Description of Invention
Human Activity Recognition (HAR) using Wi-Fi channel state information (CSI) offers a privacy-preserving and device-free alternative to vision-based systems. Despite its potential, the development of robust HAR models requires extensive labeled data, which is labor-intensive and time-consuming to collect. This project addresses this challenge by introducing a novel data augmentation techniques to enhance model performance in CSI-based HAR.