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  • 1.
    Larsson, Fredrik
    et al.
    Linköping University, Department of Computer and Information Science. Linköping University, Faculty of Science & Engineering.
    Snögren, Hannes
    Linköping University, Department of Computer and Information Science. Linköping University, Faculty of Science & Engineering.
    Gustafsson, Sebastian
    Linköping University, Department of Computer and Information Science. Linköping University, Faculty of Science & Engineering.
    Qvigstad, Magnus
    Linköping University, Department of Computer and Information Science. Linköping University, Faculty of Science & Engineering.
    Lindholm, Hugo
    Linköping University, Department of Computer and Information Science. Linköping University, Faculty of Science & Engineering.
    Eriksson, Rasmus
    Linköping University, Department of Computer and Information Science. Linköping University, Faculty of Science & Engineering.
    Implementation av mätsystem för dricksvattenkvalitet2015Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [sv]

    Följande rapport behandlar konstruktionen av ett system som kontinuerligt ska analysera kvaliteten på vatten. Systemet är uppdelat i mätenheter som utför själva mätningen och en centraliserad server som man kan koppla upp sig mot för att övervaka/justera sina mätenheter.

    Uppdragsgivaren till projektet var forskare från IFM på Linköpings universitet. De hade sedan tidigare ett fungerande system för att analysera vatten kontinuerligt. Vår uppgift var att ersätta deras system med ett nytt, som var baserat på mindre och billigare hårdvara. Vi har visat att systemet går att implementera på den önskade hårdvaran.

    Rapporten skildrar även hur projektgruppen tog designbeslut under utvecklingsfasen. Denna designbeslutsprocess och de konsekvenser den fick för slutprodukten analyseras.

  • 2.
    Lindholm, Hugo
    Linköping University, Department of Computer and Information Science, Software and Systems.
    Map Matching to road segments using Hidden Markov Model with GNSS, Odometer and Gyroscope2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In this thesis the Hidden Markov Model (HMM) is used in the process of map matching to investigate the accuracy for road segment map matching. A few HMM algorithms using a Global Navigation Satellite System (GNSS) receiver, odometer and gyroscope sensors are presented. The HMM algorithms are evaluated on four accuracy metrics. Two of these metrics have been seen in previous literature and captures road map match accuracy. The other have not been seen before and captures road segment accuracy. In the evaluation process a dataset is created by simulation to achieve positional ground truth for each sensor measurement. The accuracy distribution for different parts of the map matched trajectory is also evaluated. The result shows that HMM algorithms presented in previous literature, falls short to capture the accuracy for road segment map matching. The results further shows that by using less noisy sensors, as odometer and gyroscope, the accuracy for road segment map matching can be increased.

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