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All Journal IJISCS (International Journal of Information System and Computer Science)
Mesioye, Emmanuel Ayobami
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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IOT AND ML-POWERED CYBER-PHYSICAL FRAMEWORK FOR REAL-TIME URBAN FLOOD RESILIENCE WITH GEOSPATIAL VISUALIZATION Mesioye, Emmanuel Ayobami; Oluwagbemi, Johnson Bisi; Akinbo, Shade Racheal; Esan, Mathew Oluwatosin
IJISCS (International Journal of Information System and Computer Science) Vol 10, No 1 (2026): IJISCS (International Journal of Information System and Computer Science)
Publisher : Bakti Nusantara Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/ijiscs.v10i1.1877

Abstract

Urban flooding remains a disastrous challenge for rapidly expanding cities in developing nations. Despite the fact deep learning models and IoT sensing are individually established in hydrology, their seamless integration into a unified, cost-effective Cyber-Physical System (CPS) specifically architected for data-scarce and infrastructure challenged environments remains a critical research gap. This research contributes a novel, end-to-end framework that bridges this divide by harmonizing three distinct pillars: a low-cost, energy-autonomous IoT sensor network, a hybrid CNN-LSTM predictive model, and a dynamic geospatial visualization dashboard. Unlike conventional systems designed for data-rich environments, our framework is contextually adapted for the unique topographical and socio-technical realities of Nigerian urban centers. Validated through a six-month deployment in the high-density Ajeromi-Ifelodun region of Lagos, the system achieved a Nash-Sutcliffe Efficiency (NSE) of 0.89 and a critical 4.5-hour forecast lead time.
Co-Authors Akinbo, Shade Racheal Esan, Mathew Oluwatosin Oluwagbemi, Johnson Bisi