Modeling and prediction of surface water contamination using on-line sensor data
Abstract
Water contamination is a great disadvantage to humans and aquatic life. Maintaining the aesthetics and quality of water bodies is a priority for environmental stake holders. The water quality sensor data can be analyzed over a period of time to give an indication of pollution incidents and could be a useful forecasting tool. Here we show our initial finding from statistical analysis on such sensor data from one of the lakes of the river Lea, south of Luton. Our initial work shows patterns which will form the basis for our forecasting model.Citation
Anyachebelu TK, Conrad M, Ajmal T (2014) 'Modeling and prediction of surface water contamination using on-line sensor data', International Journal on Smart Sensing and Intelligent Systems, 7 (5), pp.1-5.Publisher
Exeley Inc.Additional Links
https://www.exeley.com/in_jour_smart_sensing_and_intelligent_systems/doi/10.21307/ijssis-2019-117Type
ArticleLanguage
enISSN
1178-5608EISSN
1178-5608ae974a485f413a2113503eed53cd6c53
10.21307/IJSSIS-2019-117
Scopus Count
Collections
The following license files are associated with this item:
- Creative Commons
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International