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A Continuous-Time Model-Based Approach to Activity Recognition for Ambient Assisted Living

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Quantitative Evaluation of Systems (QEST 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9259))

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Abstract

In Ambient Assisted Living (AAL), Activity Recognition (AR) plays a crucial role in filling the semantic gap between sensor data and interpretation needed at the application level. We propose a quantitative model-based approach to on-line prediction of activities that takes into account not only the sequencing of events but also the continuous duration of their inter-occurrence times: given a stream of time-stamped and typed events, online transient analysis of a continuous-time stochastic model is used to derive a measure of likelihood for the currently performed activity and to predict its evolution until the next event; while the structure of the model is predefined, its actual topology and stochastic parameters are automatically derived from the statistics of observed events. The approach is validated with reference to a public data set widely used in applications of AAL, providing results that show comparable performance with state-of-the-art offline approaches, namely Hidden Markov Models (HMM) and Conditional Random Fields (CRF).

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Author information

Authors and Affiliations

  1. Department of Information Engineering, University of Florence, Florence, Italy

    Laura Carnevali, Fulvio Patara & Enrico Vicario

  2. School of Computing and Mathematics, University of Ulster, Belfast, UK

    Christopher Nugent

Authors
  1. Laura Carnevali
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  2. Christopher Nugent
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  3. Fulvio Patara
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  4. Enrico Vicario
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Corresponding author

Correspondence to Laura Carnevali .

Editor information

Editors and Affiliations

  1. Universidad de Zaragoza, Zaragoza, Spain

    Javier Campos

  2. University of Twente, Enschede, The Netherlands

    Boudewijn R. Haverkort

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Carnevali, L., Nugent, C., Patara, F., Vicario, E. (2015). A Continuous-Time Model-Based Approach to Activity Recognition for Ambient Assisted Living. In: Campos, J., Haverkort, B. (eds) Quantitative Evaluation of Systems. QEST 2015. Lecture Notes in Computer Science(), vol 9259. Springer, Cham. https://doi.org/10.1007/978-3-319-22264-6_3

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  • DOI: https://doi.org/10.1007/978-3-319-22264-6_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22263-9

  • Online ISBN: 978-3-319-22264-6

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