The AmIART represents an ambient pervasive laboratory that uses Ambient Intelligence (AmI) concepts to actively engage users in learning about fine arts (painting techniques, technology, and materials), learning through experimenting and analyzing art and crafts, as well as detecting fine art fraud. Such environment brings together various sensors connected to provide context-aware pervasive computing with self-adaptive and self-organizing services, which are able to dynamically change and (re)organize environment.
Pervasive environments are characterized by openness, decentralized process control, dynamic behaviour and asynchronous manifestation of processes that occur randomly and which may easily introduce ill-defined knowledge and inconsistencies. Hence, we propose an approach to achieve (re)engineering of the probabilistic knowledge into ontological resources.
The main research hypothesis:
- AmIART "technology lotus" consists of (a) AmI, (b) Adaptation (personalization and contextualization), (c) Online experiments
- Integration of the probabilistic models on process performance and execution into the ontological models
- Probabilistic models simulate process execution in the ambient environment for online experimenting that goes asynchronous
- Using Probabilistic Asynchronous Process Algebra to explain communication between various sensor systems
