Reliability Analysis Using Bayesian Belief Network on Drone System: A Case Study

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dc.contributor.authorDas, M.
dc.contributor.authorMohan, B.R.
dc.contributor.authorRam Mohana Reddy, G.
dc.contributor.authorChhaparwal, E.
dc.contributor.authorKrishna Kumar, K.
dc.contributor.authorChowdhury, S.
dc.contributor.authorSharma, S.
dc.date.accessioned2026-02-06T06:34:21Z
dc.date.issued2024
dc.description.abstractEnsuring the reliability of software components is of paramount importance in safety-critical systems. Grave consequences might occur if software failures in such systems. Hence, predicting software reliability is important in these systems. This research uses Bayesian Belief Network(BBN) and leverages historical failure data to find fault interdependencies, giving much more insights than methodologies like Fault Tree Analysis (FTA) and Reliability Block Diagrams (RBD). By comparing BBNs with these traditional methods, the research shows the dynamic capabilities of BBNs. BBN also shows the capability of using real-time data and machine learning together to increase the software reliability of the software components, making this system much safer. © 2024 IEEE.
dc.identifier.citation2024 IEEE Silchar Subsection Conference, SILCON 2024, 2024, Vol., , p. -
dc.identifier.urihttps://doi.org/10.1109/SILCON63976.2024.10910879
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/29203
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectBayesian Belief Network
dc.subjectConditional Probability Table (CPT)
dc.subjectFailure rate
dc.subjectFault Tree Analysis
dc.subjectOpen Markov
dc.subjectReliability Block Diagram
dc.subjectsoftware reliability
dc.titleReliability Analysis Using Bayesian Belief Network on Drone System: A Case Study

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