Small-scale distributed water treatment equipment such as sequencing batch reactor (SBR)
is widely used in the field of rural domestic sewage treatment because of its advantages of …

Soft-sensor is the most common strategy to predict hard-to-measure variables in the
wastewater treatment processes. However, existence of a large number of hard-to-measure …

Anaerobic process is regarded as a green and sustainable process due to low carbon
emission and minimal energy consumption in wastewater treatment plants (WWTPs) …

Because wastewater treatment processes are generally characterized by variables coupled,
significant nonlinearities, parameters shift and time delay, traditional hardware sensors are …

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 …

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-sensor applications for wastewater management can provide valuable information for
intelligent monitoring and process control above and beyond what is available from …

In wastewater treatment plants, the most adopted sensors are those with the properties of
low cost and fast response. Soft sensors are alternative solutions to the hardware sensor for …

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 …

In wastewater treatment processes, lack of hardware sensors together with unacceptable
dynamics, strong nonlinearity and large time delay often leads to a large number of key …