Anticipatory edge intelligence : a foundational enabler for resilient critical infrastructure systems

dc.contributor.authorLall, Shruti
dc.contributor.authorPillay, Nelishia
dc.contributor.emailshruti.lall@tuks.co.za
dc.contributor.emailnelishia.pillay@up.ac.za
dc.date.accessioned2026-04-09T06:57:12Z
dc.date.available2026-04-09T06:57:12Z
dc.date.issued2026-01
dc.description.abstractCritical infrastructure systems (CISs), such as power grids, water networks, and transportation systems, operate under stringent requirements for timeliness, resilience, and coordinated response. As these systems become increasingly data-driven and automated, decisions must often be made under uncertainty and with limited tolerance for delay. This position article advocates for anticipatory edge intelligence (AEI) as a conceptual framing for designing edge-enabled intelligence in CISs, with resilience and containment as primary objectives. AEI emphasizes the generation, exchange, and operationalization of short-horizon anticipatory information at the edge to enable coordinated, preemptive action before degradation propagates. The article examines key challenges faced by CISs, identifies opportunities where anticipatory coordination can enhance system-level resilience, and uses an illustrative scenario to motivate this perspective. By articulating AEI as a research and design lens, this work aims to guide future investigation into resilient, edge-enabled infrastructure systems.
dc.description.departmentElectrical, Electronic and Computer Engineering
dc.description.librarianhj2026
dc.description.sdgSDG-09: Industry, innovation and infrastructure
dc.description.sdgSDG-04: Quality education
dc.description.urihttps://www.computer.org/csdl/magazine/ic
dc.identifier.citationS. Lall and N. Pillay, "Anticipatory Edge Intelligence: A Foundational Enabler for Resilient Critical Infrastructure Systems" in IEEE Internet Computing, vol. 30, no. 01, pp. 71-80, Jan.-Feb. 2026, doi: 10.1109/MIC.2026.3657339.
dc.identifier.issn1089-7801 (print)
dc.identifier.issn1941-0131 (online)
dc.identifier.other10.1109/MIC.2026.3657339
dc.identifier.urihttp://hdl.handle.net/2263/109487
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers
dc.rights© 2026 IEEE. All rights reserved, including rights for text and data mining, and training of artificial intelligence and similar technologies.
dc.subjectEdge AI
dc.subjectArtificial intelligence (AI)
dc.subjectResilience
dc.subjectDegradation
dc.subjectDelays
dc.subjectCritical infrastructure
dc.subjectCloud computing
dc.subjectReal-time systems
dc.subjectDecision making
dc.subjectComputer architecture
dc.subjectEdge computing
dc.subjectCritical infrastructure systems (CISs)
dc.subjectAnticipatory edge intelligence (AEI)
dc.subjectModernity
dc.subjectTransport system
dc.subjectInternet Of Things (IoT)
dc.subjectPower grid
dc.subjectTraffic congestion
dc.subjectTight coupling
dc.subjectWater network
dc.subjectPre-emptive action
dc.subjectControl system
dc.subjectDisaster
dc.subjectForecasting
dc.subjectPhysical system
dc.subjectOnline learning
dc.subjectNoisy data
dc.subjectLearning mechanisms
dc.subjectSmart grid
dc.subjectGraph neural networks
dc.subjectCascading failures
dc.subjectEdge nodes
dc.subjectDeep uncertainty
dc.subjectDigital twin
dc.subjectStatic system
dc.subjectMulti agent reinforcement learning
dc.subjectCyber physical systems
dc.subjectInterdependent components
dc.subjectDisaster scenarios
dc.subjectFlight path
dc.titleAnticipatory edge intelligence : a foundational enabler for resilient critical infrastructure systems
dc.typePostprint Article

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