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  4. Detecting Mobility Patterns with Stationary Bluetooth Sensors: A real-world Case Study
 
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2015
Conference Paper
Titel

Detecting Mobility Patterns with Stationary Bluetooth Sensors: A real-world Case Study

Abstract
A Bluetooth sensor network was built up in the city of Bonn to measure Bluetooth MAC-addresses. The results of the acquired data are separated on a macro level and mobility patterns. We have collected nearly 5 million data points from 14 distinct stationary sensors over a period of 1 month and recognized over 85.000 unique devices. We show that the data is sufficiently dense to detect commuter patterns based on a Fourier analysis. In addition, we discuss limitations found in the dataset and present lessons learned.
Author(s)
Müller, Marc
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS
Schulz, Daniel
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS
Mock, Michael
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS
Hecker, Dirk
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS
Hauptwerk
18th AGILE International Conference on Geographic Information Science. Geographic Information Science as an Enabler of Smarter Cities and Communities. Online resource
Project(s)
DATA SIM
Funder
European Commission EC
Konferenz
International Conference on Geographic Information Science 2015
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Externer Link
Language
English
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Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS
Tags
  • bluetooth tracking

  • Fourier Transformatio...

  • mobility patterns

  • geo-sensor network

  • data-acquisition

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