Artificial Intelligence-based Renewable Energy Systems: Standards, Communication Systems, and Data Networks provides a comprehensive guide to integrating AI into renewable energy systems, addressing both fundamental principles and practical applications. Sections explore the evolution of AI in energy-efficient systems, advanced applications, architectural frameworks, standards, and distributed renewable energy networks while also delving into data communication systems, including networking protocols, advanced learning techniques, blockchain applications, big data analytics, green communication solutions, cybersecurity, and privacy challenges. Combining theoretical foundations with practical insights, this book offers students, researchers, and engineers a holistic perspective on AI communication and data networks for renewable energy systems.
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Prof. Kashif Naseer Qureshi is an Associate Professor of Cyber Security in the Department of Electronic and Computer Engineering at the University of Limerick, Ireland. He is also actively involved in the Cyber Skills project, a HEA-HCI Pillar 3 initiative Ireland. He received a Ph.D. degree from the University of Technology Malaysia (UTM) and holds two master's degrees in Computer Science and Information Technology from reputable universities. He is the Co-Principal Investigator in Cyber Reconnaissance and Combat project funded by higher education commission. His research interests focus on the security, trust and privacy concerns for Internet of Everything (IoE), Internet of Vehicles (IoV), Electronic Vehicles (EV) charging management planning and recommendation systems, and Internet of Things (IoT) and use cases implementation in wireless and wired networks. He is active member of Lero, the Science Foundation Ireland Research Centre for Software in University of Limerick (UL). His name is included in top 2% Scientist for consecutive 3 years from Stanford university USA. He has published various high-impact factor papers in international journals and conference proceedings and served on several conferences IPCs and journal editorial boards. He has number of book chapters and 5 edited books in Springer, CRC and Elsiver Publishers related to Cybersecurity, Privacy and Trust architectures. He has also part of various research projects related to wireless communication, routing and CyberSecurity domains in the UK, China, Ireland, Malaysia, Canada, Dubai, Vietnam and in Pakistan.
Gwanggil Jeon, PhD, is currently a Full Professor at Incheon National University, Incheon, Korea. He was previously a Visiting Professor at Sichuan University, China, Universitat Pompeu Fabra, Barcelona, Spain, Xinjiang University, China, King Mongkut's Institute of Technology, Ladkrabang, Bangkok, Thailand, and University of Burgundy, Dijon, France. Dr. Jeon is an IEEE Senior Member, an Associate Editor of Sustainable Cities and Society, IEEE Access, Real-Time Image Processing, Journal of System Architecture, and MDPI Remote Sensing. Dr. Jeon was a recipient of the IEEE Chester Sall Award in 2007, the ETRI Journal Paper Award in 2008, and Industry-Academic Merit Award by Ministry of SMEs and Startups of Korea Minister in 2020.
Artificial Intelligence-Based Renewable Energy Systems: Standards, Communication Systems, and Data Networks provides a comprehensive guide to integrating AI into renewable energy systems, addressing both fundamental principles and practical applications. This book is divided into two parts: Part I explores the evolution of AI in energy-efficient systems, advanced applications, architectural frameworks, standards, and distributed renewable energy networks. Part II delves into data communication systems, including networking protocols, advanced learning techniques, blockchain applications, big data analytics, green communication solutions, cybersecurity, and privacy challenges. Combining theoretical foundations with practical insights, Artificial Intelligence-based Renewable Energy Systems: Standards, Communication Systems, and Data Networks offers students, researchers, and engineers a holistic perspective on AI communication and data networks for renewable energy systems.
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