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Smart Stormwater Systems: AI-Driven Forecasting, Optimization, and Real-Time Control
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Author(s): Yassine Ezaier (University Hassan II, Casablanca, Morocco), Md. Asadullahil Galib Fardin (Rajshahi University of Engineering and Technology, Bangladesh), Likhon Chandra Roy (Rajshahi University of Engineering and Technology, Bangladesh), Mehedi Hashan Riad (Bangladesh University of Engineering and Technology, Bangladesh), Md. Rafiul Islam (Rajshahi University of Engineering and Technology, Bangladesh), Samanta Alam (Chicago State University, USA)and Ahmed Hader (University Hassan II, Casablanca, Morocco)
Copyright: 2026
Pages: 40
Source title:
Computational Intelligence and Optimization Methods for Sustainable Water Management
Source Author(s)/Editor(s): Yassine Ezaier (Hassan II University, Casablanca, Morocco), Rajae Gaamouche (Moroccan School of Engineering Sciences, Rabat, Morocco)and Mohamed Lahby (Hassan II University, Casablanca, Morocco)
DOI: 10.4018/979-8-3373-2700-6.ch007
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Abstract
This chapter emphasizes the potential of integrating green infrastructure (GI) with computational techniques to revolutionize urban stormwater management. Conventional gray infrastructure is inadequate in mitigating urban flooding and pollution, whereas green infrastructure such as rain gardens and bioswales provides nature-based remedies. Nonetheless, their efficacy is contingent upon local context, rendering models such as SWMM and GIS indispensable for planning. Machine learning, IoT sensors, and digital twins significantly improve forecasting, control, and optimization. Despite ongoing issues related to data quality and fairness, the amalgamation of intelligent technology with ecological design offers a robust and flexible strategy for constructing sustainable, flood-resilient, and inclusive urban water systems in a dynamic environment.
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