Okeyo, George, Chen, Liming, Wang, Hui and Sterritt, Roy (2010) Ontology-Enabled Activity Learning and Model Evolution in Smart Homes. In: The 7th International Conference on Ubiquitous Intelligence and Computing (UIC 2010), Xian China. Springer-Verlag. Vol 6406 6 pp. [Conference contribution]
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Activity modelling plays a critical role in activity recognition and assistance in smart home based assisted living. Ontology-based activity modelling is able to leverage domain knowledge and heuristics to create Activities of Daily Living (ADL) models with rich semantics. However, they suffer from incompleteness, inflexibility, and lack of adaptation. In this paper, we propose a novel approach for learning and evolving activity models. The approach uses predefined ”seed” ADL ontologies to identify activities from sensor activation streams. We develop algorithms that analyze logs of activity data to discover new activities as well as the conditions for evolving the seed ADL ontologies. We illustrate our approach through a scenario that shows how ADL models can be evolved to accommodate new ADL activities and preferences of individual smart home’s inhabitants.
|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
|Deposited By:||Dr Liming Chen|
|Deposited On:||07 Apr 2011 14:25|
|Last Modified:||09 May 2016 11:06|
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