Data-driven lifecycle governance for intelligent public lighting: a multi-city deployment study

Sergio Gambacorta

Digital Transformation and Society, 2026, 1-18

Abstract: PurposeThis practitioner case study addresses the persistent gap between smart city aspirations and implementable urban operator practice by examining how artificial intelligence (AI)-enabled methods can be operationalised across the full infrastructure lifecycle within real infrastructure operator workflows.Design/methodology/approachThe framework integrates four AI-enabled operational tools – GeoAI satellite asset mapping, a fuzzy-logic engine encoding national lighting standards, a Bayesian predictive maintenance model designed for data-scarce contexts and an adaptive lighting control system. The artefacts were deployed and evaluated through naturalistic pilots and retrospective analyses in municipalities in Italy, Spain and Chile.FindingsDeployment evidence (operationally observed, not from controlled experiments) shows 82–92% asset detection accuracy across sites, ∼70% design effort reduction, ∼20% maintenance efficiency gain and ∼35% energy savings beyond light-emitting diode baselines. Cross-site deployment yielded five transferable design principles for scalable, regulation-aware governance of AI-enabled civic infrastructure.Practical implicationsThe framework provides actionable guidance for municipal administrators and infrastructure operators pursuing AI-enabled infrastructure governance, contributing to SDG 7 (Affordable and Clean Energy) and SDG 11 (Sustainable Cities and Communities).Originality/valueThis study contributes an operationally validated governance framework that moves beyond isolated smart city pilots by embedding heterogeneous AI tools into systemic lifecycle management under real-world institutional and regulatory constraints.

Keywords: Smart cities; Urban informatics; Public street lighting; Infrastructure management; Geospatial artificial intelligence; Design science research; Digital transformation; Sustainable development goals; AI governance (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eme:dtspps:dts-04-2026-0170

DOI: 10.1108/DTS-04-2026-0170

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