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MetroTrack: Predictive Tracking of Mobile Events Using Mobile Phones

  • Gahng-Seop Ahn
  • Mirco Musolesi
  • Hong Lu
  • Reza Olfati-Saber
  • Andrew T. Campbell
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6131)

Abstract

We propose to use mobile phones carried by people in their everyday lives as mobile sensors to track mobile events. We argue that sensor-enabled mobile phones are best suited to deliver sensing services (e.g., tracking in urban areas) than more traditional solutions, such as static sensor networks, which are limited in scale, performance, and cost. There are a number of challenges in developing a mobile event tracking system using mobile phones. First, mobile sensors need to be tasked before sensing can begin, and only those mobile sensors near the target event should be tasked for the system to scale effectively. Second, there is no guarantee of a sufficient density of mobile sensors around any given event of interest because the mobility of people is uncontrolled. This results in time-varying sensor coverage and disruptive tracking of events, i.e., targets will be lost and must be efficiently recovered. To address these challenges, we propose MetroTrack, a mobile-event tracking system based on off-the-shelf mobile phones. MetroTrack is capable of tracking mobile targets through collaboration among local sensing devices that track and predict the future location of a target using a distributed Kalman-Consensus filtering algorithm. We present a proof-of-concept implementation of MetroTrack using Nokia N80 and N95 phones. Large scale simulation results indicate that MetroTrack prolongs the tracking duration in the presence of varying mobile sensor density.

Keywords

Sensor Node Mobile Phone Root Mean Square Mobile Sensor Mobile Event 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Gahng-Seop Ahn
    • 1
  • Mirco Musolesi
    • 2
  • Hong Lu
    • 3
  • Reza Olfati-Saber
    • 3
  • Andrew T. Campbell
    • 3
  1. 1.The City University of New YorkUSA
  2. 2.University of St. AndrewsUnited Kingdom
  3. 3.Dartmouth CollegeHanoverUSA

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