BLEselect: Gestural IoT Device Selection via Bluetooth Angle of Arrival Estimation from Smart Glasses

Tengxiang Zhang, Zitong Lan, Chenren Xu, Yanrong Li, Yiqiang Chen
{"title":"BLEselect: Gestural IoT Device Selection via Bluetooth Angle of Arrival Estimation from Smart Glasses","authors":"Tengxiang Zhang, Zitong Lan, Chenren Xu, Yanrong Li, Yiqiang Chen","doi":"10.1145/3569482","DOIUrl":null,"url":null,"abstract":"Spontaneous selection of IoT devices from the head-mounted device is key for user-centered pervasive interaction. BLEselect enables users to select an unmodified Bluetooth 5.1 compatible IoT device by nodding at, pointing at, or drawing a circle in the air around it. We designed a compact antenna array that fits on a pair of smart glasses to estimate the Angle of Arrival (AoA) of IoT and wrist-worn devices’ advertising signals. We then developed a sensing pipeline that supports all three selection gestures with lightweight machine learning models, which are trained in real-time for both hand gestures. Extensive characterizations and evaluations show that our system is accurate, natural, low-power, and privacy-preserving. Despite the small effective size of the antenna array, our system achieves a higher than 90% selection accuracy within a 3 meters distance in front of the user. In a user study that mimics real-life usage cases, the overall selection accuracy is 96.7% for a diverse set of 22 participants in terms of age, technology savviness, and body structures.","PeriodicalId":20463,"journal":{"name":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.","volume":"280 1","pages":"198:1-198:28"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3569482","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Spontaneous selection of IoT devices from the head-mounted device is key for user-centered pervasive interaction. BLEselect enables users to select an unmodified Bluetooth 5.1 compatible IoT device by nodding at, pointing at, or drawing a circle in the air around it. We designed a compact antenna array that fits on a pair of smart glasses to estimate the Angle of Arrival (AoA) of IoT and wrist-worn devices’ advertising signals. We then developed a sensing pipeline that supports all three selection gestures with lightweight machine learning models, which are trained in real-time for both hand gestures. Extensive characterizations and evaluations show that our system is accurate, natural, low-power, and privacy-preserving. Despite the small effective size of the antenna array, our system achieves a higher than 90% selection accuracy within a 3 meters distance in front of the user. In a user study that mimics real-life usage cases, the overall selection accuracy is 96.7% for a diverse set of 22 participants in terms of age, technology savviness, and body structures.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
BLEselect:通过智能眼镜的蓝牙到达角度估计进行手势物联网设备选择
从头戴式设备中自发选择物联网设备是实现以用户为中心的无处不在的交互的关键。BLEselect允许用户通过点头、指向或在周围的空气中画圈来选择未修改的蓝牙5.1兼容物联网设备。我们设计了一种紧凑型天线阵列,可以安装在一副智能眼镜上,用于估计物联网的到达角(AoA)和腕带设备的广告信号。然后,我们开发了一个传感管道,支持所有三种选择手势,使用轻量级机器学习模型,这些模型可以实时训练两种手势。广泛的特征和评估表明,我们的系统是准确的、自然的、低功耗的和隐私保护的。尽管天线阵列的有效尺寸很小,但我们的系统在用户面前3米距离内的选择精度高于90%。在一项模拟现实生活用例的用户研究中,根据年龄、技术熟练程度和身体结构,22名不同的参与者的总体选择准确率为96.7%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Multi-Subject 3D Human Mesh Construction Using Commodity WiFi UHead: Driver Attention Monitoring System Using UWB Radar DeltaLCA: Comparative Life-Cycle Assessment for Electronics Design Multimodal Daily-Life Logging in Free-living Environment Using Non-Visual Egocentric Sensors on a Smartphone Lateralization Effects in Electrodermal Activity Data Collected Using Wearable Devices
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1