Comparison Between Wi-Fi-CSI and Radar-Based HAR

The use of radio-frequency (RF) sensors in systems centered around humans, such as human-computer interfaces or smart environments, is an emerging field that aims to recognize human motion in real-time. While various RF sensors such as radar, transceivers at various center frequencies and Wi-Fi, are used in this area of research, their performance have not been compared under the same scenarios. To address this gap, this study collects datasets using mmWave Radar and Wi-Fi, creates spectrograms, and conducts a side-by-side comparison to assess the efficiency of both systems for the same scenarios. The dataset is obtained using 77 GHz mmWave FMCW TI Radar and a Raspberry Pi 3B+ equipped with Nexmon firmware, and both the datasets and the associated code are made publicly accessible. The findings reveal that the Radar accuracy outperforms the Wi-Fi in terms of a 7-class human activity recognition (HAR) scenario by 32.7%. These results underscore the superiority of radar technology in the field of HAR while also highlighting the potential of Wi-Fi for indoor activity monitoring.