IEEE Global Communications Conference
4–8 December 2022 // Rio de Janeiro, Brazil // Hybrid: In-Person and Virtual Conference
Accelerating the Digital Transformation through Smart Communications

WS11: 2nd workshop on Edge-AI and IoT for Connected Health (Edge-AI-IoT) - VIRTUAL


*All times are BRT (GMT-3)

SUNDAY, DECEMBER 4 10:00-13:00

Edge-AI and IoT for Connected Health 1

Time: 10:00-13:00 BRT
Recent Advances and Challenges of Edge AI and IoT Assisted Covid-19 Alike Detection Systems
M M Kamruzzaman (Jouf University, Saudi Arabia); Md Altab Hossin (Chengdu University, China); Ibrahim Alrashdi (Jouf University, Saudi Arabia)
An Intelligent Platform for Threat Assessment and Cyber-Attack Mitigation in IoMT Ecosystems
Nicholas Kolokotronis and Maria Dareioti (University of the Peloponnese, Greece); Stavros Shiaeles (University of Portsmouth, United Kingdom (Great Britain)); Emanuele Bellini (University of Campania Luigi Vanvitelli & Khalifa University, Italy)
An energy-efficient and robust transmission scheme for IoT-based physiological activity monitoring
Johannes Dommel (Fraunhofer Heinrich Hertz Institute, Germany); Fatma Hassan (German University in Cairo, Egypt); Zoran Utkovski (Fraunhofer HHI, Germany)
Self-Supervised WiFi-Based Activity Recognition
Mohammud Junaid Bocus, Hok-Shing Lau, Ryan McConville, Robert J Piechocki and Raul Santos-Rodriguez (University of Bristol, United Kingdom (Great Britain))
Non-invasive Blood Glucose Measurement with Mid-infrared Signal by Machine Learning Schemes
Jiang Liu (Waseda University, Japan); Shigeru Shimamoto (Waseda University & Graduate School of Global Information and Telecommunication Studies, Japan); Yang Chen (Waseda University, Japan)

SUNDAY, DECEMBER 4 13:30-15:30

Edge-AI and IoT for Connected Health 2

Time: 13:30-15:30 BRT
Cross dataset non-binary fall detection using a ConvLSTM-attention network
Abbas Shah Syed (University of Louisville, USA); Daniel Sierra-Sosa (Hood College, USA); Anup Kumar and Adel S Elmaghraby (University of Louisville, USA)
Adaptive Fuzzy Neural Network vs. Convolution Neural Network in Classifying COVID-19 from Chest X-ra
Mubarak Alrashoud (King Saud University, Saudi Arabia); Md Abdur Rahman (University of Prince Mugrin, Saudi Arabia)
On Potentials of Few-Shot Learning for AI-Enabled Internet of Medical Things
Dina Aboutahoun, Rami Zewail and Mostafa I. Soliman (Egypt Japan University of Science and Technology, Egypt)
Digital Forensics for Medical Internet of Things
Ayushi Mishra (Indian Institute of Technology, Kanpur, India); Priyanka Bagade (IIT KANPUR, India)

Platinum Patrons

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