[HTML][HTML] Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives
Enormous amounts of data are being produced everyday by sub-meters and smart sensors
installed in residential buildings. If leveraged properly, that data could assist end-users …
installed in residential buildings. If leveraged properly, that data could assist end-users …
An innovative deep anomaly detection of building energy consumption using energy time-series images
Deep anomaly detection (DAD) is essential in optimizing building energy management.
Nonetheless, most existing works concerning this field consider unsupervised learning and …
Nonetheless, most existing works concerning this field consider unsupervised learning and …
A deep and scalable unsupervised machine learning system for cyber-attack detection in large-scale smart grids
Smart grid technology increases reliability, security, and efficiency of the electrical grids.
However, its strong dependencies on digital communication technology bring up new …
However, its strong dependencies on digital communication technology bring up new …
An adaptive spatiotemporal feature learning approach for fault diagnosis in complex systems
The machine fault diagnosis is being considered in a larger-scale complex system with
numerous measurements from diverse subsystems or components, where the collected data …
numerous measurements from diverse subsystems or components, where the collected data …
Unsupervised anomaly detection using graph neural networks integrated with physical-statistical feature fusion and local-global learning
C Feng, C Liu, D Jiang - Renewable Energy, 2023 - Elsevier
Efficient and feasible anomaly detection scheme that could utilize data collected by
supervisory-control-and-data-acquisition (SCADA) system is essential for wind turbines …
supervisory-control-and-data-acquisition (SCADA) system is essential for wind turbines …
An unsupervised spatiotemporal graphical modeling approach for wind turbine condition monitoring
W Yang, C Liu, D Jiang - Renewable energy, 2018 - Elsevier
The vast installment of wind turbines and the development of condition monitoring system
provides large amounts of operational data for condition monitoring and health …
provides large amounts of operational data for condition monitoring and health …
Intelligent anomaly detection for large-scale smart grids
H Karimipour, S Geris… - 2019 IEEE Canadian …, 2019 - ieeexplore.ieee.org
This paper proposes an unsupervised anomaly detection scheme based on statistical
correlation between measurements. The goal is to design a scalable anomaly detection …
correlation between measurements. The goal is to design a scalable anomaly detection …
[HTML][HTML] Trade-off of security and performance of lightweight block ciphers in Industrial Wireless Sensor Networks
C Pei, Y Xiao, W Liang, X Han - EURASIP Journal on Wireless …, 2018 - Springer
Lightweight block ciphers play an indispensable role for the security in the context of
pervasive computing. However, the performance of resource-constrained devices can be …
pervasive computing. However, the performance of resource-constrained devices can be …
Multivariate exploration of non-intrusive load monitoring via spatiotemporal pattern network
Non-intrusive load monitoring (NILM) of electrical demand for the purpose of identifying load
components has thus far mostly been studied using univariate data, eg, using only whole …
components has thus far mostly been studied using univariate data, eg, using only whole …
ABSI: An adaptive binary splitting algorithm for malicious meter inspection in smart grid
Electricity theft is a widespread problem that causes tremendous economic losses for all
utility companies around the globe. As many countries struggle to update their antique …
utility companies around the globe. As many countries struggle to update their antique …