Deep Human Activity Recognition
Human Activity Recognition (HAR) detects the kind of movement a person has made.
Since omni-directional antenna and multiple paths, human movements change the signals received by the receiver.
- Analyzes the patterns of changes in wireless signals, extracts unique features and classifies the user's behavior.
When a user changes his/her position and orientation, the multi-paths from Tx to Rx alter, which affects the changing pattern in wireless signals. We are trying to separate multi-path at receiver-side to harvest more information from CSI.
Domain Adaptation for Robustness
The multi-paths completely changes at new spaces. It is impossible to collect all the data necessary to account for such variation of surrounding environment. To address the challenge, we are developing DL model which only requires limited samples for domain adaptation.