INNOVATIVE RADIO FREQUENCY SIGNAL APPLICATION IN SENSING AND COMMUNICATION

Abstract

Since the wireless sensor network (WSN) became one of the infrastructures of modern society, researchers have proposed to utilize the abundant radio frequency (RF) signal for innovative sensing. Various RF signals, including WiFi, ZigBee, Bluetooth, Backscatter, and customized signals, have been used to perform human localization, tracking, and activity recognition. However, due to the broadcasting nature of the RF signal, the RF sensing technology also raises privacy concerns. Silent eavesdroppers can perform sensing using ambient signals without exposing themselves. Therefore, secure sensing is also an emergent requirement. Another concern about the RF signal is that it brings electric-magnetic radiation, which makes it not ideal for continuous monitoring of some people such as the fetus. With the growth of Internet-of-Things (IoT), more signal sources and sensors would be integrated into the wireless sensor network. The final concern is that most of the proposed algorithms cannot be used for on-demand deployment because of the unavailable preset fingerprints(prior landmark or context information) in their assumption. Another issue is that the algorithms with models built in an interference-free environment cannot work in interference-rich environments. To address these issues, we propose systems that can i) perform authorized sensing while blocking the unauthorized RF sensing devices, ii) use passive acoustic sensors for continuous monitoring of the fetal heart rate and fetal heart position, and iii) dynamically divide the sensing field into areas with unique signatures and tracks the target without any fingerprints. The first system utilizes commodity-off-the-shelf (COTS) devices to create a safe area for RF sensing. The first system would not affect legitimate sensing or data communication. The second system not only measures the fetal heart rate but also tells the position of the fetus, which is an important health indicator. In the meantime, the second system can send sensing results to doctors and researchers to assist the diagnostic and research. The third system uses the high-low relationship between RSSs from each node to reduce the affection from RF fading. We also implemented a proof-of-concept localization platform for the third system to demonstrate the tracking accuracy and the algorithm performance in practical, interference-rich environments.