Real-Time Electrical Energy Measurement and Cloud Monitoring Using an ESP32-Based IoT Framework

Abstract

Real-time visibility of electrical consumption is important for improving energy awareness, identifying abnormal usage, and supporting effective demand-side management. This study presents an ESP32-based Internet of Things framework for electrical energy measurement and cloud-connected monitoring in low-voltage environments. The proposed system integrates voltage and current sensing with local embedded processing to calculate instantaneous power, accumulated energy consumption, and estimated electricity cost. An ESP32-class microcontroller performs signal acquisition, calibration, validation, and local computation before transmitting measured parameters through Wi-Fi using MQTT- or HTTP-compatible communication. The monitored data are stored in a cloud-based platform and presented through a web or mobile visualization interface for continuous observation and historical analysis. The methodology includes sensor calibration, sampling, measurement-error assessment, communication-reliability testing, energy-data logging, and threshold-based alert generation. System performance is evaluated against a reference energy meter to determine measurement accuracy and consistency, while network testing is used to assess data-delivery reliability and alert-response behavior. The framework is designed for residential laboratories, classrooms, small commercial facilities, and similar low-voltage applications where low-cost and continuous energy monitoring are required. The proposed approach provides a reproducible basis for future integration of load classification, demand-response functions, renewable-energy monitoring, and predictive energy analytics.