Explainable artificial intelligence for sustainable urban water systems engineering

• Enhances transparency in water systems through explainable decision-making models. • Boosts water demand forecasting and leak detection with interpretable AI techniques. • Case studies show a 12 % reduction in water losses via smart metering solutions. • Integrates AI for energy-efficient pump scheduling, reducing energy use by 20 %. • Supports policymakers with climate impact insights for urban drainage systems. Explainable Artificial Intelligence (XAI) has potential for revolutionary improvements in operational efficiency, resilience, and decision-making in the engineering of sustainable urban water systems. Presenting cutting-edge approaches in XAI (such as SHAP (Shapley Additive Explanations), LIME…

• SI
  Saveetha Institute of Medical and Technical Sciences