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Model-based soft sensors can enhance online monitoring in wastewater treatment processes. These soft sensor scripts are executed either locally on a programmable logic controller (PLC) or remotely on a system with data-access over the internet. This work presents a cost-effective, flexible, open source IoT solution for remote deployment of a soft sensing algorithm. The system uses low-priced hardware and open-source programming language to set up the communication and remote-access system. Advantages of the new IoT architecture are demonstrated through a case study for remote deployment of an Extended Kalman Filter (EKF) to estimate additional water quality parameters in a multistage moving bed biofilm reactor (MBBR) plant. The soft-sensor results are successfully validated against standardised laboratory measurements to prove their ability to provide real-time estimations.

A cost-effective IoT strategy for remote deployment of soft sensors – a case study on implementing a soft sensor in a multistage MBBR plant