Speaker:
Hongbo Liu
Electrical and Computer Engineering
Stevens Institute of Technology

Time: 3:00 PM -- 4:00 PM, Sep 19^th (Wednesday), 2012

Location: Babbio Center, Room 319

ABSTRACT
Indoor localization is a critical enabler for location based smartphone applications. In many environments (e.g., airport terminals, railway stations and shopping malls), the location helps users access navigation, merchandise and promotion information; businesses need it to understand the patterns of customer visit and stay. Although there have been some recent commercial offerings and a plethora of academic work on indoor localization, highly accurate indoor localization on smartphones remains elusive. Based on our empirical investigation of the suitability of WiFi localization, we find that although reasonable accuracy (e.g., 3~4m) can be achieved, there always exist large errors (e.g., 6~8m) unacceptable for many scenarios. The root cause is the existence of distinct locations with similar signatures, which is a fundamental limit of pure WiFi based methods. We also observe that smartphones are gradually woven into our social life and usually a high density of them exist in public spaces. The relative positions of nearby peer devices could be used as physical constraints on the possible location of a smartphone. Inspired by high densities of smartphones in public spaces, we propose a peer assisted localization approach to eliminate such large errors. It obtains accurate acoustic ranging estimates among peer phones, then maps their locations jointly against WiFi signature map subjecting to ranging constraints. We devise techniques for fast acoustic ranging among multiple phones and build a prototype. Experiments show that it can reduce the maximum and 80-percentile errors to as small as 2m and 1m, in time no longer than the original WiFi scanning, with negligible impact on battery lifetime.

BIOGRAPHY
Hongbo Liu is a Ph.D. candidate of the Electrical and Computer Engineering Department at Stevens Institute of Technology. His research interests include information security & privacy, mobile computing and wireless localization systems, wireless and sensor networks, and digital signal processing. He is currently working in the Data Analysis and Information SecuritY (DAISY) Lab with Prof. Yingying Chen. He received his Bachelor's and Master’s degree in Communication Engineering from Department of Communication and Information Engineering at University of Electronic Science and Technology of China in 2005 and 2008 respectively. He was the recipient of the Best Paper Award from the ACM International Conference on Mobile Computing and Networking (MobiCom) 2011. He was also the recipient of the Outstanding Undergraduate Student Thesis Award 2005.

For more information please contact:

Yingying Chen
Associate Professor & NIS Graduate Program Director (RESEARCH INTERESTS: Cyber security, mobile computing, mobile healthcare, cognitive radio networks)
Burchard
Room 210
Phone: 201.216.8066
Fax: 201.216.8246
yingying.chen@stevens.edu

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