Water Quality Monitoring and Management: Basis, Technology and Case Studies

Water Quality Monitoring and Management: Basis, Technology and Case Studies

by Daoliang Li, Shuangyin Liu

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Product Details

ISBN-13: 9780128113301
Publisher: Elsevier Science
Publication date: 10/26/2018
Pages: 710
Product dimensions: 6.00(w) x 9.00(h) x (d)

About the Author

College of Information and Electrical Engineering, China Agricultural University, China.

The author is well-recognized internationally, holding executive positions in the key international associations promoting agricultural engineering. He has long experience in teaching related courses including:

Master level and Ph.D. level courses in intelligent information system of agriculture, Systems Engineering, Agricultural advanced sensing, intelligent information processing, Internet of things of agriculture, System analysis and design, Information technologies and Undergraduate courses in Information technology in Agriculture, agriculture expert systems.

S. Liu received his B.E. degree in the Department of Computer Science, Air Force Engineering University in 2002 and his M.E. degree in Faculty of Computer, Guangdong University of Technology in 2006. He is a Ph.D. student in the College of Information and Electric Engineering of China Agriculture University. He is a lecturer in the College of Information, Guangdong Ocean University, and he is a member of China Computer Federation. He primary research interests are intelligent information system of agriculture, artificial intelligence, software engineering, computational intelligence.

Table of Contents

1. Sensors in Water Quality Monitoring
2. Wireless Sensor Networks in Water Quality Monitoring
3. System and Platform for Water Quality Monitoring
4. Water Quality Evaluation
5. Prediction of Water Quality
6. Water Quality Early Warnings
7. Detection of River Water Quality
8. Water Quality Detection for Lakes
9. Seawater Quality Detection
10. Drinking Water Detection
11. Groundwater Quality Detection
12. Water Quality Monitoring in Aquaculture
13. Detection of Industrial Water Quality

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