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

 
: Müller, Marc; Schulz, Daniel; Mock, Michael; Hecker, Dirk

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Volltext (PDF; )

Bacao, Fernando ; Association of Geographic Information Laboratories in Europe -AGILE-:
18th AGILE International Conference on Geographic Information Science. Geographic Information Science as an Enabler of Smarter Cities and Communities. Online resource : Short papers and poster abstracts, Lisbon, Portugal, June 9th - 12th, 2015
Lisbon, 2015
https://agile-online.org/conference/proceedings/proceedings-2015
6 S.
International Conference on Geographic Information Science <18, 2015, Lisbon>
European Commission EC
FP7-ICT; 270833; DATA SIM
Data Science for Simulating the Era of Electric Vehicles
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IAIS ()
bluetooth tracking; Fourier Transformation; mobility patterns; geo-sensor network; data-acquisition

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.

: http://publica.fraunhofer.de/dokumente/N-633114.html