Priamos: A middleware architecture for realtime semantic annotation of context features

Konstantinou, N; Solidakis, E; Zoi, S; Zafeiropoulos, A; Stathopoulos, P; Mitrou, N

dc.contributor.author	Konstantinou, N	en
dc.contributor.author	Solidakis, E	en
dc.contributor.author	Zoi, S	en
dc.contributor.author	Zafeiropoulos, A	en
dc.contributor.author	Stathopoulos, P	en
dc.contributor.author	Mitrou, N	en
dc.date.accessioned	2014-03-01T02:44:55Z
dc.date.available	2014-03-01T02:44:55Z
dc.date.issued	2007	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32023
dc.subject	annotation	en
dc.subject	automatic	en
dc.subject	context features	en
dc.subject	middleware	en
dc.subject	Real-time	en
dc.subject	rule-based	en
dc.subject	semantics	en
dc.subject.other	annotation	en
dc.subject.other	automatic	en
dc.subject.other	context features	en
dc.subject.other	Real-time	en
dc.subject.other	rule-based	en
dc.subject.other	Middleware	en
dc.subject.other	Ontology	en
dc.subject.other	Semantic Web	en
dc.subject.other	Semantics	en
dc.subject.other	Software prototyping	en
dc.subject.other	Feature extraction	en
dc.title	Priamos: A middleware architecture for realtime semantic annotation of context features	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1049/cp:20070353	en
heal.identifier.secondary	http://dx.doi.org/10.1049/cp:20070353	en
heal.publicationDate	2007	en
heal.abstract	This paper proposes a middleware architecture for the automated, real-time, unsupervised annotation of lowlevel context features and their mapping to high-level semantics. The distinguishing characteristic of this architecture is that both low level components such as sensors, feature extraction algorithms and data sources, and high level components such as application-specific ontologies are pluggable to the middleware architecture thus facilitating application development and system configuration to different real-world scenarios. A prototype implementation based on Semantic Web tools is presented in depth, while the benefits and drawbacks of this approach are underlined. We argue that the use of Semantic Web provides powerful answers to context awareness challenges. Furthermore, it enables the composition of simple rules through human-centric interfaces, which may launch a context-aware system that will annotate content without the need for user technical expertise. A test case of system operation in a laboratory environment is presented. Emphasis is given, along with the theoretical justification, to practical issues that arise in real-world scenarios.	en
heal.journalName	IET Conference Publications	en
dc.identifier.doi	10.1049/cp:20070353	en
dc.identifier.issue	531 CP	en
dc.identifier.spage	96	en
dc.identifier.epage	103	en