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

Tengxiang Zhang, Zitong Lan, Chenren Xu, Yanrong Li, Yiqiang Chen
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引用次数: 1

摘要

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