Demo Abstract: Underground Root Tuber Sensing via a Wi-Fi Mesh Network

We demonstrate a non-invasive Wi-Fi sensing system that uses channel state information (CSI) data and deep neural network (DNN) models to reconstruct the cross-section images of potato tubers underground. We design a Wi-Fi mesh network that can leverage both the space and frequency diversities of the wireless network. We apply a multi-branch convolutional neural network (CNN) model to perform data-driven image reconstruction. We have performed extensive experiments to build a Wi-Fi potato sensing dataset, and our demo and experimental evaluations show that the Wi-Fi system outperforms the state-of-the-art root tuber wireless sensing system in terms of image quality and estimation accuracy.