IoT-Enabled Electrical load monitoring using Simulink Modelling
TL;DR
The main contribution of this work is the development of a complete simulation-to-cloud monitoring chain that enables voltage and current signals generated from a three-phase load model to be acquired, formatted, transmitted, displayed, and remotely visualized.
Abstract
This paper presents an IoT-enabled monitoring framework for three-phase electrical loads by integrating MATLAB/Simulink modeling, ESP32-based embedded communication, local LCD visualization, and ThingSpeak cloud monitoring. The main contribution of this work is the development of a complete simulation-to-cloud monitoring chain that enables voltage and current signals generated from a three-phase load model to be acquired, formatted, transmitted, displayed, and remotely visualized. Unlike conventional IoT monitoring systems that mainly rely on direct sensor-to-cloud acquisition, the proposed approach uses MATLAB/Simulink as a controlled modeling environment for signal generation and processing before transferring the monitored quantities to an ESP32 gateway through serial communication. The Simulink processing chain includes signal measurement, string conversion, data concatenation, ASCII conversion, Zero-Order Hold sampling, Uint8 casting, and serial transmission. The ESP32 receives the formatted data, displays the monitored quantities locally on an LCD, and forwards them to the ThingSpeak cloud platform through Wi-Fi communication. The implementation demonstrates the feasibility of combining simulation-based electrical load modeling, embedded communication, and cloud visualization in a unified low-cost architecture for real-time supervision of three-phase loads. The proposed framework provides a practical basis for future extensions toward anomaly detection, fault-condition monitoring, communication reliability enhancement, and predictive maintenance in electrical power systems.