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Resilience of Cyber-Physical Systems: Role of AI, Digital Twins, and Edge Computing
Journal article   Open access   Peer reviewed

Resilience of Cyber-Physical Systems: Role of AI, Digital Twins, and Edge Computing

Andrew Shida Jin, Luke Hogewood, Steffenie Fries, James H. Lambert, Lance Fiondella, Andrew Strelzoff, Jonathan Boone, Karen Fleckner and Igor Linkov
IEEE engineering management review, Vol.50(2), pp.195-203
06/01/2022

Abstract

Cyber-physical systems Data models Digital twin Intelligent sensors Machine learning Resilience risk analysis Sensor systems Sensors
Cyber-physical systems encompass multiple system domains (i.e., water, energy, networking) with heterogeneous goals and complexity of interactions. Existing technologies do not address the disparate time and spatial scales across the many system domains, especially with the latest threats and challenge spaces. New methods to manage resilience of systems, including integrating new computing and sensing strategies, machine learning and artificial intelligence, as well as advanced resilience analytics and prediction, are required to ensure that cyber-physical systems can withstand adverse events. This article summarizes the results of the December 2021 Society for Risk Analysis "Workshop on Resilience Analytics: Methodology and Applications to Cyber-Energy Systems" in which a multidisciplinary team of researchers, policymakers, military, and industry professionals met to identify priorities for research.
url
https://doi.org/10.1109/EMR.2022.3172649View
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