Análise de regiões em cenários agrícolas utilizando um sistema de visão catadióptrico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudo das propriedades ópticas de pós cerâmicos à base de Zn3Ga2Ge2O10: X% Cr3+ (X = 0 ; 0,5 ; 0,75 ; 1,0)

Ceramic powders based on Zn3Ga2Ge2O10: Cr3+ X% (X = 0.0; 0.5; 0.75; 1.0) were synthesized by solid-state reaction method. The gallium-zinc germanate doped with chromium presents an interesting property of phosphorescence, that means, it is capable of emitting light when excited by a source of radiation, and such emission remains for some time after stopping the source. For this reason, these materials can be widely applied in night-vision surveillance, (through the use of solar energy, for example), electronic devices screen, emergency routes signals, control panels indicators in dark environments, etc. In this job were considered different amounts of dopant in order to perform a comparison of structural and photoluminescent properties. For that, some analyses were performed on samples, such as XRD, FT-Raman, SEM, UV-vis and photoluminescence measurements (PL). Such analysis allowed to infer that the presence of chromium results in no phase transformation, so that the four compositions have the same set of phases: cubic, rhombohedral and hexagonal. Although the structure was not changed, chromium influences other properties / characteristics of these materials. Examples are: increase of band-gap, decrease of average particle size, small changes in binding energy checked by Raman and especially the increase of photoluminescent property. The chromium ions have great ease in replacing gallium ions in octahedral sites, resulting in emission of light with a wavelength of about 700 nm (infrared region), which is justified by the spin-forbidden 2E 4A2 transition. In other words, chromium is a favorable luminescent center, acting as a trap in the crystal structure, since it imprisons the excitation energy easily and releases it gradually, allowing the phosphorescence. It was observed that the composition ... (Complete abastract click electronic access below)

Estudo das propriedades ópticas de pós cerâmicos à base de Zn3Ga2Ge2O10: X% Cr3+ (X = 0 ; 0,5 ; 0,75 ; 1,0)

Ceramic powders based on Zn3Ga2Ge2O10: Cr3+ X% (X = 0.0; 0.5; 0.75; 1.0) were synthesized by solid-state reaction method. The gallium-zinc germanate doped with chromium presents an interesting property of phosphorescence, that means, it is capable of emitting light when excited by a source of radiation, and such emission remains for some time after stopping the source. For this reason, these materials can be widely applied in night-vision surveillance, (through the use of solar energy, for example), electronic devices screen, emergency routes signals, control panels indicators in dark environments, etc. In this job were considered different amounts of dopant in order to perform a comparison of structural and photoluminescent properties. For that, some analyses were performed on samples, such as XRD, FT-Raman, SEM, UV-vis and photoluminescence measurements (PL). Such analysis allowed to infer that the presence of chromium results in no phase transformation, so that the four compositions have the same set of phases: cubic, rhombohedral and hexagonal. Although the structure was not changed, chromium influences other properties / characteristics of these materials. Examples are: increase of band-gap, decrease of average particle size, small changes in binding energy checked by Raman and especially the increase of photoluminescent property. The chromium ions have great ease in replacing gallium ions in octahedral sites, resulting in emission of light with a wavelength of about 700 nm (infrared region), which is justified by the spin-forbidden 2E 4A2 transition. In other words, chromium is a favorable luminescent center, acting as a trap in the crystal structure, since it imprisons the excitation energy easily and releases it gradually, allowing the phosphorescence. It was observed that the composition ... (Complete abastract click electronic access below)

Expanding the horizontal capabilities of CRT monitors using artificial inter-pixel steps for neuroscience experiments

This article describes the development of a visual stimulus generator to be used in neuroscience experiments with invertebrates such as flies. The experiment consists in the visualization of a fixed image that is displaced horizontally according to the stimulus data. The system is capable of displaying 640 x 480 pixels with 256 intensity levels at 200 frames per second (FPS) on conventional raster monitors. To double the possible horizontal positioning possibilities from 640 to 1280, a novel technique is presented introducing artificial inter-pixel steps. The implementation consists in using two video frame buffers containing each a distinct view of the desired image pattern. This implementation generates a visual effect capable of doubling the horizontal positioning capabilities of the visual stimulus generator allowing more precise and movements more contiguous. (C) 2011 Elsevier Inc. All rights reserved.

Fish quality assessment through the application of chemico-physical, sensory and microbiological analyses

The quality of fish products is indispensably linked to the freshness of the raw material modulated by appropriate manipulation and storage conditions, specially the storage temperature after catch. The purpose of the research presented in this thesis, which was largely conducted in the context of a research project funded by Italian Ministry of Agricultural, Food and Forestry Policies (MIPAAF), concerned the evaluation of the freshness of farmed and wild fish species, in relation to different storage conditions, under ice (0°C) or at refrigeration temperature (4°C). Several specimens of different species, bogue (Boops boops), red mullet (Mullus barbatus), sea bream (Sparus aurata) and sea bass (Dicentrarchus labrax), during storage, under the different temperature conditions adopted, have been examined. The assessed control parameters were physical (texture, through the use of a dynamometer; visual quality using a computer vision system (CVS)), chemical (through footprint metabolomics 1H-NMR) and sensory (Quality Index Method (QIM). Microbiological determinations were also carried out on the species of hake (Merluccius merluccius). In general obtained results confirmed that the temperature of manipulation/conservation is a key factor in maintaining fish freshness. NMR spectroscopy showed to be able to quantify and evaluate the kinetics for unselected compounds during fish degradation, even a posteriori. This can be suitable for the development of new parameters related to quality and freshness. The development of physical methods, particularly the image analysis performed by computer vision system (CVS), for the evaluation of fish degradation, is very promising. Among CVS parameters, skin colour, presence and distribution of gill mucus, and eye shape modification evidenced a high sensibility for the estimation of fish quality loss, as a function of the adopted storage conditions. Particularly the eye concavity index detected on fish eye showed a high positive correlation with total QIM score.

Dressurexperimente zur Unterscheidungsfähigkeit zwischen weißem Licht und Spektralfarben beim Goldfisch

Der Goldfisch besitzt, im Gegensatz zum Menschen, ein tetrachromatisches Farbensehsystem, das außerordentlich gut untersucht ist. Die Farben gleicher Helligkeit lassen sich hier in einem dreidimensionalen Tetraeder darstellen. Ziel der vorliegenden Arbeit war es herauszufinden, wie gut der Goldfisch Farben, die dem Menschen ungesättigt erscheinen und im Inneren des Farbtetraeders liegen, unterscheiden kann. Des Weiteren stellte sich die Frage, ob sowohl „Weiß“ (ohne UV) als auch Xenonweiß (mit UV) vom Fisch als „unbunt“ oder „neutral“ wahrgenommenen werden. Um all dies untersuchen zu können, musste ein komplexer Versuchsaufbau entwickelt werden, mit dem den Fischen monochromatische und mit Weiß gemischte Lichter gleicher Helligkeit, sowie Xenonweiß gezeigt werden konnte. Die Fische erlernten durch operante Konditionierung einen Dressurstimulus (monochromatisches Licht der Wellenlängen 660 nm, 599 nm, 540 nm, 498 nm oder 450 nm) von einem Vergleichsstimulus (Projektorweiß) zu unterscheiden. Im Folgenden wurde dem Vergleichstimulus in 10er-Schritten immer mehr der jeweiligen Dressurspektralfarbe beigemischt, bis die Goldfische keine sichere Wahl für den Dressurstimulus mehr treffen konnten. Die Unterscheidungsleistung der Goldfische wurde mit zunehmender Beimischung von Dressurspektralfarbe zum Projektorweiß immer geringer und es kristallisierte sich ein Bereich in der Grundfläche des Tetraeders heraus, in dem die Goldfische keine Unterscheidung mehr treffen konnten. Um diesen Bereich näher zu charakterisieren, bekamen die Goldfische Mischlichter, bei denen gerade keine Unterscheidung mehr zum Projektorweiß möglich war, in Transfertests gezeigt. Da die Goldfische diese Mischlichter nicht voneinander unterscheiden konnten, läßt sich schließen, dass es einen größeren Bereich gibt, der, ebenso wie Weiß (ohne UV) für den Goldfisch „neutral“ erscheint. Wenn nun Weiß (ohne UV) für den Goldfisch „neutral“ erscheint, sollte es dem Xenonweiß ähnlich sein. Die Versuche zeigten allerdings, dass die Goldfische die Farben Weiß (ohne UV) und Xenonweiß als verschieden wahrnehmen. Betrachtet man die Sättigung für die Spektralfarben, so zeigte sich, dass die Spektralfarbe 540 nm für den Goldfisch am gesättigsten, die Spektralfarbe 660 nm am ungesättigsten erscheint.

Classificazione di oggetti in immagini attraverso il modello Bag of Visual Words

Generic object recognition is an important function of the human visual system and everybody finds it highly useful in their everyday life. For an artificial vision system it is a really hard, complex and challenging task because instances of the same object category can generate very different images, depending of different variables such as illumination conditions, the pose of an object, the viewpoint of the camera, partial occlusions, and unrelated background clutter. The purpose of this thesis is to develop a system that is able to classify objects in 2D images based on the context, and identify to which category the object belongs to. Given an image, the system can classify it and decide the correct categorie of the object. Furthermore the objective of this thesis is also to test the performance and the precision of different supervised Machine Learning algorithms in this specific task of object image categorization. Through different experiments the implemented application reveals good categorization performances despite the difficulty of the problem. However this project is open to future improvement; it is possible to implement new algorithms that has not been invented yet or using other techniques to extract features to make the system more reliable. This application can be installed inside an embedded system and after trained (performed outside the system), so it can become able to classify objects in a real-time. The information given from a 3D stereocamera, developed inside the department of Computer Engineering of the University of Bologna, can be used to improve the accuracy of the classification task. The idea is to segment a single object in a scene using the depth given from a stereocamera and in this way make the classification more accurate.

Real-time image processing for crop/weed discrimination in maize fields

This paper presents a computer vision system that successfully discriminates between weed patches and crop rows under uncontrolled lighting in real-time. The system consists of two independent subsystems, a fast image processing delivering results in real-time (Fast Image Processing, FIP), and a slower and more accurate processing (Robust Crop Row Detection, RCRD) that is used to correct the first subsystem's mistakes. This combination produces a system that achieves very good results under a wide variety of conditions. Tested on several maize videos taken of different fields and during different years, the system successfully detects an average of 95% of weeds and 80% of crops under different illumination, soil humidity and weed/crop growth conditions. Moreover, the system has been shown to produce acceptable results even under very difficult conditions, such as in the presence of dramatic sowing errors or abrupt camera movements. The computer vision system has been developed for integration into a treatment system because the ideal setup for any weed sprayer system would include a tool that could provide information on the weeds and crops present at each point in real-time, while the tractor mounting the spraying bar is moving

Seed image analysis and taxonomy of Diplotaxis DC. (Brassicaceae, Brassiceae)

The genus Diplotaxis, comprising 32 or 34 species, plus several additional infraspecific taxa, displays a considerable degree of heterogeneity in the morphology, molecular markers, chromosome numbers and geographical amplitude of the species. The taxonomic relationships within the genus Diplotaxis were investigated by phenetic characterisation of germplasm belonging to 27 taxa of the genus, because there is an increasing interest in Diplotaxis, since some of its species (D. tenuifolia, D. muralis) are gathered or cultivated for human consumption, whereas others are frequent arable weeds (D. erucoides) in many European vineyards. Using a computer-aided vision system, 33 morpho-colorimetric features of seeds were electronically measured. The data were used to implement a statistical classifier, which is able to discriminate the taxa within the genus Diplotaxis, in order to compare the resulting species grouping with the current infrageneric systematics of this genus. Despite the high heterogeneity of the samples, due to the great intra-population variability, the stepwise Linear Discriminant Analysis method, applied to distinguish the groups, was able to reach over 80% correct identification. The results obtained allowed us to confirm the current taxonomic position of most taxa and suggested the taxonomic position of others for reconsideration.

Automatic detection of crop rows in maize fields with high weeds pressure

This paper proposes a new method, oriented to crop row detection in images from maize fields with high weed pressure. The vision system is designed to be installed onboard a mobile agricultural vehicle, i.e. submitted to gyros, vibrations and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of three main processes: image segmentation, double thresholding, based on the Otsu’s method, and crop row detection. Image segmentation is based on the application of a vegetation index, the double thresholding achieves the separation between weeds and crops and the crop row detection applies least squares linear regression for line adjustment. Crop and weed separation becomes effective and the crop row detection can be favorably compared against the classical approach based on the Hough transform. Both gain effectiveness and accuracy thanks to the double thresholding that makes the main finding of the paper.

Crop row detection in maize fields inspired on the human visual perception

This paper proposes a new method, oriented to image real-time processing, for identifying crop rows in maize fields in the images. The vision system is designed to be installed onboard a mobile agricultural vehicle, that is, submitted to gyros, vibrations, and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of two main processes: image segmentation and crop row detection. The first one applies a threshold to separate green plants or pixels (crops and weeds) from the rest (soil, stones, and others). It is based on a fuzzy clustering process, which allows obtaining the threshold to be applied during the normal operation process. The crop row detection applies a method based on image perspective projection that searches for maximum accumulation of segmented green pixels along straight alignments. They determine the expected crop lines in the images. The method is robust enough to work under the above-mentioned undesired effects. It is favorably compared against the well-tested Hough transformation for line detection.

A novel methodology for planning reliable wireless sensor networks

Wireless sensor networks (WSNs) have shown their potentials in various applications, which bring a lot of benefits to users from both research and industrial areas. For many setups, it is envisioned thatWSNs will consist of tens to hundreds of nodes that operate on small batteries. However due to the diversity of the deployed environments and resource constraints on radio communication, sensing ability and energy supply, it is a very challenging issue to plan optimized WSN topology and predict its performance before real deployment. During the network planning phase, the connectivity, coverage, cost, network longevity and service quality should all be considered. Therefore it requires designers coping with comprehensive and interdisciplinary knowledge, including networking, radio engineering, embedded system and so on, in order to efficiently construct a reliable WSN for any specific types of environment. Nowadays there is still a lack of the analysis and experiences to guide WSN designers to efficiently construct WSN topology successfully without many trials. Therefore, simulation is a feasible approach to the quantitative analysis of the performance of wireless sensor networks. However the existing planning algorithms and tools, to some extent, have serious limitations to practically design reliable WSN topology: Only a few of them tackle the 3D deployment issue, and an overwhelming number of works are proposed to place devices in 2D scheme. Without considering the full dimension, the impacts of environment to the performance of WSN are not completely studied, thus the values of evaluated metrics such as connectivity and sensing coverage are not sufficiently accurate to make proper decision. Even fewer planning methods model the sensing coverage and radio propagation by considering the realistic scenario where obstacles exist. Radio signals propagate with multi-path phenomenon in the real world, in which direct paths, reflected paths and diffracted paths contribute to the received signal strength. Besides, obstacles between the path of sensor and objects might block the sensing signals, thus create coverage hole in the application. None of the existing planning algorithms model the network longevity and packet delivery capability properly and practically. They often employ unilateral and unrealistic formulations. The optimization targets are often one-sided in the current works. Without comprehensive evaluation on the important metrics, the performance of planned WSNs can not be reliable and entirely optimized. Modeling of environment is usually time consuming and the cost is very high, while none of the current works figure out any method to model the 3D deployment environment efficiently and accurately. Therefore many researchers are trapped by this issue, and their algorithms can only be evaluated in the same scenario, without the possibility to test the robustness and feasibility for implementations in different environments. In this thesis, we propose a novel planning methodology and an intelligent WSN planning tool to assist WSN designers efficiently planning reliable WSNs. First of all, a new method is proposed to efficiently and automatically model the 3D indoor and outdoor environments. To the best of our knowledge, this is the first time that the advantages of image understanding algorithm are applied to automatically reconstruct 3D outdoor and indoor scenarios for signal propagation and network planning purpose. The experimental results indicate that the proposed methodology is able to accurately recognize different objects from the satellite images of the outdoor target regions and from the scanned floor plan of indoor area. Its mechanism offers users a flexibility to reconstruct different types of environment without any human interaction. Thereby it significantly reduces human efforts, cost and time spent on reconstructing a 3D geographic database and allows WSN designers concentrating on the planning issues. Secondly, an efficient ray-tracing engine is developed to accurately and practically model the radio propagation and sensing signal on the constructed 3D map. The engine contributes on efficiency and accuracy to the estimated results. By using image processing concepts, including the kd-tree space division algorithm and modified polar sweep algorithm, the rays are traced efficiently without detecting all the primitives in the scene. The radio propagation model iv is proposed, which emphasizes not only the materials of obstacles but also their locations along the signal path. The sensing signal of sensor nodes, which is sensitive to the obstacles, is benefit from the ray-tracing algorithm via obstacle detection. The performance of this modelling method is robust and accurate compared with conventional methods, and experimental results imply that this methodology is suitable for both outdoor urban scenes and indoor environments. Moreover, it can be applied to either GSM communication or ZigBee protocol by varying frequency parameter of the radio propagation model. Thirdly, WSN planning method is proposed to tackle the above mentioned challenges and efficiently deploy reliable WSNs. More metrics (connectivity, coverage, cost, lifetime, packet latency and packet drop rate) are modeled more practically compared with other works. Especially 3D ray tracing method is used to model the radio link and sensing signal which are sensitive to the obstruction of obstacles; network routing is constructed by using AODV protocol; the network longevity, packet delay and packet drop rate are obtained via simulating practical events in WSNet simulator, which to the best of our knowledge, is the first time that network simulator is involved in a planning algorithm. Moreover, a multi-objective optimization algorithm is developed to cater for the characteristics of WSNs. The capability of providing multiple optimized solutions simultaneously allows users making their own decisions accordingly, and the results are more comprehensively optimized compared with other state-of-the-art algorithms. iMOST is developed by integrating the introduced algorithms, to assist WSN designers efficiently planning reliable WSNs for different configurations. The abbreviated name iMOST stands for an Intelligent Multi-objective Optimization Sensor network planning Tool. iMOST contributes on: (1) Convenient operation with a user-friendly vision system; (2) Efficient and automatic 3D database reconstruction and fast 3D objects design for both indoor and outdoor environments; (3) It provides multiple multi-objective optimized 3D deployment solutions and allows users to configure the network properties, hence it can adapt to various WSN applications; (4) Deployment solutions in the 3D space and the corresponding evaluated performance are visually presented to users; and (5) The Node Placement Module of iMOST is available online as well as the source code of the other two rebuilt heuristics. Therefore WSN designers will be benefit from v this tool on efficiently constructing environment database, practically and efficiently planning reliable WSNs for both outdoor and indoor applications. With the open source codes, they are also able to compare their developed algorithms with ours to contribute to this academic field. Finally, solid real results are obtained for both indoor and outdoor WSN planning. Deployments have been realized for both indoor and outdoor environments based on the provided planning solutions. The measured results coincide well with the estimated results. The proposed planning algorithm is adaptable according to the WSN designer’s desirability and configuration, and it offers flexibility to plan small and large scale, indoor and outdoor 3D deployments. The thesis is organized in 7 chapters. In Chapter 1, WSN applications and motivations of this work are introduced, the state-of-the-art planning algorithms and tools are reviewed, challenges are stated out and the proposed methodology is briefly introduced. In Chapter 2, the proposed 3D environment reconstruction methodology is introduced and its performance is evaluated for both outdoor and indoor environment. The developed ray-tracing engine and proposed radio propagation modelling method are described in details in Chapter 3, their performances are evaluated in terms of computation efficiency and accuracy. Chapter 4 presents the modelling of important metrics of WSNs and the proposed multi-objective optimization planning algorithm, the performance is compared with the other state-of-the-art planning algorithms. The intelligent WSN planning tool iMOST is described in Chapter 5. RealWSN deployments are prosecuted based on the planned solutions for both indoor and outdoor scenarios, important data are measured and results are analysed in Chapter 6. Chapter 7 concludes the thesis and discusses about future works. vi Resumen en Castellano Las redes de sensores inalámbricas (en inglés Wireless Sensor Networks, WSNs) han demostrado su potencial en diversas aplicaciones que aportan una gran cantidad de beneficios para el campo de la investigación y de la industria. Para muchas configuraciones se prevé que las WSNs consistirán en decenas o cientos de nodos que funcionarán con baterías pequeñas. Sin embargo, debido a la diversidad de los ambientes para desplegar las redes y a las limitaciones de recursos en materia de comunicación de radio, capacidad de detección y suministro de energía, la planificación de la topología de la red y la predicción de su rendimiento es un tema muy difícil de tratar antes de la implementación real. Durante la fase de planificación del despliegue de la red se deben considerar aspectos como la conectividad, la cobertura, el coste, la longevidad de la red y la calidad del servicio. Por lo tanto, requiere de diseñadores con un amplio e interdisciplinario nivel de conocimiento que incluye la creación de redes, la ingeniería de radio y los sistemas embebidos entre otros, con el fin de construir de manera eficiente una WSN confiable para cualquier tipo de entorno. Hoy en día todavía hay una falta de análisis y experiencias que orienten a los diseñadores de WSN para construir las topologías WSN de manera eficiente sin realizar muchas pruebas. Por lo tanto, la simulación es un enfoque viable para el análisis cuantitativo del rendimiento de las redes de sensores inalámbricos. Sin embargo, los algoritmos y herramientas de planificación existentes tienen, en cierta medida, serias limitaciones para diseñar en la práctica una topología fiable de WSN: Sólo unos pocos abordan la cuestión del despliegue 3D mientras que existe una gran cantidad de trabajos que colocan los dispositivos en 2D. Si no se analiza la dimensión completa (3D), los efectos del entorno en el desempeño de WSN no se estudian por completo, por lo que los valores de los parámetros evaluados, como la conectividad y la cobertura de detección, no son lo suficientemente precisos para tomar la decisión correcta. Aún en menor medida los métodos de planificación modelan la cobertura de los sensores y la propagación de la señal de radio teniendo en cuenta un escenario realista donde existan obstáculos. Las señales de radio en el mundo real siguen una propagación multicamino, en la que los caminos directos, los caminos reflejados y los caminos difractados contribuyen a la intensidad de la señal recibida. Además, los obstáculos entre el recorrido del sensor y los objetos pueden bloquear las señales de detección y por lo tanto crear áreas sin cobertura en la aplicación. Ninguno de los algoritmos de planificación existentes modelan el tiempo de vida de la red y la capacidad de entrega de paquetes correctamente y prácticamente. A menudo se emplean formulaciones unilaterales y poco realistas. Los objetivos de optimización son a menudo tratados unilateralmente en los trabajos actuales. Sin una evaluación exhaustiva de los parámetros importantes, el rendimiento previsto de las redes inalámbricas de sensores no puede ser fiable y totalmente optimizado. Por lo general, el modelado del entorno conlleva mucho tiempo y tiene un coste muy alto, pero ninguno de los trabajos actuales propone algún método para modelar el entorno de despliegue 3D con eficiencia y precisión. Por lo tanto, muchos investigadores están limitados por este problema y sus algoritmos sólo se pueden evaluar en el mismo escenario, sin la posibilidad de probar la solidez y viabilidad para las implementaciones en diferentes entornos. En esta tesis, se propone una nueva metodología de planificación así como una herramienta inteligente de planificación de redes de sensores inalámbricas para ayudar a los diseñadores a planificar WSNs fiables de una manera eficiente. En primer lugar, se propone un nuevo método para modelar demanera eficiente y automática los ambientes interiores y exteriores en 3D. Según nuestros conocimientos hasta la fecha, esta es la primera vez que las ventajas del algoritmo de _image understanding_se aplican para reconstruir automáticamente los escenarios exteriores e interiores en 3D para analizar la propagación de la señal y viii la planificación de la red. Los resultados experimentales indican que la metodología propuesta es capaz de reconocer con precisión los diferentes objetos presentes en las imágenes satelitales de las regiones objetivo en el exterior y de la planta escaneada en el interior. Su mecanismo ofrece a los usuarios la flexibilidad para reconstruir los diferentes tipos de entornos sin ninguna interacción humana. De este modo se reduce considerablemente el esfuerzo humano, el coste y el tiempo invertido en la reconstrucción de una base de datos geográfica con información 3D, permitiendo así que los diseñadores se concentren en los temas de planificación. En segundo lugar, se ha desarrollado un motor de trazado de rayos (en inglés ray tracing) eficiente para modelar con precisión la propagación de la señal de radio y la señal de los sensores en el mapa 3D construido. El motor contribuye a la eficiencia y la precisión de los resultados estimados. Mediante el uso de los conceptos de procesamiento de imágenes, incluyendo el algoritmo del árbol kd para la división del espacio y el algoritmo _polar sweep_modificado, los rayos se trazan de manera eficiente sin la detección de todas las primitivas en la escena. El modelo de propagación de radio que se propone no sólo considera los materiales de los obstáculos, sino también su ubicación a lo largo de la ruta de señal. La señal de los sensores de los nodos, que es sensible a los obstáculos, se ve beneficiada por la detección de objetos llevada a cabo por el algoritmo de trazado de rayos. El rendimiento de este método de modelado es robusto y preciso en comparación con los métodos convencionales, y los resultados experimentales indican que esta metodología es adecuada tanto para escenas urbanas al aire libre como para ambientes interiores. Por otra parte, se puede aplicar a cualquier comunicación GSM o protocolo ZigBee mediante la variación de la frecuencia del modelo de propagación de radio. En tercer lugar, se propone un método de planificación de WSNs para hacer frente a los desafíos mencionados anteriormente y desplegar redes de sensores fiables de manera eficiente. Se modelan más parámetros (conectividad, cobertura, coste, tiempo de vida, la latencia de paquetes y tasa de caída de paquetes) en comparación con otros trabajos. Especialmente el método de trazado de rayos 3D se utiliza para modelar el enlace de radio y señal de los sensores que son sensibles a la obstrucción de obstáculos; el enrutamiento de la red se construye utilizando el protocolo AODV; la longevidad de la red, retardo de paquetes ix y tasa de abandono de paquetes se obtienen a través de la simulación de eventos prácticos en el simulador WSNet, y según nuestros conocimientos hasta la fecha, es la primera vez que simulador de red está implicado en un algoritmo de planificación. Por otra parte, se ha desarrollado un algoritmo de optimización multi-objetivo para satisfacer las características de las redes inalámbricas de sensores. La capacidad de proporcionar múltiples soluciones optimizadas de forma simultánea permite a los usuarios tomar sus propias decisiones en consecuencia, obteniendo mejores resultados en comparación con otros algoritmos del estado del arte. iMOST se desarrolla mediante la integración de los algoritmos presentados, para ayudar de forma eficiente a los diseñadores en la planificación de WSNs fiables para diferentes configuraciones. El nombre abreviado iMOST (Intelligent Multi-objective Optimization Sensor network planning Tool) representa una herramienta inteligente de planificación de redes de sensores con optimización multi-objetivo. iMOST contribuye en: (1) Operación conveniente con una interfaz de fácil uso, (2) Reconstrucción eficiente y automática de una base de datos con información 3D y diseño rápido de objetos 3D para ambientes interiores y exteriores, (3) Proporciona varias soluciones de despliegue optimizadas para los multi-objetivo en 3D y permite a los usuarios configurar las propiedades de red, por lo que puede adaptarse a diversas aplicaciones de WSN, (4) las soluciones de implementación en el espacio 3D y el correspondiente rendimiento evaluado se presentan visualmente a los usuarios, y (5) El _Node Placement Module_de iMOST está disponible en línea, así como el código fuente de las otras dos heurísticas de planificación. Por lo tanto los diseñadores WSN se beneficiarán de esta herramienta para la construcción eficiente de la base de datos con información del entorno, la planificación práctica y eficiente de WSNs fiables tanto para aplicaciones interiores y exteriores. Con los códigos fuente abiertos, son capaces de comparar sus algoritmos desarrollados con los nuestros para contribuir a este campo académico. Por último, se obtienen resultados reales sólidos tanto para la planificación de WSN en interiores y exteriores. Los despliegues se han realizado tanto para ambientes de interior y como para ambientes de exterior utilizando las soluciones de planificación propuestas. Los resultados medidos coinciden en gran medida con los resultados estimados. El algoritmo de planificación x propuesto se adapta convenientemente al deiseño de redes de sensores inalámbricas, y ofrece flexibilidad para planificar los despliegues 3D a pequeña y gran escala tanto en interiores como en exteriores. La tesis se estructura en 7 capítulos. En el Capítulo 1, se presentan las aplicaciones de WSN y motivaciones de este trabajo, se revisan los algoritmos y herramientas de planificación del estado del arte, se presentan los retos y se describe brevemente la metodología propuesta. En el Capítulo 2, se presenta la metodología de reconstrucción de entornos 3D propuesta y su rendimiento es evaluado tanto para espacios exteriores como para espacios interiores. El motor de trazado de rayos desarrollado y el método de modelado de propagación de radio propuesto se describen en detalle en el Capítulo 3, evaluándose en términos de eficiencia computacional y precisión. En el Capítulo 4 se presenta el modelado de los parámetros importantes de las WSNs y el algoritmo de planificación de optimización multi-objetivo propuesto, el rendimiento se compara con los otros algoritmos de planificación descritos en el estado del arte. La herramienta inteligente de planificación de redes de sensores inalámbricas, iMOST, se describe en el Capítulo 5. En el Capítulo 6 se llevan a cabo despliegues reales de acuerdo a las soluciones previstas para los escenarios interiores y exteriores, se miden los datos importantes y se analizan los resultados. En el Capítulo 7 se concluye la tesis y se discute acerca de los trabajos futuros.

Integration of multisensor hybrid reasoners to support personal autonomy in the smart home.

The deployment of the Ambient Intelligence (AmI) paradigm requires designing and integrating user-centered smart environments to assist people in their daily life activities. This research paper details an integration and validation of multiple heterogeneous sensors with hybrid reasoners that support decision making in order to monitor personal and environmental data at a smart home in a private way. The results innovate on knowledge-based platforms, distributed sensors, connected objects, accessibility and authentication methods to promote independent living for elderly people. TALISMAN+, the AmI framework deployed, integrates four subsystems in the smart home: (i) a mobile biomedical telemonitoring platform to provide elderly patients with continuous disease management; (ii) an integration middleware that allows context capture from heterogeneous sensors to program environment¿s reaction; (iii) a vision system for intelligent monitoring of daily activities in the home; and (iv) an ontologies-based integrated reasoning platform to trigger local actions and manage private information in the smart home. The framework was integrated in two real running environments, the UPM Accessible Digital Home and MetalTIC house, and successfully validated by five experts in home care, elderly people and personal autonomy.

Toward Visual Autonomous Ship Board Landing of a VTOL UAV

In this paper we tackle the problem of landing a helicopter autonomously on a ship deck, using as the main sensor, an on-board colour camera. To create a test-bed, we first adequately simulate the movement of a ship landing platform on the Sea, for different Sea States, for different ships, randomly and realistically enough. We use a commercial parallel robot to get this movement. Once we had this, we developed an accurate and robust computer vision system to measure the pose of the helipad with respect to the on-board camera. To deal with the noise and the possible fails of the computer vision, a state estimator was created. With all of this, we are now able to develop and test a controller that closes the loop and finish the autonomous landing task.

Augmented and Virtual Reality techniques for footwear

The use of 3D imaging techniques has been early adopted in the footwear industry. In particular, 3D imaging could be used to aid commerce and improve the quality and sales of shoes. Footwear customization is an added value aimed not only to improve product quality, but also consumer comfort. Moreover, customisation implies a new business model that avoids the competition of mass production coming from new manufacturers settled mainly in Asian countries. However, footwear customisation implies a significant effort at different levels. In manufacturing, rapid and virtual prototyping is required; indeed the prototype is intended to become the final product. The whole design procedure must be validated using exclusively virtual techniques to ensure the feasibility of this process, since physical prototypes should be avoided. With regard to commerce, it would be desirable for the consumer to choose any model of shoes from a large 3D database and be able to try them on looking at a magic mirror. This would probably reduce costs and increase sales, since shops would not require storing every shoe model and the process of trying several models on would be easier and faster for the consumer. In this paper, new advances in 3D techniques coming from experience in cinema, TV and games are successfully applied to footwear. Firstly, the characteristics of a high-quality stereoscopic vision system for footwear are presented. Secondly, a system for the interaction with virtual footwear models based on 3D gloves is detailed. Finally, an augmented reality system (magic mirror) is presented, which is implemented with low-cost computational elements that allow a hypothetical customer to check in real time the goodness of a given virtual footwear model from an aesthetical point of view.