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BtM, a Low-cost Open-source Datalogger to Estimate the Water Content of Nonvascular Cryptogams
Published on: March 25, 2019
A cost-effective IoT strategy for remote deployment of soft sensors - a case study on implementing a soft sensor in a
A M Nair1, A Hykkerud1, H Ratnaweera1
1Faculty of Science and Technology, Norwegian University of Life Sciences, 1432 Ås, Norway
Abstract:
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.

