AI-Driven Framework for Adaptive Water Network Management with Proof-of-Concept Implementation: Addressing Non-Revenue Water in Jordan
Researchers have developed an AI-driven framework to combat water scarcity in Jordan by reducing non-revenue water (NRW), which accounts for 50% of water loss. The system integrates hydraulic modeling, digital twins, SCADA data, and LLM agents to continuously monitor water networks and adapt decision-making. A proof-of-concept using llama3.1:8b via Ollama demonstrated automated anomaly detection and health reporting, with response times under two minutes. AI
IMPACT This framework could offer a scalable solution for water-scarce regions to leverage AI for operational efficiency and resource management.