Abstract
Ambient Assisted Living are equipped with ubiquitous technologies, and use sensors as their main element for environmental data collection, providing systems with updated information. Currently, there is a convergence combining systems for smart environments and uncertainty reasoning. Considering that the world population is aging, health-support issues are in evidence, and many dangerous situations concerning users in their living environment may arise. However, reasoning to detect situations taking into account uncertainty presents a great challenge. This paper describes a contextual model based on semantic web technologies that deals with uncertainty. This model may be used to detect unwanted situations with a certain grade of contextual uncertainty. The model was evaluated in scenario exhibiting the reasoning over uncertain data to predict unwanted or perhaps dangerous situations.
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Machado, A., Maran, V., Augustin, I., Lima, J.C., Wives, L.K., de Oliveira, J.P.M. (2017). Ambient Assisted Living Systems: A Model for Reasoning Under Uncertainty. In: Hammoudi, S., Maciaszek, L., Missikoff, M., Camp, O., Cordeiro, J. (eds) Enterprise Information Systems. ICEIS 2016. Lecture Notes in Business Information Processing, vol 291. Springer, Cham. https://doi.org/10.1007/978-3-319-62386-3_16
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