Ambient intelligence
Coordinator: Prof. Dimitris Plexousakis
Ambient intelligence (AmI) is a multi-disciplinary initiative to enable user-centered intelligent environments. From the technical viewpoint, the main objective of ambient intelligence is to provide the right information to the right users at the right time on the right device in the right way. To achieve this goal, AmI systems have to take the context into account, where context refers to any parameters relevant to the user’s situation and tasks (e.g. location, time, environmental parameters, profile, activity etc). ISL studies the use of semantic techniques for capturing key context parameters, and of reasoning techniques to manipulate such information. Particular activities include: (a) context representation and reasoning; (b) activity recognition; (c) extracting high level context information from low level sensor input; and (d) planning in intelligent environments. These technologies are applied in concrete applications of ambient assisted living, intelligent classroom and intelligent office spaces.
Ph.D. Thesis
- Patkos, Th. (2010). A Formal Theory for Reasoning About Action, Knowledge and Time. September 2010
- Bikakis, A. (2009). Defeasible Contextual Reasoning in Ambient Intelligence. July 2009
M.S. Thesis
- Efthymiou, V. (2012). A real-time semantics-aware activity recognition system. January 2012 (pdf)
- Genitsaridi , E. (2011). An Authorization Language in Ambient Intelligence Environments. July 2011 (pdf)
- Hatzivasilis, G. (2011). Multi-Agent Distributed Epistemic Reasoning in Ambient Intelligence Environments. November 2011 (pdf)
- Filippaki, Ch. (2011). Using Constraint Optimization for Conflict Resolution and Detail Control in Activity Recognition. September 2011 (pdf)
- Papatheodorou, C. (2010). A Distributed Defeasible Reasoning System for Mobile Devices in Ambient Intelligence Environments. December 2010 (pdf)
Videos
