Machine learning (ML) allows the Internet of Things (IoT) to gain hidden insights from the
treasure trove of sensed data and be truly ubiquitous without explicitly looking for knowledge …

Artificial neural networks (ANN), machine learning (ML), deep learning (DL), and ensemble
learning (EL) are four outstanding approaches that enable algorithms to extract information …

Online anomaly detection is a key challenge for industrial internet of things (IIoT)
applications, as anomalies may occur in data streams from sensors and cause losses or …

In healthcare, the Internet of Things (IoT) is used to remotely monitor patients and provide
real-time diagnoses, which is referred to as the Internet of Medical Things (IoMT). This …

Anomaly detection plays a critical role in various domains, including cybersecurity, finance,
healthcare, and industrial monitoring by identifying unusual patterns or events that deviate …

A vehicular ad hoc network (VANET) has significantly improved transportation efficiency with
efficient traffic management, driving safety, and delivering emergency messages. However …

Automated Machine Learning (AutoML) tools are revolutionizing the field of machine
learning by significantly reducing the need for deep computer science expertise. Designed …

The lack of publicly open network traffic datasets for research purposes is hindering
machine learning applications to wireless network analysis and design. In this work, a …

Anomaly detection for the control rod drive mechanism (CRDM) is key to enhancing the
security of nuclear power plant equipment. In CRDM real-time condition-based …

The large volume of data generated with the increasing development of Internet of Things
applications has encouraged the development of a large number of works related to data …