In wastewater treatment plants (WWTPs), some variables such as BOD5 and COD that are
related to e uent quality, are di cult to measure directly online due to technical or economic …

Real‐time measurements of key effluent parameters play a highly crucial role in wastewater
treatment. In this research work, we propose a soft sensor model based on deep learning …

Assessment of wastewater effluent quality in terms of physicochemical and microbial
parameters is a difficult task; therefore, an online method which combines the variables and …

Commercial instrumentation for measurement of various wastewater treatment processes
parameters is costly and time-consuming in wastewater treatment plants (WWTPs). Long …

With the development of machine learning and artificial intelligence (ML/AI) models, data-
driven soft sensors, especially the neural network-based, have widespread utilization for the …

Soft sensors have emerged as a powerful tool for predicting quality-related but hard-to-
measured variables in the wastewater treatment plants (WWTPs). However, due to high data …

This paper aims to present a comprehensive survey on water quality soft-sensing of a
wastewater treatment process (WWTP) based on artificial neural networks (ANNs). We …

With the swift industrial development, the pollution of water bodies by industrial effluent is
becoming more widespread and serious. To achieve a more effective and intelligent control …

The nonlinearity and complicated biological phenomena existing in wastewater treatment
processes (WWTP) make the operation and modeling of WWTP quite difficult. In this study, a …

Soft sensors can be an essential part of a digital twin to acquire critical wastewater
information for operation optimization. Soft sensor predictions have been successfully …