Rong-Hao Liang

ACM CHI 2021: ACM SIGCHI Conference on Human Factors in Computing Systems

NFCSense: Data-Defined Rich-ID Motion Sensing for Fluent Tangible Interaction Using a Commodity NFC Reader

Rong-Hao Liang, Zengrong Guo

TU Eindhoven


This paper presents NFCSense, a data-defined rich-ID motion sensing technique for fluent tangible interaction design by using commodity near-field communication (NFC) tags and a single NFC tag reader. An NFC reader can reliably recognize the presence of an NFC tag at a high read rate (~300 reads/s) with low latency, but such high-speed reading has rarely been exploited because the reader may not effectively resolve collisions of multiple tags. Therefore, its human–computer interface applications have been typically limited to a discrete, hands-on interaction style using one tag at a time. In this work, we realized fluent, hands-off, and multi-tag tangible interactions by leveraging gravity and anti-collision physical constraints, which support effortless user input and maximize throughput. Furthermore, our system provides hot-swappable interactivity that enables smooth transitions throughout extended use. Based on the design parameters explored through a series of studies, we present a design space with proof-of-concept implementations in various applications.


NFC, Rich-ID, Motion Sensing, Tags, Physical Constraints, Fluent, Tangible Interaction

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