The Role of Machine Learning in UAV-Assisted Communication

Abstract

An unmanned aerial vehicle (UAV) is a pilotless aircraft that is capable of flying and maintaining altitude without the need for a human operator, offers more cost-efficient solutions, and can carry out even important tasks cost-effectively. UAVs can provide several benefits and a wide range of uses because of their mobility, versatility, and flexibility at different altitudes. Over recent years, UAV technology has gained significant attention in various fields, such as traffic management, surveillance, agriculture, wireless communication, delivering medicine, border monitoring, photography, infrastructure inspection, post-disaster operations, etc. Despite the many benefits of UAVs, there are also many challenges related to UAVs, such as path planning, mission planning, optimal deployment, decision-making, collision avoidance, security, energy management, etc. The main aim of this proposed book chapter is to exploit algorithms that can provide optimal deployment and path-planning solutions for UAVs based on machine learning (ML) techniques.