IoT-Enabled Secure Energy Management System in Smart Meters with CRFN: A Novel Approach to Billing and Theft Prevention

In response to the challenges posed by missed electricity bill payments and unauthorized power consumption, this study introduces enhancements to existing smart energy meter systems. The proposed improvements include the integration of advanced security features and automation capabilities, such as refined theft control mechanisms and optimized communication protocols between energy providers and consumers. Leveraging IoT technology, the system enables real-time energy monitoring, automatic billing, and timely payment reminders via SMS. Additionally, innovative theft prevention measures, including automated power disconnection for overdue accounts and theft detection systems, bolster security and reduce losses. The integration of the Convolutive Recurrent Fusion Network (CRFN) algorithm significantly enhances the system's theft detection and prevention capabilities. The CRFN detects anomalies in power consumption that may indicate theft, such as sudden spikes or drops in usage, through advanced pattern recognition. Upon detecting potential theft, the system can trigger automated responses like alerts or power disconnection, reducing the need for manual intervention. The incorporation of a magnetic reed switch further enhances efficiency by automatically controlling power access for consumers who have not paid their bills by the due date. By addressing these challenges and integrating advancements, the proposed framework aims to create a more efficient, secure, and sustainable energy management solution, ensuring accurate billing, preventing unauthorized usage, and promoting environmental responsibility.

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Publication Details

Published
2024-12-27
DOI
https://doi.org/10.1109/icscan62807.2024.10894165
Citations
4
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
0.83
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article

IoT-Enabled Secure Energy Management System in Smart Meters with CRFN: A Novel Approach to Billing and Theft Prevention

N. Subalakshmi, M. Jeyakarthic, S. Punitha, R. Suganya et al.
4 citations
Smart Grid Energy Management
0.83
article

IoT-Enabled Secure Energy Management System in Smart Meters with CRFN: A Novel Approach to Billing and Theft Prevention

N. Subalakshmi, M. Jeyakarthic, S. Punitha, R. Suganya, K. Kavitha
article en
4 citations

Abstract

In response to the challenges posed by missed electricity bill payments and unauthorized power consumption, this study introduces enhancements to existing smart energy meter systems. The proposed improvements include the integration of advanced security features and automation capabilities, such as refined theft control mechanisms and optimized communication protocols between energy providers and consumers. Leveraging IoT technology, the system enables real-time energy monitoring, automatic billing, and timely payment reminders via SMS. Additionally, innovative theft prevention measures, including automated power disconnection for overdue accounts and theft detection systems, bolster security and reduce losses. The integration of the Convolutive Recurrent Fusion Network (CRFN) algorithm significantly enhances the system's theft detection and prevention capabilities. The CRFN detects anomalies in power consumption that may indicate theft, such as sudden spikes or drops in usage, through advanced pattern recognition. Upon detecting potential theft, the system can trigger automated responses like alerts or power disconnection, reducing the need for manual intervention. The incorporation of a magnetic reed switch further enhances efficiency by automatically controlling power access for consumers who have not paid their bills by the due date. By addressing these challenges and integrating advancements, the proposed framework aims to create a more efficient, secure, and sustainable energy management solution, ensuring accurate billing, preventing unauthorized usage, and promoting environmental responsibility.

Annamalai University (IN)
Affordable and clean energy
Openalex Percentile: Top 25%
Smart Grid Energy Management
0.83
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IoT-Enabled Secure Energy Management System in Smart Meters with CRFN: A Novel Approach to Billing and Theft Prevention — N. Subalakshmi, M. Jeyakarthic, et al. · (2024) | TGRS Research Map | TGRS