INDOOR LOCALIZATION WITH ALTERED APS AND FINGERPRINT UPDATE

MPhil Thesis Defence


Title: "INDOOR LOCALIZATION WITH ALTERED APS AND FINGERPRINT UPDATE"

By

Mr. Wenbin LIN


Abstract

Wi-Fi fingerprinting is a promising approach for indoor localization due 
to its ease of deployment and high accuracy. However, in order to maintain 
localization accuracy when the signal from access points (APs) changes 
(due to, for examples, AP movement or power adjustment), the costly 
offline site survey often needs to be conducted. In this thesis, we 
propose LAAFU, which achieves both accurate indoor localization and 
automatic fingerprint update in the presence of altered APs without the 
need of site survey. Using novel subset sampling, LAAFU is able to 
efficiently identify the altered APs and filter them out before 
localization, hence achieving high accuracy. With the locations, the 
fingerprint signal due to the altered APs can be adaptively and 
transparently updated using the non-parametric Gaussian process regression 
method. We have implemented LAAFU and conducted extensive experiments at 
our campus. Our results show that LAAFU is robust to altered AP signal 
changes to achieve high localization accuracy, and its fingerprint 
database is able to adapt to the current signal environment.


Date:			Tuesday, 11 August 2015

Time:			2:00pm - 4:00pm

Venue:			Room 3494
 			Lifts 25/26

Committee Members:	Prof. Gary Chan (Supervisor)
 			Dr. Jogesh Muppala (Chairperson)
 			Dr. Qiong Luo


**** ALL are Welcome ****