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

Year: 2025

Type: conference-paper

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.

Source: Fraunhofer-Publica (Fraunhofer-Gesellschaft)

DOI: 10.24406/h-410275

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

Language: English

Topic: Human Mobility and Location-Based Analysis

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDG: Sustainable cities and communities

Open Access status: green

OpenAlex ID: W7092500143

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