The Handbook of AI for Clean Water

Innovations in Treatment and Monitoring
1. Auflage 2025
ISBN: 978-1-032-98806-1
Verlag: Taylor & Francis Ltd

Buch, Englisch, 400 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 453 g

The Handbook of AI for Clean Water: Innovations in Treatment and Monitoring is a comprehensive guide that delves into the transformative role of Artificial Intelligence (AI) in addressing the global water crisis through advanced treatment, monitoring, and management technologies. Divided into nine thematic parts and spanning 21 chapters, this volume provides a structured and interdisciplinary examination of how AI can revolutionize clean water access, treatment efficiency, contamination control, and policymaking.

The book offers in-depth insights into AI applications across water quality monitoring, predictive maintenance, microbial detection, desalination, and governance. With a technical emphasis on AI-IoT integration, machine learning algorithms, data-driven decision-making, and sustainable water management, it explores case studies, technical models, and futuristic solutions aimed at reducing environmental impact and enhancing system efficiency. This handbook empowers readers with knowledge of both foundational principles and cutting-edge innovations.

This is an ideal resource for researchers, environmental scientists, policymakers, engineers, graduate students, and professionals in water resource management. It is also intended for AI developers and decision-makers seeking to implement data-driven strategies for clean water access and sustainability.

Zielgruppe

Postgraduate, Professional Reference, and Undergraduate Advanced

Autoren/Hrsg.

Garg, Manoj Chandra

Agarwal, Smriti

Fachgebiete

• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Wasserversorgung, Wasseraufbereitung
• Geowissenschaften Umweltwissenschaften Umwelttechnik
• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik
• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Abfallwirtschaft, Abfallentsorgung
• Geowissenschaften Umweltwissenschaften Abfallbeseitigung, Abfallentsorgung

Inhaltsverzeichnis

PART 1: UNDERSTANDING THE WATER CRISIS AND AI INTEGRATION  1. Introduction to the Global Water Crisis 2. Role of AI in Mitigating the Water Crisis  PART 2: AI APPLICATIONS IN WATER QUALITY MONITORING  3. Synergy of AI and Internet of Things (IoT) in Water Monitoring 4. Detecting Chemical Contaminants using AI 5. Artificial Intelligence Applications in Water Monitoring and Risk Management 6. Advanced Dynamic Water Quality Assessment Using Machine Learning Algorithms  PART 3: PREDICTIVE MODELING FOR EFFECTIVE WATER RESOURCE MANAGEMENT 7. AI-Driven Predictive Maintenance and Downtime Optimization in Water Treatment Plants 8. Future Prospects: AI Innovations for Enhanced Water Management 9. AI and the Future of Water Scarcity: Machine Learning for Efficient Resource Management  PART 4: AI REVOLUTIONIZING WATER TREATMENT 10. Automation and Process Optimization in Water Treatment 11. Energy Optimization and Environmental Impact Reduction through AI PART 5: AI COMBATTING CONTAMINANTS FOR SAFE DRINKING WATER 12. Detection and Mitigation of Microbial Threats using AI 13. AI-Powered Decision Support Systems for Sustainable Wastewater Management: Addressing Nutrient Cycling and Heavy Metal Contamination  PART 6: AI AND DESALINATION: A PATH TO WATER SECURITY 14. AI-Driven Optimization in Seawater Desalination  PART 7: AI-INTEGRATED WATER POLICY AND GOVERNANCE 15. AI-Enabled Water Policy Formulation and Decision Making 16. Investigation on Some Aspects of Data-Driven Insights for Effective Water Governance 17. Leveraging Data-Driven Approaches: A Case Study on Enhancing Water Governance in Africa  PART 8: AI AND COMMUNITY ENGAGEMENT FOR WATER SUSTAINABILITY 18. Community-Centric Water Conservation using AI  PART 9: CHALLENGES AND FUTURE PERSPECTIVES 19. Ethical and Privacy Challenges in AI-Driven Water Management 20. Environmental Impact of Artificial Intelligence in Water Management 21. Understanding Water Scarcity: The Role of AI in Sustainable Solutions

Über Autor(innen)

Smriti Agarwal is an accomplished academician and researcher with over 17 years of experience in teaching and research. She specializes in machine-learning, AI-driven optimization techniques microwave and millimetre wave radar imaging, antenna design and microwave absorbers. Currently, she serves as an Assistant Professor in the Department of Electronics and Communication Engineering at Motilal Nehru National Institute of Technology (MNNIT) Allahabad, a premier Indian institution of national importance.

Manoj Chandra Garg is an Assistant Professor at the Amity Institute of Environmental Sciences, Amity University Uttar Pradesh, with over ten years of teaching and research experience. He earned his Ph.D. from the Indian Institute of Technology (IIT) Roorkee, focusing on solar photovoltaic-assisted nanofiltration and reverse osmosis systems for water treatment. He also holds an M.Tech. in Environmental Science & Technology from Thapar University, where he was awarded a Gold Medal.