The telepathic phone: Frictionless activity recognition from WiFi-RSSI

S. Sigg, Ulf Blanke, G. Tröster
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引用次数: 129

Abstract

We investigate the use of WiFi Received Signal Strength Information (RSSI) at a mobile phone for the recognition of situations, activities and gestures. In particular, we propose a device-free and passive activity recognition system that does not require any device carried by the user and uses ambient signals. We discuss challenges and lessons learned for the design of such a system on a mobile phone and propose appropriate features to extract activity characteristics from RSSI. We demonstrate the feasibility of recognising activities, gestures and environmental situations from RSSI obtained by a mobile phone. The case studies were conducted over a period of about two months in which about 12 hours of continuous RSSI data was sampled, in two countries and with 11 participants in total. Results demonstrate the potential to utilise RSSI for the extension of the environmental perception of a mobile device as well as for the interaction with touch-free gestures. The system achieves an accuracy of 0.51 while distinguishing as many as 11 gestures and can reach 0.72 on average for four more disparate ones.
心灵感应手机:WiFi-RSSI无摩擦活动识别
我们研究了在手机上使用WiFi接收信号强度信息(RSSI)来识别情况、活动和手势。特别是,我们提出了一种不需要用户携带任何设备并使用环境信号的无设备被动活动识别系统。我们讨论了在移动电话上设计这样一个系统的挑战和经验教训,并提出了从RSSI中提取活动特征的适当功能。我们展示了通过手机获得的RSSI识别活动、手势和环境情况的可行性。案例研究在大约两个月的时间内进行,在两个国家,总共有11名参与者,对大约12小时的连续RSSI数据进行了采样。结果证明了利用RSSI扩展移动设备的环境感知以及与非触摸手势的交互的潜力。该系统在识别多达11种手势时,准确率达到0.51,在识别4种不同手势时,准确率平均达到0.72。
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