E3S Web of Conferences (Jan 2024)

Advancements in Solar-Powered UAV Design Leveraging Machine Learning: A Comprehensive Review

  • R Hariharan,
  • Saxena Archana,
  • Dhote Vijay,
  • S Srisathirapathy,
  • Almusawi Muntather,
  • Raja Kumar Jambi Ratna

DOI
https://doi.org/10.1051/e3sconf/202454002024
Journal volume & issue
Vol. 540
p. 02024

Abstract

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Unmanned Aerial Vehicles (UAVs), commonly known as drones, have seen significant innovations in recent years. Among these innovations, the integration of solar power and machine learning has opened up new horizons for enhancing UAV capabilities. This review article provides a comprehensive overview of the state-of-the-art in solarpowered UAV design and its synergy with machine learning techniques. We delve into the various aspects of solar-powered UAVs, from their design principles and energy harvesting technologies to their applications across different domains, all while emphasizing the pivotal role that machine learning plays in optimizing their performance and expanding their functionality. By examining recent advancements and challenges, this review aims to shed light on the future prospects of this transformative technology.

Keywords