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Poster: Understanding Mobile User Interactions with the IoT

Published:25 June 2016Publication History

ABSTRACT

The increasing reach of the Internet of Things (IoT) is leading to a world rich in sensors [3] that can be used to support physical analytics -- analogous to web analytics but targeted at user interactions with physical devices in the real-world (e.g. [2]). In contrast to web analytics, physical analytics systems typically only provide data relating to sensors and objects without consideration of individual users. This is mainly a consequence of an inability to track individual mobile user interactions across multiple physical objects (or across sessions of interaction with a single object) using, for example, an analogue of a web cookie. Indeed, such a "physical analytics cookie" could raise significant privacy concerns.

However, in many cases a more "human-centric" approach to analytics would enable us to provide new and interesting insights into interactions between mobile users and the physical world [1]. In our work we endeavour to leverage synthetic user traces of human mobility, and data from real IoT systems, to provide such insights.

References

  1. Lee, Y., and Balan, R. K. The case for human-centric personal analytics. In Proceedings of WPA'14 (New York, NY, USA, 2014), pp. 25--29. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Mikusz, M., Clinch, S., Jones, R., Harding, M., Winstanley, C., and Davies, N. Repurposing web analytics to support the IoT. Computer 48, 9 (Sept 2015), 42--49.Google ScholarGoogle Scholar
  3. Want, R., Schilit, B. N., and Jenson, S. Enabling the internet of things. Computer 48, 1 (Jan 2015), 28--35.Google ScholarGoogle ScholarCross RefCross Ref

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      • Published in

        cover image ACM Conferences
        MobiSys '16 Companion: Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Companion
        June 2016
        172 pages
        ISBN:9781450344166
        DOI:10.1145/2938559

        Copyright © 2016 Owner/Author

        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 25 June 2016

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        Overall Acceptance Rate274of1,679submissions,16%
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