A multimodal tablet-based interface for designing and reviewing 3D engineering models

The ability to view and interact with 3D models has been happening for a long time. However, vision-based 3D modeling has only seen limited success in applications, as it faces many technical challenges. Hand-held mobile devices have changed the way we interact with virtual reality environments. Their high mobility and technical features, such as inertial sensors, cameras and fast processors, are especially attractive for advancing the state of the art in virtual reality systems. Also, their ubiquity and fast Internet connection open a path to distributed and collaborative development. However, such path has not been fully explored in many domains. VR systems for real world engineering contexts are still difficult to use, especially when geographically dispersed engineering teams need to collaboratively visualize and review 3D CAD models. Another challenge is the ability to rendering these environments at the required interactive rates and with high fidelity. In this document it is presented a virtual reality system mobile for visualization, navigation and reviewing large scale 3D CAD models, held under the CEDAR (Collaborative Engineering Design and Review) project. It’s focused on interaction using different navigation modes. The system uses the mobile device's inertial sensors and camera to allow users to navigate through large scale models. IT professionals, architects, civil engineers and oil industry experts were involved in a qualitative assessment of the CEDAR system, in the form of direct user interaction with the prototypes and audio-recorded interviews about the prototypes. The lessons learned are valuable and are presented on this document. Subsequently it was prepared a quantitative study on the different navigation modes to analyze the best mode to use it in a given situation.

A Mobile Feedback System for Integrated E-health Platforms to improve Self-Care and Compliance of Diabetes Mellitus Patients

Exploiting the full potential of telemedical systems means using platform based solutions: data are recovered from biomedical sensors, hospital information systems, care-givers, as well as patients themselves, and are processed and redistributed in an either centralized or, more probably, decentralized way. The integration of all these different devices, and interfaces, as well as the automated analysis and representation of all the pieces of information are current key challenges in telemedicine. Mobile phone technology has just begun to offer great opportunities of using this diverse information for guiding, warning, and educating patients, thus increasing their autonomy and adherence to their prescriptions. However, most of these existing mobile solutions are not based on platform systems and therefore represent limited, isolated applications. This article depicts how telemedical systems, based on integrated health data platforms, can maximize prescription adherence in chronic patients through mobile feedback. The application described here has been developed in an EU-funded R&D project called METABO, dedicated to patients with type 1 or type 2 Diabetes Mellitus

Analyzing Business Models for Mobile Augmented Reality

Nowadays, a wide offer of mobile augmented reality (mAR) applications is available at the market, and the user base of mobile AR-capable devices -smartphones- is rapidly increasing. Nevertheless, likewise to what happens in other mobile segments, business models to put mAR in value are not clearly defined yet. In this paper, we focus on sketching the big picture of the commercial offer of mAR applications, in order to inspire a posterior analysis of business models that may successfully support the evolution of mAR. We have gathered more than 400 mAR applications from Android Market, and analyzed the offer as a whole, taking into account some technology aspects, pricing schemes and user adoption factors. Results show, for example, that application providers are not expecting to generate revenues per direct download, although they are producing high-quality applications, well rated by the users.

Probabilistic mapping with mobile robots in structured environments

La mayor parte de los entornos diseñados por el hombre presentan características geométricas específicas. En ellos es frecuente encontrar formas poligonales, rectangulares, circulares . . . con una serie de relaciones típicas entre distintos elementos del entorno. Introducir este tipo de conocimiento en el proceso de construcción de mapas de un robot móvil puede mejorar notablemente la calidad y la precisión de los mapas resultantes. También puede hacerlos más útiles de cara a un razonamiento de más alto nivel. Cuando la construcción de mapas se formula en un marco probabilístico Bayesiano, una especificación completa del problema requiere considerar cierta información a priori sobre el tipo de entorno. El conocimiento previo puede aplicarse de varias maneras, en esta tesis se presentan dos marcos diferentes: uno basado en el uso de primitivas geométricas y otro que emplea un método de representación cercano al espacio de las medidas brutas. Un enfoque basado en características geométricas supone implícitamente imponer un cierto modelo a priori para el entorno. En este sentido, el desarrollo de una solución al problema SLAM mediante la optimización de un grafo de características geométricas constituye un primer paso hacia nuevos métodos de construcción de mapas en entornos estructurados. En el primero de los dos marcos propuestos, el sistema deduce la información a priori a aplicar en cada caso en base a una extensa colección de posibles modelos geométricos genéricos, siguiendo un método de Maximización de la Esperanza para hallar la estructura y el mapa más probables. La representación de la estructura del entorno se basa en un enfoque jerárquico, con diferentes niveles de abstracción para los distintos elementos geométricos que puedan describirlo. Se llevaron a cabo diversos experimentos para mostrar la versatilidad y el buen funcionamiento del método propuesto. En el segundo marco, el usuario puede definir diferentes modelos de estructura para el entorno mediante grupos de restricciones y energías locales entre puntos vecinos de un conjunto de datos del mismo. El grupo de restricciones que se aplica a cada grupo de puntos depende de la topología, que es inferida por el propio sistema. De este modo, se pueden incorporar nuevos modelos genéricos de estructura para el entorno con gran flexibilidad y facilidad. Se realizaron distintos experimentos para demostrar la flexibilidad y los buenos resultados del enfoque propuesto. Abstract Most human designed environments present specific geometrical characteristics. In them, it is easy to find polygonal, rectangular and circular shapes, with a series of typical relations between different elements of the environment. Introducing this kind of knowledge in the mapping process of mobile robots can notably improve the quality and accuracy of the resulting maps. It can also make them more suitable for higher level reasoning applications. When mapping is formulated in a Bayesian probabilistic framework, a complete specification of the problem requires considering a prior for the environment. The prior over the structure of the environment can be applied in several ways; this dissertation presents two different frameworks, one using a feature based approach and another one employing a dense representation close to the measurements space. A feature based approach implicitly imposes a prior for the environment. In this sense, feature based graph SLAM was a first step towards a new mapping solution for structured scenarios. In the first framework, the prior is inferred by the system from a wide collection of feature based priors, following an Expectation-Maximization approach to obtain the most probable structure and the most probable map. The representation of the structure of the environment is based on a hierarchical model with different levels of abstraction for the geometrical elements describing it. Various experiments were conducted to show the versatility and the good performance of the proposed method. In the second framework, different priors can be defined by the user as sets of local constraints and energies for consecutive points in a range scan from a given environment. The set of constraints applied to each group of points depends on the topology, which is inferred by the system. This way, flexible and generic priors can be incorporated very easily. Several tests were carried out to demonstrate the flexibility and the good results of the proposed approach.

Jeux sur mobile: les développeurs et le rôle des plates-formes de logiciels

Les jeux sur mobile sont un exemple majeur à la fois d'une application réussie sur les mobiles et du nombre croissant de plates-formes pour les médias et les industries de loisirs. Explorant cette convergence, l'article analyse les caractéristiques principales du marché des jeux sur mobile et de son écosystème industriel, ses activités et acteurs principaux. L'article se concentre sur le rôle des différentes plates-formes de logiciels et sur les défis et opportunités futures pour les développeurs de jeux sur mobile dans un nouveau scénario dominé par les plates-formes de mobile.

3D hp-adaptive finite element simulations of a magic-T electromagnetic waveguide structure

This paper employs a 3D hp self-adaptive grid-refinement finite element strategy for the solution of a particular electromagnetic waveguide structure known as Magic-T. This structure is utilized as a power divider/combiner in communication systems as well as in other applications. It often incorporates dielectrics, metallic screws, round corners, and so on, which may facilitate its construction or improve its design, but significantly difficult its modeling when employing semi-analytical techniques. The hp-adaptive finite element method enables accurate modeling of a Magic-T structure even in the presence of these undesired materials/geometries. Numerical results demonstrate the suitability of the hp-adaptive method for modeling a Magic-T rectangular waveguide structure, delivering errors below 0.5% with a limited number of unknowns. Solutions of waveguide problems delivered by the self-adaptive hp-FEM are comparable to those obtained with semi-analytical techniques such as the Mode Matching method, for problems where the latest methods can be applied. At the same time, the hp-adaptive FEM enables accurate modeling of more complex waveguide structures.

Authentication in mobile devices through hand gesture recognition

This article proposes an innovative biometric technique based on the idea of authenticating a person on a mobile device by gesture recognition. To accomplish this aim, a user is prompted to be recognized by a gesture he/she performs moving his/her hand while holding a mobile device with an accelerometer embedded. As users are not able to repeat a gesture exactly in the air, an algorithm based on sequence alignment is developed to correct slight differences between repetitions of the same gesture. The robustness of this biometric technique has been studied within 2 different tests analyzing a database of 100 users with real falsifications. Equal Error Rates of 2.01 and 4.82% have been obtained in a zero-effort and an active impostor attack, respectively. A permanence evaluation is also presented from the analysis of the repetition of the gestures of 25 users in 10 sessions over a month. Furthermore, two different gesture databases have been developed: one made up of 100 genuine identifying 3-D hand gestures and 3 impostors trying to falsify each of them and another with 25 volunteers repeating their identifying 3- D hand gesture in 10 sessions over a month. These databases are the most extensive in published studies, to the best of our knowledge.

Multiprotocol Android Application for Smart Control and Monitoring in Buildings

This paper presents a multiprotocol mobile application for building automation which supports and enables the integration of the most representative control technologies such as KNX, LonWorks and X-10. The application includes a real-time monitoring service. Finally, advanced control functionalities based on gestures recognition and predefined scenes have been implemented. This application has been developed and tested in the Energy Efficiency Research Facility located at CeDInt-UPM, where electrical loads, blinds and HVAC and lighting systems can be controlled.

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.

Herramientas de programación multimedia en IOS y Android

En este proyecto se realiza un estudio sobre herramientas que facilitan la creación y distribución de aplicaciones en distintas plataformas móviles, con el fin de poder seleccionar la herramienta más apropiada en función del proyecto a desarrollar. Previo al estudio de las herramientas para el desarrollo en plataformas múltiples se realiza un estudio de las herramientas y metodologías que facilitan los propietarios de los entornos IOS y Android. Este estudio previo permitirá al lector conocer en más detalle las particularidades de cada uno de estos dos entornos, así como las pautas y buenas prácticas a seguir en el desarrollo de aplicaciones para dispositivos móviles. Una vez finalizado el estudio, el lector sabrá escoger una herramienta de desarrollo adaptada a cada proyecto en función de su objeto, los recursos disponibles y las habilidades de los miembros del equipo de desarrollo. Adicionalmente al estudio, y como ejemplo de aplicación, en el proyecto se realiza un caso práctico de selección de herramienta y aplicación de la herramienta seleccionada a un proyecto de desarrollo concreto. El caso práctico consiste en la creación de un entorno que permite generar aplicaciones para la visualización de apuntes. Las aplicaciones permitirán ver contenidos de tipo multimedia como ficheros de texto, sonidos, imágenes, vídeos y enlaces a contenidos externos. Además estas aplicaciones se generarán sin que el autor de las mismas tenga que modificar alguna de las líneas del código. Para ello, se han definido una serie de ficheros de configuración en los que el autor de la aplicación deberá indicar los contenidos a mostrar y su ubicación. Se han seleccionado recursos de tipo “código abierto” para el desarrollo del caso práctico, con el fin de evitar los costes asociados a las posibles licencias. El equipo de desarrollo del caso práctico estará formado únicamente por el autor de este proyecto de fin de grado, lo que hace del caso de estudio un desarrollo sencillo, de manera que su futuro mantenimiento y escalabilidad no deberían verse afectados por la necesidad de contar con equipos de desarrolladores con conocimientos específicos o complejos. ABSTRACT. This document contains a study of tools that ease the creation and the distribution of the applications through different mobile platforms. The objective o this document is to allow the selection of the most appropriate tool, depending on the development objectives. Previous to this study about the tools for developing on multiple platforms, a study of IOS and Android tools and their methodologies is included on this document. This previous analysis will allow the reader to know in more detail the peculiarities of each of these environments, together with theirs requirements and the best practices of the applications development for mobile devices. By the end of this document the reader would be able to choose the adequate development tool for a project depending of its objective, its available resources and the developers team’s capabilities. Beside this study and as example of case study this final project includes a practical case of tool selection and its application to a specific development. The case study consists in the creation of an environment that allows generating applications to visualise notes. These applications will allow seeing contents of multimedia type such as: text files, sounds, images, videos, and links to external content. Furthermore these applications will be generated without their author having to modify any line of code, because a group of configuration files will be defined for such purpose. The author of the application only has to update this configuration with the content to show by the application and its location. The selected resources for the case study were of the type “open source” in order to avoid the cost associated to the potential licenses. The developers’ team for this case study has only one member, the author of this final project document and practical case developer. As a result the case study is a very simple development in a way that the future potential maintenance and scalability should not depend on the necessity of a highly qualified developers’ teams with a very specific knowledge on mobile platforms development.