A multi-faceted approach to electricity theft detection: Using community engagement, audit analytics, and machine learning algorithms

The objective of this project is to develop an intelligent system that can accurately detect electricity theft by analyzing consumption patterns and other relevant customer data. It combines traditional anomaly detection techniques with advanced machine learning algorithms to identify unusual behavior. The system aims to enhance efficiency in monitoring electricity usage, reduce losses due to theft, and provide utility companies with a reliable tool for proactive detection and decision-making.