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Rule-Based Real-Time ADL Recognition in a Smart Home Environment

Baryannis, George, Woznowski, Przemyslaw and Antoniou, Grigoris (2016) Rule-Based Real-Time ADL Recognition in a Smart Home Environment. In: Rule Technologies. Research, Tools, and Applications. Lecture Notes in Computer Science, 9718 . Springer International Publishing, pp. 325-340. ISBN 978-3-319-42018-9

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Abstract

This paper presents a rule-based approach for both offline and real-time recognition of Activities of Daily Living (ADL), leveraging events produced by a non-intrusive multi-modal sensor infrastructure deployed in a residential environment. Novel aspects of the approach include: the ability to recognise arbitrary scenarios of complex activities using bottom-up multi-level reasoning, starting from sensor events at the lowest level; an effective heuristics-based method for distinguishing between actual and ghost images in video data; and a highly accurate indoor localisation approach that fuses different sources of location information. The proposed approach is implemented as a rule-based system using Jess and is evaluated using data collected in a smart home environment. Experimental results show high levels of accuracy and performance, proving the effectiveness of the approach in real world setups.

Item Type: Book Chapter
Uncontrolled Keywords: Event Driven Architectures, Activity Recognition, ADL, Indoor Localisation, Smart Home, Multi-Modal Sensing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Schools: School of Computing and Engineering
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge
School of Computing and Engineering > High-Performance Intelligent Computing > Planning, Autonomy and Representation of Knowledge
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Depositing User: Georgios Bargiannis
Date Deposited: 14 Jul 2016 10:57
Last Modified: 30 Nov 2016 15:35
URI: http://eprints.hud.ac.uk/id/eprint/29003

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