An Agent-mediated Ontology-based Approach for Composite Activity Recognition in Smart Homes
Activity recognition enables ambient assisted living applications to provide activity-aware services to users in smart homes. Despite significant progress being made in activity recognition research, the focus has been on simple activity recognition leaving composite activity recognition an open problem. For instance, knowledge-driven activity recognition has recently attracted increasing attention but mainly focused on simple activities. This paper extends previous work by introducing a knowledge-driven approach to recognition of composite activities such as interleaved and concurrent activities. The approach combines the recognition of single and composite activities into a unified framework. To support composite activity modelling, it combines ontological and temporal knowledge modelling formalisms. In addition, it exploits ontological reasoning for simple activity recognition and qualitative temporal inference to support composite activity recognition. The approach is organized as a multi-agent system to enable multiple activities to be simultaneously monitored and tracked. The presented approach has been implemented in a prototype system and evaluated in a number of experiments. The experimental results have shown that average recognition accuracy for composite activities is 88.26%.
Citation : Okeyo, G., Chen, L. and Wang, H. (2013) An Agent-mediated Ontology-based Approach for Composite Activity Recognition in Smart Homes. Journal of Universal Computer Science, 19 (17), pp. 2577-2597
ISSN : 0948-695X
Research Institute : Cyber Technology Institute (CTI)
Peer Reviewed : Yes
Showing items related by title, author, creator and subject.
Evaluating human activity recognition systems usually implies following expensive and time-consuming methodologies,where experiments with humans are run with the consequent ethical and legal issues. We propose a novel ...