posted on 2023-03-01, 04:20authored bySaeed Alsamhi, Alexey V Shvetsov, Santosh Kumar, Jahan HassanJahan Hassan, Mohammed A Alhartomi, Svetlana V Shvetsova, Radhya Sahal, Ammar Hawbani
Unmanned Aerial Vehicles (UAVs) are increasingly being used in a high-computation
paradigm enabled with smart applications in the Beyond Fifth Generation (B5G) wireless communication
networks. These networks have an avenue for generating a considerable amount of
heterogeneous data by the expanding number of Internet of Things (IoT) devices in smart environments.
However, storing and processing massive data with limited computational capability
and energy availability at local nodes in the IoT network has been a significant difficulty, mainly
when deploying Artificial Intelligence (AI) techniques to extract discriminatory information from the
massive amount of data for different tasks.Therefore, Mobile Edge Computing (MEC) has evolved
as a promising computing paradigm leveraged with efficient technology to improve the quality of
services of edge devices and network performance better than cloud computing networks, addressing
challenging problems of latency and computation-intensive offloading in a UAV-assisted framework.
This paper provides a comprehensive review of intelligent UAV computing technology to enable 6G
networks over smart environments. We highlight the utility of UAV computing and the critical role
of Federated Learning (FL) in meeting the challenges related to energy, security, task offloading, and
latency of IoT data in smart environments. We present the reader with an insight into UAV computing,
advantages, applications, and challenges that can provide helpful guidance for future research.