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Data and Information Quality Issues in Ambient Assisted Living Systems

McNaull, James, Augusto, Juan Carlos, Mulvenna, Maurice and McCullagh, PJ (2012) Data and Information Quality Issues in Ambient Assisted Living Systems. Journal of Data and Information Quality, 4 (1). 4:1-4:15. [Journal article]

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DOI: 10.1145/2378016.2378020


Demographic aging, as a result of people living for longer, has put an increased burden on health and social care provision across most of the economies of the developed and developing world. In order to cope with the greater numbers of older people, together with increasing prevalence of chronic diseases, governments are looking to new ways to provide care and support to older people and their care providers. A growing trend is where health and social care providers are moving towards the use of assisted living technologies to provide care and assistance in the home. In this article, the research area of Ambient Assisted Living (AAL) systems is examined and the data, information and the higher-level contextual knowledge quality issues in relation to these systems, is discussed. Lack of quality control may result in an AAL system providing assistance and support based upon incorrect data, information and knowledge inputs, and this may have a detrimental effect on the person making use of the system. We propose a model whereby contextual knowledge gained during the AAL system’s reasoning cycle can be fed back to aid in further quality checking at the various architectural layers, and a realistic AAL scenario is provided to support this. Future research should be conducted in these areas, with the requirement of building quality criteria into the design and implementation of AAL systems.

Item Type:Journal article
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute > Smart Environments
Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:23985
Deposited By: Professor Maurice Mulvenna
Deposited On:16 Nov 2012 14:15
Last Modified:17 Oct 2017 16:06

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