This chapter explores the burgeoning field of integrating artificial intelligence (AI) into unmanned aerial vehicles (UAVs) through the lens of digital twin technology. UAVs, commonly known as drones, have garnered significant interest for their diverse applications. Incorporating AI capabilities into UAVs offers enhanced functionalities and opens up new horizons in various domains. The chapter provides an extensive review of the latest advancements and applications at the intersection of AI, UAVs, and digital twin technology. It delves into AI algorithms, learning models, and data processing techniques that empower UAVs to perceive, learn, and make informed decisions. Additionally, the survey presents a comprehensive outlook on how digital twin technology contributes to real-time simulation, monitoring, and control of UAVs, enabling a deeper understanding of their behaviour and performance.
Top1. Introduction
The integration of artificial intelligence (AI) into Unmanned Aerial Vehicles (UAVs) within the context of digital twin technology represents a rapidly evolving and transformative field with far-reaching implications. This survey paper endeavours to offer a comprehensive exploration of the advancements and applications of AI within UAVs, with a specific emphasis on its integration with digital twin technology. Unmanned Aerial Vehicles, more commonly known as drones, have witnessed a substantial surge in adoption across a wide array of sectors, including agriculture, surveillance, environmental monitoring, logistics, and more. AI, when introduced into the realm of UAVs, has ushered in a new era of possibilities. 1.To, A(2021) empowers these aerial vehicles with capabilities related to autonomy, data analysis, and decision-making that were previously beyond reach.
On the other hand, digital twin technology provides an intriguing dimension to this narrative. It offers a digital representation or replica of physical systems or processes, creating a real-time, data-driven simulation that is invaluable for analysis, optimization, and predictive modelling. When AI is intricately woven into this framework, it amplifies the capacities of UAVs. The integration allows these vehicles to operate with increased efficiency, safety, and adaptability.
Throughout the course of this survey paper, we will delve into the most significant advancements in the integration of AI within UAVs and the manifold applications that stem from this union. The survey will cast light on the underlying technologies, methodologies, and the challenges that are intrinsic to this integration, offering insights into the potential for innovation and transformative change McClellan (2020).
Furthermore, we will explore the practical and tangible applications of AI-equipped UAVs in various sectors. These include but are not limited to agriculture, disaster response, and infrastructure inspection, where AI-driven drones are demonstrating their potential to revolutionize operations and deliver substantial benefits. In a world where AI and digital twin technology continue to advance at a remarkable pace, comprehending the synergistic role they play in enhancing UAV capabilities becomes paramount. This survey paper is designed to be a valuable resource, catering to the needs of researchers, practitioners, and policymakers who are keenly interested in the convergence of AI, UAVs, and digital twin technology. It aims to provide a comprehensive understanding of the current landscape while offering valuable insights into the exciting possibilities and future prospects in this ever-evolving field.