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A Novel Framework for Enhancing Resilience of Urban Underground Drainage Networks in IoT Sponge City

Dui, Hongyan, Li, Ran, Zhang, Huanqi, Wu, Shaomin (2026) A Novel Framework for Enhancing Resilience of Urban Underground Drainage Networks in IoT Sponge City. IEEE Transactions on Reliability, . ISSN 0018-9529. (doi:10.1109/TR.2026.3686421) (KAR id:113964)

Abstract

Amid increasing extreme rainfall events, urban pluvial flooding poses a significant threat to city infrastructure and public safety. To address the limitations such as poor coordination between subsystems and low resilience of conventional IoT frameworks in underground drainage networks, this paper proposes a resilience-driven architecture termed R⁴-UDN. The framework integrates four signature mechanisms: event-triggered sensing, resimulation-in-loop, cascade-aware control, and cross-layer KPI alignment, forming a closed-loop management system. The paper introduces a multi-stage resilience index and embeds it into a semi-Markov cascade model to capture system performance dynamically. Furthermore, it optimizes the resilience and sequence-sensitive cost. A case from Chengdu, China, is studied to confirm that the proposed method significantly enhances resilience compared to conventional strategies, validating the practical value of R⁴-UDN for enhancing the resilience of sponge city underground drainage systems.

Item Type: Article
DOI/Identification number: 10.1109/TR.2026.3686421
Additional information: For the purpose of open access, the author(s) has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising.
Uncontrolled keywords: resilience optimization, urban drainage networks, IoT architecture, hydrodynamic simulation coupling, multi-objective optimization
Subjects: H Social Sciences > HA Statistics > HA33 Management Science
Institutional Unit: Schools > Kent Business School
Former Institutional Unit:
There are no former institutional units.
Funders: University of Kent (https://ror.org/00xkeyj56)
Depositing User: Shaomin Wu
Date Deposited: 24 Apr 2026 07:42 UTC
Last Modified: 27 Apr 2026 12:21 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/113964 (The current URI for this page, for reference purposes)

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