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      Dealing with uncertainty in a context aware pre-embarkation prompter system to support independent living

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      Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI)

      Human Computer Interaction Conference

      4 - 6 July 2018

      Assistive technology, Intellectual disability, Activities of daily living, Context model, Context aware system, Uncertainty, Probabilistic reasoning, Presence detection, Indoor localisation, Wayfinding

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          We live in the information age, where many tasks are automated and many jobs are performed by machines. There has been a certain amount of fear about the rise of artificial intelligence (AI) and cognitive computing and its impact on traditional careers, but these developments are good news for people with disabilities. Elderly people who have lost some of their cognitive capabilities, and those who have life-long intellectual disabilities (ID) can avail of AI to become more independent and enjoy the same conveniences as the rest of society. Of course, this relies on making such systems accessible for this vulnerable group of users. Existing research has considered aids for activities of daily living including wayfinding for helping with commuting for ID service users. This work seeks to produce an assistive technology that supports people with intellectual impairment in the preparations for leaving an indoor space so that they may do so independently with only minimum interventions from the family or the caregiver.

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          Most cited references 11

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          A survey on ambient-assisted living tools for older adults.

          In recent years, we have witnessed a rapid surge in assisted living technologies due to a rapidly aging society. The aging population, the increasing cost of formal health care, the caregiver burden, and the importance that the individuals place on living independently, all motivate development of innovative-assisted living technologies for safe and independent aging. In this survey, we will summarize the emergence of 'ambient-assisted living" (AAL) tools for older adults based on ambient intelligence paradigm. We will summarize the state-of-the-art AAL technologies, tools, and techniques, and we will look at current and future challenges.
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            The Gator Tech Smart House: a programmable pervasive space

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              Bayesian learning theory applied to human cognition.

              Probabilistic models based on Bayes' rule are an increasingly popular approach to understanding human cognition. Bayesian models allow immense representational latitude and complexity. Because they use normative Bayesian mathematics to process those representations, they define optimal performance on a given task. This article focuses on key mechanisms of Bayesian information processing, and provides numerous examples illustrating Bayesian approaches to the study of human cognition. We start by providing an overview of Bayesian modeling and Bayesian networks. We then describe three types of information processing operations-inference, parameter learning, and structure learning-in both Bayesian networks and human cognition. This is followed by a discussion of the important roles of prior knowledge and of active learning. We conclude by outlining some challenges for Bayesian models of human cognition that will need to be addressed by future research. WIREs Cogn Sci 2011 2 8-21 DOI: 10.1002/wcs.80 For further resources related to this article, please visit the WIREs website.

                Author and article information

                July 2018
                July 2018
                : 1-7
                Dublin Institute of Technology Kevin Street, Dublin 7
                © Rifai et al. Published by BCS Learning and Development Ltd. Proceedings of British HCI 2018. Belfast, UK.

                This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit

                Proceedings of the 32nd International BCS Human Computer Interaction Conference
                Belfast, UK
                4 - 6 July 2018
                Electronic Workshops in Computing (eWiC)
                Human Computer Interaction Conference
                Product Information: 1477-9358BCS Learning & Development
                Self URI (journal page):
                Electronic Workshops in Computing


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