Examining Approaches for Mobility Detection Through Smartphone Sensors
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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.
KeywordsMobility 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 mo.de.
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