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.
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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 millimeter 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 10 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 and Technology from Thapar University, where he was awarded a Gold Medal.
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Hardcover. Zustand: new. Hardcover. 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 AIInternet 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 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9781032988061
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