Handbook of Artificial Intelligence in Water Management (eBook, PDF)

Towards Net Zero Emissions
Redaktion: Haddout, Soufiane; Kurniawan, Tonni Agustiono

• Format: PDF

Produktbeschreibung

The Handbook of Artificial Intelligence in Water Management explores the intersection of artificial intelligence (AI) technologies and water management strategies aimed at achieving net zero emissions. It delves into the cutting-edge applications of AI in various facets of water resource management, ranging from optimizing water distribution systems to enhancing wastewater treatment processes.

Explaining how AI-enabled water quality monitoring systems enable faster response times to water quality issues, this book presents a wide range of AI-driven innovations from smart sensors and real-time monitoring systems to intelligent decision support tools. By leveraging advanced AI algorithms, machine learning techniques, and predictive analytics, water managers can optimize water usage, minimize energy consumption, and reduce greenhouse gas emissions across the entire water cycle for an efficient, resilient, and environmentally sustainable future. This book includes case studies and real-world examples for implementing innovative approaches.

This book is a valuable resource for advanced undergraduate students, researchers, and industry professionals interested in utilizing AI to mitigate environmental impacts, enhance resilience, and achieve net zero emissions in water management.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 396
• Erscheinungstermin: 27. Januar 2026
• Englisch
• ISBN-13: 9781040548783
• Artikelnr.: 76224116

Autorenporträt

Dr. Soufiane Haddout is a researcher in the Department of Physics, Faculty of Science, Ibn Tofail University, Morocco. He is the author of 3 books, over 60 refereed journal articles with 40 refereed articles as the first author. He is involved in collaborative research with 22 universities/institutions worldwide, serves as an expert reviewer with AEIC-Academic Exchange Information Centre (China), and he is a reviewer for many project proposals from international universities. He has received more than 100 certificates from international conferences and renowned journals and been a Keynote/invited speaker and Technical Committee member for numerous international conferences. He is the Co-Chair of the scientific session of the International Conference of Coastal and Estuarine Research Federation USA; 1st and 2nd International Conference on Climate Change and Ocean Renewable Energy; and Chair of the scientific session of the 16th International Conference on Computer and Electrical Engineering (ICCEE 2023). Dr. Tonni Agustiono Kurniawan is an Associate Professor at Xiamen University, China. He is a recognized global leader in tackling complex environmental problems that have significant societal relevance and positive impact in the world. His research interests are in the areas of wastewater treatment and solid waste management. His degrees include a B.Sc. in chemistry from the Bogor Agricultural University (Indonesia), a M.Sc. in environmental technology from the Thammasat University (Thailand), and a Ph.D. in applied chemical technology from the Hong Kong Polytechnic University (China). Dr. Kurniawan has authored an extensive body of work comprising over 218 peer-reviewed journal publications, 26 conference proceedings, 14 book chapters, and 12 monographs in waste to energy and wastewater treatment. Dr. Kurniawan received the 2010 Green Talent Award from German Federal Ministry of Education and Research (BMBF), the 2013 Young Scientist Award from the World Economy Forum (WEF) (Switzerland), and the 2014 Scope-Zhongyu (France) for his outstanding research contribution to the fields of study.

Inhaltsangabe

Introduction. Understanding Artificial Intelligence. 1. SDG and Water:
Artificial Intelligence Nexus. Part I. Water Quality and Resource
Management. 2. Urban Water Management Challenges and Solutions. 3. Machine
Learning, IoT, and GIS for Water Quality Monitoring. 4. Advantages and
Challenges of AI-Driven Water Quality Monitoring. 5. Artificial
Intelligence in Water Resource Management. 6. Water Management in the
Context of Net Zero Emissions. 7. Artificial Intelligence for Global Water
Security and Management. 8. Smart Water Infrastructure. Part II.
Applications in Agriculture. 9. Smart Technologies to Achieve Net Zero
Emissions in Food Production Systems. 10. AI-Integration for Irrigation
Optimization. 11. Precision Agriculture and Water Efficiency: Predictive
Analytics, Irrigation Scheduling, and Weather Forecasting Models. Part III.
Climate Action and Conservation. 12. Aquatic Ecosystem Preservation using
Artificial Intelligence. 13. Artificial Intelligence and Water
Conservation. 14. Floodplain Width Prediction in Flood Disaster Management.
15. K-Means Clustering: Geometric Design of Double-Arch Dams. 16. Water
Security in a Changing World: Harnessing AI to Mitigate Climate Change
Impacts. 17. Building Climate-Resilient Water Systems: Challenges,
Solutions, and AI-Driven Strategies. 18. Future Trends and Emerging
Technologies in the Integration of AI and Water Management. 19. Conclusion.