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Smartphone-based Acoustic Indoor Space Mapping

S. Pradhan,Ghufran Baig,Wenguang Mao,L. Qiu,Guohai Chen,Bo Yang

Published 2018 in Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies

ABSTRACT

Constructing a map of indoor space has many important applications, such as indoor navigation, VR/AR, construction, safety, facility management, and network condition prediction. Existing indoor space mapping requires special hardware (e.g., indoor LiDAR equipment) and well-trained operators. In this paper, we develop a smartphone-based indoor space mapping system that lets a regular user quickly map an indoor space by simply walking around while holding a phone in his/her hand. Our system accurately measures the distance to nearby reflectors, estimates the user's trajectory, and pairs different reflectors the user encounters during the walk to automatically construct the contour. Using extensive evaluation, we show our contour construction is accurate: the median errors are 1.5 cm for a single wall and 6 cm for multiple walls (due to longer trajectory and the higher number of walls). We show that our system provides a median error of 30 cm and a 90-percentile error of 1 m, which is significantly better than the state-of-the-art smartphone acoustic mapping system BatMapper [64], whose corresponding errors are 60 cm and 2.5 m respectively, even after multiple walks. We further show that the constructed indoor contour can be used to predict wireless received signal strength (RSS).

PUBLICATION RECORD

  • Publication year

    2018

  • Venue

    Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies

  • Publication date

    2018-07-05

  • Fields of study

    Computer Science, Engineering, Environmental Science

  • Identifiers
    DOI 10.1145/3214278
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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