Smartwatch has become one of the most popular wearable computers on the market. We conduct an IRB-approved measurement study involving 27 Android smartwatch users. Using a 106-day dataset collected from our participants, we perform indepth characterization of three key aspects of smartwatch usage "in the wild": usage patterns, energy consumption, and network traffic. Based on our findings, we identify key aspects of the smartwatch ecosystem that can be further improved, propose recommendations, and point out future research directions.
|Original language||English (US)|
|Title of host publication||MobiSys 2017 - Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services|
|Publisher||Association for Computing Machinery, Inc|
|Number of pages||14|
|State||Published - Jun 16 2017|
|Event||15th ACM International Conference on Mobile Systems, Applications, and Services, MobiSys 2017 - Niagara Falls, United States|
Duration: Jun 19 2017 → Jun 23 2017
|Name||MobiSys 2017 - Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services|
|Conference||15th ACM International Conference on Mobile Systems, Applications, and Services, MobiSys 2017|
|Period||6/19/17 → 6/23/17|
Bibliographical noteFunding Information:
We would like to thank the smartwatch users at Indiana University Bloomington who voluntarily participated in our user study. The user study devices were sponsored by Indiana University Bloomington. We also thank the MobiSys reviewers and especially Elizabeth M. Belding for shepherding the paper. Feng Qian's research was supported in part by NSF Award #1629347. Felix Xiaozhu Lin was supported in part by NSF Award #1464357 and a Google Faculty Award. Kai Chen was supported in part by NSFC U1536106, 61100226, Youth Innovation Promotion Association CAS, and strategic priority research program of CAS (XDA06010701).
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