Anonymous Localization of Wireless Terminals in Indoors

Anonymous Localization of Wireless Terminals

in IndoorsShahrokh ValaeeWireless and Internet Research Lab (WIRLab)Dept of Electrical and Computer EngineeringUniversity of Torontowww.comm.utoronto.ca/~valaee

Joint work with Chen Feng, Anthea Au, Moshe Eizenman, Sameh Sorour, Sophia Reyes, Sam Markowitz, Deborah Gold, Keith Gordon

Opportunistic Localization Workshop - May 2012 [Valaee]

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Indoor Navigation


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Objective

To design an accurate indoor navigation system that can be easily deployed on commercially available mobile devices without any hardware modification.

Localization Off-line measurements (site survey) On-line localization

Coarse localization Fine localization

Motivation

Regulations: E911

Commercial: shopping mall advertisement

Assistive: visually challenged

precision

5Opportunistic Localization Workshop - May 2012 [Valaee]

Where Am I?


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Fingerprinting

Collect fingerprints and store

Measure and compare

What about privacy?


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Received Signal Strength (RSS)

?


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Fingerprinting Collect fingerprints by measuring the

power from access points Store the results in a location server

The user: Fetches fingerprints from the server Measures the received power from

available access points Compares the measured power with

the fingerprints Privacy observed

Looking for a systematic solution


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A newly developed theory in signal processing for sampling and reconstruction of sparse signals.

Compressive Sensing


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Localization Block Diagram

Two phases: Offline Phase

Online Phase


Offline Phase

Measure RSS from multiple AP and store the average and variance in the server


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Clustering of Fingerprints

Adjacent points have similar RSS readings

An exemplar can act as a representative for the cluster

Clustering reduces computational complexity

Clustering removes outliers


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Online Phase

Retrieve fingerprints from the server

Measure the RSS Compare to the

fingerprints in two steps Coarse localization

Fine localization

Localization Steps

Coarse Localization Find the clusters to

which I belong

Fine Localization Locate me inside the

clusters


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Anonymous Localization Localization should be done on

the mobile unit Simple localization algorithm

deployable on cellphones Possibly a three-way solution


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Two different IDs

Authentication

service

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Skip the details

Indoor Navigation

System


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Implementation and Field Tests


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Implementation Buildings

4th floor of Bahen Center, University of Toronto

Canadian National Institute for Blind (CNIB) Bayview Village Shopping Mall (North Toronto)

440,000 square feet, 110 stores

Device Windows Mobile Platform

PDA (HP iPAQ windows mobile 2003 pocket PC) Samsung Omnia II smartphone

Android Platform HTC


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Test Results (Clustering)

Localization Error with Tracking


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CDF of Error


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Testing stage- Omnia II


Testing stage 30 Subjects

15 testing group 15 control group

3 tests for each subject

Test # # of turns Distance (m)

1 2 53.6

2 2 29.4

3 0 30.8


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Comparison between 2 groups




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Bayview Village Shopping Center


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Result (positioning system in BV)

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Conclusion A localization scheme for indoor environment using

RSS, Compressive Sensing and Affinity Propagation has been proposed

Localization is done in two steps: coarse localization and fine localization

The solution has been implemented and tested in real environment and used for localization, navigation, and object finding

Since localization is done on the mobile, privacy is satisfied.

Anonymous Localization of Wireless Terminals in Indoors

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