Federated Learning Applications in the Industrial Internet of Everything (IoE)
This book presents a comprehensive exploration of federated learning and its transformative potential across industries, focusing on privacy-preserving, decentralized AI solutions. It introduces novel frameworks and applications in healthcare, smart transportation, energy optimization, and Industry...
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| Diğer Yazarlar: | , , , |
| Materyal Türü: | Elektronik Ekitap |
| Dil: | İngilizce |
| Baskı/Yayın Bilgisi: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| Edisyon: | 1st ed. 2025. |
| Seri Bilgileri: | Studies in Systems, Decision and Control,
611 |
| Konular: | |
| Online Erişim: | https://doi.org/10.1007/978-3-031-99270-4 |
| Etiketler: |
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| Özet: | This book presents a comprehensive exploration of federated learning and its transformative potential across industries, focusing on privacy-preserving, decentralized AI solutions. It introduces novel frameworks and applications in healthcare, smart transportation, energy optimization, and Industry 4.0, emphasizing real-world use cases and addressing key challenges in privacy, scalability, and collaboration. By bridging theory and practice, the book provides actionable insights into implementing federated learning for dynamic, interconnected ecosystems like the Industrial Internet of Everything (IoE). Aimed at researchers, practitioners, and policymakers, it offers cutting-edge strategies to enhance efficiency, security, and innovation in diverse industrial domains. |
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| Fiziksel Özellikler: | 1 online resource (XII, 287 p. 50 illus.). 43 illus. in color. |
| ISBN: | 9783031992704 |
| ISSN: | 2198-4190 ; |
| DOI: | 10.1007/978-3-031-99270-4 |