Spectroscopy and Machine Learning for Water Quality Analysis

Developments in artificial intelligence have provided an ever-increasingly powerful tool for better predictions across many fields. Increasing environmental pressures and population growth is having a major impact on the management and provision of safe drinking water, a constant concern of mankind throughout history. Academic, governmental, charitable, and commercial interest and initiatives are already exploring and utilizing artificial intelligence, machine learning, and deep learning as well as the IoT in the monitoring, management, and prediction of water quality. The continued application of such techniques with established spectroscopic and sensing tools has the potential for a major impact in the areas of water quality analysis and management.

Though the use of various spectroscopic methods and sensor technology is routine in water quality evaluation, coupling with artificial intelligence is opening a new era of quality monitoring and predictive analysis. This book acquaints experienced readers with recent advances and how these techniques are finding applications in water analysis for sectors including environmental protection, industry, agriculture, and drinking water provision. Taking a bottom-up approach the work is also suited for an interdisciplinary readership who may not have direct experience in a particular technique. Qualitative and quantitative analysis of data with the help of observed data is included, as are case studies