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Issue No.01 - January/February (2012 vol.27)
pp: 32-38
Diane J. Cook , Washington State University
ABSTRACT
<p>Smart home activity recognition systems can learn generalized models for common activities that span multiple environment settings and resident types.</p>
INDEX TERMS
machine learning, ubiquitous computing, pervasive computing, activity recognition
CITATION
Diane J. Cook, "Learning Setting-Generalized Activity Models for Smart Spaces", IEEE Intelligent Systems, vol.27, no. 1, pp. 32-38, January/February 2012, doi:10.1109/MIS.2010.112
REFERENCES
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3. V. Wadley et al., "Mild Cognitive Impairment and Everyday Function: Evidence of Reduced Speed in Performing Instrumental Activities of Daily Living," Am. J. Geriatric Psychiatry, vol. 16, no. 5, 2008, pp. 416–424.
4. D. Cook and S. Das eds., , Smart Environments: Technology, Protocols, and Applications, Wiley, 2004.
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7. D. Cook and M. Schmitter-Edgecombe, "Assessing the Quality of Activities in a Smart Environment," Methods Information in Medicine, vol. 48, no. 5, 2009, pp. 480–485.
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9. A. Viterbi, "Error Bounds for Convolutional Codes and an Asymptotically-Optimum Decoding Algorithm," IEEE Trans. Information Theory, vol. 13, no. 2, 1967, pp. 260–269.
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