Abstract
Unmanned aerial vehicles (UAVs) are becoming integrated into a wide range of modern IoT applications. The growing number of networked IoT devices generates a large amount of data. However, processing and memorizing this massive volume of data at local nodes have been deemed critical challenges, especially when using artificial intelligence (AI) systems to extract and exploit valuable information. In this context, mobile edge computing (MEC) has emerged as a way to bring cloud computing (CC) processes within reach of users, to address computation-intensive offloading and latency issues. This paper provides a comprehensive review of the most relevant research works related to UAV technology applications in terms of enabled or assisted MEC architectures. It details the utility of UAV-enabled MEC architecture regarding emerging IoT applications and the role of both deep learning (DL) and machine learning (ML) in meeting various limitations related to latency, task offloading, energy demand, and security. Furthermore, throughout this article, the reader gains an insight into the future of UAV-enabled MEC, the advantages and the critical challenges to be tackled when using AI.
Highlights
This paper explores the use of unmanned aerial vehicles (UAVs) in emerging Internet of Things (IoT) applications and the utility of both deep learning (DL)
Drones can serve as a link between smart devices and cloud data centers, to provide many services that can increase the performance of a given IoT system
UAVs can play in enabling communications and intelligent computing in the IoT era, by referring to the most widely emerging artificial intelligence (AI) techniques that are employed
Summary
The number of connected devices is forecasted to reach impressive heights in the coming years. Unmanned aerial vehicles (UAVs), typically known as drones, have attracted considerable attention from academia and industrial communities due to their excellent capabilities and attractive features. They promise to bring an ideal contribution to the field of IoT, based on their unique characteristics. They offer elastic and flexible mobile features, as required in many omnipresent IoT applications, making their integration into wireless network communication easy and feasible
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