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Activity Recognition for Smart Homes Using Dempster-Shafer Theory of Evidence Based on a Revised Lattice Structure. Intelligent Environments 2010: 46-51

Liao, Jing, Bi, Yaxin and Nugent, Chris D. (2010) Activity Recognition for Smart Homes Using Dempster-Shafer Theory of Evidence Based on a Revised Lattice Structure. Intelligent Environments 2010: 46-51. In: Intelligent Environments (IE), 2010 Sixth International Conference on. IEEE Press. 5 pp. [Conference contribution]

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Abstract

This paper explores an improvement to activity recognition within a Smart Home environment using the Dempster-Shafer theory of evidence. This approach has the ability to be used to monitor human activities in addition to managing uncertainty in sensor based readings. A three layer lattice structure has been proposed, which can be used to combine the mass functions derived from sensors along with sensor context and subsequently can be used to infer activities. From the total 209 recorded activities throughout a two week period, 85 toileting activities were considered. The results from this work demonstrated that this method was capable of detecting 75 of the toileting activities correctly within a Smart Home environment equating to a classification accuracy of 88.2%.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute > Smart Environments
Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:25487
Deposited By: Dr Yaxin Bi
Deposited On:19 Jan 2016 09:39
Last Modified:19 Jan 2016 09:39

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