Chaurasia,, Priyanka, Bryan, Scotney, McClean, Sally, Zhang, Shuai and Nugent, Chris (2010) Incorporating Duration Information in Activity Recognition. In: KSEM 2010, Belfast, UK. Springer LNCS. Vol 6291 16 pp. [Conference contribution]
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Activity recognition has become a key issue in smart home environments. The problem involves learning high level activities from low level sensor data. Activity recognition can depend on several variables; one such variable is duration of engagement with sensorised items or duration of intervals between sensor activations that can provide useful information about personal behaviour. In this paper a probabilistic learning algorithm is proposed that incorporates episode, time and duration information to determine inhabitant identity and the activity being undertaken from low level sensor data. Our results verify that incorporating duration information consistently improves the accuracy.
|Item Type:||Conference contribution (Paper)|
|Faculties and Schools:||Faculty of Computing & Engineering|
Faculty of Computing & Engineering > School of Computing and Mathematics
Faculty of Computing & Engineering > School of Computing and Information Engineering
|Research Institutes and Groups:||Computer Science Research Institute > Smart Environments|
Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
|Deposited By:||Professor Sally McClean|
|Deposited On:||18 Jul 2011 15:18|
|Last Modified:||18 Jul 2011 15:18|
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