<p>This research presents the development of an innovative IoT-based smart drainage system designed to address the persistent flooding challenges in Mogadishu, Somalia. The system integrates real-time water-level monitoring, flow rate measurement, and automated water management solutions, enhancing urban resilience against flooding. Utilizing a combination of ultrasonic sensors, Hall effect flow meters, and a network of water pumps, the system facilitates proactive interventions by redirecting excess water from critical collection points to the ocean. The data collected from these sensors is processed and analyzed using AWS cloud services, ensuring scalable and efficient data management. A user-friendly web application provides real-time visualization of drainage conditions and alerts stakeholders about potential flood risks, thus enabling timely decision-making. Field tests demonstrate that the system not only detects flood risks but also actively mitigates them through automated water removal, showcasing its effectiveness as a scalable and sustainable flood management solution. This research contributes significantly to the discourse on smart city infrastructure, providing a comprehensive framework for disaster resilience and urban sustainability in developing regions, and serving as a scalable model for future implementations in similar contexts.</p>

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Enhancing urban resilience: an IoT-based smart drainage system for flood management in Mogadishu, Somalia

  • Abdulaziz Yasin Nageye,
  • Abdukadir Dahir Jimale,
  • Mohamed Omar Abdullahi,
  • Mohamed Abdirahman Addow

摘要

This research presents the development of an innovative IoT-based smart drainage system designed to address the persistent flooding challenges in Mogadishu, Somalia. The system integrates real-time water-level monitoring, flow rate measurement, and automated water management solutions, enhancing urban resilience against flooding. Utilizing a combination of ultrasonic sensors, Hall effect flow meters, and a network of water pumps, the system facilitates proactive interventions by redirecting excess water from critical collection points to the ocean. The data collected from these sensors is processed and analyzed using AWS cloud services, ensuring scalable and efficient data management. A user-friendly web application provides real-time visualization of drainage conditions and alerts stakeholders about potential flood risks, thus enabling timely decision-making. Field tests demonstrate that the system not only detects flood risks but also actively mitigates them through automated water removal, showcasing its effectiveness as a scalable and sustainable flood management solution. This research contributes significantly to the discourse on smart city infrastructure, providing a comprehensive framework for disaster resilience and urban sustainability in developing regions, and serving as a scalable model for future implementations in similar contexts.