La collecte d’informations et leur transmission au travers d’un réseau de communications peut être effectuée par des réseaux de capteurs autonomes ainsi que par des satellites d’observation. L’utilisation conjointe de ces réseaux fournirait des données complémentaires et permettrait à l’Humanité de pérenniser son avenir en comprenant les mécanismes du monde qui l’entoure. Ces dernières années, le secteur spatial a montré une volonté d’unifier et de faciliter la réutilisation des développements réalisés avec la création de filières de plateformes multi-missions ainsi que la définition de protocoles applicables à différents contextes. L’objectif de cette thèse est d’étudier les caractéristiques des différentes technologies d’observation afin d’en exploiter les points communs. À ces fins, nous nous intéressons aux technologies et aux architectures utilisées dans de tels contextes. Nous proposons alors une architecture de réseau répondant aux contraintes des systèmes les plus communément utilisés dans un tel cadre. Les principales contraintes des scénarios d’observation sont liées à la forte intermittence des liens et donc au manque de connexité du réseau. Nous nous orientons donc vers une solution ayant recours au concept de réseaux tolérants au délai. Dans un tel contexte, l’existence d’une route entre la source et la destination n’est pas garantie. C’est pourquoi les protocoles de communication utilisés propagent généralement plusieurs exemplaires d’un même message vers plusieurs entités afin d’augmenter le taux de délivrance. Nous avons souhaité diminuer l’utilisation des ressources du réseau tout en conservant des performances similaires afin d’augmenter l’efficacité du réseau. Après avoir proposé une architecture commune, nous nous sommes focalisés sur les spécificités des différents segments de notre réseau afin de répondre localement à ces problèmes. Pour le segment satellite, nous nous sommes plus spécialement concentrés sur les techniques de gestion de mémoire. Nous considérons un satellite défilant avec une mémoire embarquée limitée, collectant des données en provenance de passerelles. Il s’agit alors de sélectionner les messages les plus urgents quitte à déposer sur une autre passerelle les messages moins contraints. Sur le réseau de capteurs terrestre, nous nous sommes focalisés sur la diminution de l’utilisation des ressources du réseau. Pour cela nous avons utilisé l’historique des rencontres entre les nœuds et analysé l’influence de la quantité de mémoire allouée aux accusés de réception sur les performances du réseau. Nous sommes parvenus à atteindre des performances supérieures aux solutions existantes à moindre frais. Les solutions proposées peuvent être mises en œuvre et appliquées dans différents contextes applicatifs. / Data gathering and transmission through a communicating network can be obtained thanks to wireless sensor networks and observation satellites. Using both these technologies will allow mankind to build a sustainable future by understanding the world around. In recent years, space actors have demonstrated a will to reuse the developed technologies by creating multiple programs platforms and defining context-agnostic protocols. The goal of this thesis is to study the characteristics of several observation technologies to exploit their similarities. We analyse the existing technologies and architectures in several contexts. Then, we propose a networking architecture handling constraints of most commonly used systems in such a context. The main constraints of observation scenarios are due to the links intermittence and lack of network connectivity. We focus on a solution using the delay tolerant networking concept. In such a context, a path between source and destination might not exist at all time. That is why most proposed protocols send multiple copies of a message to increase the delivery ratio. We wanted to decrease network resource use while keeping a similar performance to increase network efficiency. After having proposed a common architecture, we focused on particularities of each network segment to solve problems locally. Concerning the satellite part, we focused specifically on memory management techniques. We considered a low earth orbit satellite with a limited on-board buffer, gathering data from gateways. The goal is then to select the most urgent messages even though the least urgent ones are sent back to the ground. On the terrestrial sensor network part, we focused on the decrease of network resource use. We used the history of encounters between nodes and analysed the influence of the proportion of memory allocated to acknowledgements on network performance. We achieved better performance than existing solutions and at lower cost. The proposed solutions can be deployed and applied in several applications.

Aggressive motion can occur in clinical and elderly care settings with people suffering from dementia, mental disorders, or other conditions that affect memory. Since identifying the nature of the event can be difficult with people who have memory and communication issues, other methods to identify and record aggressive motion would be useful for care providers to reduce re-occurrences of this activity. A wearable technology approach for human activity recognition was explored in this thesis to detect aggressive movements. This approach aims to provide a means to identify the person that initiated aggressive motion and to categorize the aggressive action. The main objective of this thesis was to determine the effectiveness of smartwatch accelerometer and gyroscope sensor data for classifying aggressive and non-aggressive activities. 30 able-bodied participants donned two Microsoft Bands 2 smartwatches and performed an activity circuit of similar aggressive and non-aggressive movements. Statistical and physical features were extracted from the smartwatch sensors signals, and subsequently used by multiple classifiers to determine on a machine learning platform six performance metrics (accuracy, sensitivity, specificity, precision, F-score, Matthews correlation coefficient). This thesis demonstrated: 1) the best features for a binary classification; 2) the best and most practical machine learning classifier and feature selector model; 3) the evaluation metrics differences between unilateral smartwatch and bilateral smartwatches; 4) the most suitable machine learning algorithm for a multinomial classification.

Accurate characterisation of fluid flow at tidal energy sites is critical for cost effective Tidal Energy Converter (TEC) design in terms of efficiency and survivability. The standard instrumentation in tidal site characterisation has been Diverging acoustic-Beam Doppler Profilers (DBDPs) which remotely measure the flow over a range of scales, resolving up to three velocity vectors. However, they are understood to have several drawbacks particularly in terms of characterising turbulent aspects of the flow. This characterisation is generally based upon a small number of key transient metrics, the accuracy of which directly impacts TEC designs. This work presents an optimisation and performance assessment of newly available Single Beam Doppler Profilers (SBDPs) mounted on a commercial-scale tidal turbine at mid-channel depth in a real operating environment. It was hypothesised that SBDPs would have advantages over DBDPs for site characterisation, in terms of reduced random error, reduced uncertainty in turbulence intensities and the ability to quantify the structure of the turbulent flow. The relationship between random error, sensor orientation and flow speed is quantified for both single and diverging beam sensor types. Random error was found to increase with increasing flow velocity as a power law, the slope of which varies for different sensor orientations. Quantification of noise offers a practical method to correct turbulence metrics. To enable the use of multiple acoustic sensors mounted in close proximity, interference was quantified and mitigation techniques examined. Cross-talk between sensors of the same type were generally shown to bias measurements towards zero. In the presence of alternate types of acoustic sensors, interference caused an increase in standard deviation of velocity results. Implementing a timing offset control mechanism was able to mitigate this effect. This work has achieved a greater understanding of the drivers (spatial separation, inclination angle, pulse power) and effects on measurements of interference along with ambient-noise for users of acoustic instruments. Lessons learned of value to the industry, as site characterisation work intensifies ahead of next generation commercial scale devices, are presented. Mid-channel depth mounted SBDPs were found to have advantages over seabed mounted DBDPs in resolving the key turbulent flow metrics. SBDPs were able to resolve integral length-scales of turbulence that show an anisotropic ratio of scales as predicted from theory and in work at similar sites, while the DBDPs results were similar for all directions. Turbulence intensity measurements were found to be similar after noise correction, with the SBDPs more able to accurately capture the turbulence dissipation rate. This evidence suggests that SBDP arrays present a significant improvement over bottom mounted DBDPs in discerning information about the nature of the turbulent flow, and thus future site characterisation work should consider the use of SBDPs alongside bottom mounted DBDPs for this purpose.

Made available in DSpace on 2014-06-11T19:22:25Z (GMT). No. of bitstreams: 0 Previous issue date: 2010-08-30Bitstream added on 2014-06-13T19:07:52Z : No. of bitstreams: 1 beneditti_ca_me_prud.pdf: 3065249 bytes, checksum: b10d04069c7a91011443ee9fcf72ab9c (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Sensores ópticos são amplamente utilizados para mapeamento da cobertura da terra em escala local e pequenas regiões, com uma ampla variedade de aplicações, incluindo planejamento urbano, inventario agrícola e florestal, gerenciamento de bacias hidrográficas e monitoramento ambiental. Mapeamento de cobertura da terra com dados da banda L SAR tem focado primariamente em florestas e área úmidas de regiões tropical e boreal, com ênfase no monitoramento de desmatamento tropical e reflorestamento. No inicio de 2006, aquisições sistemáticas do ALOS PALSAR tem fornecido conjunto de dados multisazonais com alta resolução (12,5m), com potencial para substituir ou complementar os conjuntos de dados ópticos para mapeamento de cobertura da terra em regiões que a cobertura de nuvens é menos problemática, mas ainda um limitante para a variação sazonal da cobertura da terra. Este estudo avalia a utilização de dados PALSAR multitemporal, combinados com modelo digital de superfície (DSM) derivado do ALOS PRISM, para o mapeamento da cobertura da terra em uma região central do estado de São Paulo, Brasil. A área de estudo (22.5ºS 47.8 ºW) está situada na região oeste do reservatório de Barra Bonita, próximo a confluência dos rios Tietê e Piracicaba, com elevações variando entre 300 e 1000m. Os usos da terra dominante são agricultura ( cana de açúcar, cítricas e gramíneas) e florestal (eucaliptos). A vegetação natural é restrita a vegetação riparia, mata na front da cuesta e macrofitas aquáticas sazonais. Áreas urbanas presente na região são São Pedro e Aguas de São Pedro. Duas cenas PALSAR no modo Fine-Beam Single-polarization (FBS) (08 de abril de 2008 e 09 de janeiro de 2009... / Optical sensors are widely used for land cover mapping at local and small region scales, for a wide variety of applications including urban planning, forest and crop inventory, watershed management, and environmental monitoring. Land cover mapping with L-band SAR data has focused primarily on forest and wetland areas in tropical and boreal regions, with particular emphasis on monitoring tropical deforestation and regrowth. Beginning in 2006, systematic acquisitions of ALOS PALSAR have provided multi-season, near-global data sets at high (12.5 m) resolution, with the potential to substitute for or complement optical data sets for land cover mapping in regions where cloud cover is less problematic, but still limiting for seasonally varying land cover. This study evaluates the utility of multi-temporal PALSAR data, combined with a digital surface model (DSM) derived from ALOS PRISM, for land cover mapping at a site in central São Paulo state, Brazil. The study area (22.5ºS 47.8 ºW) is situated at the west end of the Barra Bonita Reservoir, at the entrance point of the Tietê River, with elevations ranging from about 300 to 1000 m. Dominant land uses are agriculture (sugar cane, citrus, pasture) and forestry (eucalyptus). Natural vegetation is largely restricted to riparian forest, forests on steep slopes, and seasonal aquatic macrophytes. Urban areas include the cities of São Pedro and Águas de São Pedro. Two PALSAR Fine-Beam Single-polarization (FBS) mode scenes (8 April 2008 and 9 January 2009... (Complete abstract click electronic access below)

Traditional flight test sensing applications require installation of not only the sensor but also supporting cabling and interfacing infrastructure. The cost of this supporting infrastructure increases when it must cross pressure vessel boundaries, extend long distances, or interfere with operation of the aircraft. The continuing cost and schedule pressures on flight test programs demand approaches that minimize installation complexity and reduce the need to modify the aircraft under test. Some emerging approaches have leveraged wireless techniques for data transmission but this can only be used in certain circumstances and does not address the problem of power distribution. This paper describes ongoing research into alternative sensing approaches that utilize a mix of video processing, distributed processing, and power harvesting to provide additional solutions.

Steam reforming of methanol and hydrocarbon are currently the processes of choice to produce hydrogen. Due to the endothermic nature of these reactions, zones of low temperature are commonly found in reformers. These zones can potentially damage the reformer through thermal stresses. Moreover, the response time and size of a reformer are controlled by the heat available to the reaction. The objective of this thesis is to demonstrate the feasibility of using fiber Bragg gratings as an alternative solution for temperature monitoring in methanol and methane steam reformers. To meet this objective, a sensor array containing seven gratings is placed in a metal-plate test reformer. First, temperature monitoring during methanol steam reforming is conducted in 12 different sets of conditions. The resulting profile of the temperature change along the length of the catalyst captures the zones of low temperature caused by the endothermic nature of the reaction. Several small changes in the temperature profile caused by increasing temperature and/or flow rates were captured, demonstrating the ability to use these gratings in methanol steam reforming. Similar experimental work was conducted to validate the possibility of using fiber Bragg gratings as temperature sensors in methane reforming. Using a regenerated grating array, data was collected for 13 operating conditions. The conclusions arising from this work are similar to those drawn from the methanol steam reforming work. The regenerated FBGs exhibited a behaviour that has not been reported in the literature which is referred to in this thesis as secondary erasure. This behaviour caused some instability in the grating signal and erroneous readings for some operating conditions. Despite this, the grating measurements captured the zones of low temperatures in the reformer and the small changes brought about by increasing the reforming temperature and lowering the steam to carbon ratio. / Graduate

A context-aware computing system is one that can deduce the state of its surroundings using input from sensors and can change its behaviour accordingly. Context-aware devices might personalise themselves to their current user, alter their functionality based on where they were being used, or take advantage of nearby computing and communications resources. Location-aware systems, whose behaviour is determined by the positions of objects in the environment, represent a practical subset of the context-aware computing paradigm, and several systems of this nature have already been demonstrated. The location sensors used by those systems, however, report the positions of objects to only a room-scale granularity, limiting the extent to which devices and applications can adapt to their surroundings. Sensor technologies that can provide more detailed information about the locations of objects must therefore be investigated. This dissertation describes a new ultrasonic location sensor, which may be deployed in indoor environments such as offices and homes. The sensor can provide fine-grain , three-dimensional position and orientation information, and its characteristics are well suited to the demands of location-aware computing- the sensor is simple, low-powered and unobtrusive. Furthermore, the location system is scalable, in both the number of objects that it can track and the volume within which they may be monitored. A thorough assessment of the sensor's performance is presented in the dissertation, so that location-aware applications can be tailored to its properties. Subsequently, a software architecture that can efficiently distribute finegrain location information to applications is described. The software system provides support for the types of query that will be made frequently by location-aware applications, such as those concerning the spatial relationships between objects and their proximity to one another. The dissertation concludes by examining the use of the ultrasonic location sensor and software architecture to implement a set of novel location-aware applications.

This thesis is concerned with the advanced topics of thin film magnetoimpedance (MI) sensors. The author proposes and develops novel MI sensors that target on the challenges arising from emerging applications such as flexible electronics, passive wireless sensing, etc. In the study of flexible MI sensor, the investigated sensors of NiFe/Cu/NiFe tri-layersare fabricated on three flexible substrates having different surface roughness: Kapton, standard and premiumphotopaper. Sensitivity versus substrate roughness analysis is carried out for the selection of optimal substrate material. The high magnetic sensing performance is achieved by using Kapton substrate. Stress simulation, incorporated with the theory of magnetostriction effect, reveals the material composition of Ni/Fe being as a key factor of the stress dependent MI effect for the flexible MI sensors. In the development of MI-SAW device for passive wireless magnetic field sensing, NiFe/Cu/NiFe tri-layersand interdigital transducers(IDT) are designed and fabricated on a single piece of LiNbO3substrate, providing a high degree of integration and the advantage of standard microfabrication. The double-electrodeIDT has been utilized and proven to have an optimal sensing performance in comparison to the bi-directional IDT design. The optimized high frequency performance of the thin film MI sensor results in a MI-SAW passive wireless magnetic sensor with high magnetic sensitivity comparing to the MI microwire approach. Benefiting from the high degree of integration of the MI thin film element, in the following study, two additional sensing elements are integrated to the SAW device to have a multifunctional passive wireless sensor with extended temperature and humidity sensing capabilities. Analytical models havebeen developed to eliminate the crossovers of different sensing signals through additional reference IDTs, resulting in a multifunctional passive wireless sensor with the capability of detecting all three measurands individually and simultaneously.

Conventional healthcare and the practice of medicine largely relies on the ineffective concept of one size fits all. Personalized medicine is an emerging therapeutic approach that aims to develop an advanced therapeutic technique that provides tailor-made therapy based on every individuals’ needs by delivering the right drug at the right time with the right amount of dosage. The advancement in technologies such as flexible electronics, microfluidics, biosensors, and advanced artificial intelligence can enable the realization of a truly effective personalized therapy. However, currently, there is a lack for a personalized minimally-invasive wearable closed-loop drug delivery system that is continuous, automated, conformal to the skin and cost-effective. Thus, this thesis focuses on the design, fabrication, optimization, and application of an automated personalized microfluidics drug delivery platform augmented with flexible biosensors, heaters, and expandable polymeric actuator. The platform provides precise drug delivery with spatiotemporal control over the administered dose as a response to real-time physiological changes of the individual. The system is flexible enough to be conformal to the skin and drug is transdermally administered through biocompatible microneedles. The platform includes a flexible multi-reservoir microfluidics layer, flexible and conformal heating elements, skin sensors and processing units which are powered by a lightweight battery integrated into the platform. The developed platform was fabricated using rapid, cost-effective techniques that are independent of advanced microfabrication facilities to expand its applications to low-resource setting and environments.

<div>Researchers have shown links between various hydrocarbons and carbonyl compounds and diseases, such as cancer using exhaled breath analysis through gas chro</div><div>matography/mass spectroscopy (GC/MS) analysis of volatile organic compounds (VOCs). Trained canines can detect these VOCs and can differentiate a patient suffering from cancer from a healthy control patient. In this project, an attempt has been made to develop highly sensitive sensors for the detection of low concentrations of aldehyde VOCs, such as nonanal, using conductive polymer composites (CPCs) and functionalized gold nanoparticles (f-GNPs). Facile methods have been used to enhance the sensitivity and cross-selectivity of the fabricated sensors towards nonanal. Interdigitated electrodes (IDEs) are fabricated through a photolithography process. Sensors of PEI/carbon black (CB) composite were developed via spin-coating of the</div><div>material followed by the heat treatment process. Sensors of 1-Mercapto-(triethyleneglycol) methyl ether functionalized GNPs are developed via drop-casting of nanomaterial and f-GNP/PEI sensors are fabricated by spin casting PEI film on top of f-GNPs. Fourier Transform Infrared (FTIR) analysis, X-Ray Diffraction (XRD) analysis, contact angle measurement, and Field Emission Scanning Electron Microscopy (FESEM) analysis was conducted to characterize the fabricated devices. The fabricated sensors have been tested with a low concentration of nonanal, nonanone, dodecane, and 1-octanol in dry air. Multiple sensors are fabricated to ensure sensors reproducibility. The sensors have been exposed repeatedly to the targeting VOCs to assess the repeatability of the sensors. PEI/CB sensor degradation was studied over a period of 36 days.</div><div><br></div><div>The fabricated PEI/CB film could detect (1-80 ppm) of nonanal with higher selectivity, than the f-GNPs. The sensor0s sensitivity to nonanal was over fourteen times</div><div>higher than 2-nonanone, 1-octanol, and dodecane. This shows the high selectivity of the fabricated sensor toward nonanal. In addition, the proposed sensor maintained its</div><div>sensitivity to nonanal over time showing minimal degradation. The sensor response to nonanal at a relative humidity (RH) of 50% and 85% dropped less than 13% and</div><div>32% respectively. The Response of f-GNP sensors to nonanal (400 ppb - 15 ppm), dodecane (5 - 15 ppm), 1-octanol (5 - 15 ppm), and 2-nonanone (5 - 15 ppm) presented a sensitivity (∆R/R0) of 0.217%, 0.08%, 0.192% and 0.182% per ppm of the VOCs respectively. Despite the high sensitivity to the targeting VOCs, the fabricated</div><div>sensors were damaged in an environment with relative humidity (RH) at 45%. A thin layer of PEI over the film was developed to ensure the sensor could tolerate long</div><div>time exposure to water vapor in an environment with RH up to 85% and enhance the sensor selectivity towards nonanal. The f-GNP/PEI sensors with nonanal (400 ppb- 15 ppm), dodecane (100 -200 ppm), 1-octanol (5 - 15 ppm) and 2-nonanone (5 - 15 ppm) presented sensitivity (∆R/R0) of 0.21%, 0.017%, 0.0438% and 0.0035% per ppm of the VOCs respectively. The sensor fabrication, characterization, testing methods, and results are presented and discussed.</div>