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 …

Rapid growth in numbers of connected devices including sensors, mobile, wearable, and
other Internet of Things (IoT) devices, is creating an explosion of data that are moving across …

Existing deep learning systems in the Internet of Things (IoT) environments lack the ability of
assigning compute tasks reasonably which leads to resources wasting. In this letter, we …

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 …

Artificial Intelligence of Things (AIoT) is an emerging area of future Internet of Things (IoT) to
support intelligent IoT applications. In AIoT, intelligent edge computing technologies …

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 …

Recently, the application of Artificial Intelligence (AI) in the Internet of Things (IoT) devices is
increasing. As these devices are limited in processing and storing massive computations of …

The Internet of Things (IoT) is widely regarded as a key component of the Internet of the
future and thereby has drawn significant interests in recent years. IoT consists of billions of …

With the development of the Internet of Things (IoT) and the birth of various new IoT devices,
the capacity of massive IoT devices is facing challenges. Fortunately, edge computing can …

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 …