Abstract
In order to control filamentous bulking, it is very important and beneficial that plant operators can precisely identify filamentous microorganisms in the activated sludge, and that they utilize the information of the identification as an index of the operational conditions at the plant.
In this study, the computer aided system for the identification of the filamentous microorganisms was tried to develop by applying the knowledge engineering (or artificial intelligence ; AI) techniques. This knowledge-based system is designed to support operators at the plant for easy and precise identification of the filaments in their wastewater treatment plants.
The prototype system described in this paper has shown the reliability of being in agreement with human expert in approximately 67% of the cases investigated. It is expected that the reliability (or intelligent ability) can be improved by refining the knowledge base.
This study has given the instance to evaluate whether the knowledge engineering techniques is useful and promising in the field of wastewater treament.
