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As vehicle manufacturers continue to increase their emphasis on safety with advanced driver assistance systems (ADAS), I propose a ubiquitous device that is able to analyze and advise on safety conditions. Mobile smartphones are increasing in popularity among younger generations with an estimated 64% of 25-34 year olds already using one in their daily lives. with over 10 million car accidents reported in the United States each year, car manufacturers have shifted their focus of a passive approach (airbags) to more active by adding features associated with ADAS (lane departure warnings). However, vehicles manufactured with these sensors are not economically priced while older vehicles might only have passive safety features. Given its accessibility and portability, I target a mobile smartphone as a device to compliment ADAS that can bring a driver assist to any vehicle without regards for any on-vehicle communication system requirements. I use the 3-axis accelerometer of multiple Android based smartphone to record and analyze various safety factors which can influence a driver while operating a vehicle. These influences with respect to the driver, vehicle and road are lane change maneuvers, vehicular comfort and road conditions. Each factor could potentially be hazardous to the health of the driver, neighboring public, and automobile and is therefore analyzed thoroughly achieving 85.60% and 89.89% classification accuracy for identifying road anomalies and lane changes, respectively. Effective use of this data can educate a potentially dangerous driver on how to operate a vehicle safely and efficiently. with real time analysis and auditory alerts of these factors, I hope to increase a driver's overall awareness to maximize safety.

The brightness and photostability of semiconductor quantum dots (QDs) has prompted the exploration of their use in a wide variety of fields. Several examples of QD-based biosensors have been reported but none have actually replaced their preexisting technologies. This work reveals the barriers hindering widespread use of QD based biosensors and examines how QDs can be engineered for improved utility in bioassay designs. The first portion of this project aims to improve Förster Resonance Energy Transfer (FRET) that use QDs as both the donor and acceptor. FRET-based sensors often use fluorescent dyes (FD) or proteins (FPs), but their photo- and chemical instability can be problematic. Contemporary QD-QD FRET systems suffer from unacceptably high background signal due to direct acceptor excitation. Materials engineering is used to create QD donors that are brighter than their QD acceptors to mitigate this effect. First, CdSe/xCdS/xZnS QDs of increasing shell thickness were synthesized and tested in a QD-fluorescent dye system to elucidate the effect of increased donor size on the performance of a FRET sensor. The optimal donors were medium-sized and 8 times brighter than commercially available QDs while retaining ~60% FRET efficiency. When used in a sensor, changes in sensor brightness were visible by eye. Moving towards QD-QD systems, a pH-based aggregation assay was used to test how QD heterostructures comprised of different semiconductor materials perform as FRET donors or acceptors. The fundamental principles uncovered are used to improve contemporary QD-QD FRET sensing and show that sensors can be designed to use color change as a visible, easy-to-decipher readout. Color change-based sensor output is further explored in an allosteric transcription factor-based small-molecule sensor that employs QDs as the sole fluorescent label. A highly modular design is presented that achieves a nanomolar concentration visual limit of detection. The ease of use, and fast, instrument-free readout of the sensor shows promise for its development into a fully integrated point-of-care device, endorsing the value of further developing QD-based in vitro biosensors for clinical or commercial translation. / 2020-06-04T00:00:00Z

Chiral nematic thin films containing responsive dopants have previously been considered as sensors and dosimeters. Some systems have been developed, with mixed results. The investigation so far has been piecemeal, with little attention paid towards understanding the properties that govern how these sensors operate. By carefully considering these properties, we believe that it is possible to predict the effectiveness of a sensor, and therefore a framework can be established which would allow only sensors with significant potential to be investigated. The applications of a variety of chiral nematic thin films incorporating responsive dopants is modelled and then investigated experimentally. The systems chosen for investigation were selected using the criteria of commercial potential and synthetic simplicity. In each case it was found that the behaviour of these systems could be predicted well from simple experimental data. The systems chosen for investigation were judged on the basis of two key criteria: They must be systems that deal with a target that is of commercial interest, so that performance expectations for 'real-life' applications can be given at the start of the research process. They must be manufactured only using materials and processes that are commercially available. These limitations were chosen to highlight the conditions under which such a model would be expected to operate. In this work, a successful model that predicts sensors behaviour from basic experimental information was developed and shown to match well with experimental results. In the process, three new sensing systems were developed, all with potential commercial significance. Additionally, some observations regarding the methods of operation which are most likely to result in high sensitivity and low cross-sensitivity have been made.

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Hand and arm gestures are a great way of communication when you don't want to be heard, quieter and often more reliable than whispering into a radio mike. In recent years hand gesture identification became a major active area of research due its use in various applications. The objective of my work is to develop an integrated sensor system, which will enable tactical squads and SWAT teams to communicate when there is absence of a Line of Sight or in the presence of any obstacles. The gesture set involved in this work is the standardized hand signals for close range engagement operations used by military and SWAT teams. The gesture sets involved in this work are broadly divided into finger movements and arm movements. The core components of the integrated sensor system are: Surface EMG sensors, Flex sensors and accelerometers. Surface EMG is the electrical activity produced by muscle contractions and measured by sensors directly attached to the skin. Bend Sensors use a piezo resistive material to detect the bend. The sensor output is determined by both the angle between the ends of the sensor as well as the flex radius. Accelerometers sense the dynamic acceleration and inclination in 3 directions simultaneously. EMG sensors are placed on the upper and lower forearm and assist in the classification of the finger and wrist movements. Bend sensors are mounted on a glove that is worn on the hand. The sensors are located over the first knuckle of each figure and can determine if the finger is bent or not. An accelerometer is attached to the glove at the base of the wrist and determines the speed and direction of the arm movement. Classification algorithm SVM is used to classify the gestures.

Les expériences conduites auprès du futur accélérateur LHC au CERN nécessitent la construction des détecteurs les plus grands et les plus complexes jamais conçus. En particulier, le trajectographe de la collaboration CMS utilisera uniquement des détecteurs micropiste silicium et ce, en très grandes quantités. Ce dernier dépend donc de manière capitale de la qualité de toute la production des senseurs et la collaboration CMS a ainsi décidé de mettre en place un vaste programme de contrôle de cette qualité. Cette thèse présente une partie des travaux réalisés à l'UCL dans ce cadre. La discussion porte en particulier sur résistance aux radiations des senseurs en silicium, testée de manière routinière à Louvain-la-Neuve. Le texte débute par une présentation du détecteur CMS et des dégâts radiatifs subits par les détecteurs micropiste silicium. Les dispositifs expérimentaux mis en place auprès des cyclotrons et dans le laboratoire de l'institut de Physique nucléaire sont ensuite détaillés. Finalement, les résultats des tests systématiques sont résumés, et discutés au regard des critères posés par la collaboration

Poly(arylenenethynylene)s or PAEs are an interesting class of conjugated polymers that have potential uses in the field of thin film transistors, organic LEDs, sensors, and molecular wires. The field of PAEs have grown in recent years, however very few of its conjugated polymers have a heterocyclic motif contained within them. We have designed some conjugated heterocyclic polymers that contain quinoline, benzothidiazole, and quinoxaline. These polymers show interesting ionochromic and solvochromic effects as well as unusual solid state properties. Some of these polymers will demonstrate their ability to form fascinating nanostructures by use of either mesoporous discs or gold mediated nanotubes. Finally, we also have produced peralkynylated heterocyclic molecules for use in potential n-semiconductive devices. These molecules are not only aesthtically pleasing, but versatile molecules that could be used in conjugated PAEs.

A new impetus to develop autonomous aerial refueling has arisen out of the growing demand to expand the capabilities of unmanned aerial vehicles (UAVs). With autonomous aerial refueling, UAVs can retain the advantages of being small, inexpensive, and expendable, while offering superior range and loiter-time capabilities. VisNav, a vision based sensor, offers the accuracy and reliability needed in order to provide relative navigation information for autonomous probe and drogue aerial refueling for UAVs. This thesis develops a Kalman filter to be used in combination with the VisNav sensor to improve the quality of the relative navigation solution during autonomous probe and drogue refueling. The performance of the Kalman filter is examined in a closed-loop autonomous aerial refueling simulation which includes models of the receiver aircraft, VisNav sensor, Reference Observer-based Tracking Controller (ROTC), and atmospheric turbulence. The Kalman filter is tuned and evaluated for four aerial refueling scenarios which simulate docking behavior in the absence of turbulence, and with light, moderate, and severe turbulence intensity. The docking scenarios demonstrate that, for a sample rate of 100 Hz, the tuning and performance of the filter do not depend on the intensity of the turbulence, and the Kalman filter improves the relative navigation solution from VisNav by as much as 50% during the early stages of the docking maneuver. For the aerial refueling scenarios modeledin this thesis, the addition of the Kalman filter to the VisNav/ROTC structure resulted in a small improvement in the docking accuracy and precision. The Kalman filter did not, however, significantly improve the probability of a successful docking in turbulence for the simulated aerial refueling scenarios.

Safety in automobiles is gaining increasing importance. With the increasing trend of U.S. buyers towards SUVs, appropriate safety measures for SUVs need to be implemented. Since SUVs, as a vehicle type, have a higher center of gravity and hence have a greater tendency to rollover at high cornering speeds. The rollover can also occur due to the vertical road inputs like bumps and potholes which induce a rolling moment. The proposed rollover identification system would "couple" the two inputs from the suspension relative position sensors and the lateral acceleration sensor to predict rollover. The input to the suspension relative position sensors could be either due to the vehicle cornering, which results in the outer suspension getting compressed and the inner suspension getting extended, or maybe due to vertical road inputs. The principal objective is to differentiate the two types of inputs (since they can have opposing moment values) and further couple the same with the lateral acceleration input to form a rollover identification system. The work involves modeling of a semi-car model using the Dymola-vehicle dynamics simulation software. The semi-car model is developed to simulate values for the two proposed sensors. Then using NHTSA standard steering procedures and steering angle as the input, the lateral tire forces are generated. These tire forces serve as input to the Dymola model which is integrated into a Simulink model. The lateral acceleration and suspension relative position sensor values obtained are then used by LabVIEW to pass judgments on the type of rollover. The model was successfully developed in Dymola. The model with steering angle as input was able to generate values of lateral acceleration and lateral tire forces. The roll angle induced due to road inputs and vehicle cornering were estimated. Since the principal objective of modeling was to generate lateral acceleration values, these values were subsequently used in the LabVIEW Rollover Identification System where rollover induced either by maneuver or through road inputs were clearly identified.