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Activity-Aware Map: Identifying Human Daily Activity Pattern Using Mobile Phone Data

  • Santi Phithakkitnukoon
  • Teerayut Horanont
  • Giusy Di Lorenzo
  • Ryosuke Shibasaki
  • Carlo Ratti
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6219)

Abstract

Being able to understand dynamics of human mobility is essential for urban planning and transportation management. Besides geographic space, in this paper, we characterize mobility in a profile-based space (activity-aware map) that describes most probable activity associated with a specific area of space. This, in turn, allows us to capture the individual daily activity pattern and analyze the correlations among different people’s work area’s profile. Based on a large mobile phone data of nearly one million records of the users in the central Metro-Boston area, we find a strong correlation in daily activity patterns within the group of people who share a common work area’s profile. In addition, within the group itself, the similarity in activity patterns decreases as their work places become apart.

Keywords

Mobile Phone Human Mobility Work Cell Daily Activity Pattern Spatial Window 
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

  • Santi Phithakkitnukoon
    • 1
  • Teerayut Horanont
    • 1
    • 2
  • Giusy Di Lorenzo
    • 1
  • Ryosuke Shibasaki
    • 2
  • Carlo Ratti
    • 1
  1. 1.SENSEable City Laboratory, School of Architecture and PlanningMassachusetts Institute of TechnologyCambridgeUSA
  2. 2.Department of Civil Engineering, School of EngineeringThe University of TokyoTokyoJapan

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