Product details:
| ISBN13: | 9780443333217 |
| ISBN10: | 0443333211 |
| Binding: | Paperback |
| No. of pages: | 498 pages |
| Size: | 234x190 mm |
| Weight: | 450 g |
| Language: | English |
| 700 |
Category:
Computational Automation for Water Security
Enhancing Water Quality Management
Publisher: Elsevier
Date of Publication: 1 March 2025
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Long description:
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Water Quality Management is a comprehensive and insightful guide which explores the challenges posed by inefficient and outdated practices, presenting innovative solutions to enhance decision-making, optimizing water treatment processes, and ultimately improving environmental outcomes.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.
Table of Contents:
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