Finding the Right Match: Human Cognition via Indoor Route Descriptions Versus Existing Indoor Networks and Algorithms to Support Navigation | SpringerLink
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Finding the Right Match: Human Cognition via Indoor Route Descriptions Versus Existing Indoor Networks and Algorithms to Support Navigation

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Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017) (COSIT 2017)

Part of the book series: Lecture Notes in Geoinformation and Cartography ((LNGC))

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Abstract

This working paper aims to compare existing approaches in indoor navigation. In this we focus on networks and algorithms to respectively model the indoor space and to calculate routes. This is compared with crowdsourced and text-based route instructions. As such the goal is to develop and evaluate an indoor solution that can generate indoor networks and route descriptions which are in line with human intuition, which is a consequence of cognition.

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Notes

  1. 1.

    GML = Geography Markup Language.

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Author information

Authors and Affiliations

  1. Department of Geography, Ghent University, Krijgslaan 281 (S8), 9000, Ghent, Belgium

    Kristien Ooms & Nico Van de Weghe

Authors
  1. Kristien Ooms
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  2. Nico Van de Weghe
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Corresponding author

Correspondence to Kristien Ooms .

Editor information

Editors and Affiliations

  1. Department of Geodesy and Geoinformation, Vienna University of Technology(TU-Wien), Wien, Austria

    Paolo Fogliaroni

  2. Department of Geography, Birkbeck, University of London, London, Middlesex, United Kingdom

    Andrea Ballatore

  3. Department of Industrial and Information Engineering and Economics, University of L'Aquila , L'Aquila, Italy

    Eliseo Clementini

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Ooms, K., Van de Weghe, N. (2018). Finding the Right Match: Human Cognition via Indoor Route Descriptions Versus Existing Indoor Networks and Algorithms to Support Navigation. In: Fogliaroni, P., Ballatore, A., Clementini, E. (eds) Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017). COSIT 2017. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-63946-8_32

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