Citation
Ye-Sheng Kuo, Pat Pannuto, Ko-Jen Hsiao, Prabal Dutta. "Indoor Positioning with Mobile Phones and Visible Light". ACM MobiCom: The 20th Annual International Conference on Mobile Computing and Networking, ACM, 7, September, 2014.

Abstract
We explore the indoor positioning problem with unmodified smartphones and slightly-modified commercial LED luminaries. The luminaries, modified to allow rapid, on-off keying, transmit their identifiers and/or locations encoded in human-imperceptible optical pulses. A camera-equipped smartphone, using just a single camera image frame capture, can detect the presence of the luminaires in the image, decode their transmitted identifiers and/or locations, and determine the smartphone's location and orientation relative to the luminaires. The key insights underlying this work are (i) the driver circuits of emerging LED lighting systems can be trivially modified to transmit data through on-off keying; (ii) the rolling shutter effect of CMOS imagers, which normally results in motion blur, can be leveraged to receive many bits of data encoded in the optical transmissions with just a single frame capture, (iii) a camera is intrinsically an angle-ofarrival sensor, so the projection of multiple light sources with known positions onto a camera's image plane can be framed as an instance of a sufficiently-constrained angle-of-arrival localization problem, and (iv) this problem can be solved with optimization techniques. We explore the feasibility of the design through an analytical model, demonstrate the viability of the design through a prototype system, identify the challenges to a practical deployment including lighting density and camera constraints, and offer suggestions to better support such indoor positioning schemes through simple enhancements to smartphone APIs.

Electronic downloads

• https://www.src.org/library/publication/p069954/. (Link to paper on SRC website.)
• http://dx.doi.org/10.1145/2639108.2639109

• HTML

  Ye-Sheng Kuo, Pat Pannuto, Ko-Jen Hsiao, Prabal Dutta. <a
  href="http://www.terraswarm.org/pubs/304.html"
  >Indoor Positioning with Mobile Phones and Visible
  Light</a>, ACM MobiCom: The 20th Annual International
  Conference on Mobile Computing and Networking, ACM, 7,
  September, 2014.

• Plain text

  Ye-Sheng Kuo, Pat Pannuto, Ko-Jen Hsiao, Prabal Dutta.
  "Indoor Positioning with Mobile Phones and Visible
  Light". ACM MobiCom: The 20th Annual International
  Conference on Mobile Computing and Networking, ACM, 7,
  September, 2014.

• BibTeX

  @inproceedings{KuoPannutoHsiaoDutta14_IndoorPositioningWithMobilePhonesVisibleLight,
      author = {Ye-Sheng Kuo and Pat Pannuto and Ko-Jen Hsiao and
                Prabal Dutta},
      title = {Indoor Positioning with Mobile Phones and Visible
                Light},
      booktitle = {ACM MobiCom: The 20th Annual International
                Conference on Mobile Computing and Networking},
      organization = {ACM},
      day = {7},
      month = {September},
      year = {2014},
      abstract = {We explore the indoor positioning problem with
                unmodified smartphones and slightly-modified
                commercial LED luminaries. The luminaries,
                modified to allow rapid, on-off keying, transmit
                their identifiers and/or locations encoded in
                human-imperceptible optical pulses. A
                camera-equipped smartphone, using just a single
                camera image frame capture, can detect the
                presence of the luminaires in the image, decode
                their transmitted identifiers and/or locations,
                and determine the smartphone's location and
                orientation relative to the luminaires. The key
                insights underlying this work are (i) the driver
                circuits of emerging LED lighting systems can be
                trivially modified to transmit data through on-off
                keying; (ii) the rolling shutter effect of CMOS
                imagers, which normally results in motion blur,
                can be leveraged to receive many bits of data
                encoded in the optical transmissions with just a
                single frame capture, (iii) a camera is
                intrinsically an angle-ofarrival sensor, so the
                projection of multiple light sources with known
                positions onto a camera's image plane can be
                framed as an instance of a
                sufficiently-constrained angle-of-arrival
                localization problem, and (iv) this problem can be
                solved with optimization techniques. We explore
                the feasibility of the design through an
                analytical model, demonstrate the viability of the
                design through a prototype system, identify the
                challenges to a practical deployment including
                lighting density and camera constraints, and offer
                suggestions to better support such indoor
                positioning schemes through simple enhancements to
                smartphone APIs.},
      URL = {http://terraswarm.org/pubs/304.html}
  }
  

Posted by Barb Hoversten on 21 Apr 2014.
Groups: services