Design and Implementation of an IoTBased ThreePhase Voltage and Current Monitoring System Using PZEM004T Sensors and ESP8266 with Cloud Integration

The increasing demand for reliable and efficient power management in industrial and commercial environments necessitates advanced monitoring solutions. Traditional methods of voltage and current monitoring, which rely on analog meters and manual data collection, suffer from limitations including high costs, lack of real-time capabilities, and limited scalability. This paper presents the design and implementation of a smart, IoT-based three-phase voltage and current monitoring system that addresses these challenges through the integration of modern sensor technology, microcontroller-based data processing, and cloud computing platforms. The proposed system utilizes three PZEM-004T sensors—one dedicated to each phase—to measure critical electrical parameters including voltage, current, power, and energy consumption. An Arduino Mega microcontroller serves as the central processing unit, acquiring data from all three sensors simultaneously via serial communication. The processed data is transmitted wirelessly using an ESP8266 Wi-Fi module to the ThingSpeak cloud platform, enabling real-time visualization, historical data analysis, and remote monitoring through a web-based interface. The prototype was tested under various load conditions to evaluate measurement accuracy, system responsiveness, and data transmission reliability. Results demonstrate voltage and current measurement accuracy within ±1%, successful real-time data logging with 15-second update intervals, and reliable cloud integration with minimal data loss. The total system cost remains significantly lower than commercial alternatives while offering comparable functionality, making it suitable for industrial plants, commercial buildings, educational institutions, and renewable energy applications. This work contributes a cost-effective, scalable, and accessible solution for three-phase electrical monitoring, with potential extensions to predictive maintenance, power quality analysis, and integration with building management systems.