1. Title, Journal and Authors
Title Decision support systems (DSS) for wastewater treatment plants – A review of the state of the art
Journal : ELSEVIER
Authors : Giorgio Manninaa*, Taise Ferreira Reboucasa, Alida Cosenzaa, Miquel Sanchez-Marreb,d, Karina Givertc,d
a Engineering Department, Palermo University, Viale delle Scienze Ed. 8, 90128 Palermo, Italy
b Dept. of Computer Science, Campus Nord, Building OMEGA, UPC, Barcelona, Catalonia, Spain
c Dept. of Statistics and Operations Research, Campus Nord, Building C5, UPC, Barcelona, Catalonia, Spain
d Knowledge Engineering and Machine Learning Group at Intelligent Data Science and Artificial Intelligence Research Centre (KEMLG-at-IDEAI-UPC), Universitat
Politècnica de Catalunya BarcelonaTech, C. Jordi Girona 1-3, 08034 Barcelona, Catalonia, Spain
This paper is a review paper describing the latest research and case studies on the application of decision support system(DSS) in sewage treatment plants. DSS is classified into four types and described as follows: Life cycle assessment(LCA), mathematical models(MM), multi-criteria decision making(MCDM), intelligent decision support systems(IDSS). The key focuses of applying a DSS in wastewater treatment plant(WWTP) field are: design new plants, reduce energy consumption, improve effluent quality, making WWPTs sustainable, improve plants operation and, their combination. The papers effectively suggest different papers related to the direction in which the types should develop. The combination of AI technology with DSS creates a new type of IDSS. Various methods are used to predict the final parameters in a relatively accurate manner, including the use of an ensemble of fuzzy logic models.
3. Originality & Creativity
The researchers explained the benefits of adopting IDSS in terms of process. The direction of how to develop DSS in sewage treatment plant using artificial intelligence and big data was well presented.
4. Application to research
In addition to good water emissions, increasing energy efficiency in plant systems is also important. There are various papers on the use of AI-based decision systems to reduce energy consumption in sewage treatment plants. It is possible to develop a more accurate model considering various aspects rather than using only some of the four methods presented above.