Semantic Enrichment of Location-Based Services

Location-based services (LBS) are considered the most popular mobile telecommunication services besides the traditional ones, for example, SMS and MMS. They are believed to constitute the killer applications for next generation mobile networks, since they enable adaptive location-driven content provision. Such services can be provided wherever the location of mobile users can be determined. Nowadays, there is a wide range of methods for estimating the location of users in both indoor (i.e., in-building areas) and outdoor environments (Schiller & Voisard, 2004). Outdoor LBS are more developed than their indoor counterparts due to the existence of positioning and topological information systems, GPS (global positioning system) and GIS (geographic information system) respectively. However, almost all known LBS provide their functionality irrespectively of the actual user context, which may consist of user’s location, physical capabilities, and/or cognitive status. Furthermore, most services ignore the semantic information of the spatial elements (e.g., stairs, elevators, and physical obstacles), other than the Euclidean distance. In this article, we describe issues related to the development of intelligent and human-centered LBS for indoor environments. We focus on the navigation service. Navigation is probably the most challenging LBS since it involves relatively complex algorithms and many cognitive processes (e.g., combining known paths for reaching unknown destinations, minimizing path length). With the proposed system, we try to incorporate intelligence to navigation services by enriching them with the semantics of users and navigation spaces. Such semantic information is represented and reasoned using state-of-the-art semantic Web technologies (Berners-Lee, Hendler, & Lassila, 2001). BACKGROUND