Spectroscopy and Machine Learning for Water Quality Analysis

The use of various spectroscopic and sensor techniques and the impact of AI techniques to water quality analysis constitute the subject matter of the book. Encompassing the established spectroscopic and sensing technologies, each of the chapters will introduce the technique followed by its application for water quality analysis, and in particular review and present impact of artificial intelligence, machine learning and deep learning to enhance the efficiency of spectroscopic techniques and its use in predictive analysis. Multi-target modelling approach for spectral regression is also planned.
The aim is introduce scientists to the techniques and their applications and at the same time to acquaint the experienced readers with recent advances including artificial intelligence and machine learning and how this is being applied to water quality management. Pedagogic style will be preferred using bottom-up approach which is beneficial in a book aimed at an interdisciplinary readership and who do not have prior experience in a particular technique. Qualitative and quantitative analysis of data using a particular tool with the help of observed data will be included wherever appropriate. Chapters will include case studies which will provide deeper insight. Content will be woven so as to link the assessment/monitoring to the treatment methods.

The proposed volume highlights the applications of modern spectroscopic approaches applying artificial intelligence and machine learning for water quality analysis in different sectors including environmental protection, industry, agriculture and for drinking water.