GeoTools-Android. Eines geogràfiques per Android

El present Treball Final de Carrera (TFC), basat en el tema dels Sistemes d'informació Geogràfica i Geotelemàtica, es centra en les diverses aplicacions geoespacials per al sistema operatiu Android.

Mobile Marketing in Japan

Mobiilimarkkinoinnin markkinat ovat vasta rakentumassa ja suurin osa alan toimijoista etenkin Suomessa yrittää vielä löytää rooliaan. Sen sijaan Japanissa sisällöntuotantoliiketoiminta matkapuhelimille kukoistaa ja mobiilimarkkinointi on jo saavuttanut merkittävän aseman mobiili-internetin palvelutarjonnassa. Toisin kuin Suomessa, jossa mobiilimarkkinat ovat vielä lastenkengissä, Japanissa myös mobiilimarkkinoinnin arvoketju on vähitellen muotoutumassa.Tämän tutkimuksen tavoitteena oli antaa käsitys Japanin mobiilimarkkinoinnin dynamiikasta ja luoda viitekehys operaattorin tulevalle roolille mobiilimarkkinoinnin markkinoiden rakentamisessa. Tutkimus on deskriptiivinen ja aineisto on kerätty alan kirjallisuudesta sekä haastattelemalla tärkeitä mobiilimarkkinoiden toimijoita Japanissa. Japanissa operaattoreilla (NTT DoCoMo, J-Phone ja KDDI) on erittäin vahva asema mobiili-internetin ja mobiilimarkkinoinnin markkinoilla. Ne hallitsevat asiakasrajapintaa, päättävät mobiiliverkon ja matkapuhelimien ominaisuuksista sekä siitä, ketkä sisällöntuottajista pääsevät osaksi heidän laskutusjärjestelmäänsä. Markkinoinnissa operaattoreilla ei ole yhtä näkyvää roolia. Omistussuhteiden kautta ne kuitenkin vaikuttavat lähes koko arvoketjuun. Operaattorit ovat yhdessä Japanin suurimpien mainostoimistojen kanssa luoneet tytäryhtiöitä, jotka hoitavat mainonnan operaattorin mobiiliportaalissa. Japanissa operaattori on ottanut hallitsevan roolin mobiilimarkkinoiden rakentamisessa. Tiivis yhteistyö eri toimijoiden, kuten matkapuhelinvalmistajien, sisällöntuottajien ja mainostoimistojen kanssa, on mahdollistanut kokonaisvaltaisen palvelupaketin tarjoamisen. Palvelupaketti sisältää käyttäjäystävällisen liittymän mobiili-internetiin sekä edulliset puhelimet. Juuri tiivis yhteistyö onkin ollut yksi tärkeimmistä menestystekijöistä Japanin markkinoita rakennettaessa. Mobiilimarkkinoita rakennettaessa operaattorilla on merkittävä rooli markkinoiden muodostajana ja sisällön kokoojana. Operaattorien tulee varautua roskapostin vastaiseen taisteluun, jos sähköpostia annetaan lähettää suoraan matkapuhelimeen. On erityisen tärkeää varmistaa, ettei käyttäjien tarvitse kärsiä roskapostista, muuten suoramarkkinoinnin mahdollisuus matkapuhelimeen menetetään. Ainoastaan aktiivisella edistämisellä ja osallistumisella mobiili-internetin sisällöntuotanto- ja markkinointiliiketoimintaan operaattori voi vahvistaa markkina-asemaansa ja varmistaa osuutensa tulevista markkinoista.

User Centered Desing in E-Learning Environments : from Usability to Learner Experience

The advent of the Internet had a great impact on distance education and rapidly e-learning has become a killer application. Education institutions worldwide are taking advantage of the available technology in order to facilitate education to a growing audience. Everyday, more and more people use e-learning systems, environments and contents for both training and learning. E-learning promotes educationamong people that due to different reasons could not have access to education: people who could nottravel, people with very little free time, or withdisabilities, etc. As e-learning systems grow and more people are accessing them, it is necessary to consider when designing virtual environments the diverse needs and characteristics that different users have. This allows building systems that people can use easily, efficiently and effectively, where the learning process leads to a good user experience and becomes a good learning experience.

Designing and Implementing Mouse Emulation to Touchscreen Operated Mobile Web Browsers

Browsing the web has become one of the most important features in high end mobile phones and in the future more and more people will be using mobile phone for web browsing. Large touchscreens improve browsing experience but many web sites are designed to be used with a mouse. A touchscreen differs substantially from a mouse as a pointing device and therefore mouse emulation logic is required in the browsers to make more web sites usable. This Master's thesis lists the most significant cases where the differences of a mouse and a touchscreen affect web browsing. Five touchscreen mobile phones and their web browsers were evaluated to find out if and how these cases are handled in them. Also as a part of this thesis, a simple QtWebKit based mobile web browser with advanced mouse emulation model was implemented, aiming to solve all the problematic cases. The conclusion of this work is that it is feasible to emulate a mouse with a touchscreen and thus deliver good user experience in mobile web browsing. However, current highend touchscreen mobile phones have relatively underdeveloped mouse emulations in their web browsers and there is a lot to improve.

Metrics for Predicting User Behavior and Experience in an Interactive Storytelling System

In much of the previous research into the field of interactive storytelling, the focus has been on the creation of complete systems, then evaluating the performance of those systems based on user experience. Less focus has been placed on finding general solutions to problems that manifest in many different types of interactive storytelling systems. The goal of this thesis was to identify potential candidates for metrics that a system could use to predict player behavior or how players experience the story they are presented with, and to put these metrics to an empirical test. The three metrics that were used were morality, relationships and conflict. The game used for user testing of the metrics, Regicide is an interactive storytelling experience that was created in conjunction with Eero Itkonen. Data, in the forms of internal system data and survey answers, collected through user testing, was used to evaluate hypotheses for each metric. Out of the three chosen metrics, morality performed the best in this study. Though further research and refinement may be required, the results were promising, and point to the conclusion that user responses to questions of morality are a strong predictor for their choices in similar situations later on in the course of an interactive story. A similar examination for user relationships with other characters in the story did not produce promising results, but several problems were recognized in terms of methodology and further research with a better optimized system may yield different results. On the subject of conflict, several aspects, proposed by Ware et al. (2012), were evaluated separately. Results were inconclusive, with the aspect of directness showing the most promise.

Think: guia de desenvolvimento mobile ágil em equipes reduzidas

Currently, applications for smartphones and tablets, called apps, are becoming increasingly relevant and attract more attention from users and finally the developers. With the Application Stores, services provided by the company that maintains the platform, access to such applications is as or more simplified than to web sites, with the advantage of anenhanced user experience and focused on the mobile device, and enjoy natives resources as camera, audio, storage, integration with other applications, etc. They present a great opportunity for independent developers, who can now develop an application and make it availabl e to all users of that platform, at free or at a cost that is usually low. Even students may create their applications in the intervals of their classes and sell them in stores. Making use of tools and services, free or at low cost, anyone can develop quality applications, that can be marketed and have a large number of users even in adverse situations in which the application is not the focus of developer productivity. However, such to ols do not seem to be well used, or are unknown, or its purpose is not considered important, and this paper tries to show the real importance of these tools in the rapid development of quality software. This project presents several tools, services and practices, which together make it possible to develop an application for various mobile platforms, independently and with a team of a few people, as demonstrated. However, this paper aims not to say that the development of software today it is easy and simple, but there are currently a large set of tools, for various platforms, that assists and enhances the work of the programmer

Concepção e implementação de um serviço baseado em localização na plataforma ANDROID/GOOGLE

The mobile application proposed in this undergraduate project, classified as a Location-Based Service and named Traveller, was developed to support users of mobile phones equipped with GPS in unknown locations by providing information about weather, location of users and stores in urban areas. The mobile devices whose this project is intended are those equipped with Android. The programming language Java was selected and the Eclipse development environment was used along with the toolkit for developing Android (ADT - Android Development Tools)

Geophotohunt: Studio di algoritmi di confronto di immagini per realizzare una caccia al tesoro fotografica

Questo studio si propone di realizzare un’applicazione per dispositivi Android che permetta, per mezzo di un gioco di ruolo strutturato come caccia al tesoro, di visitare in prima persona città d’arte e luoghi turistici. Gli utenti finali, grazie alle funzionalità dell’app stessa, potranno giocare, creare e condividere cacce al tesoro basate sulla ricerca di edifici, monumenti, luoghi di rilevanza artistico-storica o turistica; in particolare al fine di completare ciascuna tappa di una caccia al tesoro il giocatore dovrà scattare una fotografia al monumento o edificio descritto nell’obiettivo della caccia stessa. Il software grazie ai dati rilevati tramite GPS e giroscopio (qualora il dispositivo ne sia dotato) e per mezzo di un algoritmo di instance recognition sarà in grado di affermare se la foto scattata rappresenta la risposta corretta al quesito della tappa. L’applicazione GeoPhotoHunt rappresenta non solo uno strumento ludico per la visita di città turistiche o più in generale luoghi di interesse, lo studio propone, infatti come suo contributo originale, l’implementazione su piattaforma mobile di un Content Based Image Retrieval System (CBIR) del tutto indipendente da un supporto server. Nello specifico il server dell’applicazione non sarà altro che uno strumento di appoggio con il quale i membri della “community” di GeoPhotoHunt potranno pubblicare le cacce al tesoro da loro create e condividere i punteggi che hanno totalizzato partecipando a una caccia al tesoro. In questo modo quando un utente ha scaricato sul proprio smartphone i dati di una caccia al tesoro potrà iniziare l’avventura anche in assenza di una connessione internet. L’intero studio è stato suddiviso in più fasi, ognuna di queste corrisponde ad una specifica sezione dell’elaborato che segue. In primo luogo si sono effettuate delle ricerche, soprattutto nel web, con lo scopo di individuare altre applicazioni che implementano l’idea della caccia al tesoro su piattaforma mobile o applicazioni che implementassero algoritmi di instance recognition direttamente su smartphone. In secondo luogo si è ricercato in letteratura quali fossero gli algoritmi di riconoscimento di immagini più largamente diffusi e studiati in modo da avere una panoramica dei metodi da testare per poi fare la scelta dell’algoritmo più adatto al caso di studio. Quindi si è proceduto con lo sviluppo dell’applicazione GeoPhotoHunt stessa, sia per quanto riguarda l’app front-end per dispositivi Android sia la parte back-end server. Infine si è passati ad una fase di test di algoritmi di riconoscimento di immagini in modo di avere una sufficiente quantità di dati sperimentali da permettere di effettuare una scelta dell’algoritmo più adatto al caso di studio. Al termine della fase di testing si è deciso di implementare su Android un algoritmo basato sulla distanza tra istogrammi di colore costruiti sulla scala cromatica HSV, questo metodo pur non essendo robusto in presenza di variazioni di luminosità e contrasto, rappresenta un buon compromesso tra prestazioni, complessità computazionale in modo da rendere la user experience quanto più coinvolgente.

Realtà aumentata per dispositivi android: lo stato dell'arte

Obiettivo di questa tesi è quello di illustrare il mondo della realtà aumentata (AR) ed in particolare delle tecnologie software disponibili per lo sviluppo di applicazioni su dispositivi Android. Si partirà dal darne una definizione e riassumerne i principali fatti storici, all'illustrarne i vari hardware disponibili sul mercato e le tecnologie software per sviluppare progetti. Non verranno tralasciati utilizzi e settori di ricerca, e si presenterà poi il sistema operativo Android. Dopo uno sguardo alla sua architettura e alle sue caratteristiche, nonché al linguaggio di programmazione Java, cardine per lo sviluppo in questo sistema, si presenteranno alcune API dell'SDK nativo che si rivelano utili per lo sviluppo di applicazioni per la realtà aumentata. Infine, verrà presentato un approfondimento sull'SDK Metaio.

Find to play Android App

L’argomento centrale della tesi sono i centri sportivi, l’applicazione permette quindi all’utente di cercare un centro sportivo per nome, per città o per provincia. Consente inoltre di visualizzare la disponibilità per ogni campo offerto dalle strutture ed eventualmente di effettuare una prenotazione. Il centro sportivo renderà disponibili informazioni altrimenti difficilmente reperibili come gli orari, il numero telefonico, l’indirizzo, ecc.. Il progetto si compone di una parte front end e una parte back end. Il front consiste in un’applicazione android nativo (sviluppata in java). Il back-end invece vede un applicativo basato su ASP.NET Web API 2, con db Entity Framework Code First. Per la gestione degli user è stato scelto il framework ASP.NET Identity 2.1.

Sviluppo di applicazioni mobili attraverso framework cross-platform: una valutazione sperimentale

Sviluppare e manutenere applicativi destinati a differenti piattaforme è un’opzione esclusiva di quelle entità capaci di sostenere costi molto alti per la realizzazione di queste applicazioni. Questo esclude gli sviluppatori indipendenti, che spesso realizzano prodotti in totale autonomia; le start-up, che hanno l’esigenza di sviluppare un’idea di business avendo a disposizione budget estremamente ridotti; le piccole aziende, alle quali viene così preclusa la possibilità di competere con player più importanti. Questo tipo di emergenze rende lo sviluppo cross-platform una soluzione interessante per la realizzazione delle applicazioni mobili, abbattendo i costi di sviluppo e permettendo di raggiungere più velocemente un pubblico più ampio. C'è quindi sempre maggiore interesse, da parte degli sviluppatori, per gli strumenti di sviluppo cross-platform. Per catturare l’attenzione degli sviluppatori è necessario che lo strumento sia dotato di buona stabilità, che offra un ambiente di sviluppo confortevole, una buona user experience, facilità di aggiornamento, tempi di sviluppo contenuti e possibilità di immissione delle applicazioni su diversi ecosistemi software. L’idea alla base di questa Tesi di laurea è valutare i pro e i contro di uno di questi framework cross-platform e compararlo con le tecnologie native. Il framework scelto è Ionic per via della sua popolarità tra gli sviluppatori e della ridotta bibliografia scientifica a riguardo. Molte ricerche scientifiche valutano le prestazioni di uno o più framework cross-platform rispetto ad una soluzione nativa, tuttavia è raro un confronto tra un framework e più soluzioni native. Per questo, oltre a valutare i pro e i contro del framework, verrà anche effettuata una comparazione tra gli applicativi nativi per Android e iOS e le controparti sviluppate attraverso Ionic, permettendo di identificare eventuali differenze di performance e aiutare gli sviluppatori nelle scelte tecnologiche.

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

Modelado de sistemas de inteligencia ambiental para el entrenamiento de las cualidades físicas

En un ejercicio no extenuante la frecuencia cardíaca (FC) guarda una relación lineal con el consumo máximo de oxígeno (V O2max) y se suele usar como uno de los parámetros de referencia para cuantificar la capacidad del sistema cardiovascular. Normalmente la frecuencia cardíaca puede remplazar el porcentaje de V O2max en las prescripciones básicas de ejercicio para la mejora de la resistencia aeróbica. Para obtener los mejores resultados en la mejora de la resistencia aeróbica, el entrenamiento de los individuos se debe hacer a una frecuencia cardíaca suficientemente alta, para que el trabajo sea de predominio dinámico con la fosforilación oxidativa como fuente energética primaria, pero no tan elevada que pueda suponer un riesgo de infarto de miocardio para el sujeto que se está entrenando. Los programas de entrenamiento de base mínima y de base óptima, con ejercicios de estiramientos para prevenir lesiones, son algunos de los programas más adecuados para el entrenamiento de la resistencia aeróbica porque maximizan los beneficios y minimizan los riesgos para el sistema cardiovascular durante las sesiones de entrenamiento. En esta tesis, se ha definido un modelo funcional para sistemas de inteligencia ambiental capaz de monitorizar, evaluar y entrenar las cualidades físicas que ha sido validado cuando la cualidad física es la resistencia aeróbica. El modelo se ha implementado en una aplicación Android utilizando la camiseta inteligente “GOW running” de la empresa Weartech. El sistema se ha comparado en el Laboratorio de Fisiología del Esfuerzo (LFE) de la Universidad Politécnica de Madrid (UPM) durante la realización de pruebas de esfuerzo. Además se ha evaluado un sistema de guiado con voz para los entrenamientos de base mínima y de base óptima. También el desarrollo del software ha sido validado. Con el uso de cuestionarios sobre las experiencias de los usuarios utilizando la aplicación se ha evaluado el atractivo de la misma. Por otro lado se ha definido una nueva metodología y nuevos tipos de cuestionarios diseñados para evaluar la utilidad que los usuarios asignan al uso de un sistema de guiado por voz. Los resultados obtenidos confirman la validez del modelo. Se ha obtenido una alta concordancia entre las medidas de FC hecha por la aplicación Android y el LFE. También ha resultado que los métodos de estimación del VO2max de los dos sistemas pueden ser intercambiables. Todos los usuarios que utilizaron el sistema de guiado por voz para entrenamientos de 10 base mínima y de base óptimas de la resistencia aeróbica consiguieron llevar a cabo las sesiones de entrenamientos con un 95% de éxito considerando unos márgenes de error de un 10% de la frecuencia cardíaca máxima teórica. La aplicación fue atractiva para los usuarios y hubo también una aceptación del sistema de guiado por voz. Se ha obtenido una evaluación psicológica positiva de la satisfacción de los usuarios que interactuaron con el sistema. En conclusión, se ha demostrado que es posible desarrollar sistemas de Inteligencia Ambiental en dispositivos móviles para la mejora de la salud. El modelo definido en la tesis es el primero modelo funcional teórico de referencia para el desarrollo de este tipo de aplicaciones. Posteriores estudios se realizarán con el objetivo de extender dicho modelo para las demás cualidades físicas que suponen modelos fisiológicos más complejos como por ejemplo la flexibilidad. Abstract In a non-strenuous exercise, the heart rate (HR) shows a linear relationship with the maximum volume of oxygen consumption (V O2max) and serves as an indicator of performance of the cardiovascular system. The heart rate replaces the %V O2max in exercise program prescription to improve aerobic endurance. In order to achieve an optimal effect during endurance training, the athlete needs to work out at a heart rate high enough to trigger the aerobic metabolism, while avoiding the high heart rates that bring along significant risks of myocardial infarction. The minimal and optimal base training programs, followed by stretching exercises to prevent injuries, are adequate programs to maximize benefits and minimize health risks for the cardiovascular system during single session training. In this thesis, we have defined an ambient intelligence system functional model that monitors, evaluates and trains physical qualities, and it has been validated for aerobic endurance. It is based on the Android System and the “GOW Running” smart shirt. The system has been evaluated during functional assessment stress testing of aerobic endurance in the Stress Physiology Laboratory (SPL) of the Technical University of Madrid (UPM). Furthermore, a voice system, designed to guide the user through minimal and optimal base training programs, has been evaluated. Also the software development has been evaluated. By means of user experience questionnaires, we have rated the attractiveness of the android application. Moreover, we have defined a methodology and a new kind of questionnaires in order to assess the user experience with the audio exercise guide system. The results obtained confirm the model. We have a high similarity between HR measurements made of our system and the one used by SPL. We have also a high correlation between the VO2max estimations of our system and the SPL system. All users, that tried the voice guidance system for minimal and optimal base training programs, were able to perform the 95% of the training session with an error lower than the 10% of theoretical maximum heart rate. The application appeared attractive to the users, and it has also been proven that the voice guidance system was useful. As result we obtained a positive evaluation of the users' satisfaction while they interacted with the system. In conclusion, it has been demonstrated that is possible to develop mobile Ambient Intelligence applications for the improvement of healthy lifestyle. AmIRTEM model is the first theoretical reference functional model for the design of this kind of applications. Further studies will be realized in order to extend the AmIRTEM model to other physical qualities whose physiological models are more complex than the aerobic endurance.

Mars: a personalised mobile activity recognition system

Mobile activity recognition focuses on inferring the current activities of a mobile user by leveraging the sensory data that is available on today’s smart phones. The state of the art in mobile activity recognition uses traditional classification learning techniques. Thus, the learning process typically involves: i) collection of labelled sensory data that is transferred and collated in a centralised repository; ii) model building where the classification model is trained and tested using the collected data; iii) a model deployment stage where the learnt model is deployed on-board a mobile device for identifying activities based on new sensory data. In this paper, we demonstrate the Mobile Activity Recognition System (MARS) where for the first time the model is built and continuously updated on-board the mobile device itself using data stream mining. The advantages of the on-board approach are that it allows model personalisation and increased privacy as the data is not sent to any external site. Furthermore, when the user or its activity profile changes MARS enables promptly adaptation. MARS has been implemented on the Android platform to demonstrate that it can achieve accurate mobile activity recognition. Moreover, we can show in practise that MARS quickly adapts to user profile changes while at the same time being scalable and efficient in terms of consumption of the device resources.

Contribution to proactivity in mobile context-aware recommender systems

Los sistemas de recomendación son potentes herramientas de filtrado de información que permiten a usuarios solicitar sugerencias sobre ítems que cubran sus necesidades. Tradicionalmente estas recomendaciones han estado basadas en opiniones de los mismos, así como en datos obtenidos de su consumo histórico o comportamiento en el propio sistema. Sin embargo, debido a la gran penetración y uso de los dispositivos móviles en nuestra sociedad, han surgido nuevas oportunidades en el campo de los sistemas de recomendación móviles gracias a la información contextual que se puede obtener sobre la localización o actividad de los usuarios. Debido a este estilo de vida en el que todo tiende a la movilidad y donde los usuarios están plenamente interconectados, la información contextual no sólo es física, sino que también adquiere una dimensión social. Todo esto ha dado lugar a una nueva área de investigación relacionada con los Sistemas de Recomendación Basados en Contexto (CARS) móviles donde se busca incrementar el nivel de personalización de las recomendaciones al usar dicha información. Por otro lado, este nuevo escenario en el que los usuarios llevan en todo momento un terminal móvil consigo abre la puerta a nuevas formas de recomendar. Sustituir el tradicional patrón de uso basado en petición-respuesta para evolucionar hacia un sistema proactivo es ahora posible. Estos sistemas deben identificar el momento más adecuado para generar una recomendación sin una petición explícita del usuario, siendo para ello necesario analizar su contexto. Esta tesis doctoral propone un conjunto de modelos, algoritmos y métodos orientados a incorporar proactividad en CARS móviles, a la vez que se estudia el impacto que este tipo de recomendaciones tienen en la experiencia de usuario con el fin de extraer importantes conclusiones sobre "qué", "cuándo" y "cómo" se debe notificar proactivamente. Con este propósito, se comienza planteando una arquitectura general para construir CARS móviles en escenarios sociales. Adicionalmente, se propone una nueva forma de representar el proceso de recomendación a través de una interfaz REST, lo que permite crear una arquitectura independiente de dispositivo y plataforma. Los detalles de su implementación tras su puesta en marcha en el entorno bancario español permiten asimismo validar el sistema construido. Tras esto se presenta un novedoso modelo para incorporar proactividad en CARS móviles. Éste muestra las ideas principales que permiten analizar una situación para decidir cuándo es apropiada una recomendación proactiva. Para ello se presentan algoritmos que establecen relaciones entre lo propicia que es una situación y cómo esto influye en los elementos a recomendar. Asimismo, para demostrar la viabilidad de este modelo se describe su aplicación a un escenario de recomendación para herramientas de creación de contenidos educativos. Siguiendo el modelo anterior, se presenta el diseño e implementación de nuevos interfaces móviles de usuario para recomendaciones proactivas, así como los resultados de su evaluación entre usuarios, lo que aportó importantes conclusiones para identificar cuáles son los factores más relevantes a considerar en el diseño de sistemas proactivos. A raíz de los resultados anteriores, el último punto de esta tesis presenta una metodología para calcular cuán apropiada es una situación de cara a recomendar de manera proactiva siguiendo el modelo propuesto. Como conclusión, se describe la validación llevada a cabo tras la aplicación de la arquitectura, modelo de recomendación y métodos descritos en este trabajo en una red social de aprendizaje europea. Finalmente, esta tesis discute las conclusiones obtenidas a lo largo de la extensa investigación llevada a cabo, y que ha propiciado la consecución de una buena base teórica y práctica para la creación de sistemas de recomendación móviles proactivos basados en información contextual. ABSTRACT Recommender systems are powerful information filtering tools which offer users personalized suggestions about items whose aim is to satisfy their needs. Traditionally the information used to make recommendations has been based on users’ ratings or data on the item’s consumption history and transactions carried out in the system. However, due to the remarkable growth in mobile devices in our society, new opportunities have arisen to improve these systems by implementing them in ubiquitous environments which provide rich context-awareness information on their location or current activity. Because of this current all-mobile lifestyle, users are socially connected permanently, which allows their context to be enhanced not only with physical information, but also with a social dimension. As a result of these novel contextual data sources, the advent of mobile Context-Aware Recommender Systems (CARS) as a research area has appeared to improve the level of personalization in recommendation. On the other hand, this new scenario in which users have their mobile devices with them all the time offers the possibility of looking into new ways of making recommendations. Evolving the traditional user request-response pattern to a proactive approach is now possible as a result of this rich contextual scenario. Thus, the key idea is that recommendations are made to the user when the current situation is appropriate, attending to the available contextual information without an explicit user request being necessary. This dissertation proposes a set of models, algorithms and methods to incorporate proactivity into mobile CARS, while the impact of proactivity is studied in terms of user experience to extract significant outcomes as to "what", "when" and "how" proactive recommendations have to be notified to users. To this end, the development of this dissertation starts from the proposal of a general architecture for building mobile CARS in scenarios with rich social data along with a new way of managing a recommendation process through a REST interface to make this architecture multi-device and cross-platform compatible. Details as regards its implementation and evaluation in a Spanish banking scenario are provided to validate its usefulness and user acceptance. After that, a novel model is presented for proactivity in mobile CARS which shows the key ideas related to decide when a situation warrants a proactive recommendation by establishing algorithms that represent the relationship between the appropriateness of a situation and the suitability of the candidate items to be recommended. A validation of these ideas in the area of e-learning authoring tools is also presented. Following the previous model, this dissertation presents the design and implementation of new mobile user interfaces for proactive notifications. The results of an evaluation among users testing these novel interfaces is also shown to study the impact of proactivity in the user experience of mobile CARS, while significant factors associated to proactivity are also identified. The last stage of this dissertation merges the previous outcomes to design a new methodology to calculate the appropriateness of a situation so as to incorporate proactivity into mobile CARS. Additionally, this work provides details about its validation in a European e-learning social network in which the whole architecture and proactive recommendation model together with its methods have been implemented. Finally, this dissertation opens up a discussion about the conclusions obtained throughout this research, resulting in useful information from the different design and implementation stages of proactive mobile CARS.