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 rapid emergence of low-power embedded devices and modern machine learning (ML)
algorithms has created a new Internet of Things (IoT) era where lightweight ML frameworks …

In this era of the Internet of Everything (IoE), edge computing has emerged as the critical
enabling technology to solve a series of issues caused by an increasing amount of …

The energy consumption of data centers accounts for approximately 1% of that of the world,
the average power usage effectiveness is in the range of 1.4–1.6, and the associated carbon …

Purpose The purpose of this study is to examine how the implementation of edge computing
can enhance the progress of the circular economy within supply chains and to address the …

This article presents the results of research with the main goal of identifying possible
applications of edge computing (EC) in industry. This study used the methodology of …

In recent years, the landscape of computing paradigms has witnessed a gradual yet
remarkable shift from monolithic computing to distributed and decentralized paradigms such …

The rapid development of the Industrial Internet of Things (IIoT) has led to the explosive
growth of industrial control data. Cloud computing-based industrial control models cause …

Autonomous driving services depends on active sensing from modules such as camera,
LiDAR, radar, and communication units. Traditionally, these modules process the sensed …

Serverless computing, especially when deployed at the edge of the network, is seen as an
enabling technology for the future development of more complex Internet of Things systems …