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Indoor pedestrian navigation system using a modern smartphone

Published:07 September 2010Publication History

ABSTRACT

In this work we present a pedestrian navigation system for indoor environments based on the dead reckoning positioning method, 2D barcodes, and data from accelerometers and magnetometers. All the sensing and computing technologies of our solution are available in common smart phones. The need to create indoor navigation systems arises from the inaccessibility of the classic navigation systems, such as GPS, in indoor environments.

References

  1. Kougori, M. and Kurata, T. 2003. Personal Positioning based on walking locomotion Analysis with self-contained sensor and a wearable camera. In Proceedings of ISMAR2003, 103--112 Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Krach, B. and Robertson, P. 2008. Integration of Foot-Mounted Inertial Sensors into a Bayesian Location Estimation Framework. In Proceedings of 5th Workshop on Positioning, Navigation and Communication 2008 (WPNC 2008), Hannover, Germany.Google ScholarGoogle ScholarCross RefCross Ref
  3. Woodman, O. and Harle, R. 2008. Pedestrian Localisation for Indoor Environments. In Proceedings of the 10th International Conference on Ubiquitous Computing (UbiComp), Seoul, Korea, ACM 2008, 114--123 Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Indoor pedestrian navigation system using a modern smartphone

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      • Published in

        cover image ACM Other conferences
        MobileHCI '10: Proceedings of the 12th international conference on Human computer interaction with mobile devices and services
        September 2010
        552 pages
        ISBN:9781605588353
        DOI:10.1145/1851600
        • General Chairs:
        • Marco de Sá,
        • Luís Carriço,
        • Program Chair:
        • Nuno Correia

        Copyright © 2010 Copyright is held by the author/owner(s)

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 7 September 2010

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        Acceptance Rates

        MobileHCI '10 Paper Acceptance Rate46of225submissions,20%Overall Acceptance Rate202of906submissions,22%

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