Drainage Blockage Monitoring and Detection System using IoT

Abstract: Urban drainage systems are essential for maintaining infrastructure, controlling stormwater, and preventing flooding. However, blockages within these systems present significant operational challenges, leading to inefficiencies and increased flood risks. This paper introduces an innovative Internet of Things (IoT)-based solution for the real-time monitoring and detection of drainage blockages. The proposed system utilizes a network of sensors, including ultrasonic sensors for level measurement and vibration sensors for detecting obstruction, all integrated with a cloud platform for continuous data analysis. In addition to monitoring blockages, the system collects valuable data that is processed using machine learning algorithms to predict potential obstructions based on historical trends, allowing for proactive maintenance and better resource allocation. Real-time notifications are sent to relevant authorities, enabling swift intervention. The system’s scalability makes it suitable for deployment in various urban settings, improving the efficiency of drainage management, reducing operational costs, and ensuring public safety. Experimental results show that the system can detect blockages with high accuracy and low latency, offering a promising approach to drainage management that significantly reduces the risk of flooding.