Desing and Validation of a Light Inference System to Support Embedded Context Reasoning

Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications—it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ‘Activity Monitor’ has been designed and implemented: a personal health-persuasive application that provides feedback on the user’s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user’s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.d

Design and Validation of a Light Inference System to Support Embedded Context Reasoning

Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications?it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ?Activity Monitor? has been designed and implemented: a personal health-persuasive application that provides feedback on the user?s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user?s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.

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.

Project management in cloud

Este proyecto consiste en la construcción de un prototipo para la gestión de proyectos, destinada a usuarios del entorno profesional. La herramienta pretende servir de soporte a los equipos que realicen un proyecto dotando al usuario con la posibilidad de gestionar los tiempos del proyecto, gestión de requisitos, gestión de recursos, gestión de la documentación, etc. Adicionalmente, este trabajo llevará asociado un plan de negocio para poder estudiar la viabilidad del proyecto, en este plan de negocio se analizará; el entorno externo (competencia); análisis de las debilidades, fortalezas, amenazas y oportunidades; plan de marketing; plan económicofinanciero; análisis de riesgos del proyecto. A grandes rasgos, la herramienta desarrollada se compone de dos bases de datos (una relacional y otra no relacional), un conjunto de módulos que implementan la funcionalidad y una interfaz gráfica que proporciona a los usuarios una forma cómoda de interactuar con el sistema, principalmente ofrecerá las siguientes opciones:  Gestión de proyectos  Gestión de usuarios.  Gestión de recursos  Gestión de tiempos  Cuadro de mando y notificaciones. ---ABSTRACT---This Project consist of the construction of a prototype for Project management, intended for users of the profesional environment. The software aims to support teams conducting a project by providing the user with the ability to manage time, requirements management, resource management, document management, etc. In addition, this work includes a business plan to study the viability of the project. This business plan addresses the following; analysis of the external enviroment; analysis of the strengths, weaknesses, opportunities and threats; marketing plan; economic and financial plan; analysis of project risks. In general terms, the developed tools are composed of two databases (relational and nonrelational), a set of modules that implement the functionality and a web interface that gives users a convenient way to interact with the system. The options that the system offers are:  Project management  User management  Resource management  Time management  Dashboard and notifications

Sistema multiplataforma de gestión integral de huertos urbanos

En este Proyecto Fin de Grado se construirá una herramienta de gestión integral de centros hortícolas donde una serie de huertos cuidados por personas en situación de discapacidad son alquilados a terceros. Esta iniciativa se lleva a cabo gracias a la iniciativa “La Huerta de Montecarmelo” de la Fundación Carmen Pardo-Valcarce de Madrid. Este proyecto es el resultado de la colaboración entre la Escuela Técnica Superior de Ingeniería de Sistemas Informáticos y la Fundación, a través de un programa de Prácticas Externas que duró doce meses. Por una parte, tras años de trabajo en esta Obra Social, se encontró que muchos de los clientes, pasado el verano, se desvinculaban de las tareas y del medio. A fin de solucionar esos problemas, se propuso construir una aplicación web, comunicada con otros dispositivos, como Smartphones, permitiendo un flujo de trabajo más ágil y notificando a los arrendatarios de cada cambio en sus huertos, por ejemplo: fotos recientes, notificaciones de recolecta o futuros cursos. El proyecto se llevó a cabo con éxito a lo largo de 2012 y 2013. Abstract In this Final Degree Project we build a complete horticulture center management tool where a set of gardens, which are kept by people with disabilities, are leased to third parties. This project is carried out within the La Huerta Montecarmelo initiative of the Carmen Pardo-Valcarce Foundation in Madrid. The project was the result of collaboration between the School of Computer Systems Engineering of the Technical University of Madrid and that Foundation through an External Practices program that lasted twelve months. By one hand, over the years of Social Work in this initiative, it was found that some clients after spring were easily disconnected from the tasks involved to the garden. By the other, all the management of more than two hundred of gardens becomes a very complex task due to lots of paperwork. To solve these problems and more, we proposed to build a web application, relying on other devices, such as Smartphones, allowing a more agile workflow and notifying customers of any change related to its garden, for example: recent photographs, notifications of harvest or future courses. The project was successfully carried out throughout 2012 and 2013.