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

Authors :
R Hariharan
Saxena Archana
Dhote Vijay
S Srisathirapathy
Almusawi Muntather
Raja Kumar Jambi Ratna
Source :
E3S Web of Conferences, Vol 540, p 02024 (2024)
Publication Year :
2024
Publisher :
EDP Sciences, 2024.

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

Language :
English, French
ISSN :
22671242
Volume :
540
Database :
Directory of Open Access Journals
Journal :
E3S Web of Conferences
Publication Type :
Academic Journal
Accession number :
edsdoj.05dd9796f22e4c5d87e979ba18f167f3
Document Type :
article
Full Text :
https://doi.org/10.1051/e3sconf/202454002024