International Journal of Advanced Research in Computer and Communication Engineering

Abstract: The Integrated Dam Automation System (IDAS) deals with safety and efficiency challenges in dam management by combining IoT, image processing, and deep learning technologies. The system features crack and leakage detection, water quality monitoring, automated gate control, and emergency alert mechanisms. It uses sensors and an ESP32 microcontroller to enable real-time monitoring and quick responses to environmental changes, aiming to reduce flood risks and structural failures. Mismanagement of dams can lead to catastrophic outcomes due to unforeseen events. Currently, most countries rely on manual systems to monitor and control dams, which are slow and imprecise. To address this issue, a method based on IoT is suggested for monitoring dams and aiding in disaster prevention. Real-time data such as temperature, water level, rainfall, and water flow rates are collected to monitor dam safety. This setup provides efficient alert systems that categorize potential threats into blue (low risk), orange (medium risk), or red (high risk) alerts through a mobile app. With this approach, experts can monitor the situation, respond quickly, and take necessary actions to prevent dangerous consequences. Depending on the situation and requirements, the dam operator can choose to control the gates manually or automatically. This capability simplifies the management of multiple dams and allows for accurate predictions based on the collected data. Drought, which is also a disaster, can be partially managed with dams. The proposed system demonstrates its effectiveness in drought prevention. This work utilizes the Arduino open-source electronic platform.
Index Terms: IoT, Dam Automation, Crack Detection, Water Level Monitoring, Deep Learning, ESP32, Image Processing, Turbidity Sensor, pH Sensor, Emergency Alert System, YOLOv5, Smart Infrastructure, Real-Time Monitoring.

Downloads: | DOI: 10.17148/IJARCCE.2025.141238