Title: Industrial Internet of Things and Digital Health Ecosystem: A Finnish Perspective
Presenter: Rajeev Kanth, Savonia University of Applied Sciences, Kuopio Finland
The importance of the Industrial IoT and digital health ecosystem and value proposition will be discussed in this keynote talk. In the beginning, the IoT education at Savonia University of Applied Sciences, along with the CDIO and OIS method, will be addressed. I will be focusing a couple of slides on attitude, creativity, inventiveness, innovation, and profound innovation for engineering education. The application areas in Healthcare, Industrial perspectives of the Internet of Things, and the concept of smart city are rapidly growing across the globe. I will be highlighting the manufacturing revolution from Industry 1.0 to Industry 4.0, the digital twin, and the recent sensors technologies vision. We will also be looking at the future trends and pervasive nature of IoT, including edge computing, 5G, and Artificial Intelligence solution for upcoming IoT applications. Finally, the Savonia healthcare IoT project, UCN drone project, 5G-6G flagship project (forthcoming), and our recent applied research publications (snow depth measurement, solar cell optimization, Image, and video analytics) will be addressed during the keynote talk.
Modeling Epidemic dynamics thru contact networks
Dr. Sharanjit Kaur, Acharya Narendra Dev College, University of Delhi, Delhi, India; Email: email@example.com
Ms Kirti Jain, Department of Computer Science, University of Delhi, India; Email: firstname.lastname@example.org
Dr. Vasudha Bhatnagar, Department of Computer Science, University of Delhi, India; Email: email@example.com
Special Session on
Remote Patient Monitoring using IoT and Sensors (RPMIS 2022)
Dr. Sushree Bibhuprada B.Priyadarshini, Asst. Professor, Siksha O’ Anusandhan University, Bhubaneswar, Khurdha, Odisha, Member IEEE; Email: firstname.lastname@example.org
Ms Sucheta Panda, Ph.D scholar, Siksha O’ Anusandhan University, Bhubaneswar, Khurdha, Odisha; Email: email@example.com
The Jury Member and the Session chairs of the conference have decided to choose the best paper for the conference. The details for the best paper is as follows:
Paper ID : 89
Paper Name : Evaluation of Spatiotemporal Fetal Cardiac Imaging Using Deep Learning Techniques.
Paper Author Name : Dipak Kumar Nidhi, Khushboo Srivastav, Jukka Heikkonen and Rajeev Kanth.