A Semantic -Enhanced Augmented Reality Tool for OpenStreetMap POI Discovery

Abstract The Augmented Reality (AR) is often said to have the potential for a revolution in the way we discover Points Of Interest (POIs) and experience our cities. Nevertheless, to date the AR promise has only partially become true, because the information content supporting location-based resource discovery is usually shallow. Semantic-based technologies allow expressing rich, accurate and meaningful descriptions of POIs, so helping in improving the quality of discovery. Building upon a general framework for the semantic annotation of nodes in the crowd-sourced OpenStreetMap (OSM) cartography, a novel discovery tool in AR is proposed for mobile devices. Based on the user's personal profile, it shows markers for POIs in the field of sight upon the real-time device camera view. The tool performs automatically a semantic matchmaking between the user profile and the resource descriptions extracted from OSM. Both are expressed according to a common reference ontology. The tool displays the results of matchmaking without user effort, by color-coding the markers. The user can select a marker to see the complete annotated description of the POI as well as matching, missing and conflicting elements with respect to her profile. A fully functional tool prototype was developed for Android mobile devices. Its context-aware user interface makes advanced discovery practical and seamless. A case study was conducted in the city of Trani of the Apulia region in Italy to assess the effectiveness of the proposal.