CSI-BFI-HAR: Datasets for Human Activity Recognition with Integrated Sensing and Communications in Wi-Fi

Wi-Fi sensing has emerged as a promising non-intrusive approach for human activity recognition (HAR), leveraging the widespread availability of Wi-Fi-enabled devices. While machine learning tools help extract meaningful features from complex wireless propagation patterns, developing robust and domain-adaptive models remains challenging without diverse datasets. To address this, we release two comprehensive datasets containing Channel State Information (CSI) and Beamforming Feedback Information (BFI), collected using commercial IEEE 802.11ac devices across multiple days in both LoS and NLoS scenarios. The first dataset includes 20 activities performed by six subjects across six setups. The second captures simultaneous multi-subject activities, with three individuals performing distinct actions concurrently. Notably, this is the first public HAR dataset to include corresponding BFI measurements