5G IoT and Edge Computing for Smart Healthcare

Dr. Akash Kumar Bhoi accomplished academic and researcher with over a decade of experience in Computer Science and Engineering, Artificial Intelligence, Machine Learning, Data Science, and Biomedical Computing. Recognized globally for research excellence, ranked in the Top 0.5% of Scholars worldwide (ScholarGPS, 2024 & 2025) and listed among the World’s Top 2% Scientists (Stanford University & Elsevier, 2022, 2023 & 2025). Prolific contributor with 200+ Scopus-indexed publications, multiple edited books with Springer/Elsevier, and an h-index of 39 (Google Scholar). Dr. Bhoi is currently associated with Graphic Era Deemed to be University, Dehradun. More than a decade of academic & research experience in India, Italy, Australia, and South Korea. Expertise spans computational intelligence, data analytics, healthcare informatics, biomedical signal and image processing, cloud/edge computing, and IoT applications.Victor Hugo C. de Albuquerque [M’17, SM’19] is a collaborator Professor and senior researcher at the Graduate Program on Teleinformatics Engineering at the Federal University of Ceará, Brazil, and at the Graduate Program on Telecommunication Engineering, Federal Institute of Education, Science and Technology of Ceará, Fortaleza/CE, Brazil. He has a Ph.D in Mechanical Engineering from the Federal University of Paraíba (UFPB, 2010), an MSc in Teleinformatics Engineering from the Federal University of Ceará (UFC, 2007), and he graduated in Mechatronics Engineering at the Federal Center of Technological Education of Ceará (CEFETCE, 2006). He is a specialist, mainly, in Image Data Science, IoT, Machine/Deep Learning, Pattern Recognition, Robotic. Dr. Samarendra Nath Sur (M’2016). He received B.Sc degree in Physics (Hons.) from the University of Burdwan in 2007. He received M.Sc. degree in Electronics Science from Jadavpur University in 2007 and M.Tech degree in Digital Electronics and Advanced Communication from Sikkim Manipal University in 2012. He received his Ph. D degree from NIT, Durgapur. Since 2008, he has been associated with the Sikkim Manipal Institute of Technology, India, where he is currently an assistant professor in the Department of Electronics & Communication Engineering. His current research interests include Broadband Wireless Communication (MIMO and Spread Spectrum Technology), Advanced Digital Signal Processing, and Remote Sensing. He is a Member of the Institute of Electrical and Electronics Engineers (IEEE), IEEE-IoT, IEEE Signal Processing Society, Institution of Engineers (India) (IEI) and International Association of Engineers (IAENG). He was the recipient of the University Medal & Dr. S.C. Mukherjee Memorial Gold Centered Silver Medal from Jadavpur University in 2007. Paolo Barsocchi is a researcher at the Information Science and Technologies Institute (ISTI) of the National Research Council (CNR) at Pisa, Italy. He received his M.Sc. and Ph.D. degrees in information engineering from the University of Pisa in 2003 and 2007, respectively. Since 2017 he is Head of the Wireless Networks Research Laboratory. He is currently involved in several European projects, national and regional projects. The overall amount of attracted and managed funds both at European and national level is about €3M. He has been nominated as a regional competence reference person for advanced manufacturing solutions in Industry 4.0 in 2017, and as a contact person in the Cluster-PON call in 2017 for the CNR Department DIITET, which ISTI belongs to. His research interests are in the areas of internet of things (IoT), wireless sensor networks, cyberphysical systems, machine learning and data analysis techniques, smart environments, ambient assisted living, activity recognition and indoor localization.

• 1. Fundamentals and architecture of edge computing platform: 5G IoT/IoMT2. Physical layer architecture of 5G enabled IoT/IoMT system3. HetNet/M2M/D2D communication in 5G technologies4. Sensor Networks: Data and Traffic Models in 5G Network5. Convergent Network Architecture of 5G and MEC6. Privacy and Security aspect of MEC enabled 5G- IoT network7. Healthcare data encryption, data processing for the data acquired from smart sensors and smart city healthcare approaches8. Artificial Neural Networks/ Deep Learning approaches for the disease diagnosis and treatment9. Advanced pattern recognition tools/ computer vision algorithm for the disease diagnosis10. Cognitive computing for the data cognition for the information relevant to the user’s disease and resource management11. Computational Intelligence in Human-machine interface (HMI) for telemedicine application12. Case Study: challenges and implications of smart healthcare applications and solutions to address these challenges