A deep learning-based intrusion detection system for mqtt enabled iot
A large number of smart devices in Internet of Things (IoT) environments communicate via
different messaging protocols. Message Queuing Telemetry Transport (MQTT) is a widely …
different messaging protocols. Message Queuing Telemetry Transport (MQTT) is a widely …
[HTML][HTML] Machine learning empowered COVID-19 patient monitoring using non-contact sensing: An extensive review
The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), which caused the
COVID-19 pandemic, has affected more than 250 million people worldwide. With the recent …
COVID-19 pandemic, has affected more than 250 million people worldwide. With the recent …
[PDF][PDF] A self monitoring and analyzing system for solar power station using IoT and data mining algorithms
S Shakya - Journal of Soft Computing Paradigm, 2021 - irojournals.com
Renewable energy sources are gaining a significant research attention due to their
economical and sustainable characteristics. In particular, solar power stations are …
economical and sustainable characteristics. In particular, solar power stations are …
Multi-sensor gearbox fault diagnosis by using feature-fusion covariance matrix and multi-Riemannian kernel ridge regression
Intelligent fault diagnosis of gearbox holds important implications for the safety assessment
and risk analysis of rotating machinery. Due to many monitoring variables in engineering …
and risk analysis of rotating machinery. Due to many monitoring variables in engineering …
A fuzzy preference-based Dempster-Shafer evidence theory for decision fusion
Dempster-Shafer evidence theory (DS) is an effective instrument for merging the collected
pieces of basic probability assignment (BPA), and it exhibits superiority in achieving …
pieces of basic probability assignment (BPA), and it exhibits superiority in achieving …
A distributed principal component regression method for quality-related fault detection and diagnosis
Modern industrial processes are confronted with a large-scale challenge in recent years. In
this paper, a novel distributed kernel principal component regression (DKPCR) approach is …
this paper, a novel distributed kernel principal component regression (DKPCR) approach is …
A new method for fault detection of aero-engine based on isolation forest
H Wang, W Jiang, X Deng, J Geng - Measurement, 2021 - Elsevier
The research on fault detection of aero-engine is of great significance to its safe and reliable
operation. In this paper, a dynamic threshold method for aero-engine fault detection based …
operation. In this paper, a dynamic threshold method for aero-engine fault detection based …
[HTML][HTML] CAFD: context-aware fault diagnostic scheme towards sensor faults utilizing machine learning
Sensors' existence as a key component of Cyber-Physical Systems makes it susceptible to
failures due to complex environments, low-quality production, and aging. When defective …
failures due to complex environments, low-quality production, and aging. When defective …
[HTML][HTML] Current Status and Prospects of Research on Sensor Fault Diagnosis of Agricultural Internet of Things
X Zou, W Liu, Z Huo, S Wang, Z Chen, C Xin, Y Bai… - Sensors, 2023 - mdpi.com
Sensors have been used in various agricultural production scenarios due to significant
advances in the Agricultural Internet of Things (Ag-IoT), leading to smart agriculture …
advances in the Agricultural Internet of Things (Ag-IoT), leading to smart agriculture …
Uncertainty utilization in fault detection using Bayesian deep learning
Up to now, extensive literature on the usage of deep learning in manufacturing can be
found. Though, actual usage of deep learning in manufacturing sites is somehow restrained …
found. Though, actual usage of deep learning in manufacturing sites is somehow restrained …