Following the International Water Association Good Activated Sludge Modeling Practice Unified Protocol, 39 the long-term continuous online monitoring data collected were assessed for their quality and reconciled to detect, identify, and isolate faults in the dataset. As a method to remove outliers in the sensor signals, a kernel smoother, a statistical technique to smooth out the shortterm fluctuations in signals as the weighted average of neighboring data, was adopted. To this end, the kernel smoothing method of a Python package for functional data analysis (scikit-fda)