Resumen

KINJO, Erika Midori; LIBRANTZ, André Felipe Henriques; SOUZA, Edson Melo de  y  SANTOS, Fábio Cosme Rodrigues dos. Bayesian modeling applied to calculate the probability of failure in IoT Health Systems. RISTI [online]. 2022, n.47, pp.87-108.  Epub 30-Sep-2022. ISSN 1646-9895.  https://doi.org/10.17013/risti.47.87-108.

The implementation of the Internet of Things (IoT) technology provides benefits to life, such as remote pest control in agriculture, monitoring the supply chain, improvement environment in education, and monitoring patients. However, despite the benefits, there are challenges embedded in the implementation of this technology. One of the biggest challenges in the area is the violation of privacy and data security. Therefore, it is necessary to assess the probability of failure of the components and, consequently, the cause of this problem. So, it is in this context that this work proposes to identify, model, and calculate the failure probability through a systematic analysis, using Bayesian Networks. The results showed that through the use of the proposed model it was possible to evaluate different scenarios for the use of Internet of Things networks, as well as to simulate the effect of the probability of failure in the critical components of the system.

Palabras clave : Bayesian Network; Failure; Health; Internet of Things; IoT; Noisy-OR.

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