d-Ruta, un sistema móvil de información turística

d-Ruta is a new location based service designed for the visualization, planning, follow-up, interaction, maintenance and distribution of information about tourist routes and their associated points of interest, in the Vall de Ribes, in the Catalan Pyrenees. (...)

gvSIG Mini y Phone Cache

gvSIG Mini es una aplicación open-source de usuario final cliente móvil de Infraestructura de Datos Espaciales IDEs con licencia GNU/ GPL, diseñada para teléfonos móviles Java y Android que permite la visualización y navegación sobre cartografía digital estructurada en tiles procedente de servicios web OGC como WMS(-C) y de servicios como OpenStreetMap (OSM), Yahoo Maps, Maps Bing, así como el almacenamiento en caché para reducir al mínimo el ancho de banda. gvSIG Mini puede acceder a servicios geoespaciales como NameFinder, para la búsqueda de puntos de interés y YOURS (Yet Another OpenStreetMap Routing Service) para el cálculo de rutas y la renderización de la información vectorial el lado del cliente. Por otra parte, gvSIG Mini también ofrece servicio de localización GPS. La versión de gvSIG Mini para Android, posee algunas características adicionales como son el soporte de localización Android o el uso del lacelerómetro para centrado. Esta versión también hace uso de servicios como son la predicción del tiempo o TweetMe que permite compartir una localización utilizando el popular servicio social Twitter. gvSIG Mini es una aplicación que puede ser descargada y usada libremente, convirtiéndose en una plataforma para el desarrollo de nuevas soluciones y aplicaciones en el campo de Location Based Services (LBS). gvSIG Mini ha sido desarrollado por Prodevelop, S.L. No es un proyecto oficial de gvSIG, pero se une a la familia a través del catálogo de extensiones no oficiales de gvSIG. Phone Cache es una extensión que funciona sobre gvSIG 1.1.2 que permite generar una caché, para poder utilizar gvSIG Mini para Java en modo desconectado

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Two methods for voltage sag source location

This paper presents and compares two approaches to estimate the origin (upstream or downstream) of voltage sag registered in distribution substations. The first approach is based on the application of a single rule dealing with features extracted from the impedances during the fault whereas the second method exploit the variability of waveforms from an statistical point of view. Both approaches have been tested with voltage sags registered in distribution substations and advantages, drawbacks and comparative results are presented

Application for fault location in electrical power distribution systems

Fault location has been studied deeply for transmission lines due to its importance in power systems. Nowadays the problem of fault location on distribution systems is receiving special attention mainly because of the power quality regulations. In this context, this paper presents an application software developed in Matlabtrade that automatically calculates the location of a fault in a distribution power system, starting from voltages and currents measured at the line terminal and the model of the distribution power system data. The application is based on a N-ary tree structure, which is suitable to be used in this application due to the highly branched and the non- homogeneity nature of the distribution systems, and has been developed for single-phase, two-phase, two-phase-to-ground, and three-phase faults. The implemented application is tested by using fault data in a real electrical distribution power system

A hybrid approach of knowledge-based reasoning for structural assessment

La idea básica de detección de defectos basada en vibraciones en Monitorización de la Salud Estructural (SHM), es que el defecto altera las propiedades de rigidez, masa o disipación de energía de un sistema, el cual, altera la respuesta dinámica del mismo. Dentro del contexto de reconocimiento de patrones, esta tesis presenta una metodología híbrida de razonamiento para evaluar los defectos en las estructuras, combinando el uso de un modelo de la estructura y/o experimentos previos con el esquema de razonamiento basado en el conocimiento para evaluar si el defecto está presente, su gravedad y su localización. La metodología involucra algunos elementos relacionados con análisis de vibraciones, matemáticas (wavelets, control de procesos estadístico), análisis y procesamiento de señales y/o patrones (razonamiento basado en casos, redes auto-organizativas), estructuras inteligentes y detección de defectos. Las técnicas son validadas numérica y experimentalmente considerando corrosión, pérdida de masa, acumulación de masa e impactos. Las estructuras usadas durante este trabajo son: una estructura tipo cercha voladiza, una viga de aluminio, dos secciones de tubería y una parte del ala de un avión comercial.