Machine learning‐based model for prediction of power consumption in smart grid‐smart way towards smart city

S Tiwari, A Jain, NMOS Ahmed, Charu… - Expert …, 2022 - Wiley Online Library
A smart city is an idea that is realized by the computing of a large amount of data collected
through sensors, cameras, and other electronic methods to provide services, manage …

A novel wind speed-sensing methodology for wind turbines based on digital twin technology

Y Li, X Shen - IEEE Transactions on Instrumentation and …, 2021 - ieeexplore.ieee.org
Wind speed sensors of wind turbines are prone to suffer from performance degeneration or
even drastic failures due to their inherent issues or environmental influence, which directly …

Identification failure data for cluster heads aggregation in WSN based on improving classification of SVM

TK Dao, TT Nguyen, JS Pan, Y Qiao, QA Lai - IEEE Access, 2020 - ieeexplore.ieee.org
Wireless sensor network (WSN) has been paid more attention due to its efficient system of
communication devices for transferring information from a target environment to the base …

A machine-learning-based distributed system for fault diagnosis with scalable detection quality in industrial IoT

R Marino, C Wisultschew, A Otero… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
In this article, a methodology based on machine learning for fault detection in continuous
processes is presented. It aims to monitor fully distributed scenarios, such as the Tennessee …

LSTM-GAN-AE: A promising approach for fault diagnosis in machine health monitoring

H Liu, H Zhao, J Wang, S Yuan… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Recent years have witnessed that real-time health monitoring for machine gains more and
more importance with the goal of achieving fault diagnosis (FD) and predictive maintenance …

[HTML][HTML] Outlier detection strategies for WSNs: A survey

B Chander, G Kumaravelan - Journal of King Saud University-Computer …, 2022 - Elsevier
Abstract Wireless Sensor Networks (WSNs) are developed significantly from the last
decades and attracted the attention of scientific and industrial domains. In WSNs, sensor …

[HTML][HTML] Identifying correctness data scheme for aggregating data in cluster heads of wireless sensor network based on naive Bayes classification

SC Chu, TK Dao, JS Pan, TT Nguyen - EURASIP Journal on Wireless …, 2020 - Springer
Wireless sensor network (WSN) has been paid more attention by scholars due to the
practical communication of a system of devices to transfer information gathered from a …

Deep Recurrent Graph Convolutional Architecture for Sensor Fault Detection, Isolation and Accommodation in Digital Twins

H Darvishi, D Ciuonzo, PS Rossi - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
The rapid adoption of Internet-of-Things (IoT) and digital twins (DTs) technologies within
industrial environments has highlighted diverse critical issues related to safety and security …

Expect the unexpected: unsupervised feature selection for automated sensor anomaly detection

HY Teh, I Kevin, K Wang… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
With the growth of IoT applications, sensor data quality has become increasingly important
to ensure the success of these data-driven applications. Sensor data riddled with errors are …

High-speed train fault detection with unsupervised causality-based feature extraction methods

Y Xu, J Liu - Advanced Engineering Informatics, 2021 - Elsevier
With the development of smart sensors, large amount of operating data collected from a
complex system as a high-speed train providing opportunities in efficient and effective fault …