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

ISSN: 2349-5162 | ESTD Year : 2014
Volume 12 | Issue 11 | November 2025

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Published in:

Volume 11 Issue 1
January-2024
eISSN: 2349-5162

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Published Paper ID:
JETIR2401177


Registration ID:
531115

Page Number

b667-b671

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Title

APPLICATION OF INTERNET OF THINGS(IOT) AND MACHINE LEARNING (ML) WITH REFERENCE TO ELECTRICITY THEFT DETECTION

Abstract

Electricity theft is a pressing issue that impacts both utility providers and consumers, leading to revenue losses and safety hazards. This project focuses on the development and implementation of an innovative solution for electricity theft detection through the application of the Internet of Things (IoT). By integrating IoT sensors, data analytics, and machine learning algorithms, we aim to create a robust and efficient system capable of identifying and mitigating electricity theft in real-time. The proposed system leverages IoT devices to monitor electricity consumption patterns, detect anomalies, and relay data to a centralized platform. Advanced data analytics techniques are employed to analyze the incoming data streams, identifying irregularities that may indicate theft or tampering. Machine learning algorithms are then applied to improve detection accuracy over time by learning from historical data. Key components of the project include the deployment of IoT sensors at strategic points within the electrical grid, the development of a secure and scalable data processing infrastructure, and the creation of a user friendly interface for utility providers to monitor and respond to potential theft incidents promptly. By harnessing the power of IoT technology, this project not only aims to reduce revenue losses for utility providers but also contributes to the overall safety and reliability of the electrical grid. Additionally, it aligns with the broader goals of energy conservation and sustainability by discouraging unauthorized electricity consumption. This abstract provides a brief overview of our project's objectives and methodology in addressing the critical issue of electricity theft. Through the integration of IoT, data analytics, and machine learning, we aspire to create a proactive and effective solution that can significantly mitigate the challenges posed by electricity theft.

Key Words

Electricity Theft ,IOT(Internet of Things),Theft Prevention, Machine Learning ,Energy Conservation

Cite This Article

"APPLICATION OF INTERNET OF THINGS(IOT) AND MACHINE LEARNING (ML) WITH REFERENCE TO ELECTRICITY THEFT DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 1, page no.b667-b671, January-2024, Available :http://www.jetir.org/papers/JETIR2401177.pdf

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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

"APPLICATION OF INTERNET OF THINGS(IOT) AND MACHINE LEARNING (ML) WITH REFERENCE TO ELECTRICITY THEFT DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 1, page no. ppb667-b671, January-2024, Available at : http://www.jetir.org/papers/JETIR2401177.pdf

Publication Details

Published Paper ID: JETIR2401177
Registration ID: 531115
Published In: Volume 11 | Issue 1 | Year January-2024
DOI (Digital Object Identifier):
Page No: b667-b671
Country: Jaysingpur, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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