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There has been increased interest in WIFI devices equipped with multiple antennas, which brings various wireless sensing applications such as localization, gesture identification and motion tracking. WIFI-based sensing has a lot of benefits such as device Free, which has shown great potential in smart scenarios. In this paper, we present WIP, a system that can distinguish a person from a small group of people. We prove that Channel State Information (CSI) can identify a person’s gait. From the related-work, different people have different gait features. Thus the CSI-based gait features can be used to identify a person. We then proposed a machine-learning model-ANN to classify different person. The results show that ANN has a good performance in our scenario.
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