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Article type: Research Article
Authors: Doyle, Julie; | Kealy, Andrea | Loane, John | Walsh, Lorcan | O'Mullane, Brian | Flynn, Carl | Macfarlane, Andrew | Bortz, Brennon | Knapp, R. Benjamin | Bond, Rodd;
Affiliations: CASALA, Dundalk Institute of Technology, Dundalk, Co. Louth, Ireland | Netwell Centre, Dundalk Institute of Technology, Dundalk, Co. Louth, Ireland | Institute for Creativity, Arts and Technology, Virginia Tech, Blacksburg, Virginia 24060, USA
Note: [] Corresponding author. E-mail: julie.doyle@casala.ie.
Abstract: With an ageing population and the constant need towards improving the quality of life for older people in our society, there comes an urgent challenge to support people where they live in an environment that adapts to their needs as they age. While much research on ubiquitous sensor systems and telehealth devices focuses on this need, many of these solutions operate at less than full capacity, and with little scope at present to assess everyday aspects of wellbeing. They focus on detecting sudden critical physiological and behavioural changes and offer few mechanisms to support preventative actions. The challenge of predicting changes and prompting positive preventative intervention measures, aiding the avoidance of severe physical or mental harm, has not adequately been addressed. This paper discusses our experiences of designing, deploying and testing an integrated home-based ambient assisted living (AAL) system for older adults, consisting of ambient monitoring, behaviour recognition and feedback to support self-management of wellness, in addition to providing feedback on home security and home energy. It offers a complete system overview of an AAL solution in smart environments and discusses our lessons learned with the goal of assisting other researchers in the field in designing and deploying similar environments.
Keywords: Aging in place, smart homes, independent living, older adults, activity recognition, behaviour change, telecare
DOI: 10.3233/AIS-140270
Journal: Journal of Ambient Intelligence and Smart Environments, vol. 6, no. 4, pp. 359-383, 2014
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