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User Attribute Classification Method Based on Trajectory Patterns with Active Scanning Devices

  • Kenji Takayanagi
  • Kazuya Murao
  • Masahiro Mochizuki
  • Nobuhiko Nishio
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 240)

Abstract

Technologies for grasping the distribution and flow of people are required for urban planning, traffic planning, evacuation, rescue activities in case of disaster, and marketing. In order to grasp what kind of attribute the distribution and flow of people are formed, this paper proposes a method that estimates the attributes of users. As a method of estimating user attributes, we utilize probe request frame of Wi-Fi that smartphones are emitting. Probe request frame includes MAC address, enabling us to acquire the movement trajectory of a user by tracking the MAC address. By using the feature values obtained from the movement trajectory of the user, users are roughly classified into several types. In this paper, we focus on the user attribute estimation in underground city comprising of stations, shops, restaurants and so on. Through the practical experiment at Osaka underground city, we confirmed that the proposed method can classify the users into commuter or not by using the intervals between probe request frames.

Keywords

People flow analysis Attribute estimation Spatiotemporal data Probe request frame 

References

  1. 1.
    Fukuzaki, Y., Mochizuki, M., Murao, K., Nishio, N.: Statistical analysis of actual number of pedestrians for Wi-Fi packet-based pedestrian flow sensing. In: Proceedings of the 1st International Workshop on Smart Cities, pp. 1519–1526 (2015)Google Scholar
  2. 2.
    Robyns, P., Bonné, B., Quax, P., Lamotte, W.: Non-cooperative 802.11 MAC layer fingerprinting and tracking of mobile devices. Secur. Commun. Netw. 2017, 1–26 (2017)CrossRefGoogle Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  • Kenji Takayanagi
    • 1
  • Kazuya Murao
    • 1
  • Masahiro Mochizuki
    • 2
  • Nobuhiko Nishio
    • 1
  1. 1.College of Information Science and EngineeringRitsumeikan UniversityKusatsuJapan
  2. 2.Research Organization of Science and TechnologyRitsumeikan UniversityKusatsuJapan

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