Outlier detection is a method used to identify outliers in data, such as power consumption in non-residential buildings, online leakage detection in water distribution systems, and efficient water quality prediction systems. It is also used in healthcare fraud, coastal water temperature data, and monitoring water quality data. The method has been applied in various case studies, such as a survey, healthcare fraud, and fault detection for circulating water pumps. It is also used in acoustic feature-based leakage event detection for large-scale water distribution networks.