Chandima Gomes

Work place: Department of Electrical Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, 43400, Selangor, Malaysia



Research Interests: Engineering


Chandima Gomes is a professor of electrical engineering and researcher in high voltage
engineering and lightning protection at Universiti Putra Malaysia. He is also an expert in
power and energy, electromagnetic interference and compatibility and occupational safety
management. He has conducted over 120 training programs in 12 countries so far. Chandima
has published over 300 research papers and several books on his expertise. He obtained a First
Class Degree in Physics from the University of Colombo in 1993. He has done his PhD (1999)
and postdoctoral research on lightning protection and high voltage engineering at Uppsala University, Sweden.

Author Articles
Physical and Soft Sensor Technologies for Wastewater Quality Management

By Nor Hana Mamat Saliza Ramli Nor Arymaswati Abdullah Samia Khan Chandima Gomes

DOI:, Pub. Date: 8 Nov. 2018

Physical sensors are used mostly to detect sludge and odour in wastewater. Black box modelling or data-derived model using the correlation of input-output parameters is the preferred method as we have assessed. This is due to the non-complex approach of such models as opposed to model-driven, mechanistic models. The latter is hard to be adopted for soft-sensor development due to the inherent complexities and uncertainties. The commonest methods for soft sensor model development are ANN and ANFIS. Many other improvements of these methods are achieved by combining with other techniques to enhance the prediction performance of the soft sensors. Accuracy and precision of data collected for soft sensor modelling has become a vital concern at present to ensure the reliability of wastewater quality indices predicted by the soft sensors. Reduction of the level of reliability of the sensor system in monitoring and controlling of WWTPs would lead to serious lapses in the wastewater quality management. In this backdrop we recommend SEVA soft sensor as one of the best potential solutions which could be offered by the existing technologies.

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