Huerta, Schade, Granell (Eds): Connecting a Digital Europe through Location and Place. Proceedings of the AGILE'2014 International Conference on Geographic Information Science, Castellón, June, 3-6, 2014. ISBN: 978-90-816960-4-3 1 Introduction Cities are becoming more intelligent over the time, producing huge amount of data. Citizens living in Smart Cities must have applications that allow access to their services and data. Having them handy, maybe on our smartphones and in the near future accessible in our own wearable technology, is also a challenge. FHC25 is leading a Smart City Project called Perception 1 . This research project studies different fields related to Smart Cities, such as indoor location, speech recognition and augmented reality. As a testing prototype of the project, an application called Smart U-TAD was implemented at Las Rozas, Madrid. It was conceived as a Smart City prototype bounded to a smaller space: a university building. The idea was to offer information services adapted to new technologies and mobile devices. In the last few years, several solutions related with these technologies have appeared. Google, probably the most important worldwide map provider, presented his Google Indoor Maps [1], oriented to indoor mapping and localization. It is composed of an online indoor map uploading service, indoor visualization technology and a training mobile application for fine localization. However, their usage is restricted to public buildings and their map uploading service is not automatic. ESRI is also considered one of the leading companies delivering geographical information. Their indoor technology [2] is a complete bundle offering indoor mapping, 2d and 3D 1 This project is framed in the Avanza 2 Plan of the Spanish’s Ministry of Industry, Tourism and Trade visualization and routing. Finally, worth to mention Microsoft’s Bing Venue Maps [3] indoor mapping service. However, in comparison with the rest of the technologies aforementioned, it is not mature enough and still under development. The work herein presented studies the problem of creating an information system capable of serving geographical information, accurate indoor positioning and advanced methods of human to machine interaction. For this purpose, Open Street Maps data and tools were used in conjunction with a NoSQL geospatial database, a Restful web interface and a smartphone application. This paper is organised as follows. Section 2 describes the functional architecture adopted. In Section 3 the mapping task process is explained. Afterwards, Section 4 introduces MongoDB as a geospatial storage solution while Section 5 describes the adopted web service approach. Lastly, Section 6 shows the Android client. 2 System overview The proposed system’s architecture consists of three different elements: a data layer, a set of public REST web services and a mobile client. In order to guarantee secure communications, an additional intermediate layer between the client and server was included, providing certificate-based encrypted communications. Figure 1 shows the basic structure and the relations between layers. The data layer persistence was relayed to MongoDB. Nowadays, there are many applications and websites based on geolocation that require infrastructure for storing and processing geographic information. MongoDB provides this capability and also geospatial queries. In addition, it supports Using Open Street Maps data and tools for indoor mapping in a Smart City scenario Guillermo Amat FHC25 Roger de Lauria 19 5-B Valencia, Spain guillermo.amat@glass.u -tad.com Javier Fernandez FHC25 Calle Rozabella, 4 Las Rozas, Madrid, España javier.fernandez@glass.u -tad.com Alvaro Arranz FHC25 Calle Rozabella, 4 Las Rozas, Madrid, España alvaro.arranz@glass.u- tad.com Angel Ramos FHC25 Calle Rozabella, 4 Las Rozas, Madrid, España angel.ramos@glass.u- tad.com Abstract 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. Keywords: OSM, GIS, Smart Cities, indoor location, indoor navigation, HCI.