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.

This masters thesis project, "Occupancy Sensor System", was conducted at Kungliga Tekniska Högskolan (KTH), Stockholm, Sweden, during the period 2007-04-24 – 2007-12-17. The goal of the project was to design an occupancy sensor system that determines if there exists more than one person in a defined region. The output of this system is for use in a context-aware system at the KTH Center for Wireless Systems (Wireless@KTH). The system is important because there is a need for specific input to context-aware systems concerning occupancy of spaces and because this thesis has focused on a problem that enables new complex and interesting services. Additionally, the specific problem of determining not only occupancy, but if this occupancy is zero, one, many has not been widely examined previously. The significance of zero occupants indicating an empty room has already been recognized as having economic and environmental value in terms of heating, ventilating, air-conditioning, and lighting. However, there has not been an effort to differentiate between a person being alone or if more than one person is present. A context-aware system might be able to use this later information to infer that a meeting is taking place in a meeting room, a class taking place in a classroom or that an individual is alone in a conference room, class room, etc. Thus enabling context-aware services to change their behavior based upon the differences in these situations. An occupancy sensor system prototype was designed to monitor a boundary by using a thermal detector, gumstix computer, an analog to digital converter prototype board, laptop computer, and a context broker. The testing and evaluation of the system, proved it to be sound. However, there are still further improvements and tests to be made. These improvements include: dynamic configuration of the system, communication between the different system entities, detection algorithms, and code improvements. Tests measuring accuracy of a detection algorithm and determining optimal detector placement need to be performed. The next step is to design applications that use the context information provided from the occupancy sensor system and expand the system to use multiple detectors. / Examensarbetet "Occupancy Sensor System" genomfördes på Kungliga Tekniska Högskolan (KTH), Stockholm, Sverige, under perioden 2007-04-24 – 2007-12-17. Målet med examensarbetet var att designa ett sensorsystem, som avgör om ett rum är befolkat med fler än en person i ett definierat område. Resultatet av detta system är till för användning i ett kontextmedvetet system som finns i KTH Center for Wireless Systems (Wireless@KTH). Systemet är viktigt eftersom det finns ett behov för specifik input till kontextmedvetna system som berör befolkning av rum och eftersom detta examensarbete har fokuserat på ett problem som möjliggör nya komplexa och intressanta tjänster. Dessutom har det inte tidigare undersökts i vidare bemärkelse hur man kan avgöra om ett rum befolkats av noll, en eller flera personer. Betydelsen av att ett rum är obefolkat har redan ansetts ha ekonomiskt och miljöbetingat värde vad gäller uppvärming, ventilation, luftkonditionering och belysning. Däremot har det inte gjorts ansträngningar att differentiera mellan att en ensam person eller flera är närvarande. Ett kontextmedvetet system skulle kunna använda den senare nämnda informationen för att dra slutsatsen att ett möte pågår i ett mötesrum, en lektion är igång i ett klassrum o.s.v. Detta möjliggör i sin tur för kontextmedvetna tjänster att ändra på sina beteenden baserat på skillnaderna i dessa situationer. En prototyp utvecklades för att övervaka en gräns genom användningen av en termisk detektor, gumstixdator, analog till digital signalkonverterare, bärbar dator och en context broker (kontextförmedlare). Testningar och utvärderingar av systemet visade att systemet var dugligt. Flera förbättringar och tester behöver dock göras i framtiden. Dessa förbättringar inkluderar: dynamisk konfiguration av systemet, kommunikation mellan de olika systementiteterna, detektionsalgoritmer och kodförbättringar. Återstående tester inkluderar mätning av en detektionsalgoritms tillförlitlighet samt optimal placering av detektorer. Nästa steg är att utveckla applikationer som använder kontextinformationen från systemet samt att utveckla systemet till att kunna använda flera detektorer.

Underwater communication within underwater sensor network is crucial for surveillance of coast and ocean areas. The aim of this report was to examine whether it is realistic to use the communication signal which is sent from one node to another as a sonar pulse, and in such case at what distances. To examine the problem, a system consisting of two nodes and one approaching target was simulated in Matlab. At first, the system tries to detect the target by using a generalized likelihood ratio test, which calculates the probability of a present target from the surrounding sounds. When a target is detected by a node, it estimates the bearing to the target by using beamforming and sends out a communication signal to the other node. The communication signal spreads out in the water, and bounces on the target before it is received by the second node. To calculate the distance, the second node decodes the signal to get the time difference, from which the distance is calculated. In the end, the target's position was estimated with a weighted least square estimator with measurements of the bearing and distance. The result shows that the distance to the target could be estimated with high precision in the given scenario, and that the width of the Cramér-Rao lower bound depends mainly on the variance of the beamforming algorithm. The maximum distance reached up to two kilometers but was mainly restricted by the detection algorithm. In conclusion, the result shows that the communication pulse can be used as a sonar pulse at the tested distances. However, the simulated scenario is a simplified version of the real world so more testing should be performed before a final conclusion can be made. / För övervakning av kust- och havsområden, vid exempelvis militära operationer eller för oceanografska observationer, används ofta ett undervattenssystem som är uppbyggt av flera noder som finns utplacerade på botten. Noderna lyssnar efter mål såsom ubåtar, fartyg etc, med syftet att kunna detektera och lokalisera dessa. Om en nod lyckas detektera ett mål så skickar den ut en akustisk kommunikationssignal till övriga noder i systemet. Målet med detta examensarbete var att undersöka om den kommunikationssignal som skickas mellan noderna också kan användas som en sonarpuls för att bestämma avståndet till målet, och därmed förbättra lokaliseringen av målets position. Under antagandet att kommunikationssignalen kan användas som sonarpuls, så undersöktes dessutom vid vilka avstånd mellan noden och målet som det var möjligt att använda signalen som sonarpuls. Resultatet visar att det är möjligt att använda kommunikationssignalen som en sonarpuls. Bäst funkar det på nära avstånd, då är den estimerade positionen i stort sett lika med det riktiga positionen. I takt med att avståndet till målet ökar så ökar även osäkerheten i vilken rikting målet befinner sig, estimeringen av avståndet höll sig däremot väldigt nära den faktiska distansen i alla simuleringar som gjordes. Simuleringen som gjordes var dock en förenkling av verkligheten, och flera av de störningsmoment som finns ute i naturen har inte tagits med i beräkningarna. För att undersöka detta så simulerades ett sensorsystem bestående av två noder tillsammans med ett mål som närmade sig noderna. Noderna försöker detektera målet genom att lyssna efter ljud som tillhör målet. Genom att mäta energinivåer i de ljudsignaler som noderna hör, så kan man utifrån sannolikhetslära bestämma hur troligt det är att det finns ett mål i närheten. När sannolikheten är tillräckligt hög säger man att ett mål detekterats. För att bestämma positionen så uppskattades målets riktning och avstånd i förhållande till noderna, som i sin tur användes för att beräkna målets position.

In our society with its aging population, the design and implementation of a highperformance distributed multi-sensor and information system for autonomous physical services become more and more important. In line with this, this thesis proposes an Intelligent Multi-Sensor System, IMSS, that surveys a human activities space to detect and identify a target for a specific service. The subject of this thesis covers three main aspects related to the set-up of an IMSS: an improved depth measurement and reconstruction method and its related uncertainty, a surveillance and tracking algorithm and finally a way to validate and evaluate the proposed methods and algorithms. The thesis discusses how a model of the depth spatial quantisation uncertainty can be implemented to optimize the configuration of a sensor system to capture information of the target objects and their environment with required specifications. The thesis introduces the dithering algorithm which significantly reduces the depth reconstruction uncertainty. Furthermore, the dithering algorithm is implemented on a sensor-shifted stereo camera, thus simplifying depth reconstruction without compromising the common stereo field of view. To track multiple targets continuously, the Gaussian Mixture Probability Hypothesis Density, GM-PHD, algorithm is implemented with the help of vision and Radio Frequency Identification, RFID, technologies. The performance of the tracking algorithm in a vision system is evaluated by a circular motion test signal. The thesis introduces constraints to the target space, the stereo pair characteristics and the depth reconstruction accuracy to optimize the vision system and to control the performance of surveillance and 3D reconstruction through integer linear programming. The human being within the activity space is modelled as a tetrahedron, and a field of view in spherical coordinates are used in the control algorithms. In order to integrate human behaviour and perception into a technical system, the proposed adaptive measurement method makes use of the Fuzzily Defined Variable, FDV. The FDV approach enables an estimation of the quality index based on qualitative and quantitative factors for image quality evaluation using a neural network. The thesis consists of two parts, where Part I gives an overview of the applied theory and research methods used, and Part II comprises the eight papers included in the thesis.

Le risque de chute provoqué par le phénomène épisodique de ‘Freeze of Gait’ (FoG) est un symptôme commun de la maladie de Parkinson. Cette étude concerne la détection et le diagnostic des épisodes de FoG à l'aide d'un prototype multi-capteurs. La première contribution est l'introduction de nouveaux capteurs (télémètres et goniomètres) dans le dispositif de mesure pour la détection des épisodes de FoG. Nous montrons que l'information supplémentaire obtenue avec ces capteurs améliore les performances de la détection. La seconde contribution met œuvre un algorithme de détection basé sur des réseaux de neurones gaussiens. Les performance de cet algorithme sont discutées et comparées à l'état de l'art. La troisième contribution est développement d'une approche de modélisation probabiliste basée sur les réseaux bayésiens pour diagnostiquer le changement du comportement de marche des patients avant, pendant et après un épisode de FoG. La dernière contribution est l'utilisation de réseaux bayésiens arborescents pour construire un modèle global qui lie plusieurs symptômes de la maladie de Parkinson : les épisodes de FoG, la déformation de l'écriture et de la parole. Pour tester et valider cette étude, des données cliniques ont été obtenues pour des patients atteints de Parkinson. Les performances en détection, classification et diagnostic sont soigneusement étudiées et évaluées. / Freezing of Gait (FoG) is an episodic phenomenon that is a common symptom of Parkinson's disease (PD). This research is headed toward implementing a detection, diagnosis and correction system that prevents FoG episodes using a multi-sensor device. This particular study aims to detect/diagnose FoG using different machine learning approaches. In this study we validate the choice of integrating multiple sensors to detect FoG with better performance. Our first level of contribution is introducing new types of sensors for the detection of FoG (telemeter and goniometer). An advantage in our work is that due to the inconsistency of FoG events, the extracted features from all sensors are combined using the Principal Component Analysis technique. The second level of contribution is implementing a new detection algorithm in the field of FoG detection, which is the Gaussian Neural Network algorithm. The third level of contribution is developing a probabilistic modeling approach based on Bayesian Belief Networks that is able to diagnosis the behavioral walking change of patients before, during and after a freezing event. Our final level of contribution is utilizing tree-structured Bayesian Networks to build a global model that links and diagnoses multiple Parkinson's disease symptoms such as FoG, handwriting, and speech. To achieve our goals, clinical data are acquired from patients diagnosed with PD. The acquired data are subjected to effective time and frequency feature extraction then introduced to the different detection/diagnosis approaches. The used detection methods are able to detect 100% of the present appearances of FoG episodes. The classification performances of our approaches are studied thoroughly and the accuracy of all methodologies is considered carefully and evaluated

Value of leather produced from sheep is determined by its quality and looseness is one of the quality attributes that determines the value of the leather. As of now, looseness in sheep skin can be determined only after the tanning process is done and it is a long and expensive process to treat the looseness in skins after the tanning process. An interdigital sensor based sensing system has been developed which works on the principle of sensing technique based on interaction of electric field with the materials under test. Finite element software has been used for analysis and design of sensors. It has been reported that a good correlation was found between the actual looseness values and calculated looseness values.

The widespread use of Liquid Petroleum Gas (LPG) for cooking and as fuel for automobile vehicles requires fast and selective detection of LPG to precisely measure the leakage of gas for preventing the occurrence of accidental explosions. The adoption of Micro-Electro-Mechanical-System (MEMS) technology for fabricating the gas sensor provides other potential advantages for sensing applications, which includes low power consumption, low fabrication cost, high quality, small size and reliability. MEMS based gas sensor requires a sensitive layer of oxide material like ZnO, SnO2, TiO2, Fe2O3, etc. The tin oxide material used in the present work changes its electrical properties, as it interacts with the reducing gas like LPG. The sensor material becomes active only at high temperature such as 400ºC, thereby realizing the need of a micro heater to reach the desired temperature. To control the temperature of micro heater and to determine the change in electrical properties of the sensor due to its interaction with LPG an Application Specific Integrated Circuit (ASIC) forms an essential constituent of the MEMS based gas sensor. In the present work, an attempt has been made to improve the sensitivity of LPG gas sensor and it is correlated with other properties by different characterization techniques. The work also includes the design as well as testing of ASIC for gas sensor system. Process parameters particularly deposition time and substrate temperature have a profound influence on the microstructure of the tin oxide film, which in turn affects the gas sensing properties. To study the effects of these parameters, RF magnetron sputtering system is used for depositing tin oxide films onto the silicon substrate, which is compatible with CMOS technology. The effects of structural properties, optical properties and the porosity of the films are also studied and correlated with the gas sensing properties. In this direction the deposited films are characterized using X-Ray Diffraction (XRD) to determine the structure orientation. The morphology of the sensor films are analyzed by Scanning Electron Microscope (SEM) while the refractive index, thickness and porosity of the films are determined using ellipsometry studies. The thickness of the deposited films is also confirmed by the surface profilometer. The change in composition of the deposited film along its depth is determined using Secondary Ion Mass Spectrometer (SIMS). Maximum sensitivity 5.5 is obtained for 470 nm thick films, which corresponds to a grain size of 38nm at the operating temperature of 4000C. Following these studies, an ASIC has been designed using Tanner EDA Tools on AMIS 0.7 µm CMOS process, fabricated through Euro practice’s ASIC prototyping service, Belgium and tested successfully after fabrication. The temperature control module of ASIC has been designed using relaxation oscillator technique to control the temperature of the in house developed heater. The resistance to period conversion technique is explored for the design of the sensor read out module of ASIC. The heater is integrated successfully with the sensor film, ASIC and microcontroller based LCD module. The test results show good agreement with the simulation results.

Poor water quality is a global health concern affecting one billion people around the world. It is important to monitor water sources in order to maintain the quality of our drinking water and to avoid disease outbreaks. Targeting Escherichia coli as a faecal indicator is a widely used procedure, but the current methods are time consuming and not adequate to prevent spreading of faecal influence.   This Master thesis demonstrates the development of a near infrared fluorescence flow cytometer sensor system targeting Escherichia coli, using fluorescently labeled chicken IgY antibodies. The near infrared light was chosen to avoid fluorescence from blue-green algae that are present in the water source.   The hardware was developed with a 785  nm laser line to detect Alexa Fluor 790 labeled antibodies, using a photomultiplier tube or two different CMOS cameras. The antibodies were labeled using a commercial labeling kit, and evaluated using antibody binding assays and the developed hardware.   The IgY antibodies were successfully labeled with Alexa Fluor 790 and the function was maintained after the labeling process. The result demonstrates the principles of the sensor system and how it solved to the problem with fluorescence from blue-green algae. An aperture was used to overcome the suboptimal laser and filter setup, and to increase the sensitivity of the system. However, only a small fraction of the cells could be detected, due to challenges with the focal depth and loss of sensitivity in the photomultiplier tube at near infrared wavelengths. Further development is required to create a working product.

With the proliferation of industries world-wide, there is a growing need and interest in sensing and monitoring environmental pollutants and monitoring the concentration of chemicals/gases in industrial process control. There is also an increasing demand for chemical sensors in other applications such as home security, breath analysis and food processing. Design and development of metal-oxide based gas sensor system is reported in this thesis. The system consists of three components viz. micro heater(which aids inheating the sensor film to required temperatures), CMOS ASIC (the sensor interface circuit) and the thin film transducer(a semiconducting metal oxide thin film whose resistance changes with the concentration of the target gas). Microheaters were realized through PolyMUMPs process. Thermal characterization of surface-micromachined microheaters is carried out from their dynamic response to electrothermal excitations. An electrical equivalent circuit model is developed for the thermo-mechanical system. The mechanical parameters are extracted from the frequency response obtained using a Laser Doppler Vibrometer. The resonant frequencies of the microheaters are measured and compared with FEM simulations. The thermal time constants are obtained from the electrical equivalent model by fitting the model response to the measured frequency response. Microheaters with an active area of140m × 140m have been realized on two different layers(poly-1 andpoly-2) with two different air-gaps (2m and 2.75m). The effective time constants, combining thermal and mechanical responses, are intherangeof0.13msto0.22msforheatersonpoly-1,and1.9s to0.15ms for microheaters on poly-2 layer. The thermal time constants of the best microheaters are in the range of a few s, thus making them suitable for sensor applications that need faster thermal response. The mechanical deformation of the microheaters subjected to an electrothermal excitation, due to thermal stress, is also analyzed using lensless in-line digital holographic microscopy (DHM). The numerically reconstructed holographic images of the micro-heaters clearly indicate the regions under high stress. Double exposure method has been used to obtain the quantitative measurements of the deformations, from the phase analysis of the hologram fringes. The measured deformations correlate well with the theoretical values predicted by a thermo-mechanical analytical model. The results show that lensless in-line DHM with Fourier analysis is an effective method for evaluating the thermo-mechanical characteristics of MEMS components. A sensor interface circuit comprising a resistance-to-time period converter as the front-end circuit and a proportional temperature controller to control the microheater temperature is designed and realized in 130nm UMC CMOS technology. The impact of biasing the transistors in subthreshold versus saturation conditions on analog circuit performance is systematically analyzed. A cascode current mirror, designed in 130nm CMOS technology, is biased in subthreshold and saturation regions and its performance has been analyzed through rigorous analytical modeling. The analytical results have been validated with SPICE simulations. It is demonstrated that the subthreshold operation provides better performance in terms of linearity, power, area, output impedance and tolerance to temperature variation, making it a preferable option for applications such as signal conditioning circuitry for environmental sensors. On the other hand, biasing the circuit in saturation is preferable for applications like transceivers and data converters where high bandwidth, SNR and low sensitivity to process variations are the key requirements. Based on this analysis, a sensor interface circuit has been prototyped for resistance measurement on 130nm CMOS technology, using subthreshold cascode current mirrors as the key building blocks. This current mirror results in 14X lower power compared to above-threshold operation. The interface circuit spans 5 orders of magnitude of resistance, and consumes an ultra low power of 326W. A proportional temperature controller with an integrated on-chip power MOSFET is also realized on the same chip for heating and temperature control of microheaters. The microheater is reused as temperature sensor. The entire circuit works with 1.2V supply, except the power MOSFET and the heater driver circuit, which operate with 3.3V supply. ZnO, a semiconducting metal-oxide, is used as the sensing material. Thin films of ZnO are spin-coated over insulating substrates using sol-gel processing technique. Gold pads deposited over the sensing film act as electrodes. The sensor film is characterized at different temperatures for its sensitivity to ethanol. A peak response of 14% change in resistance is observed for 5ppm ethanol, at a working temperature of 275◦C.

Die Erweiterung experimenteller Infrastrukturen um neuartige Sensor eröffnen die Möglichkeit, qualitativ neuartige Erkenntnisse zu gewinnen. Um diese Informationen vollständig zu erschließen ist ein Abdecken der gesamten Verarbeitungskette von der Datenauslese bis zu anwendungsbezogenen Auswertung erforderlich. Eine Erweiterung bestehender wissenschaftlicher Instrumente beinhaltet die strukturelle und zeitbezogene Integration der neuen Sensordaten in das Bestandssystem. Das hier vorgestellte Framework bietet durch seinen flexiblen Ansatz das Potenzial, unterschiedliche Sensortypen in unterschiedliche, leistungsfähige Plattformen zu integrieren. Zwei unterschiedliche Integrationsansätze zeigen die Flexibilität dieses Ansatzes, wobei einer auf die Steigerung der Sensitivität einer Anlage zur Sekundärionenmassenspektroskopie und der andere auf die Bereitstellung eines Prototypen zur Untersuchung von Rezyklaten ausgerichtet ist. Die sehr unterschiedlichen Hardwarevoraussetzungen und Anforderungen der Anwendung bildeten die Basis zur Entwicklung eines flexiblen Softwareframeworks. Um komplexe und leistungsfähige Applikationsbausteine bereitzustellen wurde eine Softwaretechnologie entwickelt, die modulare Pipelinestrukturen mit Sensor- und Ausgabeschnittstellen sowie einer Wissensbasis mit entsprechenden Konfigurations- und Verarbeitungsmodulen kombiniert.:1. Introduction 2. Hardware Architecture and Application Background 3. Software Concept 4. Experimental Results 5. Conclusion and Outlook / Novel sensors with the ability to collect qualitatively new information offer the potential to improve experimental infrastructure and methods in the field of research technology. In order to get full access to this information, the entire range from detector readout data transfer over proper data and knowledge models up to complex application functions has to be covered. The extension of existing scientific instruments comprises the integration of diverse sensor information into existing hardware, based on the expansion of pivotal event schemes and data models. Due to its flexible approach, the proposed framework has the potential to integrate additional sensor types and offers migration capabilities to high-performance computing platforms. Two different implementation setups prove the flexibility of this approach, one extending the material analyzing capabilities of a secondary ion mass spectrometry device, the other implementing a functional prototype setup for the online analysis of recyclate. Both setups can be regarded as two complementary parts of a highly topical and ground-breaking unique scientific application field. The requirements and possibilities resulting from different hardware concepts on one hand and diverse application fields on the other hand are the basis for the development of a versatile software framework. In order to support complex and efficient application functions under heterogeneous and flexible technical conditions, a software technology is proposed that offers modular processing pipeline structures with internal and external data interfaces backed by a knowledge base with respective configuration and conclusion mechanisms.:1. Introduction 2. Hardware Architecture and Application Background 3. Software Concept 4. Experimental Results 5. Conclusion and Outlook