Advances in soft sensors for Wastewater Treatment Plants: A systematic review (original) (raw)

Software (soft) sensors have been developed by using mathematical modelling to translate easy-to-measure parameters or existing sensors into other important operating parameters. This review surveys the advancements of soft sensor development for water resource recovery facilities (WRRFs) with the intention of establishing a baseline for these soft sensor models. Although a variety of data-driven modelling approaches have been proposed, it is difficult to identify the state-of-the-art. This is because each study uses a unique WRRF dataset, which differ based on statistical attributes (e.g., range, distribution) and qualitative attributes (e.g., supporting on-line sensors, nature of the wastewater). This is a problem as certain methods may only be effective for datasets with specific attributes. Moreover, it makes direct comparison based on common performance measures inadequate and misleading. To address this, the current review summarized (1) the different supporting on-line sensors that have been used in soft sensor development; (2) the methods applied in soft sensor development as well as the specific problem addressed by these methods; and (3) model performance in relation to the source and size of the datasets.