With special emphasis on the integration of big data, artificial intelligence (AI), and machine learning (ML), Volume 3 pursues real-world applications in water supply, wastewater treatment and flood management through a host of diverse and well-researched case studies.
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, 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.
1. The Role of Big Data and AI Policy in Big Data during the Earthquake
Using the k-Means Algorithm for Defining the Seismic Input;
2. A Lightweight
Deep Learning LSTM Model for Efficient Real-time Water Quality Classification
in IoT-Enabled Aquaculture;
3. Machine Learning-Based Energy Consumption
Model of Wastewater Treatment Plants: A Case Study from China;
4. Can
Indonesian Maritime Education Harness Big Data to Meet the Belt and Road
Initiatives Demands?;
5. Unlocking the Potential of Big Earth Data to Track
Water Scarcity;
6. AI-Driven Intelligent Water Systems: A New Paradigm for
Water Resource Management;
7. Water Conservation and AI;
8. Water Banking as
a Management and Conservation Strategy for a Vital Resource;
9. AI-Integrated
Drone Systems for Illegal Waste Monitoring in Indonesia: Enhancing
Environmental Compliance and Data-Driven Waste Management;
10. The Trajectory
of Digital Transformation within the Water Sector;
11. Artificial Neural
Network (ANN) Modeling of Wastewater Effluent Treatment: A Case Study from
Asia Region;
12. Conventions on International Water and the Abuse of
Transboundary
Tonni Agustiono Kurniawan is a recognized global leader in tackling complex environmental problems that have significant societal relevance and positive impact in the world. His focus on sustained scientific research is evident from more than 355 journal articles, 25 articles in conference proceedings, twelve monographs, and 28 book chapters. To date, Kurniawan is the first author of 15% of the works with an h-index of 68 and citations of over 19,500 counts (Scopus), while being the corresponding author of one third of the same works. The scientific contributions are tangible manifestations of his competence and research impact in the discipline.
Abdelkader Anouzla received his Ph.D. in Science & Technology at Hassan II University -Faculty of Science and Technology Mohammedia, specializing in water treatment. Dr. Abdelkader Anouzla has published almost 100 peer-reviewed articles and twenty books. He has been invited as a guest speaker to several conferences and has also published his research in numerous proceedings. His research interests include water and waste treatment, wastewater treatment plant operation, leachate discharge treatment, solid waste sorting, technical landfill management, composting of solid waste and sludge from wastewater treatment plants, water-food-energy nexus, microplastic pollution, digitalization in the water sector and nitrogen pollution.
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