Abstract

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.

Details

Title
Advancements in Solar-Powered UAV Design Leveraging Machine Learning: A Comprehensive Review
Author
Hariharan, R; Saxena, Archana; Dhote, Vijay; Srisathirapathy, S; Almusawi, Muntather; Jambi Ratna Raja Kumar
Section
Electric Drives and Vehicles
Publication year
2024
Publication date
2024
Publisher
EDP Sciences
ISSN
25550403
e-ISSN
22671242
Source type
Conference Paper
Language of publication
English
ProQuest document ID
3181345759
Copyright
© 2024. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and conditions, you may use this content in accordance with the terms of the License.