Artificial Intelligence (AI) at the edge is the utilization of AI in real-world devices. Edge AI
refers to the practice of doing AI computations near the users at the network's edge, instead …

The Internet of Things (IoT) has created a ubiquitously connected world powered by a
multitude of wired and wireless sensors generating a variety of heterogeneous data over …

Many enterprise companies migrate their services and applications to the cloud to benefit
from cloud computing advantages. Meanwhile, the rapidly increasing number of connected …

Recent advances in smart connected vehicles and Intelligent Transportation Systems (ITS)
are based upon the capture and processing of large amounts of sensor data. Modern …

Ubiquitous sensors and smart devices from factories and communities are generating
massive amounts of data, and ever-increasing computing power is driving the core of …

Deep learning is currently widely used in a variety of applications, including computer vision
and natural language processing. End devices, such as smartphones and Internet-of-Things …

Over the past decade, we have witnessed an enormous amount of research effort dedicated
to the design of efficient outlier detection techniques while taking into consideration …

Recently, smart cities, healthcare system, and smart vehicles have raised challenges on the
capability and connectivity of state-of-the-art Internet-of-Things (IoT) devices, especially for …

Sending data to the cloud for analysis was a prominent trend during the past decades,
driving cloud computing as a dominant computing paradigm. However, the dramatically …

Federated learning (FL) has emerged in edge computing to address limited bandwidth and
privacy concerns of traditional cloud-based centralized training. However, the existing FL …