Guest Editors
Dr. Faheem Khan, Gachon University, Korea.
Dr. Muhammad Adnan Khan, Riphah International University, Pakistan.
Dr. Muhammad Fayaz, University of Central Asia, Russia.
Dr. Inam Ullah Khan, King’s College London, United Kingdom.
Dr. Israr Ullah, Ulster University, UK.
Summary
Due to the rapid growth in science and technology, many modern and automatic devices are developed to support the healthcare system and education. Modern hospitals and education systems are engaged with a number of challenges to facilitate patients and students. The current progress in the healthcare domain aims to support complete monitoring of the patient during the various stages of the treatment process. Similarly, the Covid-19 changed the shape of the education system for students, faculty and parents.
Currently, the Internet of Things (IoT) is gaining popularity. It has an enormous effect virtually on everything and it remodels the digital world by connecting it all to the internet There are few IoT applications relevant to smart industries, smart cities, healthcare systems, education, etc. The IoT framework is complex and heterogeneous, bringing a range of challenges including decentralization, poor interoperability, privacy, and vulnerability to attack. Because of its many advantages, such as distributed data storage and immutability, blockchain has become the solution for IoT safety. It has the potential to improve the overall safety of the IoT ecosystem.
This special path will offer a forum for researchers and industry to share new research findings on IoT convergence, ranging from overviews, case studies of evidence-of-concept to applications.
Keywords
Blockchain platforms for IoT development
Blockchain implementation in IoT embedded systems
standards and protocols for the Internet of Things
IoT toward COVID-19
trusted IoT ecosystem
Smart home
Big Data for IoT
Network Virtualization Techniques in IoT Systems
Software Defined Networking in IoT Applications
Mobile Health applications in IoT Sytems
Machine learning and artificial intelligence for the Internet of Things
Internet of Things Network Traffic Classification
Intelligent systems for security and privacy in IoT Network
IoT Network Traffic Management Using Machine Learning
Malicious IoT Traffic Identification Using Machine Learning
IoT in education
IoT in the healthcare system
SLR approach
Published Papers
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