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Analyzing Activity Recognition Uncertainties in Smart Home Environments

Kim, Eunju, Helal, Sumi, Nugent, CD and Beattie, Mark (2015) Analyzing Activity Recognition Uncertainties in Smart Home Environments. ACM Transactions on Intelligent Systems and Technology, 6 (4). pp. 1-28. [Journal article]

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URL: http://dx.doi.org/10.1145/2651445

DOI: doi:10.1145/2651445


In spite of the importance of activity recognition (AR) for intelligent human-computer interaction in emerging smart space applications, state-of-the-art AR technology is not ready or adequate for real-world deployments due to its insufficient accuracy. The accuracy limitation is directly attributed to uncertainties stemming from multiple sources in the AR system. Hence, one of the major goals of AR research is to improve system accuracy by minimizing or managing the uncertainties encountered throughout the AR process. As we cannot manage uncertainties well without measuring them, we must first quantify their impact. Nevertheless, such a quantification process is very challenging given that uncertainties come from diverse and heterogeneous sources. In this article, we propose an approach, which can account for multiple uncertainty sources and assess their impact on AR systems. We introduce several metrics to quantify the various uncertainties and their impact. We then conduct a quantitative impact analysis of uncertainties utilizing data collected from actual smart spaces that we have instrumented. The analysis is intended to serve as groundwork for developing “diagnostic” accuracy measures of AR systems capable of pinpointing the sources of accuracy loss. This is to be contrasted with the currently used accuracy measures.

Item Type:Journal article
Keywords:Reasoning under uncertainty
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Faculty of Life and Health Sciences > School of Sport
Faculty of Life and Health Sciences
Research Institutes and Groups:Computer Science Research Institute > Smart Environments
Computer Science Research Institute
ID Code:32546
Deposited By: Professor Christopher Nugent
Deposited On:02 Nov 2015 11:03
Last Modified:02 Nov 2015 11:03

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