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BEGIN:VEVENT
DTSTAMP:20230701T133930Z
UID:AE46695C-B92D-42CE-823B-5C5DE581D58B
DTSTART;TZID=Europe/Athens:20230628T163000
DTEND;TZID=Europe/Athens:20230628T183000
DESCRIPTION:Artificial intelligence (AI) has the potential to revolutionize
  many fields\, including the operation and management of unmanned aerial v
 ehicles (UAVs). With AI\, UAVs can be equipped with intelligent decision-m
 aking capabilities\, allowing them to adapt to changing environments and m
 ake autonomous decisions. This can improve their efficiency and reliabilit
 y\, as well as reduce the workload on human operators. In addition\, the u
 se 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\, s
 uch as 5G and beyond\, could further enhance the capabilities of UAVs. The
 se 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 (F
 WNs) hold great promise for a wide range of applications and industries.\n
 \nCo-sponsored by: IEEE Greece Section\n\nAgenda: \n16:30 - 16:50 --- Serv
 ice recommendation for a group of users on the internet of things using th
 e most popular service\n\n16:50 - 17:10 --- The human blockage impact on A
 RIS assisted D2D communication systems\n\n17:10 - 17:30 --- DOA estimation
  for 6G communication systems\n\n17:30 - 17:50 --- 3D adaptive beamforming
  approach with a fine-tuned deep neural network\n\n17:50 - 18:10 --- A rev
 iew of deep learning solutions in 360° video streaming\n\n18:10 - 18:30 -
 -- FDTD modeling of graphene-based materials and its application in sensin
 g devices\n\nRoom: B2\, Bldg: Conference Center of University of West Atti
 ca\, L. Alexandras 196\, Athens\, Attiki\, Greece
LOCATION:Room: B2\, Bldg: Conference Center of University of West Attica\, 
 L. Alexandras 196\, Athens\, Attiki\, Greece
ORGANIZER:zaharis@auth.gr
SEQUENCE:20
SUMMARY:Special Session on Complementary Aspects of Artificial Intelligence
 \, Unmanned Aerial Vehicles\, and Future Wireless Networks
URL;VALUE=URI:https://events.vtools.ieee.org/m/363183
X-ALT-DESC:Description: <br /><p>Artificial intelligence (AI) has the poten
 tial to revolutionize many fields\, including the operation and management
  of unmanned aerial vehicles (UAVs). With AI\, UAVs can be equipped with i
 ntelligent decision-making capabilities\, allowing them to adapt to changi
 ng environments and make autonomous decisions. This can improve their effi
 ciency and reliability\, as well as reduce the workload on human operators
 . In addition\, the use of AI in UAVs can facilitate the development of ne
 w applications\, such as autonomous search and rescue missions or precisio
 n agriculture. In the future\, the integration of AI with next-generation 
 wireless networks\, such as 5G and beyond\, could further enhance the capa
 bilities of UAVs. These networks will provide higher data rates\, lower la
 tencies\, and greater reliability\, enabling UAVs to process and transmit 
 large amounts of data in real-time\, enabling new levels of autonomy and i
 ntelligence. Overall\, the complementary aspects of AI\, UAVs\, and future
  wireless networks (FWNs) hold great promise for a wide range of applicati
 ons and industries.</p><br /><br />Agenda: <br /><p>16:30 - 16:50 --- Serv
 ice recommendation for a group of users on the internet of things using th
 e most popular service</p>\n<p>16:50 - 17:10 --- The human blockage impact
  on ARIS assisted D2D communication systems</p>\n<p>17:10 - 17:30 --- DOA 
 estimation for 6G communication systems</p>\n<p>17:30 - 17:50 --- 3D adapt
 ive beamforming approach with a fine-tuned deep neural network</p>\n<p>17:
 50 - 18:10 --- A review of deep learning solutions in 360&deg\; video stre
 aming</p>\n<p>18:10 - 18:30 --- FDTD modeling of graphene-based materials 
 and its application in sensing devices</p>
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