IOT Energy Meter with Current Voltage and Cost Monitoring System Cost Monitoring System

The proposed IoT-based smart energy monitoring system integrates advanced signal processing techniques with the ESP32 microcontroller and PZEM-004T sensor fusion to achieve a high measurement accuracy of 98.7%.By implementing adaptive sampling, the system effectively reduces power consumption by 37% while maintaining precise readings.A dual-cloud architecture enhances its functionality, utilizing ThingSpeak for MATLAB-based analytics and Firebase for real-time monitoring.Additionally, a machine learning-based load forecasting model provides an accurate prediction of energy usage patterns with 92% accuracy.Extensive testing over six months has demonstrated an impressive system reliability of 99.86%, while the cost is reduced by 60% compared to commercially available alternatives.Designed as an open-source and modular solution, the system is suitable for residential, commercial, and industrial applications, ensuring compliance with IEC 62053-21 energy metering standards.

Authors

Publication Details

Journal
International Journal of Innovations in Engineering and Science
Published
2025-04-08
DOI
https://doi.org/10.46335/ijies.2025.10.2.1
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
0.00
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IOT Energy Meter with Current Voltage and Cost Monitoring System Cost Monitoring System

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IOT Energy Meter with Current Voltage and Cost Monitoring System Cost Monitoring System

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article en

Abstract

The proposed IoT-based smart energy monitoring system integrates advanced signal processing techniques with the ESP32 microcontroller and PZEM-004T sensor fusion to achieve a high measurement accuracy of 98.7%.By implementing adaptive sampling, the system effectively reduces power consumption by 37% while maintaining precise readings.A dual-cloud architecture enhances its functionality, utilizing ThingSpeak for MATLAB-based analytics and Firebase for real-time monitoring.Additionally, a machine learning-based load forecasting model provides an accurate prediction of energy usage patterns with 92% accuracy.Extensive testing over six months has demonstrated an impressive system reliability of 99.86%, while the cost is reduced by 60% compared to commercially available alternatives.Designed as an open-source and modular solution, the system is suitable for residential, commercial, and industrial applications, ensuring compliance with IEC 62053-21 energy metering standards.

International Journal of Innovations in Engineering and ScienceVol. 10(2)
Affordable and clean energy
Openalex Percentile: Top 83%
Smart Grid Energy Management
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