Dependability Analysis of High-Consequence Augmented Reality Systems

Ernest Edifor () and Eleanor E. Cranmer
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Ernest Edifor: Manchester Metropolitan University
Eleanor E. Cranmer: Manchester Metropolitan University

A chapter in Augmented Reality and Virtual Reality, 2020, pp 349-359 from Springer

Abstract: Abstract 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.

Keywords: Augmented reality; Fault tree analysis; Risk analysis; Monte Carlo simulation (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-030-37869-1_28

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DOI: 10.1007/978-3-030-37869-1_28

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