Examining approaches for mobility detection through Smartphone Sensors
Key: TGK+18-1
Author: Thomas Tregel, Andreas Gilbert, Robert Konrad, Petra Schäfer, Stefan Göbel
Date: November 2018
Kind: In proceedings
Publisher: Springer
Book title: Proceedings of the 4th Joint International Conference on Serious Games
Keywords: Mobility, Mobility detection, Machine learning
Abstract: 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. Locationbased 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 scenariobased 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.
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