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Activity Inference through Sequence Alignment

  • Conference paper
Location and Context Awareness (LoCA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5561))

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Abstract

Activity inference attempts to identify what a person is doing at a given point in time from a series of observations. Since the 1980s, the task has developed into a fruitful research field and is now considered a key step in the design of many human-centred systems. For activity inference, wearable and mobile devices are unique opportunities to sense a user’s context unobtrusively throughout the day. Unfortunately, the limited battery life of these platforms does not always allow continuous activity logging. In this paper, we present a novel technique to fill in gaps in activity logs by exploiting both short- and long-range dependencies in human behaviour. Inference is performed by sequence alignment using scoring parameters learnt from training data in a probabilistic framework. Experiments on the Reality Mining dataset show significant improvements over baseline results even with reduced training and long gaps in data.

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Author information

Authors and Affiliations

  1. Imperial College London, London, SW7 2AZ, United Kingdom

    Driss Choujaa & Naranker Dulay

Authors
  1. Driss Choujaa
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  2. Naranker Dulay
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Editor information

Editors and Affiliations

  1. Computer Science Department, NH 03755, Dartmouth, Hanover, USA

    Tanzeem Choudhury

  2. Complex & Adaptive Systems Laboratory, School of Computer Science & Informatics, University College Dublin, Belfield Office Park, Dublin 4, Ireland

    Aaron Quigley

  3. Institute of Communications and Navigation, German Aerospace Center, 82234 Wessling/Oberpfaffenhofen, Germany, and Digital Enterprise Research Institute (DERI), University of Innsbruck, 6020, Innsbruck, Austria

    Thomas Strang

  4. Semiconductor Group R&D Division, Sony Corporation, 1-11-1 Osaki, Shinagawa-ku, 141-0032, Tokyo, Japan

    Koji Suginuma

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© 2009 Springer-Verlag Berlin Heidelberg

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Choujaa, D., Dulay, N. (2009). Activity Inference through Sequence Alignment. In: Choudhury, T., Quigley, A., Strang, T., Suginuma, K. (eds) Location and Context Awareness. LoCA 2009. Lecture Notes in Computer Science, vol 5561. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01721-6_2

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  • DOI: https://doi.org/10.1007/978-3-642-01721-6_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01720-9

  • Online ISBN: 978-3-642-01721-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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