Smokey: Ubiquitous smoking detection with commercial WiFi infrastructures
Smokey: Ubiquitous smoking detection with commercial WiFi infrastructures
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DOI：
10.1109/infocom.2016.7524399
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发表时间：
2016-04
期刊：
影响因子：
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通讯作者：
Xiaolong Zheng;Jiliang Wang;Longfei Shangguan;Zimu Zhou;Yunhao Liu
中科院分区：
文献类型：
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作者：
Xiaolong Zheng;Jiliang Wang;Longfei Shangguan;Zimu Zhou;Yunhao Liu
尽管文明国家正在实施室内禁烟，但现有的基于视觉或传感器的吸烟检测方法不能提供无处不在的吸烟检测。在本文中，我们首次尝试构建了一个无处不在的被动吸烟检测系统，该系统利用WiFi信号上的烟叶模式来识别吸烟活动，即使在非视线和穿墙的环境中也是如此。我们研究吸烟者的行为，利用吸烟过程中的共同特征来识别吸烟过程中的一系列运动，避免了依赖于目标的训练集，以达到较高的准确率。我们设计了一种基于前景检测的运动捕获方法，从多个即使受姿态变化影响的噪声副载波中提取有意义的信息。在没有目标遵从性要求的情况下，我们利用吸烟的有节奏的模式来减少检测的误报。我们用商用WiFi基础设施制作了Smokey的原型，并在真实环境中评估了其性能。实验结果表明，Smokey在各种场景下都具有较高的准确性和健壮性。
Even though indoor smoking ban is being put into practice in civilized countries, existing vision or sensor-based smoking detection methods cannot provide ubiquitous smoking detection. In this paper, we take the first attempt to build a ubiquitous passive smoking detection system, which leverages the patterns smoking leaves on WiFi signals to identify the smoking activity even in the non-line-of-sight and through-wall environments. We study the behaviors of smokers and leverage the common features to recognize the series of motions during smoking, avoiding the target-dependent training set to achieve the high accuracy. We design a foreground detection based motion acquisition method to extract the meaningful information from multiple noisy subcarriers even influenced by posture changes. Without requirements of target's compliance, we leverage the rhythmical patterns of smoking to reduce the detection false positives. We prototype Smokey with the commodity WiFi infrastructure and evaluate its performance in real environments. Experimental results show Smokey is accurate and robust in various scenarios.