Dependability Analysis of High-Consequence Augmented Reality Systems
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Research on Augmented Reality (AR) has gained traction due to its plethora of benefits and range of applications. In high-consequence environments where the failure of a system can have devastating effects on human life and/or the environment, dependability (that is reliability and availability) are of utmost importance. Therefore, AR systems that form part of or constitute a high-consequence system need to be evaluated for their dependability. Unfortunately, AR research lacks a significant focus on this. Fault Tree Analysis (FTA) is a proven probabilistic risk analysis technique mainly used in engineering to analyse how the individual component failures of a system contribute to a total system failure. This research explores the use of an FTA-based technique for the dependability analysis of high-consequence AR systems. The proposed solution is applied to a real-world case study in the medical field and the results are discussed.
KeywordsAugmented reality Fault tree analysis Risk analysis Monte Carlo simulation
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