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Transportation mode detection based on mobile sensor data

Jasna Urbančič (2018) Transportation mode detection based on mobile sensor data. MSc thesis.

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    This thesis addresses transportation mode detection based primarily on mobile phone data using machine learning methods. Our approach uses short samples of accelerometer readings taken while traveling in a vehicle to distinguish between three modalities --- car, bus, and train. We use gravity estimation to pre-process the samples. We extract features from statistical, frequency-based, and peak-based domain. With statistical analysis of the features we gain an introspective into the data. To additionally analyze the features we construct several feature sets for classification. As a classifier we use random forest, support vector machine, and neural network. Our approach correctly classifies 65% cars, 63% buses, and 18% trains using neural network.

    Item Type: Thesis (MSc thesis)
    Keywords: machine learning, mobile sensing, data mining, pattern recognition, intelligent transportation systems
    Number of Pages: 75
    Language of Content: English
    Mentor / Comentors:
    Name and SurnameIDFunction
    doc. dr. Veljko PejovićMentor
    prof. dr. Dunja MladenićComentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1538102979)
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 4325
    Date Deposited: 27 Nov 2018 15:38
    Last Modified: 21 Jan 2019 09:29
    URI: http://eprints.fri.uni-lj.si/id/eprint/4325

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