Thursday, June 22, 2016, 2:30 pm EST
JEC 3117
LESA Seminar Series Presents
Ubiquitous Sensing Using Visible Light
Xia Zhou, PhD
Assistant Professor
Department of Computer Science
Dartmouth College
Hanover, NH
Abstract
The ability to sense what we do and how we behave is crucial to help detect diseases, diagnose early symptoms of health issues, and foster healthier lifestyles. Existing sensing technologies, however, have significant drawbacks. They either are intrusive — we have to constantly carry or wear sensing devices (e.g., Apple Watch, Fitbit), or present serious privacy risks by capturing raw images, or are limited in sensing granularity.
In this talk, I will present a radically different approach to unobtrusive human sensing, which exploits the ubiquitous light around us as a sensing medium that senses and responds to what we do, without requiring any on-body devices nor any cameras. I will first present LiSense, the first-of-its-kind system that reconstructs a 3D human skeleton in real time (60 Hz) using purely the light around us. Empowered by Visible Light Communication (VLC), LiSense uses shadows created by a human body from blocked light to reconstruct the 3D skeleton. I will then present our recent effort StarLight, which advances LiSense by addressing several practical issues and pushes light sensing closer to practice. I will conclude with our ongoing work and future directions.
Dr. Zhou Bio
Xia Zhou is an Assistant Professor in the Department of Computer Science at Dartmouth College. She received her PhD at UC Santa Barbara in 2013. Her research interests are in mobile systems and wireless networking. Her recent work on visible light communication systems has won the Best Paper Award at ACM VLCS 2014, Best Demo Award at MobiSys 2015, and Best Video Award at MobiCom 2015. Her work on spectrum distributions won Best Practical Paper Award at SIGMETRICS 2013, and Best Paper Award Finalist at MobiCom 2008. She also won other paper awards in UbiComp 2014 and 2015, HotWireless 2015. She is the recipient of the NSF CAREER Award in 2016 and Google Faculty Research Award in 2014.
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For series details contact: Dr. Silvia Mioc, Director of Industrial Collaborations, miocs@rpi.edu, 518-276-4010.