Reliable and Efficient Data Collection in UAV-based IoT Networks

TL;DR

This paper reviews methods and strategies for reliable and efficient data collection in UAV-assisted IoT networks, addressing challenges like connectivity, security, and environmental factors, and exploring optimization techniques and future challenges.

Contribution

It provides a comprehensive survey of UAV-based data collection methods, discusses performance metrics, and explores optimization strategies including AI and swarm formations.

Findings

Analysis of UAV-based data collection methods and their advantages/disadvantages

Discussion on performance metrics for data collection

Presentation of UAVs as a service for improved data reliability

Abstract

Internet of Things (IoT) involves sensors for monitoring and wireless networks for efficient communication. However, resource-constrained IoT devices and limitations in existing wireless technologies hinder its full potential. Integrating Unmanned Aerial Vehicles (UAVs) into IoT networks can address some challenges by expanding its' coverage, providing security, and bringing computing closer to IoT devices. Nevertheless, effective data collection in UAV-assisted IoT networks is hampered by factors, including dynamic UAV behavior, environmental variables, connectivity instability, and security considerations. In this survey, we first explore UAV-based IoT networks, focusing on communication and networking aspects. Next, we cover various UAV-based data collection methods their advantages and disadvantages, followed by a discussion on performance metrics for data collection. As this article primarily emphasizes reliable and efficient data collection in UAV-assisted IoT networks, we briefly discuss existing research on data accuracy and consistency, network connectivity, and data security and privacy to provide insights into reliable data collection. Additionally, we discuss efficient data collection strategies in UAV-based IoT networks, covering trajectory and path planning, collision avoidance, sensor network clustering, data aggregation, UAV swarm formations, and artificial intelligence for optimization. We also present two use cases of UAVs as a service for enhancing data collection reliability and efficiency. Finally, we discuss future challenges in data collection for UAV-assisted IoT networks.