Citation :

Olha Prokopenko, Svitlana Kovalchuk, Anna Chechel, Nataliia Protsiuk, Stanislav Suslikov, "Mechanisms of IoT-based Financial and Economic Optimization of Smart Management of Urban Infrastructure," International Journal of Engineering Trends and Technology (IJETT), vol. 74, no. 6, pp. 386-400, 2026. Crossref, https://doi.org/10.14445/22315381/IJETT-V74I6P126

Abstract

Effective management of urban infrastructure is a challenge for urbanized systems that require flexible and scalable data-driven coordination mechanisms. The aim of the research is to develop and evaluate an integrated smart governance model that combines dynamic pricing, multi-criteria optimization, causal analysis, and federated learning for coordinated management of urban services. The research employed the following methods: Difference-In-Differences (DID) to identify the net effect of the intervention, IV estimates to account for demand endogeneity, and mediation analysis to determine the influence channel. A federated optimization algorithm was used to train the model without transmitting local data. These methods provided a reliable separation of causal effect, preserved confidentiality, and ensured robustness under stochastic conditions. The results show a significant reduction in operating costs (-17.0% or -1,700 €/week), a +6.2 pp increase in QoS, a 35% reduction in network congestion, and a reduction in the risk of extreme costs (CVaR95 by -12,100 €), indicating a significant positive systemic effect. The model demonstrates the ability to generate sustainable behavioural changes in users (up to +26 pp in the transition to off-peak hours), maintaining the effect even after the intervention is completed, showing its practical value for scalable implementation in Smart City ecosystems.

Keywords

Smart city, Internet of Things, Urban infrastructure, Financial and Economic Optimization, Adaptive Management, Energy Management, Digital Transformation.

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