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Inferring Asymmetry of Inhabitant Flow Using Call Detail Records

Santi Phithakkitnukoon and Carlo Ratti
SENSEable City Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

Abstract—In this research, we carry out a study of the inhabitant flow using a large mobile phone data with location estimates from subscribers in Suffolk county, Massachusetts, USA that reveals the asymmetry in the flows, which reflects the way that people travel daily. People occasionally travel in a non-symmetrical way. For instance, they would take one route traveling from home to a destination and a different route while returning home. By analyzing the flow over the space, the results show that there exists asymmetrical flows, which account for 33% of all inhabitant flows. In addition, high asymmetrical flows are observed in trips between low and high congested areas e.g. urban and suburban areas, as well as trips made to and from low populated areas e.g. commercial areas.

Index Terms—Inhabitant flow, mobile phone data mining, urban computing

Cite: Santi Phithakkitnukoon and Carlo Ratti, "Inferring Asymmetry of Inhabitant Flow Using Call Detail Records," Journal of Advances in Information Technology, Vol. 2, No. 4, pp. 239-249, November, 2011.doi:10.4304/jait.2.4.239-249