Research Projects
International Projects
To leverage online learning with immersive communications, this project aims at designing a VR platform that anyone can use to teach, assist, and learn as a member of a class in real-time using the new communications and networking technologies, with interactive content. Situations, like the COVID-19 pandemic, demand embracing innovation in schools and universities, via new ways to teach and support experiential learning in virtual classrooms. This project focuses on the design and the implementation of adaptive end-to-end lifecycle management tools that increases the benefits of intelligent, autonomous orchestration of cloud, edge, and network resources, to enable such emerging applications.
One of the main challenges of Connected Autonomous Vehicles (CAVs) is security that requires the protection of large volumes of sensory data that is processed in real-time. Therefore, new security methods and privacy protection solutions that depend on Deep and Reinforcement learning are required to build secure and robust privacy-preserving personal CAV systems. An increasing trend in integrating AI and deep learning with access control, intrusion detection/prevention, and behavior analysis of personal and ubiquitous systems has been recently observed. Such integration will play a vital role in providing enhanced security for intelligent autonomous systems. Machine learning can be deployed to protect autonomous cars from cyberattacks and malware.
The long-term goals of this project are to devise an Integrated Service Management Framework (ISMF) that integrates a set of AI algorithmic techniques to ultimately secure self-driving vehicles for the betterment of smart city services and applications. To meet these goals, the project investigators believe that the project needs to be investigated from these points:
- Connectivity and Networking: CAVs connectivity and networking with in-vehicle components and the surrounding environment.
- Sensory, Perceiving, and Processing: Understand CAVs capabilities and strengths in order to fit it within the smart city concept as well as make use of the collected data to be used with machine learning.
- Security and Privacy-based AI-Decision Making: Address vehicles safety and security for safer, more secure, and more efficient, and thereby make their widespread deployment practical and commercially viable by developing effective machine learning algorithms such as deep and reinforcement learning.
This could be a full decription about the project