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SenST*: Approaches for Reducing the Energy Consumption of Smartphone-Based Context Recognition

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Modeling and Using Context (CONTEXT 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6967))

Abstract

Modern smartphones provide sensors that can be used to describe the current context of the device and its user. Contextual knowledge allows software systems to adapt to personal preferences of users and to make data processing context-aware. Different sensors or measurement approaches used for recognizing the values of particular context elements vary greatly in their energy consumption. This paper presents approaches for reducing the energy consumption of utilizing smartphone sensors. We discuss sensor substitution strategies as well as logical dependencies among sensor measurements. The paper describes the first milestone towards a generalization of such strategies. Furthermore, We show that energy awareness benefits from a more abstract view on context elements.

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Author information

Authors and Affiliations

  1. Bauhaus University of Weimar, Bauhausstr. 11, 99423, Weimar, Germany

    Maximilian Schirmer & Hagen Höpfner

Authors
  1. Maximilian Schirmer
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  2. Hagen Höpfner
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Editor information

Editors and Affiliations

  1. TecO/Pervasive Computing Systems, Karlsruhe Institute of Technology, Am Fasanengarten 5, 76131, Karlsruhe, Germany

    Michael Beigl  & Hedda R. Schmidtke  & 

  2. Department of Communication, Business and Information Technologies, Roskilde University, P.O. box 260, 4000, Roskilde, Denmark

    Henning Christiansen

  3. Institut für Informatik, AG Erklärungsfähige Softwaresystems, Universität Hildesheim, Marienburger Platz 22, 31141, Hildesheim, Germany

    Thomas R. Roth-Berghofer

  4. Department of Computer and Information Science, Intelligent Systems Group, Norwegian University of Science and Technology (NTNU), Sem Saelandsvei 7-9,, 7491, Trondheim, Norway

    Anders Kofod-Petersen

  5. Cognition and Communication Research Centre, Northumbria University, Newcastle upon Tyne, NE1 8ST, UK

    Kenny R. Coventry

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© 2011 Springer-Verlag Berlin Heidelberg

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Schirmer, M., Höpfner, H. (2011). SenST*: Approaches for Reducing the Energy Consumption of Smartphone-Based Context Recognition. In: Beigl, M., Christiansen, H., Roth-Berghofer, T.R., Kofod-Petersen, A., Coventry, K.R., Schmidtke, H.R. (eds) Modeling and Using Context. CONTEXT 2011. Lecture Notes in Computer Science(), vol 6967. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24279-3_27

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  • DOI: https://doi.org/10.1007/978-3-642-24279-3_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24278-6

  • Online ISBN: 978-3-642-24279-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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