Indoor Navigation Service using UHF Passive RFID

PhD Thesis Proposal Defence


Title: "Indoor Navigation Service using UHF Passive RFID"

by

Mr. Yi GUO


Abstract:

Radio frequency identification (RFID) has experienced tremendous development in 
recent decades and has been widely applied into many areas in industry and 
daily life. The rapid development of microelectronic technology makes RFID tags 
smaller, cheaper, and more powerful, especially in UHF passive RFID technology. 
These remarkable technical advances have resulted in more and more supermarkets 
and libraries, such as Walt-Mart and university libraries, introducing RFID 
techniques into their traditional systems. Utilizing these existing RFID 
infrastructure to perform value-added services, such as user behavior analysis 
and item positioning, becomes a hot research topic, where indoor navigation 
using UHF passive RFID system is the representational one.

A typical process of indoor navigation service contains three periods: 
identifying the user, positioning the user, and navigating the user. In our 
first work, we propose a user identification mechanism called OpenSesame, which 
employs the users' waving patterns to identify the user. The key feature of 
this work lies in using four fine-grained and statistic features of handwaving 
to verify users. In our second work, we propose BackPos, a fine-grained 
backscatter positioning technique using the COTS RFID products with detected 
phases. Our studies show that the phase is a stable indicator highly related to 
tag's position and preserved over frequency or tag orientation, but challenged 
by its periodicity and tag's diversity. We attempt to infer the distance 
differences from phases detected by antennas under triangle constraint. 
Further, hyperbolic positioning using the distance differences is employed to 
shrink the tag's candidate positions until finding out the real one. In our 
third work, we propose RollCaller to utilize existing indoor objects with 
attached RFID tags and a reader to navigate users to their destinations, 
without need of any extra hardware. The key insight is that a person's movement 
has an impact on the frequency shift values collected from indoor objects when 
close to a tag. Such local human-item spatial relation is leveraged to infer 
the user's position and further navigate the user to a destination step by 
step.


Date:			Friday, 13 March 2015

Time:                   3:00pm - 5:00pm

Venue:                  Room 5503
                         lifts 25/26

Committee Members:	Prof. Lionel Ni (Supervisor)
  			Dr. Qiong Luo (Chairperson)
  			Dr. Lei Chen
 			Dr. Ke Yi


**** ALL are Welcome ****