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Incorporating Duration Information in Activity Recognition.

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

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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DOI: 10.1007/978-3-642-15280-1_24

Abstract

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 Information Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
Computer Science Research Institute > Smart Environments
ID Code:19094
Deposited By:Professor Sally McClean
Deposited On:18 Jul 2011 16:18
Last Modified:18 Jul 2011 16:18

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