In this paper, we investigate how to deploy computational intelligence and deep learning
(DL) in edge-enabled industrial IoT networks. In this system, the IoT devices can …

With the revolution of smart industry, more and more Industrial Internet of Things (IIoT)
devices as well as AI algorithms are deployed to achieve industrial intelligence. While …

As a typical application of the Internet of Things (IoT), the Industrial IoT (IIoT) connects all the
related IoT sensing and actuating devices ubiquitously so that the monitoring and control of …

Edge computing is a new paradigm enabling intelligent applications for the Internet of
Things (IoT) using mobile, low-cost IoT devices embedded with data analytics. Due to the …

The rapid development of artificial intelligence and 5G paradigm, opens up new possibilities
for emerging applications in industrial Internet of Things (IIoT). However, the large amount of …

The Industrial Internet of Things (IIoT) enables intelligent industrial operations by
incorporating artificial intelligence (AI) and big data technologies. An AI-enabled framework …

Edge computing has emerged as a trend to improve scalability, overhead, and privacy by
processing large-scale data, eg, in deep learning applications locally at the source. In IoT …

In this paper, we aim to make the best joint decision of device selection and computing and
spectrum resource allocation for optimizing federated learning (FL) performance in …

In this article, we study edge artificial intelligence (AI) for industrial Internet of Things (IIoT)
applications. We discuss edge AI technology, which is considered the combination of AI with …

Deep learning is a promising approach for extracting accurate information from raw sensor
data from IoT devices deployed in complex environments. Because of its multilayer structure …