Abstract
The level of intelligence in monitoring & controlling systems are increasing dramatically. The critical issue for an autonomous resilient system is detecting the anomalous behavior through standard patterns to react properly and on time. In cyber-physical systems with the interaction of humans and machines, this will be more complicated. Deceptive alarm is a common dilemma in real systems which could reduce awareness and readiness and accordingly resilience of the system. In this paper, Markov modeling technique is used to predict human behaviors patterns to distinguish between human anomalous behavior and system failure. The data is from the real experience of implementing innovative monitoring system in a five-star hotel which was part of the project of gamification for changing guests’ behavior. The idea was to develop Resilience Supported System to decrease the fault error and alarms and to increase the reliability and resilience of the system.
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This work has been partially supported by “Temptation Keeper” through Optishower project.
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Aslansefat, K., Ghodsirad, M.H., Barata, J., Jassbi, J. (2018). Resilience Supported System for Innovative Water Monitoring Technology. In: Camarinha-Matos, L., Adu-Kankam, K., Julashokri, M. (eds) Technological Innovation for Resilient Systems. DoCEIS 2018. IFIP Advances in Information and Communication Technology, vol 521. Springer, Cham. https://doi.org/10.1007/978-3-319-78574-5_7
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DOI: https://doi.org/10.1007/978-3-319-78574-5_7
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