MetroTrack - MetroTrack Presented By Philip Shibly...

Info iconThis preview shows pages 1–7. Sign up to view the full content.

View Full Document Right Arrow Icon
MetroTrack Presented By Philip Shibly Predictive Tracking of Mobile Events Using Mobile Phones Gahng-Seop Ahn, Mirco Musolesi, Hong Lu, Reza Olfati-Saber, and Andrew T. Campbell, “Metro Track: Predictive Tracking of Mobile Events Using Mobile Phones.”The City University of New York, USA, [email protected] University of St. Andrews, United Kingdom Dartmouth College, Hanover, NH, USA
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Contents What is MetroTrack? Initial Pros/Cons Framework Information-Driven Tracking Prediction-Based Recovery Assumptions Prediction Algorithm Distributed Kalman-Consensus Filter Experiments and Simulations
Background image of page 2
What is MetroTrack Mobile Phone Event Tracking System Tracks moving targets by collaborative sensing devices. Predicts future location of a target that may be lost during tracking. Does not rely on static networks or backend computation, but rather mobile users, so it is susceptible to spacial density, user participation, and realtime computation/feedback needs.
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Initial Pros/Cons Relies on participatory users. Does not rely on user action. Needs dense network of users. Why would someone participate to track someone else's target? Why participate at all? Mobility of users is unpredictable and uncontrollable. Requires common sensors between users. Requires application to be running. Battery consumption? Does not rely on central nodes. Does not use node grouping. No back-end requirements.
Background image of page 4
Framework MetroTrack consists of two algorithms (1) Information-Driven Tracking The sensor node begins tracking when certain criteria is met. Forwards tracking task to neighboring nodes.
Background image of page 5

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
(2) Prediction-Based Recovery If a nodes neighbor(s) do not report a tracked event task, then it is assumed that the target is lost. Recovery is based on estimation of the targets
Background image of page 6
Image of page 7
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 08/25/2011 for the course EEL 6788 taught by Professor Boloni,l during the Spring '08 term at University of Central Florida.

Page1 / 24

MetroTrack - MetroTrack Presented By Philip Shibly...

This preview shows document pages 1 - 7. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online