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.
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.
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.
Shruti Sharma is a Research Scientist at Ajou University, working on AI/machine learning and 5G/6G wireless communication systems. She earned a PhD in Electrical and Computer Engineering at Ajou University, Korea. She holds a masters degree in Electronics from Pt. Ravishankar Shukla University, India, and a Postgraduate Diploma in Computer Applications from Guru Ghasidas Vishwavidyalaya, India, along with a Diploma in Embedded Systems and Design from CDAC, Kolkata, India. Additionally, she has taught undergraduate and postgraduate science students for a couple of years at CMD P.G. Science College, Bilaspur, Chhattisgarh, India.
Ashutosh Sharma is an Associate Professor at the Department of Physics, Amity Institute of Applied Sciences in Amity University Jharkhand, Ranchi, India. Previously, he served as an Assistant Professor at Ajou University, South Korea. He has more than 11 years of research and teaching experience. He earned a PhD degree at IIT Kharagpur, India. His research focuses on electrochemical deposition, leadfree soldering, AI in microelectronic packaging, additive manufacturing, highentropy alloys, and biomaterials. He has been recognized by the TMS Society, USA and has been ranked in the top 2% of scientists globally by Stanford University for the past three consecutive years.
Trinh Van Chien earned a BS in Electronics and Telecommunications in 2012 at the Hanoi University of Science and Technology (HUST), Vietnam. In 2014, he earned an MS in Electrical and Computer Engineering at Sungkyunkwan University, Korea, and in 2020, he earned a PhD in Communication Systems at Linkoping University, Sweden. He is with the School of Information and Communication Technology at the Hanoi University of Science and Technology, Vietnam.
