Anomaly detection is concerned with identifying data patterns that deviate remarkably from
the expected behavior. This is an important research problem, due to its broad set of …

Determining how to structure vehicular network environments can be done in various ways.
Here, we highlight vehicle networks' evolution from vehicular ad-hoc networks (VANET) to …

In the traditional cloud-based Internet of Vehicles (IoV) architecture, it is difficult to guarantee
the low latency requirements of the current intelligent transportation system (ITS). As a …

Coupled with the rise of Deep Learning, the wealth of data and enhanced computation
capabilities of Internet of Vehicles (IoV) components enable effective Artificial Intelligence …

The emergency of federated learning (FL) enables distributed data owners to collaboratively
build a global model without sharing their raw data, which creates a new business chance …

Performing deep neural network (DNN) inference in real time requires excessive network
resources, which poses a big challenge to the resource-limited industrial Internet of things …

Space–air–ground-integrated networks (SAGINs) are deemed as a promising solution to
support multifarious Internet of Vehicles (IoV) services with diversified Quality-of-Service …

Renewable energy sources (RES) and low-carbon technology users play a vital role in
modern power systems. However, RES generation is easily affected by the environment …

Vehicular Edge Computing (VEC) is a promising paradigm that leverages the vehicles to
offload computation tasks to the nearby VEC server with the aim of supporting the low …

The Internet of vehicles (IoV) is a large information interaction network that collects
information on vehicles, roads and pedestrians. One of the important uses of vehicle …