Abstract
Home automation systems are ambient intelligence systems that are designed to help people proactively, but sensibly. In this paper we propose a system that learns and automates patterns in the interactions of the user with the home automation devices. We will show our approach and architecture. We use an event processing tool to handle the events from the home automation devices, prediction algorithms to predict the next action and reinforcement learning to decide which action are suitable to be automated.
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References
Cook, D.J.: Mavhome: An agent-based smart home. In: PERCOM 2003, p. 521 (2003)
Cook, D.J.: Review: Ambient intelligence: Technologies, applications, and opportunities. Pervasive Mob. Comput. 5(4), 277–298 (2009)
Ghalsasi, S.Y.: Critical success factors for event driven service oriented architecture. In: ICIS 2009, pp. 1441–1446 (2009)
Hagras, H.: Creating an ambient-intelligence environment using embedded agents. IEEE Intelligent Systems 19(6), 12–20 (2004)
Hartmann, M., Schreiber, D.: Prediction algorithms for user actions. In: LWA, pp. 349–354 (2007)
Jacobs, N., Blockeel, H.: Sequence prediction with mixed order markov chains. In: Proceedings of the Belgian/Dutch Conference on Artificial Intelligence (2003)
Mozer, M.: The neural network house: an environment that adapts to its inhabitants. In: Proceedings of the AAAI Spring Symposium on Intelligent Environments, pp. 110–114 (1998)
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Ché, N.K., Pardons, N., Vanrompay, Y., Preuveneers, D., Berbers, Y. (2010). An Intelligent Domotics System to Automate User Actions. In: Augusto, J.C., Corchado, J.M., Novais, P., Analide, C. (eds) Ambient Intelligence and Future Trends-International Symposium on Ambient Intelligence (ISAmI 2010). Advances in Soft Computing, vol 72. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13268-1_26
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DOI: https://doi.org/10.1007/978-3-642-13268-1_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13267-4
Online ISBN: 978-3-642-13268-1
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