Abstract. We implemented the semantic models required to develop an indoor navigation system to assist the movement of users with different physical mobility conditions inside the building of the Faculty of Agricultural Sciences of the National University of Colombia. Everything starts with the recollection of architectural data followed by an analysis and depuration of unnecessary elements (geometrically and semantically) ending with two models: 1) a CityGML model of the interior of the building (LOD4), being the data source for the IndoorGML model and for visualization, 2) an IndoorGML model, provider of the semantic network for the future application of routing algorithms. We present resulting models with the discussion of the challenges and limitations that authors face during this work.

Abstract. Indoor navigation is a complex task for people and especially for visually impaired ones. This research proposes an indoor navigation system oriented to visually impaired users, integrating the OGC IndoorGML and CityGML standards with Bluetooth Low Energy devices (BLE) by using the RSSI signal loss value and the Weighted Path Loss - techniques to calculate the user’s location. This paper describes the design of the system and its implementation as a functional prototype in a mobile web application. Several operational tests were conducted to determine both the accuracy and precision of the user location. The user’s positioning results show a root-mean-squared error (RMSE) of 0.88 m in a scenario with obstacles and no height difference of the BLE devices location, and a RMSE of 1.06 m in a scenario with obstacles and height difference. These results confirm the potential of the implemented prototype to grow into a fully operational system.