Lane, ND; Georgiev, P; Mascolo, C; Gao, Y; (2015) ZOE: A cloud-less dialog-enabled continuous sensing wearable exploiting heterogeneous computation. In: Borriello, G and Pau, G and Gruteser, M and Hong, J, (eds.) MobiSys '15: Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services. (pp. pp. 273-286). Association for Computing Machinery (ACM): New York, NY, USA.

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Abstract

The wearable revolution, as a mass-market phenomenon, has finally arrived. As a result, the question of how wearables should evolve over the next 5 to 10 years is assuming an increasing level of societal and commercial importance. A range of open design and system questions are emerging, for instance: How can wearables shift from being largely health and fitness focused to tracking a wider range of life events? What will become the dominant methods through which users interact with wearables and consume the data collected? Are wearables destined to be cloud and/or smartphone dependent for their operation? Towards building the critical mass of understanding and experience necessary to tackle such questions, we have designed and implemented ZOE - a match-box sized (49g) collar- or lapel-worn sensor that pushes the boundary of wearables in an important set of new directions. First, ZOE aims to perform multiple deep sensor inferences that span key aspects of everyday life (viz. personal, social and place information) on continuously sensed data; while also offering this data not only within conventional analytics but also through a speech dialog system that is able to answer impromptu casual questions from users. (Am I more stressed this week than normal?) Crucially, and unlike other rich-sensing or dialog supporting wearables, ZOE achieves this without cloud or smartphone support - this has important side-effects for privacy since all user information can remain on the device. Second, ZOE incorporates the latest innovations in system-on-a-chip technology together with a custom daughter-board to realize a three-tier low-power processor hierarchy. We pair this hardware design with software techniques that manage system latency while still allowing ZOE to remain energy efficient (with a typical lifespan of 30 hours), despite its high sensing workload, small form-factor, and need to remain responsive to user dialog requests.

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