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Full Description
This comprehensive guide to the emerging areas and synergistic relationships among the domains of 6G, machine learning, and embedded systems offers readers a detailed analysis of their converging paths and contributions to the development of intelligent wireless systems. Readers will gain a solid understanding of the principles and technologies behind 6G, machine learning, and embedded systems. They will learn how these three areas intertwine and why this intersection is pivotal for the next generation of wireless technologies.
The contributors to this volume present a thorough and detailed analysis of this technology, highlighting its promising features, underlying technologies, and potential applications. The book first explores various applications of machine learning algorithms in areas such as network optimization, resource allocation, interference management, and intelligent data processing and analysis. Design considerations and challenges are presented, and case studies of innovative applications, such as smart cities, autonomous vehicles, healthcare, and industrial automation, are examined. The book concludes with a discussion of future trends and opportunities in this rapidly evolving field. Readers will benefit from the theoretical foundations and practical insights presented within and will be prepared to address future challenges and opportunities in these three fields.
This book is a valuable resource for academic researchers and industry professionals working in the fields of wireless communication, machine learning, embedded systems, and artificial intelligence.
Contents
Section I: Synergies of AI/ML, Wireless Communication, IoT, and Embedded Systems. 1. Convergence of 6G, Blockchain, and Intelligent Transportation Systems: Pioneering Next-Generation Traffic Management at Intersections. 2. A Review on Spectrum Standardization for Wireless Networks: Past, Present and Future Advancements. 3. Converging Horizons: Synergies of 6G Wireless Communication, Machine Learning, and Embedded Systems for Intelligent Connectivity. 4. Edge Computing in IoT: Empowering the Internet of Things with Cloud Power for Intelligent Applications. 5. Experiment, Modelling, and Analysis of an RF WPT-Enabled Wireless Sensor Network for Industry 5.0. 6. Empowering Edge-Enabled Resource Efficient Collaborative Deep Learning over B5G/6G Networks. 7. Artificial Intelligence: A Gateway to the Twenty-First Century. Section II: Revolutionizing Connectivity: Smart Transit and Communication Management. 8. FSO and 5G/6G Convergence with Machine Learning: Revolutionized Communication Network. 9. Modernizing Transit: Intelligent Traffic and Transportation Management with Artificial Intelligence in the Era of 5G and 6G. 10. Bridging Domains with Artificial Intelligence and Machine Learning. 11. Artificial Intelligence, IOT, and Machine Learning Technologies Introduction in Various Domains. 12. Intelligent Transportation and Traffic Management. Section III: Application of AI/ML, Wireless, IoT, and Embedded Systems. 13. Ensuring Safety and Security in Control Area Network-Based Automotive Embedded Systems with Advanced Encryption Standard Method Using Cloud Technology. 14. Design of an Efficient High-Trust Model for Improving Network Communication Consistency via Incremental Bioinspired Optimizations: HTMNCB. 15. Data Analytics and Automation for a Broadband Franchise. 16. Unlocking the Power of Machine Learning in Education: A Comprehensive Overview of Opportunities and Challenges. 17. Future-Proofing IoT Security: The Impact of Artificial Intelligence. 18. Data Analysis and Detection of Object Based on Hybrid Whale Optimisation Algorithm with Artificial Neural Network.
