| dc.description.abstract | The research work focuses on Situation Awareness and Context Awareness topics.
Specifically, Situation Awareness involves being aware of what is happening in the vicinity
to understand how information, events, and one’s own actions will impact goals and objectives,
both immediately and in the near future. Thus, Situation Awareness is especially
important in application domains where the information flow can be quite high and poor
decisions making may lead to serious consequences.
On the other hand Context Awareness is considered a process to support user applications
to adapt interfaces, tailor the set of application-relevant data, increase the precision of
information retrieval, discover services, make the user interaction implicit, or build smart
environments.
Despite being slightly different, Situation and Context Awareness involve common
problems such as: the lack of a support for the acquisition and aggregation of dynamic environmental
information from the field (i.e. sensors, cameras, etc.); the lack of formal approaches
to knowledge representation (i.e. contexts, concepts, relations, situations, etc.)
and processing (reasoning, classification, retrieval, discovery, etc.); the lack of automated
and distributed systems, with considerable computing power, to support the reasoning on a
huge quantity of knowledge, extracted by sensor data.
So, the thesis researches new approaches for distributed Context and Situation Awareness
and proposes to apply them in order to achieve some related research objectives such
as knowledge representation, semantic reasoning, pattern recognition and information retrieval.
The research work starts from the study and analysis of state of art in terms of
techniques, technologies, tools and systems to support Context/Situation Awareness. The
main aim is to develop a new contribution in this field by integrating techniques deriving
from the fields of Semantic Web, Soft Computing and Computational Intelligence. From
an architectural point of view, several frameworks are going to be defined according to the
multi-agent paradigm.
Furthermore, some preliminary experimental results have been obtained in some application
domains such as Airport Security, Traffic Management, Smart Grids and
Healthcare.
Finally, future challenges is going to the following directions: Semantic Modeling of
Fuzzy Control, Temporal Issues, Automatically Ontology Elicitation, Extension to other
Application Domains and More Experiments. [edited by author] | en_US |
