Human Behavior Recognition Based on WiFi Channel State Information

Nowadays, with the continuous development of WiFi technology, more researchers come to realize that human behavior can be recognized by the application of WiFi Channel State Information (CSI). When human behavior has some changes, it will influence reflections of WiFi signals, which will also cause some changes to the CSI. Using the Intel WiFi Link 5300 network interface controller (NIC) and CSI-Tool, we can obtain the CSI data of corresponding behaviors. In this paper, we design a system to recognize different human behaviors based on the Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU). Firstly, we use the original data collected by the CSI-Tool, then extract the CSI amplitude values of different behaviors as features and input them into neural network structures where the GRU and CNN are connected in parallel. Based on the above works, we can successfully identify different human behaviors.