Dams are critical infrastructures; their management and control are essential to ensure their safety, optimal utilization of water resources, and proactive maintenance. In this paper, we propose an innovative IoT-based intelligent framework for real-time dam monitoring and control. The system integrates a network of advanced sensors, edge devices, and cloud-based data analytics to enable real-time monitoring and predictive maintenance of dam infrastructures. The system utilizes ultrasonic water level sensors, temperature probes, and environmental sensors to collect critical data, which is then processed by microcontrollers equipped with integrated wireless connectivity. A key originality of our approach lies in the adoption of IoT design patterns, particularly the Delta Update and Incremental Update patterns, which significantly optimize data transmission, reduce bandwidth consumption, and improve energy efficiency. Data are securely transmitted via protocols to a cloud platform. Experimental results demonstrate the framework’s capability to enhance the accuracy, responsiveness, and efficiency of dam monitoring. Our approach not only addresses the limitations of conventional monitoring techniques but also provides a scalable, pattern-driven solution that supports data-driven decision-making for improved dam safety and operational performance.
Tounsi et al. (Thu,) studied this question.