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Demo: AWSense: A Framework for Collecting Sensing Data from the Apple Watch

Published: 16 June 2017 Publication History

Abstract

We present a framework - AWSense - for eased sensing data collection from an Apple Watch wearable device. The framework eases the access, transmission and export of sensing data from the device. This data comprises: heart rate, raw acceleration, and computed device motion. In our demo, we present sample applications built on top of this framework to show its capabilities, of real-time presentation and recording of the sensing data.

Reference

[1]
N. Lane, E. Miluzzo, H. Lu, D. Peebles, T. Choudhury, and A. Campbell. A survey of mobile phone sensing. IEEE Communications Magazine, 48(9):140--150, 2010.

Cited By

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  • (2020)WatchOverAdjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers10.1145/3410530.3414373(488-493)Online publication date: 10-Sep-2020
  • (2017)PAMS: A new position-aware multi-sensor dataset for human activity recognition using smartphones2017 19th International Symposium on Computer Architecture and Digital Systems (CADS)10.1109/CADS.2017.8310680(1-7)Online publication date: Dec-2017

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  1. Demo: AWSense: A Framework for Collecting Sensing Data from the Apple Watch

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    cover image ACM Conferences
    MobiSys '17: Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services
    June 2017
    520 pages
    ISBN:9781450349284
    DOI:10.1145/3081333
    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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    New York, NY, United States

    Publication History

    Published: 16 June 2017

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    Author Tags

    1. sensing libraries
    2. wearable computing

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    • Demonstration

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    MobiSys '17 Paper Acceptance Rate 34 of 188 submissions, 18%;
    Overall Acceptance Rate 274 of 1,679 submissions, 16%

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    • (2020)WatchOverAdjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers10.1145/3410530.3414373(488-493)Online publication date: 10-Sep-2020
    • (2017)PAMS: A new position-aware multi-sensor dataset for human activity recognition using smartphones2017 19th International Symposium on Computer Architecture and Digital Systems (CADS)10.1109/CADS.2017.8310680(1-7)Online publication date: Dec-2017

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