LoRaWAN AI-Powered Digital Twins for Smart Water Distribution Networks

Abstract

Water Distribution Networks (WDNs) are complex, dynamic systems critical to modern society but increasingly difficult to manage due to urbanization, fluctuating demands, and resource constraints. To address these challenges, Smart Water Distribution Networks (SWDNs) utilize Internet of Things (IoT) devices and protocols like Long Range Wide Area Network (LoRaWAN) for real-time monitoring and analysis, enabling smarter and more efficient water management. This demo presents SWIM (Smart Water Interaction & Monitoring), an innovative application designed to modernize SWDNs. SWIM integrates Digital Twins (DTs), established simulation tools like EPANET, and Machine Learning (ML) to provide predictive analytics, anomaly detection, and real-time control. By employing neural networks, SWIM achieves high-accuracy hydraulic predictions with minimal input data. Built on IoTs and Low Power Wide Area Networks (LPWANs), SWIM delivers scalable, efficient, and user-friendly solutions. It aligns with the principles of Industry 5.0, demonstrating the potential to revolutionize water distribution networks and ensure their sustainability in the face of modern challenges.