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.
A Multi Agent System that provides a (cared for) person, the subject, with assistance and support through an Ambient Assisted Living Flexible Interface (AALFI) during the day while complementing the night time assistance offered by NOCTURNAL with feedback assistance, is presented. It has been tailored to the subject's requirements profile and takes into account factors associated with the time of day; hence it attempts to overcome shortcomings of current Ambient Assisted Living Systems. The subject is provided with feedback that highlights important criteria such as quality of sleep during the night and possible breeches of safety during the day. This may help the subject carry out corrective measures and/or seek further assistance. AALFI provides tailored interaction that is either visual or auditory so that the subject is able to understand the interactions and this process is driven by a Multi-Agent System. User feedback gathered from a relevant user group through a workshop validated the ideas underpinning the research, the Multi-agent system and the adaptable interface.
Abstract-Technology has been adopted to mitigate adverse effects associated with aging. Ambient Assisted Living solutions provide user assistance and support which is potentially both efficient and effective. This paper describes initial evaluation results for a Multi-Agent system prototype that provides assistance and support during the day and night through an interface that is adapted according to a person's requirements profile, time of day and current activity or event. Appropriate feedback based on user context is important. This includes historical feedback which may indicate trends, which may not be apparent, particularly where the user may be forgetful.
Multi-Agent Systems provide the software to analyse and understand the data emanating from sensor networks in support of Ambient Assisted Living. We report on the implementation of interfaces which are controlled and dynamically updated by such a multi-agent system. The system can respond to changes of context and tailor interventions and interactions based on the individual who is interacting with the interface.
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