[HTML][HTML] Hybrid continuous density hmm-based ensemble neural networks for sensor fault detection and classification in wireless sensor network
M Emperuman, S Chandrasekaran - Sensors, 2020 - mdpi.com
Sensor devices in wireless sensor networks are vulnerable to faults during their operation in
unmonitored and hazardous environments. Though various methods have been proposed …
unmonitored and hazardous environments. Though various methods have been proposed …
A data fusion based data aggregation and sensing technique for fault detection in wireless sensor networks
Abstract Wireless Sensor Networks (WSNs) are networks formed using a large number of
low-cost sensor nodes that have limited energy sources, limited processing capability, low …
low-cost sensor nodes that have limited energy sources, limited processing capability, low …
Energy-efficient and QoS-aware data routing in node fault prediction based IoT networks
N Sharma, U Agarwal, S Shaurya… - … on Network and …, 2023 - ieeexplore.ieee.org
Internet of Things (IoT) enables important data collection of the sensor nodes at desired
location through device-to-device communication. It helps us in various applications …
location through device-to-device communication. It helps us in various applications …
Real-time sensor fault detection, isolation and accommodation for industrial digital twins
The development of Digital Twins (DTs) has bloomed significantly in last years and related
use cases are now pervading several application domains. DTs are built upon Internet of …
use cases are now pervading several application domains. DTs are built upon Internet of …
Player target tracking and detection in football game video using edge computing and deep learning
G Jin - The Journal of Supercomputing, 2022 - Springer
The purpose is to explore the player detection and motion tracking in football game video
based on edge computing and deep learning (DL), thus improving the detection effect of …
based on edge computing and deep learning (DL), thus improving the detection effect of …
Outlier detection in sensor data using machine learning techniques for IoT framework and wireless sensor networks: A brief study
Outlier or anomaly detection in the sensed data for Internet of Things framework and
Wireless Sensor Networks is a growing trend among researchers. Wireless Sensor …
Wireless Sensor Networks is a growing trend among researchers. Wireless Sensor …
Mask-MRNet: A deep neural network for wind turbine blade fault detection
C Zhang, C Wen, J Liu - Journal of Renewable and Sustainable …, 2020 - pubs.aip.org
In this paper, a deep neural network named Mask-MRNet is proposed to detect wind turbine
(WT) blade fault based on images taken by unmanned aerial vehicles. Two datasets of the …
(WT) blade fault based on images taken by unmanned aerial vehicles. Two datasets of the …
A method for fault detection in wireless sensor network based on pearson's correlation coefficient and support vector machine classification
Sensor nodes are tiny low-cost devices prone to various faults. So, it is imperative to detect
those faults. This paper presents a sensor measurement fault detection algorithm based on …
those faults. This paper presents a sensor measurement fault detection algorithm based on …
Enhancement of security and energy efficiency in WSNs: Machine Learning to the rescue
D Puri, B Bhushan - 2019 International Conference on …, 2019 - ieeexplore.ieee.org
With the new emerging technologies of this era, demands are increasing, concerning the
increase in the population, Consumer desires everything to be high tech and automatized …
increase in the population, Consumer desires everything to be high tech and automatized …
Parity space-based fault isolation using minimum error minimax probability machine
In this paper, a new parity space-based fault isolation (FI) approach is proposed for linear
discrete time-invariant systems. The main contribution lies in the integrated design of FI …
discrete time-invariant systems. The main contribution lies in the integrated design of FI …