Mobile Device Based Tracking: Technology & Applications

NSF Project CNS #1718585

Synopsis

Accurate tracking is essential to many applications, including controlling video gaming, Virtual Reality (VR), Augmented Reality (AR), and Smart Appliances. Motivated by these applications, this project aims to develop accurate, fast, and robust motion tracking algorithms and apply it to enable new applications, such as imaging, follow-me drones, and user interfaces. 

We develop novel audio based tracking. Audio based tracking is attractive due to its slow propagation speed, which makes it possible to achieve high accuracy. Moreover, it can be easily generated and received by the speakers and microphones, which are already available. In addition, it penetrates through obstacles and works without line-of-sight and under different lighting conditions. Our technology not only allows us to track a mobile device in real time, but also uses reflected signals to track movement without any device.

The goal of the proposed research includes:

-        Design algorithms and systems to track motion

-        Develop applications that can leverage the motion

-        Incorporate the research outcome in curriculum and outreach.

Personnel

·        Prof. Lili Qiu

·        Wenguang Mao

·        Swadhin Pradhan

·        Wei Sun

·        Mei Wang

Publication

• Rotation Sensing Using Passive RFID Tags. Swadhin Pradhan, Shuozhe Li, Lili Qiu. In Proc. of MobiHoc, July 2021.
• DeepRange: Ranging via Deep Learning. Wenguang Mao, Wei Sun, Mei Wang, Lili Qiu. In Proc. of UbiComp, Dec. 2020.
• RTSense: Passive RFID based Temperature Sensing. Swadhin Pradhan and Lili Qiu. In Proc. of ACM Sensys, Nov. 2020.
• Mobile Imaging Using Acoustic Signals. In GetMobile: Mobile Computing and Communications, 2019.
• AIM: Acoustic Imaging on a Mobile. Wenguang Mao, Mei Wang, Lili Qiu. ACM MobiSys 2018 (Best paper award).
• DroneTrack: An Indoor Follow-Me System Using Acoustic Signals. Wenguang Mao, Lili Qiu. GetMobile: Mobile Computing and Communications, 2018.
• Indoor Follow Me Drone. Wenguang Mao, Lili Qiu, Jian He, Yuchen Cui, Sangki Yun. ACM MobiSys, 2017 (Best paper nomination). 

Outreach

- Talk at IoT Seminar at MIT Fall 2020

- Talk at RICE, Fall 2020.

- Talk at Texas A&M, 2019

- Talk at UW, 2018

- Talk at SIGMOBILE China, 2017

- Talk at Women Doing Math, 2017

- Talks at various companies and other venues, including Bose, Cisco, Microsoft, Samsung, CES, SXSW.