Social networks provide rich data sources for analyzing people journeys in urban environments. This paper introduces a trusted path system that helps users to find their routes based in two criteria: low crime rate and no theft report. These data are obtained from two complementary sources: geo-tagged tweets from the social network Twitter, and an official database given by the Police of Mexico City. Recommended paths are computed automatically from these data sources by a complementary application of social mining techniques, Bayes algorithm and an adaptation of the Dijkstra algorithm. This system can be also used to identify the probability that an event occurs in specific locations and times. A proof of concept of the system is illustrated through two example scenarios.

Social networks provide rich data sources for analyzing people activities. This paper introduces a mobile recommender system that suggests places to visit to tourists acting in the city of Mexico. The system developed generates itineraries based on the implicit users' behaviors. Recommendations are automatically extracted and analyzed from Twitter thanks to the application of Bayes and Tree algorithms. Suggested itineraries are cross-analyzed to take into account user profiles and preferences. The recommender system provides an augmented reality navigation system that suggests itineraries to the users according to some places of interest. The preliminary prototype developed is an Android app so-called "Turicel Social".

This paper introduces an augmented-reality system that provides navigation facilities, generation of itineraries and services delivery. The approach offers the possibility of combining real sceneries with digital representations of places of interest and services for a given itinerary. The first level of the approach supports the identification of a given place based on Augmented reality (AR), offering additional information (images and description) of that place. The second level generates navigation itineraries based on semantic Web services, user profiles and recommendations obtained from tourism sources. The experimental setup integrates smartphones with digital compass, GPS, camera and accelerometer. The framework has been experimented in Mexico downtown in the historical center "Zocalo". The applications are available in App Store and Google Play Store called "Turicel aumentado" and "Turicel2", respectively.

Indoor environments offer many possibilities for the development of navigation-aided systems and location-based services. This paper introduces an experimental setup that combines navigation facilities with augmented reality, and which is applied to two museums in the city of Mexico. The approach is based on a semantic model of a museum environment that reflects its organization and spatial structure. The experimental setup combines augmented reality, digital compass devices with smartphones. While several constraints reduce interaction capabilities among exhibitions and visitors, augmented reality offers the possibility of relaxing these constraints by combining real sceneries with digital representations. This enhances interactions between users and objects of interest pointed by the users, where additional multimedia information on the collections presented is available on demand.