What is it about?
Real-time estimation of nutrient composition is vital for the optimal operation of the wastewater treatment process. However, this high price of online sensors is a major huddle in the pathway. A model-based soft sensor using cost-effective and reliable physical sensors were explored.
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Why is it important?
In this digitalization era where online and remote monitoring or wastewater quality parameter is gaining momentum, this paper explores how to use cheap sensors to obtain advanced information on the state of the wastewater treatment plant.
Perspectives
The method explained in this work enables us to check that the cheap sensors not only provide accurate information but also validate that they are indeed linked to the treatment process. In a world where AI and machine learning are explored intensively this work reinstates that still value in obtaining online information and linking it to a good understanding of the physical state of the system.
Mr Abhilash Muralidharan Nair
Norwegian University of Life Sciences
Read the Original
This page is a summary of: Implementing an Extended Kalman Filter for estimating nutrient composition in a sequential batch MBBR pilot plant, Water Science & Technology Water Supply, July 2019, IWA Publishing,
DOI: 10.2166/wst.2019.272.
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