LiquImager: Fine-grained Liquid Identification and Container Imaging System with COTS WiFi Devices

Fei Shang, Panlong Yang, Dawei Yan, Sijia Zhang, Xiang-Yang Li
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Abstract

WiFi has gradually developed into one of the main candidate technologies for ubiquitous sensing. Based on commercial off-the-shelf (COTS) WiFi devices, this paper proposes LiquImager, which can simultaneously identify liquid and image container regardless of container shape and position. Since the container size is close to the wavelength, diffraction makes the effect of the liquid on the signal difficult to approximate with a simple geometric model (such as ray tracking). Based on Maxwell's equations, we construct an electric field scattering sensing model. Using few measurements provided by COTS WiFi devices, we solve the scattering model to obtain the medium distribution of the sensing domain, which is used for identifing and imaging liquids. To suppress the signal noise, we propose LiqU-Net for image enhancement. For the centimeter-scale container that is randomly placed in an area of 25 cm × 25 cm, LiquImager can identify the liquid more than 90% accuracy. In terms of container imaging, LiquImager can accurately find the edge of the container for 4 types of containers with a volume less than 500 ml.
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LiquImager:使用 COTS WiFi 设备的精细液体识别和容器成像系统
WiFi 已逐渐发展成为泛在感知的主要候选技术之一。基于现成的商用 WiFi 设备,本文提出了液体成像仪(LiquImager),它可以同时识别液体和成像容器,而不受容器形状和位置的影响。由于容器尺寸与波长接近,衍射使得液体对信号的影响难以用简单的几何模型(如射线跟踪)来近似。基于麦克斯韦方程,我们构建了一个电场散射传感模型。利用 COTS WiFi 设备提供的少量测量数据,我们对散射模型进行求解,从而获得传感域的介质分布,用于对液体进行识别和成像。为了抑制信号噪声,我们提出了用于图像增强的 LiqU-Net。对于在 25 cm × 25 cm 区域内随机放置的厘米级容器,LiquImager 识别液体的准确率超过 90%。在容器成像方面,LiquImager 可以准确找到 4 种容积小于 500 毫升的容器的边缘。
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