A Complex Human Activities Testbed For Cross-Domain WiFi Sensing Dataset
Prior researches have shown the potential that WiFi signals could be used for human activities recognition (HAR), or monitor a person's gait for human identification (HI). Recently researchers pay more attention to the impact of environmental factors such as activity orientation, walking trajectory, WiFi device location, etc. on the HAR or HI tasks' performance. Existing experimental data set mostly record a limited amount of subjects and activities in a certain fixed moving orientation, which illy support the cross-domain or domain independent study on WiFi human sensing. To foster WiFi sensing to be applicable in realistic environment, we build a WiFi-based complex human activities testbed for cross-domain study in WiFi sensing area. This is the open access data set of the testbed.
Since the dataset is quite large and hardly upload to ieee dataport, we choose to upload the dataset to Code Ocean platform and here is the link: https://codeocean.com/capsule/7200789/tree