Location-based applications require knowing the user position constantly in order to find out and provide information about user's context. They use GPS signals to locate users, but unfortunately GPS location systems do not work in indoor environments. Therefore, there is a need of new methods that calculate the location of users in indoor environments using smartphone sensors. There are studies that propose indoor positioning systems but, as far as we know, they neither run on Android devices, nor can work in real environments. The goal of this chapter is to address that problem by presenting two methods that estimate the user position through a smartphone. The first method is based on euclidean distance and use Received Signal Strength (RSS) from WLAN Acces Points present in buildings. The second method uses sensor fusion to combine raw data of accelerometer and magnetometer inertial sensors. An Android prototype that implements both methods has been created and used to test both methods. The conclusions of the test are that RSS technique works efficiently in smartphones and achieves to estimate the position of users well enough to be used in real applications. On the contrary, the test results show that sensor fusion technique can be discarded due to bias errors and low frequency readings from accelerometers sensor.

Several applications that support users when doing tourism have appeared during the last years. These applications, though popular, have not become a reliable and dependable tourist assistant because they offer little personalization, which eventually may overwhelm users with too much information. An effective mobile application should store tourist information in a way that facilitates the identification of relevant points of interest to the user and the relevant information about them. The relevance of information depends also on the context. This paper presents an ontology that can store information about points of interest (POI), preferences and habits of users and time information.The presented ontology is aligned with the ontology LinkedGeoData to facilitate the importation of data to and from it. The ontology has been integrated into a mobile application called Itiner@ to create custom routes for each user based on his/her preferences, personal situation, means of transport, area to visit, date and duration of the visit. The main contribution of this work is to identify the relevant information to mobile touristic applications and to show how to use an ontology to improve the functionalities of geographic information system through the use of semantic information.

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