WiRoI: Spatial Region of Interest Human Sensing with Commodity WiFi

In the era of Internet of Things, human sensing, which detects and interprets human motions including gestures or postures, has emerged as a challenging problem in areas such as assisted living and remote monitoring. Besides conventional sensing methodologies that rely on wearable devices and camera systems, WiFi-based technologies are evolving as a promising solution for indoor monitoring and activity recognition recently. In this paper, we propose WiRoI, a device-free human sensing scheme which is able to precisely detect and interpret human motions within certain spatial region of interest (RoI) using only commodity WiFi devices. To this end, the channel state information (CSI) data in PHY layer is obtained directly by upgrading the firmware. To make the system robust enough, we propose a method to eliminate the noises caused by other humans between TX and RX. And particularly, we are the first to explore spatial region of interest towards accurate and robust human sensing. Experiments were conducted in a common office and the results demonstrated that WiRoI is able to accurately detect and interpret gestures (In order to test the performance of the proposed method, we build a gesture recognition system.) with the accuracy lowered by less than 5% when there are other humans walking or standing between the TX and RX.