In this constantly evolving landscape of urbanization, the relationship between technology
and automation, in regards to sustainability, holds immense significance. The intricate …

Intelligent transportation systems (ITSs) have been fueled by the rapid development of
communication technologies, sensor technologies, and the Internet of Things (IoT) …

Federated learning (FL) is a promising machine learning approach for Internet of Things
(IoT), but it has to address network congestion problems when the population of IoT devices …

In the realm of machine learning (ML) systems featuring client-host connections, the
enhancement of privacy security can be effectively achieved through federated learning (FL) …

Malware propagation in IoT (Internet of Things) systems can lead to data leakages, financial
losses, and other serious consequences. To solve this issue, we propose a new active IoT …

The widespread deployment of the smart meters makes it possible to record massive fine-
grained energy consumption data. However, the end energy users (eg, prosumers) may …

In this paper, an energy scheduling problem is formulated for the prosumer-based urban
area, where prosumers are regarded as the drone charging stations for urban air mobility …

Distributed model training is made possible by federated learning on various computing
nodes, and compute nodes can submit model updates individually while preserving data …

The fusion of federated learning (FL) and unmanned aerial vehicles (UAVs) garnered
significant attention as a propitious paradigm, enabling the provision of ubiquitous Artificial …

Prosumers nowadays not only can generate renewable energy and consume energy, but
also can be the charging stations for charging both electric vehicles (EVs) and drone taxis …