Iot-Enabled Current–Differential Analytics for Electricity Meter Bypass Detection in Low-Voltage Distribution Systems

Abstract

Electricity theft remains a critical challenge for power utilities, particularly in developing economies where non-technical losses significantly disrupt revenue recovery and system reliability. Meter bypassing, where consumers divert current away from the energy meter, is the most pervasive form of electricity theft in Ghana. This study develops and evaluates a conceptual Internet of Things (IoT)-based monitoring system designed to detect meter bypass using a dual current-sensing architecture. The system employs two ACS712 Hall-effect current sensors, an ATmega328p-PU microcontroller, a SIM800A GSM module for SMS alerts, and an ESP8266 WiFi module for cloud-based reporting to the ThingSpeak® platform. Detection relies on a real-time current-difference algorithm that compares load and meter currents within a mathematical tolerance threshold. Simulation using Proteus 8.3 and prototype implementation confirm that the system accurately detects bypass conditions and enables remote disconnection of supply. This research demonstrates a scalable approach for reducing non-technical losses in low-voltage networks.