Tagnoo: Enabling Smart Room-Scale Environments with RFID-Augmented Plywood

要旨

Tagnoo is a computational plywood augmented with RFID tags, aimed at empowering woodworkers to effortlessly create room-scale smart environments. Unlike existing solutions, Tagnoo does not necessitate technical expertise or disrupt established woodworking routines. This battery-free and cost-effective solution seamlessly integrates computation capabilities into plywood, while preserving its original appearance and functionality. In this paper, we explore various parameters that can influence Tagnoo's sensing performance and woodworking compatibility through a series of experiments. Additionally, we demonstrate the construction of a small office environment, comprising a desk, chair, shelf, and floor, all crafted by an experienced woodworker using conventional tools such as a table saw and screws while adhering to established construction workflows. Our evaluation confirms that the smart environment can accurately recognize 18 daily objects and user activities, such as a user sitting on the floor or a glass lunchbox placed on the desk, with over 90% accuracy.

著者
Yuning Su
Simon Fraser University, Burnaby, British Columbia, Canada
Tingyu Zhang
Simon Fraser University, Burnaby, British Columbia, Canada
Jiuen Feng
University of Science and Technology of China, Hefei, Anhui, China
Yonghao Shi
Simon Fraser University, Burnaby, British Columbia, Canada
Xing-Dong Yang
Simon Fraser University, Burnaby, British Columbia, Canada
Te-Yen Wu
Florida State University, Tallahassee, Florida, United States
論文URL

https://doi.org/10.1145/3613904.3642356

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Smart Homes and Environments

313C
5 件の発表
2024-05-15 01:00:00
2024-05-15 02:20:00