Sensor data quality plays a vital role in Internet of Things (IoT) applications as they are
rendered useless if the data quality is bad. This systematic review aims to provide an …

The paradigm of the Internet of everything (IoE) is advancing toward enriching people's lives
by adding value to the Internet of things (IoT), with connections among people, processes …

Multimodal Learning Analytics (MMLA) innovations make use of rapidly evolving sensing
and artificial intelligence algorithms to collect rich data about learning activities that unfold in …

The Internet of Things (IoT) is a key and growing technology for many critical real-life
applications, where it can be used to improve decision making. The existence of several …

The widespread adoption of the Internet of Things (IoT) has transformed various sectors
globally, making them more intelligent and connected. However, this advancement comes …

Although Internet of Things (IoT) systems are widely used in various industries, they are
prone to data collection errors due to device limitations and environmental factors. These …

In this chapter, we provide an overview of the current trends in using semantic technologies
in the IoT domain, presenting practical applications and use cases in different domains, such …

As an important tool of data mining, classification is also one of the major components of the
research of Internet of Things (IoT), which has been widely used in many cases, such as …

Semantic technology can provide a bridge between smart applications and Internet of
Things (IoT) to enable possible integration and interoperability of data produced by …

Abstract In the Industrial Internet of Things (IIoT) applications, sensor data quality has an
essential role as they become useless if the quality of data is poor. When the data collected …