Electricity Theft Detection Using Internet of Things

Abstract : Electricity theft in power distribution networks leads to significant revenue losses and grid instability worldwide. This project introduces an IoT-based electricity theft detection system that uses the ESP32 microcontroller for real-time monitoring and prevention. The system installs two smart meters, one at the distribution transformer (feeding point) and another at the consumer end. These meters have ACS712 current sensors, voltage sensors, and ESP32 boards to measure electrical parameters such as voltage, current, power factor, active power, and total energy consumption. The ESP32 processes data locally with Arduino IDE programming. It compares upstream and downstream readings to find discrepancies that exceed normal technical losses, which are typically between 5 and 10 percent. Anomalies like sudden drops in downstream power, reverse current flow, or signs of tampering trigger immediate alerts. The data is sent wirelessly through the ESP32's built-in Wi-Fi module to a cloud platform, like Thing Speak or a Blynk app. This allows remote visualization, historical logging, and automated notifications to utility staff via SMS or email. Key features include low-cost implementation (under $20 per unit), tamper-proof enclosures, low-power operation for continuous monitoring, and scalability for smart grid integration. By reducing non-technical losses, the system improves revenue protection, encourages fair energy use, and supports sustainable power management in both urban and rural networks. Keywords: ESP32, smart energy meter, current sensor ACS712, Blynk app, cloud computing, Internet Of Things