Fault Matters: Sensor data fusion for detection of faults using Dempster–Shafer theory of evidence in IoT-based applications

N Ghosh, R Paul, S Maity, K Maity, S Saha - Expert Systems with …, 2020 - Elsevier
Fault detection in sensor nodes is a pertinent issue that has been an important area of
research for a very long time. But it is not explored much as yet in the context of Internet of …

Markov models for anomaly detection in wireless body area networks for secure health monitoring

O Salem, K Alsubhi, A Mehaoua… - IEEE Journal on …, 2020 - ieeexplore.ieee.org
The use of Wireless Body Area Networks (WBANs) in healthcare for pervasive monitoring
enhances the lives of patients and allows them to fulfill their daily life activities while being …

Stochastic geometric analysis of multiple unmanned aerial vehicle-assisted communications over Internet of Things

S Zhang, J Liu, W Sun - IEEE Internet of Things Journal, 2019 - ieeexplore.ieee.org
Due to the advantages of large area coverage, low capital cost and fast deployment,
unmanned aerial vehicles (UAVs) are believed to play a key role in the emerging Internet of …

Reliability evaluation method based on dynamic fault diagnosis results: A case study of a seabed mud lifting system

C Wang, Y Liu, D Wang, G Wang, D Wang… - Reliability Engineering & …, 2021 - Elsevier
In this paper, a reliability evaluation method based on dynamic fault diagnosis results is
proposed. The feasibility of the method is verified by taking the seabed mud lifting system as …

An active safety control method of collision avoidance for intelligent connected vehicle based on driving risk perception

C Sun, S Zheng, Y Ma, D Chu, J Yang, Y Zhou… - Journal of Intelligent …, 2021 - Springer
As the complex driving scenarios bring about an opportunity for application of deep learning
in safe driving, artificial intelligence based on deep learning has become a heatedly …

FMDBN: A first-order Markov dynamic Bayesian network classifier with continuous attributes

S Wang, S Zhang, T Wu, Y Duan, L Zhou… - Knowledge-Based Systems, 2020 - Elsevier
With the development of data driven decision making and prediction, time-series data are
ubiquitous and the demand for its classification is vast. Although a large body of research …

Deep learning with LPC and wavelet algorithms for driving fault diagnosis

CSA Gong, CHS Su, YE Liu, DY Guu, YH Chen - Sensors, 2022 - mdpi.com
Vehicle fault detection and diagnosis (VFDD) along with predictive maintenance (PdM) are
indispensable for early diagnosis in order to prevent severe accidents due to mechanical …

Unsupervised deep transfer learning for fault diagnosis in fog radio access networks

W Wu, M Peng, W Chen, S Yan - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
The rapid development of the Internet of Things with the requirements of ultrareliability and
ultralow latency has imposed huge challenges on the radio access network operation and …

A Review of Real-Time Fault Diagnosis Methods for Industrial Smart Manufacturing

W Yan, J Wang, S Lu, M Zhou, X Peng - Processes, 2023 - mdpi.com
In the era of Industry 4.0, highly complex production equipment is becoming increasingly
integrated and intelligent, posing new challenges for data-driven process monitoring and …

An improved hash algorithm for monitoring network traffic in the internet of things

T Zhan, S Chen - Cluster Computing, 2023 - Springer
With the prompt development of network technology, Internet of Things (IoT), and the speedy
enhancement of network performance, numerous network behaviors, including traffic …