Indiana University-Purdue University Indianapolis (IUPUI) / Volatile organic compounds (VOCs) are endogenous byproducts of metabolic pathways that can be altered by a disease or condition, leading to an associated and unique VOC profile or signature. Current methodologies for VOC detection include canines, gas chromatography-mass spectrometry (GC-MS), and electronic nose (eNose). Some of the challenges for canines and GC-MS are cost-effectiveness, extensive training, expensive instrumentation. On the other hand, a significant downfall of the eNose is low selectivity. This thesis proposes to design a breathalyzer using chemiresistive gas sensors that detects VOCs from human breath, and subsequently create an interface to process and deliver the results via Bluetooth Low Energy (BLE). Breath samples were collected from patients with hypoglycemia, COVID-19, and healthy controls for both. Samples were processed, analyzed using GC-MS, and probed through statistical analysis. A panel of 6 VOC biomarkers distinguished between hypoglycemia (HYPO) and Normal samples with a training AUC of 0.98 and a testing AUC of 0.93. For COVID-19, a panel of 3 VOC biomarkers distinguished between COVID-19 positive symptomatic (COVID-19) and healthy Control samples with a training area under the curve (AUC) of receiver operating characteristic (ROC) of 1.0 and cross-validation (CV) AUC of 0.99. The model was validated with COVID-19 Recovery samples. The discovery of these biomarkers enables the development of selective gas sensors to detect the VOCs. Polyethylenimine-ether functionalized gold nanoparticle (PEI-EGNP) gas sensors were designed and fabricated in the lab and metal oxide (MOX) semiconductor gas sensors were obtained from Nanoz (Chip 1: SnO2 and Chip 2: WO3). These sensors were tested at different relative humidity (RH) levels and VOC concentrations. The contact angle which measures hydrophobicity was 84° and the thickness of the PEI-EGNP coating was 11 µ m. The PEI-EGNP sensor response at RH 85% had a signal 10x higher than at RH 0%. Optimization of the MOX sensor was performed by changing the heater voltage and concentration of VOCs. At RH 85% and heater voltage of 2500 mV, the performance of the sensors increased. Chip 2 had higher sensitivity towards VOCs especially for one of the VOC biomarkers identified for COVID-19. PCA distinguished VOC biomarkers of HYPO, COVID-19, and healthy human breath using the Nanoz. A sensor interface was created to integrate the PEI-EGNP sensors with the printed circuit board (PCB) and Bluno Nano to perform machine learning. The sensor interface can currently process and make decisions from the data whether the breath is HYPO (-) or Normal (+). This data is then sent via BLE to the Hypo Alert app to display the decision.

Im Rahmen von UPNS4D+ wird von mir der Teilbereich der automatisierten untertägigen Detektion von Gangerzlagerstätten und seltenen Erden bearbeitet. Dies erfolgt mittels eines Multisensoransatzes, der aus einer Hyperspektralkamera, einer RGB-Kamera und einem Laserscanner besteht. Die Grundlagen für die Kombination von hyperspektraler Bildverarbeitung und einer RGB-Kamera sind in der Industrie im Bereich von automatisierten Sortieranlagen zu finden. Im Bereich der Fernerkundung ist der Einsatz hyperspektraler Bilder für die Detektion geologischer Merkmale seit einigen Jahrzehnten üblich. Hier kann im Rahmen meiner Forschung gezeigt werden, dass mittels hyperspektraler Bilder Pyrit unter Tage detektiert werden kann. / In my research I work on a system which detects automatically the ore and rare earth element in a mine. This is part of UPNS4D+. For the detection I use a multi sensor system which consists of a hyperspectral camera, a RGB camera and a Laser scanner. Basics of this combination can be found in the industry. The combination of a RGB camera and a hyperspectral camera enables an automatic sorting of for example waste materials. Landsat satellites in the 1970 uses spectral information in order to detect the geology of the surface. I have tested the hyperspectral imaging in the Reiche Zeche and I can now show that Pyrite can be detected.

The rapid developments in the sensor and its related technology have made automation possible in many processes in diverse fields. Also sensor-based fault diagnosis and quality improvements have been made possible. These tasks depend highly on the sensor network for the accurate measurements. The two major problems that affect the reliability of the sensor system/network are sensor failures and sensor anomalies. The usage of redundant sensors offers some tolerance against these two problems. Hence the redundancy analysis of the sensor system is essential in order to clearly know the robustness of the system against these two problems. The degree of sensor redundancy defined in this thesis is closely tied with the fault-tolerance of the sensor network and can be viewed as a parameter related to the effectiveness of the sensor system design. In this thesis, an efficient algorithm to determine the degree of sensor redundancy for linear sensor systems is developed. First the redundancy structure is linked with the matroid structure, developed from the design matrix, using the matroid theory. The matroid problem equivalent to the degree of sensor redundancy is developed and the mathematical formulation for it is established. The solution is obtained by solving a series of l1-norm minimization problems. For many problems tested, the proposed algorithm is more efficient than other known alternatives such as basic exhaustive search and bound and decomposition method. The proposed algorithm is tested on problem instances from the literature and wide range of simulated problems. The results show that the algorithm determines the degree of redundancy more accurately when the design matrix is dense than when it is sparse. The algorithm provided accurate results for most problems in relatively short computation times.

<p>A full custom integrated circuit design of a serial bitstream processor is proposed for remote smart sensor systems. This dissertation describes details of the architectural exploration, circuit implementation, algorithm simulation, and testing results. The design is fabricated and demonstrated to be a successful working processor for basic algorithm functions. In addition, the energy performance of the processor, in terms of energy per operation, is evaluated. Compared to the multi-bit sensor processor, the proposed sensor processor provides improved energy efficiency for serial sensor data processing tasks, and also features low transistor count and area reduction advantages.</p><p>Operating in long-term, low data rate sensing environments, the serial bitstream processor developed is targeted at low-cost smart sensor systems with serial I/O communication through wireless links. This processor is an attractive option because of its low transistor count, easy on-chip integration, and programming flexibility for low data duty cycle smart sensor systems, where longer battery life, long-term monitoring and sensor reliability are critical. </p><p>The processor can be programmed for sensor processing algorithms such as delta sigma processor, calibration, and self-test algorithms. It also can be modified to utilize Coordinate Rotation Digital Computer (CORDIC) algorithms. The applications of the proposed sensor processor include wearable or portable biomedical sensors for health care monitoring or autonomous environmental sensors.</p> / Dissertation

Alternative diesel fuels have been the subject of extensive investigation. Fatty acid methyl ester (FAME) based Biodiesel manufactured from vegetable oils or animal fats is an excellent candidate to replace common diesel fuel being renewable, non-toxic and often giving rise to reduced exhaust gas emissions. The transesterification process has been commonly and widely used to produce biodiesel from vegetable oil or animal fat. Vegetable oils or animal fats generally have viscosities higher than standard diesel oil. This means that it is necessary to reduce the viscosity by means of reacting vegetable oil with alcohol in the presence of a suitable catalyst. The target product for this reaction is methyl ester, with glycerol and potentially soap produced as by products with the process of transesterification. Methylester (Biodiesel) is produced by converting triglycerides to alkylesters. A batch transesterification process has two significant mechanisms, and exhibits a mass transfer controlled region that precedes a second order kinetically controlled region. In order to control the conversion process it is useful to employ process monitoring. In particular monitoring of the mass transfer processes that limits the initial reaction rates could prove to be beneficial in allowing for process optimization and control. This thesis proposes the use of a new method of biodiesel process monitoring using low frequency (15kHz) impedance sensing which is able to provide information regarding the progress of mass transfer and chemical reaction during biodiesel production. An interdigitated (ID) sensor has been used to monitoring the biodiesel process The ID sensor is of simple construction and consists of two sets of interleaved electrodes (fingers). The two sets of electrodes are separated by a gap and when an AC excitation voltage is applied across the interleaved electrodes an oscillating electric field is developed. The response of the fluid surrounding the sensor to the applied excitation was then used to determine progress of the chemical reaction by evaluating the real and complex impedance. A significant and unambiguous change in the components of impedance has been shown to occur during mixing (mass transfer) and transesterification. The impedance measurements gained during transesterification were then used for the development of a system model. A systematic approach was used to select mathematical models and system identification techniques were evaluated. The system identification investigation used real process measurement data in conjunction with the Matlab system identification toolbox.

Main task of the Master Thesis is to introduce into sensor systems used in the field. On Advantech sensor system with use of ADAM 4000 modules is shown decentralized sensor system which comunicates over RS 485 and using master computer. Within Master Thesis was compiled measuring board and were assembled three programs which demonstrate possible use of different types of modules. Main development environment is used ADAMView. Each modules has different number and types of inputs and outputs. Using of sensor system saving measurement time, increasing measurement effeciency, relieves data processing and automatize measurement.

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This report deals with the development of a wireless sensor system that measures the environmental energy and predicts if energy harvesting could be possible in different areas. It provides an overview over the hardware used to build this system and gives a detailed description of the software implementation of the system. The hardware part presents the microcontroller and platform that is used, as well as the sensors integrated in the system. The software part explains how the used hardware was put together in a program that controls the different components. It explains the possibility to save captured sensor values on an SD card or send them to a remote receiver with an XBee radio module in real time. Also the inclusion of the mbed software library, which provides a lot of useful applications and functions for the project, is an important part. The final part of the report presents the results, showing how the system works.

<p>U ovoj doktorskoj disertaciji dat je predlog nove metode za merenje talasne dužine monohromatske svetlosti pomoću spektralno osetljivih optičkih komponenti. Princip rada predložene metode se zasniva na kombinovanju spektralnih osetljivosti fiber-optičke račve i dva različita fotodetektora.<br />Izvršena je implementacija i karakterizacija senzorskog sistema za merenje talasne dužine monohromatske svetlosti. U eksperimentalnoj postavci korišćena je 2&times;2 fiber-optička račva, germanijumska (Ge) fotodioda i indijum-galijum-arsenid (InGaAs) fotodioda. Postignuta je linearnost sa faktorom korelacije R2=0.99942 i merna rezolucija od 17 pm u opsegu talasnih dužina svetlosti od 1575 do 1615 nm (L-opseg). U istom opsegu, dobijena je merna greška od približno &plusmn;0.2 nm i ponovljivost od &plusmn;0.16 nm. Ispitani su uticaji promena temperature, snage optičkog izvora i šuma na karakteristike senzorskog sistema.</p> / <p>In this thesis, a new method for measurement of monohromatic light<br />wavelength by using wavelength-dependent optical components is proposed.<br />The principle of operation of the proposed method is based on combining<br />spectral sensitivities of fiber-optic coupler and two different photodetectors.<br />Sensor system for measurement of monochromatic light wavelength is<br />implemented and characterized. Experimental setup consists of 2&times;2 fiberoptic<br />coupler, germanium (Ge) photodiode and indium-gallium-arsenide<br />(InGaAs) photodiode. Excellent linearity (R2=0.99942) and measurement<br />resolution of 17 pm are achieved in measurement range 1575-1615 nm (Lband).<br />In the same measurement range, measurement error of approximately<br />&plusmn;0.2 nm and repeatibility of &plusmn;0.16 nm are obtained. The influence of<br />temperature, optical source power and noise on sensor system characteristics<br />is investigated.</p>