This is a project which is currently making use of HPC facilities at Newcastle University. It is active.
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The PRO-BES project (Pioneering Real-time Observations with BioElectrochemical Systems) has developed a bioelectrochemical sensor for real-time measurement of the level of organic pollutants in wastewater treatment systems. The project generates high frequency data on electrical signal from the sensor, temperature, pH and conductivity which is processed using python scripts for interactive display of the data. Machine Learning approaches have been used to improve the accuracy of the outputs from the sensor taking into account temperature, pH and conductivity and offline measurements of organic pollutants using standard methods
bash, python, Conda used to process data from a sensor system using python scripts to generate interactive display of the data. Training of a Machine Learning algorithm using outputs from the sensor, pH conductivity and offline measurements of organic pollutant levels using standard methods to improve the accuracy of calibration of the sensor.