Characterizing smartwatch usage in the wild

Xing Liu, Tianyu Chen, Feng Qian, Zhixiu Guo, Felix Xiaozhu Lin, Xiaofeng Wang, Kai Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

30 Scopus citations

Abstract

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 languageEnglish (US)
Title of host publicationMobiSys 2017 - Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services
PublisherAssociation for Computing Machinery, Inc
Pages385-398
Number of pages14
ISBN (Electronic)9781450349284
DOIs
StatePublished - Jun 16 2017
Externally publishedYes
Event15th ACM International Conference on Mobile Systems, Applications, and Services, MobiSys 2017 - Niagara Falls, United States
Duration: Jun 19 2017Jun 23 2017

Publication series

NameMobiSys 2017 - Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services

Conference

Conference15th ACM International Conference on Mobile Systems, Applications, and Services, MobiSys 2017
CountryUnited States
CityNiagara Falls
Period6/19/176/23/17

Bibliographical note

Funding 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).

Publisher Copyright:
© 2017 ACM.

Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

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