An ontology-based context-aware framework for behavior analysis and reminder delivery is described within this Chapter. Such a framework may be used to assist elderly persons maintain a healthy daily routine and help them to live safely and independently within their own home for longer periods of time. Behavior analysis associated with the delivery of reminders offers strategies to promote a healthier lifestyle. Current studies addressing reminder based systems have focused largely on the delivery of prompts for a prescribed schedule at fixed times. This is not ideal given that such an approach does not consider what the user is doing and whether the reminder is relevant to them at that specific point in time. Our proposed solution is based upon high-level domain concept reasoning, to account for more complex scenarios. The solution, referred to as iMessenger, addresses the problem of efficient and appropriate delivery of feedback by combining context such as current activity, posture, location, time and personal schedule to manage any inconsistency between what the user is expected to do and what the user is actually doing. The ontology-based context-aware approach has the potential to integrate knowledge and data from different ontology-based repositories. Therefore, iMessenger can utilize a set of potential ontological, context extracting frameworks, to locate, monitor, address and deliver personalized behaviour related feedback, aiding people in the self-management of their well-being.
|Title of host publication||Activity Recognition in Pervasive Intelligent Environments|
|Editors||L Chen, C D Nugent, J Biswas, J Hoey|
|Publication status||Published - 2011|
Zhang, S., McCullagh, P., Nugent, C., & Zheng, H. (2011). An Ontology-Based Context-aware Approach for Behaviour Analysis. In L. Chen, C. D. Nugent, J. Biswas, & J. Hoey (Eds.), Activity Recognition in Pervasive Intelligent Environments (Vol. 4, pp. 127-148). Atlantis Press. https://doi.org/10.2991/978-94-91216-05-3_6