New technologies bring opportunities to deploy AI and machine learning to the edge of the
network, allowing edge devices to train simple models that can then be deployed in practice …

IoT systems are widely used in various applications, including healthcare, agriculture,
manufacturing, and smart cities. However, these systems still have limitations, such as lack …

The rapid growth in the number of interconnected devices on the Internet (referred to as the
Internet of Things—IoT), along with the huge volume of data that are exchanged and …

Abstract The integration of Deep Learning (DL) and the Internet of Things (IoT) has
revolutionized technology in the twenty-first century, enabling humans and machines to …

Over the last few decades, Internet of Things (IoT) has become the spotlight area of research
within the Industries and Academics. Primarily, IoT devices are characterized by small and …

In recent decades, deep-learning dependent fruit disease detection and classification
techniques have evinced outstanding results in technologically advanced horticulture …

The burgeoning growth of the Internet of Things (IoT) has prompted a paradigm shift in
computing architectures, leading to the emergence and rapid evolution of edge computing …

In the field of the Internet of Things (IoT), Edge computing has emerged as a revolutionary
paradigm that offers unprecedented benefits by serving the IoT at the network edge. One of …

Driven by the demand of time-sensitive and data-intensive applications, edge computing
has attracted wide attention as one of the cornerstones of modern service architectures. An …

As blockchain technology merges with Mobile Edge Computing (MEC) and the Internet of
Things (IoT), we encounter increasing challenges such as high energy consumption and …