UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 12 | Issue 10 | October 2025

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Published in:

Volume 12 Issue 3
March-2025
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2503486


Registration ID:
556973

Page Number

e637-e642

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Title

TriVolt Tracker:The Montoring andFluctuation Detection

Abstract

Ensuring power stability in three-phase electrical systems is essential to prevent equipment failures and operational inefficiencies. This project, "TriVolt Tracker:The Montoring and Fluctuation Detection," introduces a smart, automated monitoring solution that leverages the Internet of Things (IoT) to track voltage levels in real time. Traditional monitoring methods often rely on manual inspections or delayed alerts, increasing the risk of damage due to unstable voltage conditions. This system provides continuous monitoring, immediate notifications, and remote accessibility, improving efficiency and safety. The system employs voltage sensors to measure the voltage levels of each phase, feeding the data to a microcontroller for processing. When fluctuations beyond the safe range occur, LED indicators alert users locally, and data is transmitted to an IoT cloud platform. Users can access real-time and historical voltage data via a mobile application or web dashboard, allowing them to respond proactively to potential issues. The integration of IoT enhances monitoring accuracy and reduces the need for manual supervision. Key hardware components include voltage sensors (ZMPT101B), a microcontroller (ESP32/Arduino), a Wi-Fi module (ESP8266/ESP32), and a relay module for protective actions. The system software comprises Arduino IDE for programming, cloud-based storage solutions such as ThingSpeak or Firebase, and user-friendly mobile or web interfaces. Testing has shown that the system accurately detects voltage variations, providing timely alerts and enabling better power management. This project offers an efficient, cost-effective solution for real-time power monitoring. Future enhancements could incorporate AI-based predictive maintenance and advanced anomaly detection, further improving power reliability and efficiency. By utilizing IoT technology, this system supports the development of smarter electrical infrastructures, ensuring stability, sustainability, and safety in power distribution networks.

Key Words

three phase power monitoring,IOT,voltage fluctuation,realtime alerts,predictive maintanence,load balancing,fault detection

Cite This Article

"TriVolt Tracker:The Montoring andFluctuation Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.e637-e642, March-2025, Available :http://www.jetir.org/papers/JETIR2503486.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"TriVolt Tracker:The Montoring andFluctuation Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppe637-e642, March-2025, Available at : http://www.jetir.org/papers/JETIR2503486.pdf

Publication Details

Published Paper ID: JETIR2503486
Registration ID: 556973
Published In: Volume 12 | Issue 3 | Year March-2025
DOI (Digital Object Identifier):
Page No: e637-e642
Country: Tirupur, Tamil Nadu, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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