LSTM learning with Bayesian and Gaussian processing for anomaly detection in industrial IoT
The data generated by millions of sensors in the industrial Internet of Things (IIoT) are
extremely dynamic, heterogeneous, and large scale and pose great challenges on the real …
extremely dynamic, heterogeneous, and large scale and pose great challenges on the real …
[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 …
decades and attracted the attention of scientific and industrial domains. In WSNs, sensor …
[HTML][HTML] A survey of anomaly detection in industrial wireless sensor networks with critical water system infrastructure as a case study
The increased use of Industrial Wireless Sensor Networks (IWSN) in a variety of different
applications, including those that involve critical infrastructure, has meant that adequately …
applications, including those that involve critical infrastructure, has meant that adequately …
Gaussian distribution-based machine learning scheme for anomaly detection in healthcare sensor cloud
Smart information systems are based on sensors that generate a huge amount of data. This
data can be stored in cloud for further processing and efficient utilization. Anomalous data …
data can be stored in cloud for further processing and efficient utilization. Anomalous data …
[HTML][HTML] A novel machine learning-based approach for outlier detection in smart healthcare sensor clouds
A smart healthcare sensor cloud is an amalgamation of the body sensor networks and the
cloud that facilitates the early diagnosis of diseases and the real-time monitoring of patients …
cloud that facilitates the early diagnosis of diseases and the real-time monitoring of patients …
A study on machine learning based anomaly detection approaches in wireless sensor network
RK Dwivedi, AK Rai, R Kumar - 2020 10th International …, 2020 - ieeexplore.ieee.org
Wireless sensor networks (WSN) became very popular in last few years. They are deployed
in distributed manner for collecting variety of data. There are a lot of research issues and …
in distributed manner for collecting variety of data. There are a lot of research issues and …
Near real-time anomaly detection in NFV infrastructures
A Derstepanians, M Vannucci… - … IEEE Conference on …, 2022 - ieeexplore.ieee.org
This paper presents a scalable cloud-based archi-tecture for near real-time anomaly
detection in the Vodafone NFV infrastructure, spanning across multiple data centers in 11 …
detection in the Vodafone NFV infrastructure, spanning across multiple data centers in 11 …
Anomaly detection and redundancy elimination of big sensor data in internet of things
S Xie, Z Chen - arXiv preprint arXiv:1703.03225, 2017 - arxiv.org
In the era of big data and Internet of things, massive sensor data are gathered with Internet
of things. Quantity of data captured by sensor networks are considered to contain highly …
of things. Quantity of data captured by sensor networks are considered to contain highly …
A secure barrier coverage scheduling framework for WSN-based IoT applications
D Thomas, R Shankaran - Proceedings of the 23rd International ACM …, 2020 - dl.acm.org
Wireless sensor networks (WSNs) are network enabling technology for a variety of mission-
critical IoT applications. The essential Quality of Service (QoS) requirements of these …
critical IoT applications. The essential Quality of Service (QoS) requirements of these …
Smart textiles for smart home control and enriching future wireless sensor network data
The increasing number of objects within homes connected to the Cloud is not going to
recede. Our growing acceptance of automated appliances and items connected in wireless …
recede. Our growing acceptance of automated appliances and items connected in wireless …