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Phone Call Detection Based on Smartphone Sensor Data

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Cloud Computing and Security (ICCCS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10039))

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Abstract

Smartphones are now equipped with as many as 30 embedded sensors, which have been widely used in human activity recognition, context monitoring, and localization. In this paper, we propose a phone call detection scheme using smartphone sensor data. We design Android applications to record, upload and display smartphone sensor data. We show how proximity and orientation sensors together can be used to accurately predict phone calls. Furthermore, the activity state during a phone call can be classified into three categories: sitting/standing, lying down, and walking. Features are extracted from proximity and orientation sensors to determine the range of values satisfying each state. Our system achieves an overall accuracy of 85 %.

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Authors and Affiliations

  1. Department of Computer Science, New York University, New York, NY, 10012, USA

    Huiyu Sun & Suzanne McIntosh

Authors
  1. Huiyu Sun
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  2. Suzanne McIntosh
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Corresponding author

Correspondence to Huiyu Sun .

Editor information

Editors and Affiliations

  1. University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Michigan State University , EAST LANSING, Michigan, USA

    Alex Liu

  3. National Dong Hwa University , Shoufeng, Taiwan

    Han-Chieh Chao

  4. Purdue University , West Lafayette, Indiana, USA

    Elisa Bertino

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Sun, H., McIntosh, S. (2016). Phone Call Detection Based on Smartphone Sensor Data. In: Sun, X., Liu, A., Chao, HC., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2016. Lecture Notes in Computer Science(), vol 10039. Springer, Cham. https://doi.org/10.1007/978-3-319-48671-0_26

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  • DOI: https://doi.org/10.1007/978-3-319-48671-0_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48670-3

  • Online ISBN: 978-3-319-48671-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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