WiFi's Unspoken Tales: Deep Neural Network Decodes Human Behavior from Channel State Information

WiFi Channel State Information (CSI) represents the characteristics of wireless channels in wireless networks. WiFi CSI plays a pivotal role in wireless communications, primarily due to the variability of channel characteristics across time and space. By leveraging data analysis techniques based on Deep Neural Networks, we can capture the variations in channel characteristics associated with people's movements and behaviors indoors using WiFi CSI data. This offers a novel approach to Human Behavior Recognition, providing an alternative to camera-based methods that potentially infringe on privacy. In this paper, we delve into the structural design analysis of deep neural networks for human behavior recognition using WiFi CSI data and explore the training strategies vital for delivering extended services.