Название: Federated Learning Based Intelligent Systems to Handle Issues and Challenges in IoVs (Part 2)
Автор: Shelly Gupta, Puneet Garg, Jyoti Agarwal, Hardeo Kumar Thakur, Satya Prakash Yadav
Издательство: Bentham Books
Год: 2025
Страниц: 373
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

Federated Learning for Internet of Vehicles: IoV Image Processing, Vision, and Intelligent Systems (Volume 3) Federated Learning Based Intelligent Systems to Handle Issues and Challenges in IoVs (Part 2) explores how Federated Learning (FL) is revolutionizing the Internet of Vehicles (IoV) by enabling secure, decentralized, and scalable solutions. Combining theoretical insights with practical applications, this book addresses key challenges such as data privacy, heterogeneous information, and network latency in IoV systems.

This volume offers cutting-edge strategies to build intelligent, resilient vehicular systems, from privacy-enhanced data collection to blockchain-based payments, smart transportation systems, and vehicle number plate recognition. It highlights how Federated Learning drives advancements in secure data sharing, identity-based authentication, and real-time road safety improvements.

By examining the cutting-edge Federated Learning paradigm, this book, Federated Learning Based Intelligent Systems to Handle Issues and Challenges in IoVs, aims to answer these urgent problems. Federated learning, in contrast to conventional centralized methods, permits decentralized data processing, allowing cars to jointly learn from local data while maintaining privacy. This approach not only reduces the hazards connected with data exchange, but also improves the adaptability of intelligent systems under a variety of driving situations.

We explore the major issues that IoVs are now confronting throughout this work, such as data heterogeneity, network latency, and the requirement for strong security measures. Each chapter mixes theoretical ideas with practical examples, showing how federated learning can be used to develop resilient, intelligent systems that can thrive in the dynamic environment of connected automobiles.

Key Features:
- In-depth exploration of federated learning applications in IoV.
- Solutions for privacy, security, and scalability challenges.
- Practical examples of blockchain integration and smart systems.
- Insights into future research directions for IoV.






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