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OptoSense

Dingtian Zhang,Jung Wook Park,Yang Zhang,Yuhui Zhao,Yiyang Wang,Yunzhi Li,Tanvi Bhagwat,Wen-Fang Chou,Xiaojia Jia,B. Kippelen,C. Fuentes-Hernandez,Thad Starner,G. Abowd

Published 2020 in Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies

ABSTRACT

Ubiquitous computing requires robust and sustainable sensing techniques to detect users for explicit and implicit inputs. Existing solutions with cameras can be privacy-invasive. Battery-powered sensors require user maintenance, preventing practical ubiquitous sensor deployment. We present OptoSense, a general-purpose self-powered sensing system which senses ambient light at the surface level of everyday objects as a high-fidelity signal to infer user activities and interactions. To situate the novelty of OptoSense among prior work and highlight the generalizability of the approach, we propose a design framework of ambient light sensing surfaces, enabling implicit activity sensing and explicit interactions in a wide range of use cases with varying sensing dimensions (0D, 1D, 2D), fields of view (wide, narrow), and perspectives (egocentric, allocentric). OptoSense supports this framework through example applications ranging from object use and indoor traffic detection, to liquid sensing and multitouch input. Additionally, the system can achieve high detection accuracy while being self-powered by ambient light. On-going improvements that replace Optosense's silicon-based sensors with organic semiconductors (OSCs) enable devices that are ultra-thin, flexible, and cost effective to scale.

PUBLICATION RECORD

  • Publication year

    2020

  • Venue

    Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies

  • Publication date

    2020-09-04

  • Fields of study

    Computer Science, Engineering

  • Identifiers
    DOI 10.1145/3411826
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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