Applications of Federated Learning in Technological Advancements

This book explores the applications and advancements of Federated Learning across diverse sectors, focusing on its integration with cutting-edge technologies like IoT, AI, Blockchain, and Digital Twins.

1. Journey Towards Federated Learning: Fundamentals, Tools Paradigms, Opportunities and Challenges 2. Federated Learning-based algorithms for deployment and model optimization 3. Automation of AI and IoT-based Data-driven Decision-Making Approaches using Federated Learning Systems 4. Federated Learning for sustainable development using IoT/Edge Computing Systems 5. Advances in 5G/6G enabled federated reinforcement learning in IoT 6. Blockchain Integrated Federated Learning for IoT-based Smart Applications 7. Federated Learning in Heterogeneous Unmanned Aerial Vehicle 8. Advanced Technologies for Federated learning in Smart Cities and its use cases 9. Federated Deep Learning for Cyber-Physical Systems in Real-World Scenarios 10. Use-Cases and Scenarios for Federated Learning Adoption in IoT.