delivery systems.
Titolo autorizzato: Integrating Cloud, Fog, and Edge Computing in Healthcare: Federated Learning and Blockchain Approaches  Visualizza cluster
ISBN: 3-031-96265-6
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9911049212503321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Serie: Advances in Science, Technology & Innovation, IEREK Interdisciplinary Series for Sustainable Development, . 2522-8722