Affiliation:
1. University of Massachusetts Amherst, Amherst, MA
2. Stanford University
Abstract
Recent years have seen exciting developments in the use of RFID tags as sensors to enable a range of applications including home automation, health and wellness, and augmented reality. However, widespread use of RFIDs as sensors requires significant instrumentation to deploy tethered readers, which limits usability in mobile settings. Our solution is WearID, a low-power wrist-worn backscatter reader that bridges this gap and allows ubiquitous sensing of interaction with tagged objects. Our end-to-end design includes innovations in hardware architecture to reduce power consumption and deal with wrist attenuation and blockage, as well as signal processing architecture to reliably detect grasping, touching, and other hand-based interactions. We show via exhaustive characterization that WearID is roughly 6× more power efficient than state-of-art commercial readers, provides 3D coverage of 30 to 50 cm around the wrist despite body blockage, and can be used to reliably detect hand-based interactions. We also open source the design of WearID with the hope that this can enable a range of new and unexplored applications of wearables.
Publisher
Association for Computing Machinery (ACM)
Reference62 articles.
1. Chris Diorio. (n.d.) Engineering RAIN RFID Solutions. Retrieved February 26 2020 from http://www.rainrfid.org/wp-content/uploads/2015/07/Diorio-RAIN-solutions-presentation-2015-06-24.pdf. Chris Diorio. (n.d.) Engineering RAIN RFID Solutions. Retrieved February 26 2020 from http://www.rainrfid.org/wp-content/uploads/2015/07/Diorio-RAIN-solutions-presentation-2015-06-24.pdf.
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