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Facing up Social Activity Recognition Using Smartphone Sensors

Part of the Lecture Notes in Computer Science book series (LNISA,volume 9454)

Abstract

In the last years context awareness has become a reality in real-world applications. However, building comprehensive context recognition systems which are able to recognize both low and high-level context information remains a challenge. In this paper, we discuss environment recognition as a means to address the issue of recognizing a high-level user context, social activity. In many countries, bars, pubs and similar establishments are one of the main places where social engagement takes place, and thus we propose recognizing these types of environments using data collected from mobile device sensors as a proxy for inferring social activity. For this purpose, we discuss the common defining characteristics of these establishments and the sensors we will use to recognize them. After that, we introduce the design of our system. Finally, we present the preliminary evaluation carried out to assess the validity of our proposal.

Keywords

  • Mobile sensing
  • Multimodal sensors
  • Environment recognition
  • Activity recognition
  • Context awareness

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Correspondence to Pablo Curiel .

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Curiel, P., Pretel, I., Lago, A.B. (2015). Facing up Social Activity Recognition Using Smartphone Sensors. In: García-Chamizo, J., Fortino, G., Ochoa, S. (eds) Ubiquitous Computing and Ambient Intelligence. Sensing, Processing, and Using Environmental Information. UCAmI 2015. Lecture Notes in Computer Science(), vol 9454. Springer, Cham. https://doi.org/10.1007/978-3-319-26401-1_11

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  • DOI: https://doi.org/10.1007/978-3-319-26401-1_11

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-26401-1

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