Cheng, N.; Wu, S.; Wang, X.; Yin, Z.; Li, C.; Chen, W.; Chen, F. AI for UAV-Assisted IoT Applications: A Comprehensive Review. IEEE Internet of Things Journal 2023, 1–1, doi:10.1109/jiot.2023.3268316.
Cheng, N.; Wu, S.; Wang, X.; Yin, Z.; Li, C.; Chen, W.; Chen, F. AI for UAV-Assisted IoT Applications: A Comprehensive Review. IEEE Internet of Things Journal 2023, 1–1, doi:10.1109/jiot.2023.3268316.
Cheng, N.; Wu, S.; Wang, X.; Yin, Z.; Li, C.; Chen, W.; Chen, F. AI for UAV-Assisted IoT Applications: A Comprehensive Review. IEEE Internet of Things Journal 2023, 1–1, doi:10.1109/jiot.2023.3268316.
Cheng, N.; Wu, S.; Wang, X.; Yin, Z.; Li, C.; Chen, W.; Chen, F. AI for UAV-Assisted IoT Applications: A Comprehensive Review. IEEE Internet of Things Journal 2023, 1–1, doi:10.1109/jiot.2023.3268316.
Abstract
With the rapid development of the Internet of Things (IoT), there are dramatic increasing number of devices in the network, which causes the challenge that only using infrastructure such as based station cannot provide service with all devices with high quality. Therefore, due to their flexibility and economy, unmanned aerial vehicles (UAV) are widely used to increase the performance of IoT networks. UAVs can not only provide communication services for IoT devices in the absence of a network, but they can also perform video surveillance, cargo transportation, pesticide spraying, and other specialized tasks. However, due to the complexity of the scenario and the need for real-time decision making, it is challenging to schedule UAVs in the network using traditional optimization methods, and growing attention has focused on using AI to optimize UAVs in the network. In this paper, we focus on the AI-enabled UAV optimization method in IoT networks and give a comprehensive scope on what and how to use AI-enabled methods to increase the performance of UAV-assisted IoT networks. Moreover, a brief analysis of the challenges of using AI methods in IoT networks and some potential research directions are given.
Keywords
AI; UAV; IoT; mobile edge computing; reinforcement learning
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
