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Inferring Phone Location State

  • Author(s): Chen, S
  • Park, W
  • Yang, J
  • Wagner, D
  • et al.

Published Web Location

https://people.eecs.berkeley.edu/~daw/papers/phoneloc-stwimob18.pdf
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Abstract

© 2018 IEEE. Smartphone sensors are becoming more universal and more accurate. In this paper, we aim to distinguish between four common positions or states a phone can be in: in the hand, pocket, backpack, or on a table. Using a uniquely designed neural network and data from the accelerometer and the screen state, we achieve a 92% accuracy on the same phone. We also explore extending this to different phones and propose an acceleration calibration technique to do so.

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