Conference paper, Creative achievement

Using Wearables to Learn from Human Dynamics

Recent technological advances have allowed the development of miniaturized sensors and the emergence of a wide range of connected objects. Whether it’s smartphones or in the broader sense wearables, the diversity of these devices and their accessibility opens up new fields for applications in the computer sciences [2, 3]. Smartwatches, which are experiencing a boom on the market, will be integral to the research that will shape the Internet in the years to come, namely big data, sensing systems and human behavior. Our demonstration falls within this context and aims to demonstrate the potential of these emerging technologies to respond to problems and to way of thinking introduced by industry and the scientific community, which are generally limited to smartphone sensing frameworks [1]. Further, we plan to present our research platform, SWIPE, which is dedicated to collecting, studying and learning about human dynamics by means of an ecosystem of wearables.

Reference

  • [PDF] [DOI] S. Faye and R. Frank, “Using Wearables to Learn from Human Dynamics (Demo),” in Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services (ACM Mobisys), 2015, p. 445–445.
    @inproceedings{SF-MS-15,
    Author = {Faye, S{\'e}bastien and Frank, Raphael},
    Booktitle = {Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services (ACM Mobisys)},
    Doi = {10.1145/2742647.2745932},
    Organization = {ACM},
    Pages = {445--445},
    Pdf = {http://www.sfaye.com/data/faye_mobisys_2015.pdf},
    Title = {Using Wearables to Learn from Human Dynamics (Demo)},
    Year = {2015},
    Bdsk-Url-1 = {http://dx.doi.org/10.1145/2742647.2745932}}