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MobiSens: A Versatile Mobile Sensing Platform for Real-World Applications

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Abstract

We present the design, implementation and evaluation of MobiSens, a versatile mobile sensing platform for a variety of real-life mobile sensing applications. MobiSens addresses common requirements of mobile sensing applications on power optimization, activity segmentation, recognition and annotation, interaction between mobile client and server, motivating users to provide activity labels with convenience and privacy concerns. After releasing three versions of MobiSens to the Android Market with evolving UI and increased functionalities, we have collected 13,993 h of data from 310 users over five months. We evaluate and compare the user experience and the sensing efficiency in each release. We show that the average number of activities annotated by a user increases from 0.6 to 6. This result indicates the activity auto-segmentation/recognition feature and certain UI design changes significantly improve the user experience and motivate users to use MobiSens more actively. Based on the MobiSens platform, we have developed a range of mobile sensing applications including Mobile Lifelogger, SensCare for assisted living, Ground Reporting for soldiers to share their positions and actions horizontally and vertically, and CMU SenSec, a behavior-driven mobile Security system.

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Notes

  1. The data reported are based on the average performance of three Motorola Droid “Milestone” used in our experiment, the performance may vary between phones from different manufacturers.

  2. The upload cycle varies from 1 to 3 h during the whole experiment

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Acknowledgements

This research was supported by CyLab at Carnegie Mellon under grants DAAD19-02-1-0389 and W911NF-09-1-0273, from the Army Research Office (ARO), Nokia research award on “Mobile Sensing and Behavior Modeling for Social Computing,” Google research award on “Social Behavior Sensing and Reality Mining,” and a Cisco research award on “Behavior Modeling for Human Network.” The views and conclusions contained here are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either express or implied, of ARO, CMU, Nokia, Google, or Cisco.

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  1. Carnegie Mellon University, Silicon Valley Campus, NASA Research Park, Bldg. 23 (MS 23-11), P.O. Box 1, Moffett Field, CA 94035, USA

    Pang Wu, Jiang Zhu & Joy Ying Zhang

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  1. Pang Wu
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Correspondence to Pang Wu.

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Wu, P., Zhu, J. & Zhang, J.Y. MobiSens: A Versatile Mobile Sensing Platform for Real-World Applications. Mobile Netw Appl 18, 60–80 (2013). https://doi.org/10.1007/s11036-012-0422-y

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