Author: Diego Martín-Serrano

Supervisor: Ramón Hervás

February 2012

Nowadays, tourism industry is one of the most important economic activities related to employment and generation of richness. Additionally, tourism applications are a relevant scenario to study the potential of the Ambient Intelligence paradigm. The Telemaco system generates custom trips and has two different components: an Android application and a Django-powered server application. The mobile application updates the information when possible and makes data available at all times without a permanent connection to the Internet. The intermediate Web server gets the information from the Internet and offers it to mobile devices. Web 3.0 technologies are used to extract information from different services available on the Internet, to define the user's context using the FOAF ontology and to recommend personalized places of interest. This mobile guide supports tourism by using touristic, geographic, historical, cultural contents in an agile way, interacting with social networks and creating a new profile of the global traveler.


Author: Alberto García Lillo

Supervisor: Ramón Hervás

February 2011


This project presents a proposal for supporting daily user needs by simple interactions with the environment through an augmented-reality perspective that applies proactive adaptation through knowledge representation using ontologies. The proposed architecture (i-ARA) uses principles of the Semantic Web that endow context-awareness and user personalization.In addition, these types of services allow the supervision and management of what is happening in the environment and, consequently, improve the information offered to users. The architecture has been used to implement applications using iPhone technology and has been applied to illustrative scenarios.

Author: Iván Raso

Supervisor: Ramón Hervás

July 2010

This project proposes a rehabilitation system based on new technological tendencies in the mobility and ubiquitous computing areas. Specialists and patients related to rehabilitation area can use this proposed system to improve the fulfillment of exercises and the supervision of rehabilitation tasks. We have developed our system using a mobile device and a bracelet to capture patient's rehabilitation relevant data. As a pre-process procedure, raw data output by mobile device accelerometer is filtered, and then we use the technique called Dynamic Time Warping to train and recognize movements. Based on this recognition, patients can perform rehabilitation without the continuous specialist's surveillance and can be sure of its accuracy. Experimental results show us that our system is able to adapt itself dynamically to the peculiarities of each user and enhance healthy rehabilitation in a proactive way. A general view of the system flow is presented in the following figure.