This special session is organised and supported by the University of Lincoln , United Kingdom.
Session Chair:
Dr. Mohammed Al-khafajiy, University of Lincoln, UK
Session Co-Chairs:
- Dr. Neil Buckley, Liverpool Hope University
Session Committee:
Dr. Kamaran Fathulla, University of Lincoln, UK
Dr. Mubeen Ghafoor, University of Lincoln, UK
Dr. Ghaith Al-Tameemi, University of Northampton, UK
Dr. Murtada Dohan, University of Northampton, UK
Dr. Mohammed Al-Jameel, University of Northampton, UK
Synopsis:
This special track aims to discuss new theoretical and practical advances on the Internet of things technologies with a specific focus on smart things that are powered by Artificial Intelligence and the big data mining at the edge of the network. The IoT generates data in seconds or even milliseconds, imposing the importance of big data mining at the network’s edge. Utilising this data to create AI models hosted at the network’s edge to feature the IoT network with smart/cognitive things nodes. These cognitive abilities will allow networked nodes to reason about their surroundings, learn from the past and adapt to changes. Hence, things/nodes will respond to events and interpret the surrounding activities to invoke new services/processes as required.
Topics:
The track welcomes submissions related to the practical, applied, and theoretical development related to IoT and AI. Authors are solicited to submit significant, original, complete, and unpublished papers covering topics which include, but are not limited to:
- Machine Learning (Deep Learning, Reinforcement Learning, Tiny ML, etc.)
- Cognitive Systems and smart IoT
- Knowledge Representation and Reasoning
- Multi-agent Systems
- Self-* Systems (self-configuring, self-healing, self-optimizing, etc.)
- AI and Cloud Computing
- AI and Edge Computing
- Data Mining/Social Network Analysis and Mining
- AI network applications in security, sustainability, healthcare, smart cities, logistics, and manufacturing.
- Cyber Physical Systems
- Big Data Challenges, Systems, Mining and Management, Tools and Applications.
- TinyML datasets, applications, algorithms, systems, and hardware.
Paper Submission:
| Prospective authors are invited to submit full-length papers (not exceeding 6 pages) conform to the IEEE format . All papers will be handled and processed electronically via the EDAS online submission system. |