person identification
The dataset includes channel frequency response (CFR) data collected through an IEEE 802.11ax device for human activity recognition. This is the first dataset for Wi-Fi sensing with the IEEE 802.11ax standard which is the most updated Wi-Fi version available in commercial devices. The dataset has been collected within a single environment considering a single person as the purpose of the study was to evaluate the impact of communication parameters on the performance of sensing algorithms.
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The human gait is unique and so is the impact of a walking human on the propagation of wireless signals within a wireless network. Using appropriate pattern recognition techniques, a person can thus be identified just from a time series of Received Signal Strength (RSS) measurements. This dataset holds bidirectional RSS measurements recorded within a mesh network of four Bluetooth sensor devices. During the measurements, a total of 14 subjects walked individually through the setup. A total of more than 10,000 recordings are provided.
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The complete description of the dataset can be found at: https://arxiv.org/abs/2305.03170
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