A Novel Hybrid Deep Learning-Based Framework for Intelligent Anomaly Detection in Smart Meters

A Novel Hybrid Deep Learning-Based Framework for Intelligent Anomaly Detection in Smart Meters

Smart meters deployment in residential buildings generates a large volume of time-series data that offers valuable insights about electricity consumption. The proposed work exploits smart meter data to identify abnormal behavior in electricity consumption and sensor malfunctioning. In this paper, a...

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Bibliographic Details
Main Authors: Simarjit Kaur, Priyansh Chowhan, Aashima Sharma
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Anomaly detection
bidirectional LSTM
classification
electricity consumption monitoring
hybrid model
random forest
Online Access:https://ieeexplore.ieee.org/document/11044360/
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https://ieeexplore.ieee.org/document/11044360/

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