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    Multi-modal emotive computing in a smart house environment

    Access Status
    Fulltext not available
    Authors
    Moncrieff, Simon
    Venkatesh, Svetha
    West, Geoffrey
    Greenhill, Steward
    Date
    2007
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Moncrieff, Simon and Venkatesh, Svetha and West, Geoffrey and Greenhill, Stewart. 2007. Multi-modal emotive computing in a smart house environment. Pervasive and Mobile Computing. 3 (2): pp. 74-94.
    Source Title
    Pervasive and Mobile Computing
    DOI
    10.1016/j.pmcj.2006.07.003
    ISSN
    15741192
    Faculty
    School of Electrical Engineering and Computing
    Department of Computing
    Faculty of Science and Engineering
    Remarks

    The link to the journal’s home page is: http://www.elsevier.com/wps/find/journaldescription.cws_home/704220/description#description

    Copyright © 2007 Elsevier Ltd. All rights reserved

    URI
    http://hdl.handle.net/20.500.11937/6323
    Collection
    • Curtin Research Publications
    Abstract

    We determine hazards within a smart house environment using an emotive computing framework. Representing a hazardous situation as an abnormal activity, we model normality using the concept of anxiety, using an agent based probabilistic approach. Interactions between a user and the environment are determined using multi-modal sensor data. The anxiety framework is a scalable, real-time approach that is able to incorporate data from a number of sources, or agents, and able to accommodate interleaving event sequences. In addition to using simple sensors, we introduce a method for using audio as a pervasive sensor indicating the presence of an activity. The audio data enabled the detection of activity when interactions between a user and a monitored device didn’t occur, successfully preventing false hazardous situations from being detected. We present results for a number of activity sequences, both normal and abnormal.

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