Non invasive moisture measurement in agricultural fiel using a rolling spherical robot

Irrigation management in large crop fields is a very important practice. Since the farm management costs and the crop results are directly connected with the environmental moisture, water control optimization is a critical factor for agricultural practices, as well as for the planet sustainability. Usually, the crop humidity is measured through the water stress index (WSI), using imagery acquired from satellites or airplanes. Nevertheless, these tools have a significant cost, lack from availability, and dependability from the weather. Other alternative is to recover to ground tools, such as ground vehicles and even static base stations. However, they have an outstanding impact in the farming process, since they can damage the cultivation and require more human effort. As a possible solution to these issues, a rolling ground robot have been designed and developed, enabling non-invasive measurements within crop fields. This paper addresses the spherical robot system applied to intra-crop moisture measurements. Furthermore, some experiments were carried out in an early stage corn field in order to build a geo-referenced WSI map.

Time derivatives in air temperature and enthalpy as non-invasive welfare indicators during long distance animal transport in Spain and Portugal.

High temperatures and relative humidity can compromise animal welfare on the farm level, but less is known about those changes during long distance transport of domestic animals to slaughter. Although upper temperature limits have been established to transport pigs in Europe, few indices include relative or absolute humidity maxima or mention appropriate enthalpy ranges.

Non-destructive measurement techniques for taper equation development: a study case in the Spanish Northern Iberian Range

In recent years, the technology for measuring the diameter and height of standing trees has improved significantly. These enhancements allow estimation of the volume of standing trees using stem taper equations, which traditionally have been constructed with data from felled trees, in an accurate and economically feasible way. A nondestructive method was evaluated with data from 38 pines and was validated with data from another 38 pines, both in the Northern Iberian Range (Spain). The electronic dendrometer Criterion RD1000 (Laser Technology Inc.) and the laser hypsometer TruPulse (Laser Technology Inc.) were used due to their accuracy and interoperability. The methodology was valid (unbiased and precise) measuring from a distance similar to the height of the tree. In this distance, statistical criteria and plots based on the residuals showed no clear advantage in volume estimation with models fitted with data from destructive methods against models fitted with data from the proposed non-destructive technique. This methodology can be considered useful for individual volume estimation and for developing taper equations.

Non-invasive user monitoring in daily tasks for cognitive rehabilitation

El uso de técnicas para la monitorización del movimiento humano generalmente permite a los investigadores analizar la cinemática y especialmente las capacidades motoras en aquellas actividades de la vida cotidiana que persiguen un objetivo concreto como pueden ser la preparación de bebidas y comida, e incluso en tareas de aseo. Adicionalmente, la evaluación del movimiento y el comportamiento humanos en el campo de la rehabilitación cognitiva es esencial para profundizar en las dificultades que algunas personas encuentran en la ejecución de actividades diarias después de accidentes cerebro-vasculares. Estas dificultades están principalmente asociadas a la realización de pasos secuenciales y al reconocimiento del uso de herramientas y objetos. La interpretación de los datos sobre la actitud de este tipo de pacientes para reconocer y determinar el nivel de éxito en la ejecución de las acciones, y para ampliar el conocimiento en las enfermedades cerebrales, sus consecuencias y severidad, depende totalmente de los dispositivos usados para la captura de esos datos y de la calidad de los mismos. Más aún, existe una necesidad real de mejorar las técnicas actuales de rehabilitación cognitiva contribuyendo al diseño de sistemas automáticos para crear una especie de terapeuta virtual que asegure una vida más independiente de estos pacientes y reduzca la carga de trabajo de los terapeutas. Con este objetivo, el uso de sensores y dispositivos para obtener datos en tiempo real de la ejecución y estado de la tarea de rehabilitación es esencial para también contribuir al diseño y entrenamiento de futuros algoritmos que pudieran reconocer errores automáticamente para informar al paciente acerca de ellos mediante distintos tipos de pistas como pueden ser imágenes, mensajes auditivos o incluso videos. La tecnología y soluciones existentes en este campo no ofrecen una manera totalmente robusta y efectiva para obtener datos en tiempo real, por un lado, porque pueden influir en el movimiento del propio paciente en caso de las plataformas basadas en el uso de marcadores que necesitan sensores pegados en la piel; y por otro lado, debido a la complejidad o alto coste de implantación lo que hace difícil pensar en la idea de instalar un sistema en el hospital o incluso en la casa del paciente. Esta tesis presenta la investigación realizada en el campo de la monitorización del movimiento de pacientes para proporcionar un paso adelante en términos de detección, seguimiento y reconocimiento del comportamiento de manos, gestos y cara mediante una manera no invasiva la cual puede mejorar la técnicas actuales de rehabilitación cognitiva para la adquisición en tiempo real de datos sobre el comportamiento del paciente y la ejecución de la tarea. Para entender la importancia del marco de esta tesis, inicialmente se presenta un resumen de las principales enfermedades cognitivas y se introducen las consecuencias que tienen en la ejecución de tareas de la vida diaria. Más aún, se investiga sobre las metodologías actuales de rehabilitación cognitiva. Teniendo en cuenta que las manos son la principal parte del cuerpo para la ejecución de tareas manuales de la vida cotidiana, también se resumen las tecnologías existentes para la captura de movimiento de manos. Una de las principales contribuciones de esta tesis está relacionada con el diseño y evaluación de una solución no invasiva para detectar y seguir las manos durante la ejecución de tareas manuales de la vida cotidiana que a su vez involucran la manipulación de objetos. Esta solución la cual no necesita marcadores adicionales y está basada en una cámara de profundidad de bajo coste, es robusta, precisa y fácil de instalar. Otra contribución presentada se centra en el reconocimiento de gestos para detectar el agarre de objetos basado en un sensor infrarrojo de última generación, y también complementado con una cámara de profundidad. Esta nueva técnica, y también no invasiva, sincroniza ambos sensores para seguir objetos específicos además de reconocer eventos concretos relacionados con tareas de aseo. Más aún, se realiza una evaluación preliminar del reconocimiento de expresiones faciales para analizar si es adecuado para el reconocimiento del estado de ánimo durante la tarea. Por su parte, todos los componentes y algoritmos desarrollados son integrados en un prototipo simple para ser usado como plataforma de monitorización. Se realiza una evaluación técnica del funcionamiento de cada dispositivo para analizar si es adecuada para adquirir datos en tiempo real durante la ejecución de tareas cotidianas reales. Finalmente, se estudia la interacción con pacientes reales para obtener información del nivel de usabilidad del prototipo. Dicha información es esencial y útil para considerar una rehabilitación cognitiva basada en la idea de instalación del sistema en la propia casa del paciente al igual que en el hospital correspondiente. ABSTRACT The use of human motion monitoring techniques usually let researchers to analyse kinematics, especially in motor strategies for goal-oriented activities of daily living, such as the preparation of drinks and food, and even grooming tasks. Additionally, the evaluation of human movements and behaviour in the field of cognitive rehabilitation is essential to deep into the difficulties some people find in common activities after stroke. This difficulties are mainly associated with sequence actions and the recognition of tools usage. The interpretation of attitude data of this kind of patients in order to recognize and determine the level of success of the execution of actions, and to broaden the knowledge in brain diseases, consequences and severity, depends totally on the devices used for the capture of that data and the quality of it. Moreover, there is a real need of improving the current cognitive rehabilitation techniques by contributing to the design of automatic systems to create a kind of virtual therapist for the improvement of the independent life of these stroke patients and to reduce the workload of the occupational therapists currently in charge of them. For this purpose, the use of sensors and devices to obtain real time data of the execution and state of the rehabilitation task is essential to also contribute to the design and training of future smart algorithms which may recognise errors to automatically provide multimodal feedback through different types of cues such as still images, auditory messages or even videos. The technology and solutions currently adopted in the field don't offer a totally robust and effective way for obtaining real time data, on the one hand, because they may influence the patient's movement in case of marker-based platforms which need sensors attached to the skin; and on the other hand, because of the complexity or high cost of implementation, which make difficult the idea of installing a system at the hospital or even patient's home. This thesis presents the research done in the field of user monitoring to provide a step forward in terms of detection, tracking and recognition of hand movements, gestures and face via a non-invasive way which could improve current techniques for cognitive rehabilitation for real time data acquisition of patient's behaviour and execution of the task. In order to understand the importance of the scope of the thesis, initially, a summary of the main cognitive diseases that require for rehabilitation and an introduction of the consequences on the execution of daily tasks are presented. Moreover, research is done about the actual methodology to provide cognitive rehabilitation. Considering that the main body members involved in the completion of a handmade daily task are the hands, the current technologies for human hands movements capture are also highlighted. One of the main contributions of this thesis is related to the design and evaluation of a non-invasive approach to detect and track user's hands during the execution of handmade activities of daily living which involve the manipulation of objects. This approach does not need the inclusion of any additional markers. In addition, it is only based on a low-cost depth camera, it is robust, accurate and easy to install. Another contribution presented is focused on the hand gesture recognition for detecting object grasping based on a brand new infrared sensor, and also complemented with a depth camera. This new, and also non-invasive, solution which synchronizes both sensors to track specific tools as well as recognize specific events related to grooming is evaluated. Moreover, a preliminary assessment of the recognition of facial expressions is carried out to analyse if it is adequate for recognizing mood during the execution of task. Meanwhile, all the corresponding hardware and software developed are integrated in a simple prototype with the purpose of being used as a platform for monitoring the execution of the rehabilitation task. Technical evaluation of the performance of each device is carried out in order to analyze its suitability to acquire real time data during the execution of real daily tasks. Finally, a kind of healthcare evaluation is also presented to obtain feedback about the usability of the system proposed paying special attention to the interaction with real users and stroke patients. This feedback is quite useful to consider the idea of a home-based cognitive rehabilitation as well as a possible hospital installation of the prototype.

Non-destructive optical characterisation of fruits with time-resolved reflectance spectroscopy.

Increasing attention is being paid to the possible development of non-invasive tests for the assessment of the quality of fruits We propose a novel non-destructive method for the measurement of the internal optical properties of fruits and vegetables by means of time resolved reflectance spectroscopy in the visible and NIR range. A fully automated instrumentation for time-resolved reflectance measurements was developed It is based on mode-locked laser sources and electronics for time-correlated single photon counting, and provides a time-resolution of 120-160 ps The system was used to probe the optical properties of several species and varieties of fruits and vegetables in the red and NIR range (650-1000 nm). In most fruits, the absorption line shape is dominated by the absorption peak of water, centred around 970 nm Generally, the absorption spectra also show the spectral features typical of chlorophyll, with maximum at 675 nm In particular, for what concerns apples, variations in peak intensity are observed depending on the variety, the degree of ripeness as well as the position on the apple. For all the species and varieties considered, the transport scattering coefficient decreases progressively upon increasing the wavelength.

Non-destructive optical characterization of fruits in the red and near infrared.

Increasing attention is being paid to the possible development of non-invasive tests for the assessment of the quality of Fruits. We propose a novel non-destructive method for the measurement of the internal optical properties of fruits and vegetables by means of lime-resolved reflectance spectroscopy in the visible and NIR range. A Fully automated instrumentation for time-resolved reflectance measurements was developed. It is based on mode-locked laser sources and electronics for time-correlated single photon counting, and provides a time-resolution of 120-160 ps. The system was used to probe the optical properties of several species and varieties of Fruits and vegetables in the red and NIR range (650-1000 nm). In most Fruits, the absorption line shape is dominated by the absorption peak of water, centred around 970 nm. Generally, the absorption spectra also show the spectral features typical of chlorophyll, with maximum at 675 nm. In particular, for what concerns apples, variations in peak intensity are observed depending on the variety, the degree of ripeness as well as the position on the apple. For all the species and varieties considered, the transport scattering coefficient decreases progressively upon increasing the wavelength.

Space-time ocean wave measurement using variational stereo vision systems

Remote sensing imaging systems for the measurement of oceanic sea states have recently attracted renovated attention. Imaging technology is economical, non-invasive and enables a better understanding of the space-time dynamics of ocean waves over an area rather than at selected point locations of previous monitoring methods (buoys, wave gauges, etc.). We present recent progress in space-time measurement of ocean waves using stereo vision systems on offshore platforms. Both traditional disparity-based systems and modern elevation-based ones are presented in a variational optimization framework: the main idea is to pose the stereoscopic reconstruction problem of the surface of the ocean in a variational setting and design an energy functional whose minimizer is the desired temporal sequence of wave heights. The functional combines photometric observations as well as spatial and temporal smoothness priors. Disparity methods estimate the disparity between images as an intermediate step toward retrieving the depth of the waves with respect to the cameras, whereas elevation methods estimate the ocean surface displacements directly in 3-D space. Both techniques are used to measure ocean waves from real data collected at offshore platforms in the Black Sea (Crimean Peninsula, Ukraine) and the Northern Adriatic Sea (Venice coast, Italy). Then, the statistical and spectral properties of the resulting observed waves are analyzed. We show the advantages and disadvantages of the presented stereo vision systems and discuss the improvement of their performance in critical issues such as the robustness of the camera calibration in spite of undesired variations of the camera parameters.

Análisis y clasificación de maderas mediante técnicas no invasivas de baja energía

El estudio de materiales, especialmente biológicos, por medios no destructivos está adquiriendo una importancia creciente tanto en las aplicaciones científicas como industriales. Las ventajas económicas de los métodos no destructivos son múltiples. Existen numerosos procedimientos físicos capaces de extraer información detallada de las superficie de la madera con escaso o nulo tratamiento previo y mínima intrusión en el material. Entre los diversos métodos destacan las técnicas ópticas y las acústicas por su gran versatilidad, relativa sencillez y bajo coste. Esta tesis pretende establecer desde la aplicación de principios simples de física, de medición directa y superficial, a través del desarrollo de los algoritmos de decisión mas adecuados basados en la estadística, unas soluciones tecnológicas simples y en esencia, de coste mínimo, para su posible aplicación en la determinación de la especie y los defectos superficiales de la madera de cada muestra tratando, en la medida de lo posible, no alterar su geometría de trabajo. Los análisis desarrollados han sido los tres siguientes: El primer método óptico utiliza las propiedades de la luz dispersada por la superficie de la madera cuando es iluminada por un laser difuso. Esta dispersión produce un moteado luminoso (speckle) cuyas propiedades estadísticas permiten extraer propiedades muy precisas de la estructura tanto microscópica como macroscópica de la madera. El análisis de las propiedades espectrales de la luz laser dispersada genera ciertos patrones mas o menos regulares relacionados con la estructura anatómica, composición, procesado y textura superficial de la madera bajo estudio que ponen de manifiesto características del material o de la calidad de los procesos a los que ha sido sometido. El uso de este tipo de láseres implica también la posibilidad de realizar monitorizaciones de procesos industriales en tiempo real y a distancia sin interferir con otros sensores. La segunda técnica óptica que emplearemos hace uso del estudio estadístico y matemático de las propiedades de las imágenes digitales obtenidas de la superficie de la madera a través de un sistema de scanner de alta resolución. Después de aislar los detalles mas relevantes de las imágenes, diversos algoritmos de clasificacion automatica se encargan de generar bases de datos con las diversas especies de maderas a las que pertenecían las imágenes, junto con los márgenes de error de tales clasificaciones. Una parte fundamental de las herramientas de clasificacion se basa en el estudio preciso de las bandas de color de las diversas maderas. Finalmente, numerosas técnicas acústicas, tales como el análisis de pulsos por impacto acústico, permiten complementar y afinar los resultados obtenidos con los métodos ópticos descritos, identificando estructuras superficiales y profundas en la madera así como patologías o deformaciones, aspectos de especial utilidad en usos de la madera en estructuras. La utilidad de estas técnicas esta mas que demostrada en el campo industrial aun cuando su aplicación carece de la suficiente expansión debido a sus altos costes y falta de normalización de los procesos, lo cual hace que cada análisis no sea comparable con su teórico equivalente de mercado. En la actualidad gran parte de los esfuerzos de investigación tienden a dar por supuesto que la diferenciación entre especies es un mecanismo de reconocimiento propio del ser humano y concentran las tecnologías en la definición de parámetros físicos (módulos de elasticidad, conductividad eléctrica o acústica, etc.), utilizando aparatos muy costosos y en muchos casos complejos en su aplicación de campo. Abstract The study of materials, especially the biological ones, by non-destructive techniques is becoming increasingly important in both scientific and industrial applications. The economic advantages of non-destructive methods are multiple and clear due to the related costs and resources necessaries. There are many physical processes capable of extracting detailed information on the wood surface with little or no previous treatment and minimal intrusion into the material. Among the various methods stand out acoustic and optical techniques for their great versatility, relative simplicity and low cost. This thesis aims to establish from the application of simple principles of physics, surface direct measurement and through the development of the more appropriate decision algorithms based on statistics, a simple technological solutions with the minimum cost for possible application in determining the species and the wood surface defects of each sample. Looking for a reasonable accuracy without altering their work-location or properties is the main objetive. There are three different work lines: Empirical characterization of wood surfaces by means of iterative autocorrelation of laser speckle patterns: A simple and inexpensive method for the qualitative characterization of wood surfaces is presented. it is based on the iterative autocorrelation of laser speckle patterns produced by diffuse laser illumination of the wood surfaces. The method exploits the high spatial frequency content of speckle images. A similar approach with raw conventional photographs taken with ordinary light would be very difficult. A few iterations of the algorithm are necessary, typically three or four, in order to visualize the most important periodic features of the surface. The processed patterns help in the study of surface parameters, to design new scattering models and to classify the wood species. Fractal-based image enhancement techniques inspired by differential interference contrast microscopy: Differential interference contrast microscopy is a very powerful optical technique for microscopic imaging. Inspired by the physics of this type of microscope, we have developed a series of image processing algorithms aimed at the magnification, noise reduction, contrast enhancement and tissue analysis of biological samples. These algorithms use fractal convolution schemes which provide fast and accurate results with a performance comparable to the best present image enhancement algorithms. These techniques can be used as post processing tools for advanced microscopy or as a means to improve the performance of less expensive visualization instruments. Several examples of the use of these algorithms to visualize microscopic images of raw pine wood samples with a simple desktop scanner are provided. Wood species identification using stress-wave analysis in the audible range: Stress-wave analysis is a powerful and flexible technique to study mechanical properties of many materials. We present a simple technique to obtain information about the species of wood samples using stress-wave sounds in the audible range generated by collision with a small pendulum. Stress-wave analysis has been used for flaw detection and quality control for decades, but its use for material identification and classification is less cited in the literature. Accurate wood species identification is a time consuming task for highly trained human experts. For this reason, the development of cost effective techniques for automatic wood classification is a desirable goal. Our proposed approach is fully non-invasive and non-destructive, reducing significantly the cost and complexity of the identification and classification process.

Offshore Measurements of Ocean Waves using Stereo Vision Systems

In recent years, remote sensing imaging systems for the measurement of oceanic sea states have attracted renovated attention. Imaging technology is economical, non-invasive and enables a better understanding of the space-time dynamics of ocean waves over an area rather than at selected point locations of previous monitoring methods (buoys, wave gauges, etc.). We present recent progress in space-time measurement of ocean waves using stereo vision systems on offshore platforms, which focus on sea states with wavelengths in the range of 0.01 m to 10 m. Classical epipolar techniques and modern variational methods are reviewed to reconstruct the sea surface from the stereo pairs sequentially in time. The statistical and spectral properties of the resulting observed waves are analyzed. Current improvements of the variational methods are discussed as future lines of research.

Offshore remote sensing of the ocean by stereo vision systems

In recent years, remote sensing imaging systems for the measurement of oceanic sea states have attracted renovated attention. Imaging technology is economical, non-invasive and enables a better understanding of the space-time dynamics of ocean waves over an area rather than at selected point locations of previous monitoring methods (buoys, wave gauges, etc.). We present recent progress in space-time measurement of ocean waves using stereo vision systems on offshore platforms, which focus on sea states with wavelengths in the range of 0.01 m to 1 m. Both traditional disparity-based systems and modern elevation-based ones are presented in a variational optimization framework: the main idea is to pose the stereoscopic reconstruction problem of the surface of the ocean in a variational setting and design an energy functional whose minimizer is the desired temporal sequence of wave heights. The functional combines photometric observations as well as spatial and temporal smoothness priors. Disparity methods estimate the disparity between images as an intermediate step toward retrieving the depth of the waves with respect to the cameras, whereas elevation methods estimate the ocean surface displacements directly in 3-D space. Both techniques are used to measure ocean waves from real data collected at offshore platforms in the Black Sea (Crimean Peninsula, Ukraine) and the Northern Adriatic Sea (Venice coast, Italy). Then, the statistical and spectral properties of the resulting observed waves are analyzed. We show the advantages and disadvantages of the presented stereo vision systems and discuss future lines of research to improve their performance in critical issues such as the robustness of the camera calibration in spite of undesired variations of the camera parameters or the processing time that it takes to retrieve ocean wave measurements from the stereo videos, which are very large datasets that need to be processed efficiently to be of practical usage. Multiresolution and short-time approaches would improve efficiency and scalability of the techniques so that wave displacements are obtained in feasible times.

Non-Destructive Global and Localized 2D T1/T2 NMR Relaxometry to Resolve Microstructure in Apples Affected by Watercore.

Apples can be considered as having a complex system formed by several structures at different organization levels: macroscale (mayor que100 ?m) and microscale (menor que100 ?m). This work implements 2D T1/T2 global and localized relaxometry sequences on whole apples to be able to perform an intensive non-destructive and non-invasive microstructure study. The 2D T1/T2 cross-correlation spectroscopy allows the extraction of quantitative information about the water compartmentation in different subcellular organelles. A clear difference is found as sound apples show neat peaks for water in different subcellular compartments, such as vacuolar, cytoplasmatic and extracellular water, while in watercore-affected tissues such compartments appear merged. Localized relaxometry allows for the predefinition of slices in order to understand the microstructure of a particular region of the fruit, providing information that cannot be derived from global 2D T1/T2 relaxometry.

Non-Destructive Global and Localized 2D T1/T2 NMR Relaxometry to Resolve Microstructure in Apples Affected by Watercore

Apples can be considered as having a complex system formed by several structures at different organization levels: macroscale (>100 μm) and microscale (<100 μm). This work implements 2D T1/T2 global and localized relaxometry sequences on whole apples to be able to perform an intensive non-destructive and non-invasive microstructure study. The 2D T1/T2 cross-correlation spectroscopy allows the extraction of quantitative information about the water compartmentation in different subcellular organelles. A clear difference is found as sound apples show neat peaks for water in different subcellular compartments, such as vacuolar, cytoplasmatic and extracellular water, while in watercore-affected tissues such compartments appear merged. Localized relaxometry allows for the predefinition of slices in order to understand the microstructure of a particular region of the fruit, providing information that cannot be derived from global 2D T1/T2 relaxometry.