Special Session on Complementary Aspects of Artificial Intelligence, Unmanned Aerial Vehicles, and Future Wireless Networks

#FWNs #AI #ML #DL #UAVs #antennas #propagation #SmartCities
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Special session organizer: Dr. Zaharias Zaharis, Chair of Electron Devices / Microwave Theory and Techniques / Antennas and Propagation Joint Chapter, IEEE Greece Section


Artificial intelligence (AI) has the potential to revolutionize many fields, including the operation and management of unmanned aerial vehicles (UAVs). With AI, UAVs can be equipped with intelligent decision-making capabilities, allowing them to adapt to changing environments and make autonomous decisions. This can improve their efficiency and reliability, as well as reduce the workload on human operators. In addition, the use of AI in UAVs can facilitate the development of new applications, such as autonomous search and rescue missions or precision agriculture. In the future, the integration of AI with next-generation wireless networks, such as 5G and beyond, could further enhance the capabilities of UAVs. These networks will provide higher data rates, lower latencies, and greater reliability, enabling UAVs to process and transmit large amounts of data in real-time, enabling new levels of autonomy and intelligence. Overall, the complementary aspects of AI, UAVs, and future wireless networks (FWNs) hold great promise for a wide range of applications and industries.



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  • Date: 28 Jun 2023
  • Time: 04:30 PM to 06:30 PM
  • All times are (UTC+02:00) Athens
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  • L. Alexandras 196
  • Athens, Attiki
  • Greece
  • Building: Conference Center of University of West Attica
  • Room Number: B2

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  • Co-sponsored by IEEE Greece Section






Agenda

16:30 - 16:50 --- Service recommendation for a group of users on the internet of things using the most popular service

16:50 - 17:10 --- The human blockage impact on ARIS assisted D2D communication systems

17:10 - 17:30 --- DOA estimation for 6G communication systems

17:30 - 17:50 --- 3D adaptive beamforming approach with a fine-tuned deep neural network

17:50 - 18:10 --- A review of deep learning solutions in 360° video streaming

18:10 - 18:30 --- FDTD modeling of graphene-based materials and its application in sensing devices