The emergence of new services and applications in emerging wireless networks (eg,
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …

Federated learning (FL) enables collaborative training of a machine learning (ML) model
across multiple parties, facilitating the preservation of users' and institutions' privacy by …

The lack of trust is one of the major factors that hinder collaboration among Internet of Things
(IoT) devices and harness the usage of the vast amount of data generated. Traditional …

Predictive maintenance (PdM) is a policy applying data and analytics to predict when one of
the components in a real system has been destroyed, and some anomalies appear so that …

Federated Learning (FL) represents the de-facto standard paradigm for enabling distributed
learning over multiple clients in real-world scenarios. Despite the great strides reached in …

The proliferation of Internet of Things (IoT) devices, generating massive amounts of
heterogeneous distributed data, has pushed toward edge cloud computing as a promising …

Restrictive rules for data sharing in many industries have led to the development of\ac
{FL}.\ac {FL} is a\ac {ML} technique that allows distributed clients to train models …

In the rapidly evolving digital world, blockchain technology is becoming the foundation for
numerous applications, ranging from financial services to supply chain management. As the …

Digital identity has always been considered the keystone for implementing secure and
trustworthy communications among parties. The ever-evolving digital landscape has gone …

The realm of the Industrial Internet of Things (IIoT) encompasses a broad spectrum of
sensors that are integral to distributed smart manufacturing (DSM). The miscellaneous IIoT …