The Handbook of AI for Clean Water (eBook, ePUB)
Innovations in Treatment and Monitoring
Redaktion: Agarwal, Smriti; Garg, Manoj Chandra
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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 monito...
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-Internet of Things (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.
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-Internet of Things (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.
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