Artificial Intelligence of Things for Wind Energy Systems

Dr. Salah Kamel received his Ph.D. from the University of Jaén, Spain (Main), and Aalborg University, Denmark (Host), in January 2014. He is currently an Associate Professor with the Department of Electrical Engineering, Aswan University, Egypt, where he is also a Leader of the Advanced Power Systems Research Laboratory (APSR Laboratory), Power Systems Research Group. His research areas include power system analysis and optimization, smart grid, and renewable energy systems. Dr. Bhargav Appasani received his Ph.D. from Birla Institute of Technology, Mesra, India. He is currently an Assistant Professor with the School of Electronics Engineering, KIIT University, Bhubaneswar, India. He has published more than 100 articles in international journals and conference proceedings, six book chapters, one authored book, and one edited book. He acts as an academic editor of the Journal of Electrical and Computer Engineering (Hindawi) and Applied Computational Intelligence and Soft Computing (Hindwai), and reviewer for IEEE Transactions on Smart Grid, IEEE Transactions on Antennas and Propagation, and IEEE Access. His research interests are smart grid, cyber-physical systems, 5G, vehicular networks, etc. He is a member of IEEE. Dr. Sunil Kumar Mishra received his PhD in Electrical Engineering from Motilal Nehru National Institute of Technology (MNNIT) Allahabad, India. He is currently Assistant Professor in the School of Electronics Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India. His research areas are ocean wave energy (control perspectives) and nonlinear controller design. He has has published more than 30 research papers in reputed international journals and conferences, and is also a reviewer of the Transactions of Institute of Measurement and Control (TIMC) Journal.

• 1. AIoT for Wind Energy Systems: Technologies, Challenges and Future Directions2. Deep Learning and IoT for Effective Forecasting of Wind3. Novel Control Techniques for Reliable Wind Energy Generation Incorporating AI and IoT4. Energy Management in Wind Farms Using IoT, Big Data and AI5. Big Data, IoT and AI for Anomaly Detection in Wind Turbine Generators6. Digital Twins for Wind Energy Systems Using IoT and AI7. Internet of Drones and Deep Learning for Inspection of Wind Turbine Generators8. AI and IoT based Recommendation Systems for Wind Energy Generation9. Security Concerns in AIoT systems for Wind Energy Farms10. Wind Energy Microgrid Monitoring and Control using AIoT