Cooperative Location-Sensing for Wireless Networks
PERCOM '04 Proceedings of the Second IEEE International Conference on Pervasive Computing and Communications (PerCom'04)
Ontology Driven Visualisation of Maps with SVG - An Example for Semantic Programming
IV '06 Proceedings of the conference on Information Visualization
CoINS: Context Sensitive Indoor Navigation System
ISM '06 Proceedings of the Eighth IEEE International Symposium on Multimedia
Semantically enriched navigation for indoor environments
International Journal of Web and Grid Services
C-NGINE: A Contextual Navigation Guide for Indoor Environments
AmI '08 Proceedings of the European Conference on Ambient Intelligence
A Semantics-Based User Model for the Support of Personalized, Context-Aware Navigational Services
ONTORACT '08 Proceedings of the 2008 First International Workshop on Ontologies in Interactive Systems
The iNAV indoor navigation system
UCS'07 Proceedings of the 4th international conference on Ubiquitous computing systems
LoCA'05 Proceedings of the First international conference on Location- and Context-Awareness
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Location-based services have evolved significantly during the last few years and are reaching a maturity phase, relying primarily on the experience gained and the utilization of recent technologies, such as ontology-based modeling and rule-based reasoning. Ontologies are used to classify the terms used in a particular application, characterize possible relationships, and define possible constraints on using those relationships. Thus, they provide a suitable means for representing context models. The formal semantics of ontology-based approaches also enable simple reasoning tasks on the context information. Rule-based reasoning techniques are also used in order to offer extensive reasoning capabilities. Taking advantage of these opportunities, this paper presents C-NGINE, a Contextual Navigation Guide for Indoor Environments, strongly connected to the semantics behind user profile. Our approach, which focuses on indoor environments, uses OWL ontologies to capture and formally model profile and context information, and reasons on the ontology data using rules in order to support personalized context-aware navigation services. To test and demonstrate the approach, a prototype has been developed that documents the flexibility of the design.