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Experimental Validation of a Low-Cost IoT-Based Voltage and Current Measurement System Using RMS Benchmarking with a Reference Power Quality Analyzer

Jul 2026 · Electricity · Vol 7, pp. 77 · 1 citation · 21 references

TL;DR

Experimental results demonstrate that the proposed low-cost embedded architecture can provide RMS voltage and RMS current measurements with acceptable accuracy for educational applications, experimental electrical platforms, and distributed IoT-based monitoring systems.

Abstract

This paper presents a low-cost embedded monitoring system for real-time RMS voltage and RMS current acquisition in three-phase electrical networks. The proposed architecture is based on distributed Arduino Nano acquisition nodes equipped with ACS712 Hall-effect current sensors and isolated voltage transformers, while a Raspberry Pi 4 Model B is used as a centralized data acquisition and processing unit through the I2C communication protocol. The embedded acquisition nodes implement timer-controlled analog signal sampling using the internal 10-bit ADC of the ATmega328P microcontroller, allowing real-time acquisition of electrical waveforms for RMS computation. Unlike conventional low-cost IoT electrical monitoring systems focused mainly on basic parameter visualization and wireless communication, the proposed platform emphasizes synchronized three-phase RMS monitoring and experimental validation accuracy under real operating conditions. The proposed monitoring architecture is experimentally benchmarked against a FLUKE 435 professional power quality analyser used as a high-accuracy reference instrument. Experimental results demonstrate that the proposed low-cost embedded architecture can provide RMS voltage and RMS current measurements with acceptable accuracy for educational applications, experimental electrical platforms, and distributed IoT-based monitoring systems. The presented system does not aim to implement a fully IEC 61000-4-30-compliant power quality analyser but rather to validate the feasibility of low-cost embedded RMS monitoring architectures for real-time electrical applications.

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