The 2019–2020 coronavirus pandemic had far-reaching consequences beyond the spread of the disease and efforts to cure it. Today, it is obvious that the pandemic devastated key sectors ranging from health to economy, culture, and education. As far as education is concerned, one direct result of the spread of the pandemic was the resort to suspending traditional in-person classroom courses and relying on remote learning and homeschooling instead, by exploiting e-learning technologies, but many challenges are faced by these technologies. Most of these challenges are centered around the efficiency of these delivery methods, interactivity, and knowledge testing. These issues raise the need to develop an advanced smart educational system that assists home-schooled students, provides teachers with a range of smart new tools, and enable a dynamic and interactive e-learning experience. Technologies like the Internet of things (IoT) and artificial intelligence (AI), including cognitive models and context-awareness, can be a driving force in the future of e-learning, opening many opportunities to overcome the limitation of the existing remote learning systems and provide an efficient reliable augmented learning experience. Furthermore, virtual reality (VR) and augmented reality (AR), introduced in education as a way for asynchronous learning, can be a second driving force of future synchronous learning. The teacher and students can see each other in a virtual class even if they are geographically spread in a city, a country, or the globe. The main goal of this work is to design and provide a model supporting intelligent teaching assisting and engaging e-learning activity. This paper presents a new model, ViRICTA, an intelligent system, proposing an end-to-end solution with a stack technology integrating the Internet of things and artificial intelligence. The designed system aims to enable a valuable learning experience, providing an efficient, interactive, and proactive context-aware learning smart services.
Adaptive and Context-Aware Service Discovery for the Internet of Things
