Water Leakage Detection and Recognition System

An IoT-enabled water leak detection system is proposed. The proposed system uses real-time data collection and advanced machine learning techniques for continuous monitoring. It consists of two leak sensors integrated with Arduino nodes. It also uses NodeMCU to enable IoT communication and alerts. The sensors continuously monitor water flow and pressure to detect any anomalies that may indicate a leak. The system collects real-time datasets, which are then processed using a modified Long Short-Term Memory (LSTM) model for accurate leak prediction. The modified LSTM uses a new attention mechanism to increase the model's ability to focus on significant data patterns. This integration is used to increase the prediction accuracy. The loT-enabled system sends immediate alerts to users upon detecting a leak. This ensures swift response and minimizing water loss. This approach increases leak detection efficiency, resource management, and reduces manual intervention. Experimental results show that the proposed system achieves higher accuracy and best suitable for both residential and industrial water distribution networks.