Examining Approaches for Mobility Detection Through Smartphone Sensors

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11243)


The ubiquity of smartphones with integrated positioning systems, and multiple sensors for movement detection made it possible to develop context-sensitive applications for both productivity and entertainment. Location-based games like Ingress or Pokémon Go have demonstrated the public interest in this genre of mobile-only games – games that are exclusively available for mobile devices due to their sensor integration. For these games mobility is a key component, which defines and influences the game’s flow directly.

In this paper we compare different approaches and available frameworks for mobility detection and examine the frameworks’ performances in a scenario-based evaluation.

Based on our finding we present our own approach to differentiate between different modes of public transport and other common modes of movement like walking, running or riding a bicycle. Our approach already reaches an accuracy of 87% with a small sample size.


Mobility Mobility detection Machine learning 



The research presented in this paper was partially funded by the LOEWE initiative (Hessen, Germany) within the research project “Infrastruktur – Design – Gesellschaft” as project


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.TU DarmstadtDarmstadtGermany
  2. 2.Frankfurt University of Applied SciencesFrankfurtGermany

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