Date of Award
Doctor of Philosophy (PhD)
RF signals and devices have been used for wireless communication to improve the mobility and ubiquity of mobile devices. In this dissertation, we show that these RF signals can also be used for context sensing applications. Specifically, we present cyber-physical systems and algorithms to sense human vital signals, object vibrations and movements, and object’s location to deliver new sensing capabilities for a variety of new applications including health-care monitoring, privacy protection, and indoor localization. We deliver three fundamental contributions. First, we develop an RF-based system to “sense” human breathing volume continuously in fine-grained from afar. Second, we develop a technique to “sense” the wireless signals emitted from drones/fly-cams to detect them and alert users for privacy protection. Last, we present our preliminary study on building a system to enable the mobile device to “sense” their global locations at the indoor environment. To deliver these contributions, we exploit the properties of physical characteristics of RF signals, analyze and understand targeted subjects behaviors (i.e., human, drones), work across different limitations and hardware-software barriers, and introduce novel systems and new algorithms to overcome the challenges. We implement and evaluate the system on real users/patients, test the systems across different environments, and demonstrate how they can enable many other real-world applications.
Nguyen, Phuc Van, "Techniques to Leverage RF Signals for Context Sensing" (2018). Computer Science Graduate Theses & Dissertations. 192.