The development and commercial use of virtualized sensing (smooth) in the manufacturing
of Polyethylene Terephthalate (PET) and sewage treatment are both covered in this paper …

Recent studies into the estimation and control of an activated sludge process (ASP) at a
wastewater treatment plant suggest that artificial-intelligence methods, such as neural …

The on-line monitoring of wastewater treatment plant (WWTP) operations is a challenge due
to interference and breakdown from the harsh conditions endured by sensors in wastewater …

Proper monitoring of quality-related but hard-to-measure effluent variables in wastewater
plants is imperative. Soft sensors, such as dynamic neural network, are widely used to …

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

In this paper two Soft Sensors, for the estimation of pollutants in the output flow of a Sour
Water Stripping plant, are described. The plant operates in a large refinery in Italy. The Soft …

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 …

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 …

This paper presents the development and the industrial implementation of a virtual sensor
(soft-sensor) in the polyethylene terephthalate (PET) production process. This soft-sensor …