[HTML][HTML] Machine learning for Internet of Things data analysis: A survey

MS Mahdavinejad, M Rezvan, M Barekatain… - Digital Communications …, 2018 - Elsevier
Rapid developments in hardware, software, and communication technologies have
facilitated the emergence of Internet-connected sensory devices that provide observations …

Machine learning techniques in emerging cloud computing integrated paradigms: A survey and taxonomy

D Soni, N Kumar - Journal of Network and Computer Applications, 2022 - Elsevier
Cloud computing offers Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and
Software as a Service (SaaS) to provide compute, network, and storage capabilities to the …

Progress in outlier detection techniques: A survey

H Wang, MJ Bah, M Hammad - Ieee Access, 2019 - ieeexplore.ieee.org
Detecting outliers is a significant problem that has been studied in various research and
application areas. Researchers continue to design robust schemes to provide solutions to …

[HTML][HTML] Data-driven anomaly detection approach for time-series streaming data

M Zhang, J Guo, X Li, R Jin - Sensors, 2020 - mdpi.com
Recently, wireless sensor networks (WSNs) have been extensively deployed to monitor
environments. Sensor nodes are susceptible to fault generation due to hardware and …

Machine learning and deep learning algorithms on the Industrial Internet of Things (IIoT)

P Ambika - Advances in computers, 2020 - Elsevier
Deep transformation and human progress is a new industrial revolution that makes
“Automation of Everything.” It connects all digital interfaces, data analysis and control of the …

State of the art on quality control for data streams: A systematic literature review

M Mirzaie, B Behkamal, M Allahbakhsh… - Computer Science …, 2023 - Elsevier
These days, endless streams of data are generated by various sources such as sensors,
applications, users, etc. Due to possible issues in sources, such as malfunctions in sensors …

Outlier detection using AI: a survey

MNK Sikder, FA Batarseh - AI Assurance, 2023 - Elsevier
An outlier is an event or observation that is defined as an unusual activity, intrusion, or a
suspicious data point that lies at an irregular distance from a population. The definition of an …

Perspective of anomaly detection in big data for data quality improvement

V Keskar, J Yadav, A Kumar - Materials Today: Proceedings, 2022 - Elsevier
Abstract The period of Big Data examination has started in many businesses inside created
nations. With expanding headway of Internet technology, expanding measures of data are …

A vertical and cross-linked Ni (OH) 2 network on cellulose-fiber covered with graphene as a binder-free electrode for advanced asymmetric supercapacitors

LL Zhang, HH Li, CY Fan, K Wang, XL Wu… - Journal of materials …, 2015 - pubs.rsc.org
Nanostructured transition metal oxides are attractive pseudocapacitive materials with high
theoretical specific capacitance, scale-up potential and environmental benignity. However …

Using trust as a measure to derive data quality in data shared IoT deployments

J Byabazaire, G O'Hare… - 2020 29th International …, 2020 - ieeexplore.ieee.org
Recent developments in Internet of Things have heightened the need for data sharing
across application domains to foster innovation. As most of these IoT deployments are …