Artificial Intelligence in River Quality Assessment

Importance of biological monitoring in river quality assessment was well understood and various systems were developed in 20th century. But most of them were based on scoring system and later use of Artificial Intelligence (AI) in River Quality Assessment was started. AI has wide scope in river quality assessment problem and few systems were developed to model human ways of reasoning and finding the river water quality from the ecological data. The paper discusses the approaches of AI which can model human way of solving the problem, namely Neural Networks and Expert System. In this paper system based on pattern recognition (SOM, MIR-Max, RPDS) and Bayesian belief network (RPBBN) were described. RPDS and RPBBN were developed at CEIS, Stafford shire University and have shown very good results as compared to previous systems. All the system developed so far are not able to explore the relationship between chemical, environmental and biological data set of ecological data of rivers. The scope for this in AI is also proposed for development of 3D data analysis system.