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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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
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