May 17, 2016 12:49:18 PM
New CS Dept, Stony Brook Univ
Stony Brook, NY
Jul 6, 2016 10:30 AM
Jul 6, 2016 11:00 AM
A paper at #RuleML2016 by George Baryannis (University of Huddersfield), Przemyslaw Woznowski (University of Bristol), and Grigoris Antoniou (University of Huddersfield)
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 recognize 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 considerably 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.