Application of case-based reasoning to predict sludge settling and endogenous denitrification

For the last years, artificial intelligence (AI) approaches have become useful tools in environmental engineering. Here, one relevant application area is the optimization of wastewater treatment plants (WWTP). In this paper we present a tool for real-time control (RTC) and decision support, which has been tailored to sequencing batch reactors (SBR) plants. The tool, which is able to predict the sludge settling curves as well as the endogenous denitrification (ED) during settle and draw, is based on case-based reasoning (CBR), an AI method. The tool bases its decision on past events and situations captured in cases.