Computational Automation for Water Security
Enhancing Water Quality Management
- 1st Edition - May 22, 2025
- Imprint: Elsevier
- Editors: Ashutosh Kumar Dubey, Arun Lal Srivastav, Abhishek Kumar, Fausto Pedro Garcia Marquez, Dimitrios A Giannakoudakis
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 3 3 2 1 - 7
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 3 3 2 2 - 4
Computational Automation for Water Security: Enhancing Water Quality Management is a comprehensive and insightful guide which explores the challenges posed by inefficient and ou… Read more
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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Water Quality Management is a comprehensive and insightful guide which explores the challenges posed by inefficient and outdated practices, presenting innovative solutions to enhance decision-making, optimizing water treatment processes, and ultimately improving environmental outcomes.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
Water quality engineers and postgraduate students focusing on water quality management
About the Editors
Preface
1. Introduction to Computational Automation in Water Quality Management
2. Real Time Water Quality Monitoring Systems
3. Automated Water Data Sampling: Enhancing Efficiency and Accuracy in Hydrological Analysis
4. Role of Data Processing and Analysis in water quality management
5. Machine Learning and Artificial Intelligence Applications in Automating Water Quality Monitoring, Analysis and Management
6. Significance of Automation in Water Treatment Processes
7. Real-time Control Systems for Water Supply chain and management
8. Integration of Automation and Internet of Things (IoT) for water security
9. Cybersecurity and Data Privacy in Automated Systems used in water quality management.
10. Cost-Benefit Analysis of Automation in Water Quality Management
11. Automation in Water Distribution Networks
12. Remote Sensing and Satellite Imagery for Water Quality Assessment
13. Case Studies: Successful Implementation of Automation for Water Quality Assessment
14. Future Trends and Emerging Technologies in water quality management
15. Challenges and Ethical Considerations in water Automation
Preface
1. Introduction to Computational Automation in Water Quality Management
2. Real Time Water Quality Monitoring Systems
3. Automated Water Data Sampling: Enhancing Efficiency and Accuracy in Hydrological Analysis
4. Role of Data Processing and Analysis in water quality management
5. Machine Learning and Artificial Intelligence Applications in Automating Water Quality Monitoring, Analysis and Management
6. Significance of Automation in Water Treatment Processes
7. Real-time Control Systems for Water Supply chain and management
8. Integration of Automation and Internet of Things (IoT) for water security
9. Cybersecurity and Data Privacy in Automated Systems used in water quality management.
10. Cost-Benefit Analysis of Automation in Water Quality Management
11. Automation in Water Distribution Networks
12. Remote Sensing and Satellite Imagery for Water Quality Assessment
13. Case Studies: Successful Implementation of Automation for Water Quality Assessment
14. Future Trends and Emerging Technologies in water quality management
15. Challenges and Ethical Considerations in water Automation
- Edition: 1
- Published: May 22, 2025
- Imprint: Elsevier
- Language: English
AD
Ashutosh Kumar Dubey
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.
Affiliations and expertise
Department of Computer Science and Engineering, Institute of Engineering and Technology, Chitkara University, IndiaAS
Arun Lal Srivastav
Dr. Arun Lal Srivastav is an Associate Professor in the Department of Applied Sciences at Chitkara University, Himachal Pradesh, India.
Affiliations and expertise
Chitkara University, Himachal Pradesh, Solan, IndiaAK
Abhishek Kumar
Dr. Abhishek Kumar is Assistant Director and Associate Professor in the Department of Computer Science and Engineering at Chandigarh University, Punjab, India. He completed his PhD in computer science at the University of Madras (India), and previously worked as a post-doctorate fellow in computer science at Ingenium Research Group, based at the Universidad de Castilla-La Mancha in Spain. He has been teaching in academia for more than 13 years, and has over 160 publications in peer reviewed national and international journals, books, and conferences. His research area includes artificial intelligence, renewable energy applications, image processing, computer vision, data mining, and machine learning.
Affiliations and expertise
Department of Computer Science and Engineering, Chandigarh University, Punjab, IndiaFG
Fausto Pedro Garcia Marquez
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.
Affiliations and expertise
Professor, Universidad De Castilla-La Mancha, SpainDA
Dimitrios A Giannakoudakis
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
Affiliations and expertise
Assistant Professor, Institute of Physical Chemistry of Polish Academy of Sciences, GreeceRead Computational Automation for Water Security on ScienceDirect