Talk by Prof. Moustafa Youssef: "A Robust Zero-Calibration RF-based Localization System for Realistic Environments"
February 5 (Monday)
National Institute of Informatics
Room 1509, 15th floor
A Robust Zero-Calibration RF-based Localization System for Realistic Environments
Prof. Moustafa Youssef
Prof. Moustafa Youssef is the Founder & Director of the Wireless Research Center at Egypt-Japan University of Science and Technology (E-JUST). His research interests include mobile computing, location determination technologies, pervasive computing, mobile wireless networks, and network security. He is an associate editor for the ACM TSAS, a previous area editor of the ACM MC2R and served on the organizing and technical committees of numerous prestigious conferences.
Prof. Youssef is the recipient of the 2003 University of Maryland Invention of the Year award, the 2010 TWAS-AAS-Microsoft Award for Young Scientists, the 2012 Egyptian State Award, the 2013 and 2014 COMESA Innovation Awards, the 2013 ACM SIGSpatial GIS Conference Best Paper Award, multiple Google Research Awards, among many others. He is also an ACM Distinguished Speaker and an ACM Distinguished Scientist.
Due to the noisy indoor radio propagation channel, Radio Frequency (RF)-based location determination systems usually require a tedious calibration phase to construct an RF fingerprint of the area of interest. This fingerprint varies with the used mobile device, changes of the transmit power of smart access points (APs), and dynamic changes in the environment; requiring re-calibration of the area of interest; which reduces the technology ease of use. In this talk, I will present IncVoronoi: a novel system that can provide zero-calibration accurate RF-based indoor localization that works in realistic environments. The basic idea is that the relative relation between the received signal strength from two APs at a certain location reflects the relative distance from this location to the respective APs. Building on this, IncVoronoi incrementally reduces the user ambiguity region based on refining the Voronoi tessellation of the area of interest. IncVoronoi also includes a number of modules to efficiently run in realtime as well as to handle practical deployment issues including the noisy wireless environment, obstacles in the environment, heterogeneous devices hardware, smart APs, and confidence estimation.
kei (at) nii.ac.jp