Computational Automation for Water Security: Enhancing Water Quality Management - Softcover

Softcover

ISBN 10: 0443333211 ISBN 13: 9780443333217

Publisher: Elsevier, 2025

Synopsis

Computational Automation for Water Security: Enhancing Water Quality Management is a comprehensive and insightful guide which explores the challenges posed by inefficient and outdated practices, presenting innovative solutions to enhance decision-making, optimizing water treatment processes, and ultimately improving environmental outcomes. Through the coverage of advanced computational techniques, such as data analysis, machine learning, and optimization strategies, readers will gain a deep understanding of how computational automation can revolutionize decision-making. This book is an invaluable resource for professionals, researchers, and policymakers seeking to stay at the forefront of water quality management practices, harnessing the power of computational automation for a cleaner, healthier future.

• Offers a holistic understanding of the application of computational automation in water quality management
• Contains practical and unique updates to help learners how to apply computational techniques to address water quality challenges
• Provides a comprehensive and multidisciplinary perspective on water quality management

About this title

About the Authors

Ashutosh Kumar Dubey is an Associate Professor in the Department of Computer Science and Engineering at Chitkara University, Himachal Pradesh, India. He is also a Postdoctoral Fellow of the Ingenium Research Group Lab, Universidad
de Castilla-La Mancha, Ciudad Real, Spain.

Dr. Arun Lal Srivastav is an Associate Professor in the Department of Applied Sciences at Chitkara University, Himachal Pradesh, India.

Dr Abhishek Kumar is Assistant Director and Professor in the Department of Computer Science & Engineering at Chandigarh University, Punjab. He holds a PhD in Computer Science from the University of Madras and completed postdoctoral research at the Ingenium Research Group Lab, Universidad de Castilla-La Mancha, Spain. He brings extensive expertise in data science and AI-driven analytical modelling. He has published impactful research in reputed journals such as Expert Systems with Applications, Archives of Computational Methods in Engineering, and Scientific Reports, and has published books such as Computer Vision and Machine Intelligence for Renewable Energy Systems (Elsevier) and Quantum Protocols in Blockchain Security (Springer). His research areas are artificial intelligence, renewable energy, machine learning, and image processing.

Fausto Pedro García Márquez works as a Professor and as Director of the Ingenium Research Group at the Universidad De Castilla-La Mancha, Spain. He is an Honorary Senior Research Fellow at Birmingham University, UK, and a Lecturer at the Postgraduate European Institute. He has published more than 150 papers and 31 books (Elsevier, Springer, Pearson, McGraw-Hill, Intech, IGI, Marcombo, AlfaOmega). He has been Principal Investigator in 4 European projects, 6 national projects, and more than 150 projects for universities, companies, and other institutions. His main interests are: Artificial Intelligence, Maintenance, Management, Renewable Energy, Transport, Advanced Analytics, and Data Science.

Dr. Dimitrios Giannakoudakis graduated as chemist from Aristotle University of Thessaloniki (AUTh) in Greece, where he obtained also two M.Sc. degrees (in Physical-chemistry & Electrochemistry and in New Educational Technologies). He received his PhD degree on “Nanotechnology and Materials Chemistry” from the City University of New York (CUNY) with full scholarship, in 02/2017. Then, he continued as postdoctoral-fellow and adjunct tutor at the City College of New York, AUTh, and the Institute of Physical Chemistry (IChF) of Polish Academy of Sciences. Afterwards, he served at IChF as adj. Assistant Professor and tutor of “Modern nano-Topics in Physical Chemistry”. Currently, he is Research Associate and tutor at AUTh.
He has co-authored more than 105 publications in leading peer-reviewed journals (avg. Impact Factor as 1st author above 11), with the articles to be cited more than 3000 times, one monograph by Springer, three edited books by Elsevier, more than 20 book chapters, and 3 invention patents.
For more details: www.DaGchem.com

From the Back Cover

Computational Automation for Water Security: Enhancing Water Quality Management is a comprehensive and insightful guide which explores the challenges posed by inefficient and outdated practices, presenting innovative solutions to enhance decision-making, optimize water treatment processes, and ultimately improve environmental outcomes. Through the coverage of advanced computational techniques, such as data analysis, machine learning, and optimization strategies, readers will gain a deep understanding of how computational automation can revolutionize decision-making, allowing for more informed choices in water quality monitoring, pollution control, and resource allocation. This book is an invaluable resource for professionals, researchers, and policymakers seeking to stay at the forefront of water quality management practices, harnessing the power of computational automation for a cleaner, healthier future.

Edition details

• Publisher: Elsevier
• Publication date: 2025
• Language: English
• ISBN 10: 0443333211
• ISBN 13: 9780443333217
• Binding: Paperback
• Number of pages: 498
• Editor: Dubey