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International Conference on E-Business and Telecommunications

ICETE 2013: E-Business and Telecommunications pp 369–384Cite as

Automatic Geographic Enrichment by Multi-modal Bike Sensing

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 456))

Abstract

This paper focuses on the automatic geo-annotation of road/terrain types by collaborative bike sensing. The proposed terrain classification system is mainly based on the analysis of volunteered geographic information gathered by cyclists. By using participatory accelerometer and GPS sensor data collected from the cyclists’ smartphones, which is enriched with image data from geographic web services or the smartphone camera, the proposed system is able to distinguish between 6 different terrain types. For the classification of the multi-modal bike data, the system employs a random decision forest (RDF), which compared favorably for the geo-annotation task against different classification algorithms. The system classifies the features of every instance of road (over a 5 seconds interval) and maps the results onto the corresponding GPS coordinates. Finally, based on all the collected instances, we can annotate geographic maps with the terrain types, create more advanced route statistics and facilitate geo-based recommender systems. The accuracy of the bike sensing system is 92 % for 6-class terrain classification. For the 2-class on-road/off-road classification an accuracy of 97 % is achieved, almost six percent above the state-of-the-art in this domain.

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Author information

Authors and Affiliations

  1. Multimedia Lab – ELIS Department, Ghent University - iMinds, Gaston Crommenlaan 8, Bus 201, Ledeberg, Ghent, Belgium

    Steven Verstockt, Viktor Slavkovikj, Pieterjan De Potter, Olivier Janssens & Rik Van de Walle

  2. Electronics and Information Technology Lab, ISP, Ghent University, Graaf Karel de Goedelaan 5, 8500, Kortrijk, Belgium

    Olivier Janssens

  3. Barco NV, President Kennedypark 35, 8500, Kortrijk, Belgium

    Jürgen Slowack

Authors
  1. Steven Verstockt
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  2. Viktor Slavkovikj
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  3. Pieterjan De Potter
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  4. Olivier Janssens
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  5. Jürgen Slowack
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  6. Rik Van de Walle
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Corresponding author

Correspondence to Steven Verstockt .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Monmouth University, West Long Branch, New Jersey, USA

    Mohammad S. Obaidat

  2. Polytechnic Institute of Setúbal, INSTICC, Setúbal, Portugal

    Joaquim Filipe

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Verstockt, S., Slavkovikj, V., De Potter, P., Janssens, O., Slowack, J., Van de Walle, R. (2014). Automatic Geographic Enrichment by Multi-modal Bike Sensing. In: Obaidat, M., Filipe, J. (eds) E-Business and Telecommunications. ICETE 2013. Communications in Computer and Information Science, vol 456. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44788-8_22

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  • DOI: https://doi.org/10.1007/978-3-662-44788-8_22

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-44787-1

  • Online ISBN: 978-3-662-44788-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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