This three-volume set delves into the intersection of cutting-edge technology and environmental science to address pressing challenges in the water sector and develop digitalization solutions that can have practical implementation in decision-making and management of wastewater treatment.
With special emphasis on the integration of big data, artificial intelligence (AI), and machine learning (ML), Volume 1 provides theoretical, foundational, and practical insights for water systems optimization, resource conservation, and sustainable operations; Volume 2 explores pathways to a sustainable, low-carbon future by emphasizing predictive maintenance, energy-efficient operations, leak detection, and climate-adaptive planning; and Volume 3 pursues real-world applications in water supply, wastewater treatment, and flood management through a host of diverse and well-researched case studies.
Ideal for water engineers, researchers, policymakers, and sustainability practitioners, this handbook serves as an essential guide for professionals seeking to harness digitalization for smarter, data-driven water management. It is equally valuable for graduate students, academics, and technology innovators interested in bridging the gap between emerging AI capabilities and practical water sector applications.