Using Open Street Maps data and tools for indoor mapping in a Smart City scenario

This paper explains the experience of implementing a Smart City scenario using Open Street Maps tools and data. An indoor mapping system including not only a localization and navigation solution, but also a natural speaking environment as a human to machine interface is proposed. The solution is based on a NoSQL database for storing GIS data, a public web service layer used to obtain information, user’s current position, navigation routes and human language interaction. An Android mobile client application is used for providing the proper access to all these services. As a case study, the system was successfully implemented in the U-TAD University. The results shown in this paper can be considered as a demonstration of the previous work related to indoor data representation (IndoorOSM draft) and the navigation solution designed at the Universidade do Minho based on Open Trip Planner. In addition, FHC25 includes a tagging proposal for human language recognition systems.