Sustainable Water Monitoring - Harnessing IoT and AI for Real-time Leak Detection and Water Quality Prediction

Abstract

Water is an essential resource that supports both ecological sustainability and human survival, necessitating robust management strategies to meet increasing global demands, address climate change, and tackle environmental challenges. This thesis investigates the evolution of water supply monitoring systems, transitioning from traditional manual methods to advanced technologies using the Internet of Things (IoT) and Artificial Intelligence (AI). The central focus is on developing QoW-Pro, an IoT-based system that enhances water quality assessments and leak detection through AI algorithms. This system enables real-time data collection, predictive modeling, and anomaly detection, improving water resource management decisions. By integrating IoT with AI, the research offers a scalable and adaptable solution for various environments, aiming to ensure sustainable water management and quality for future generations.