ItemConference Paper

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

Title
Advancements in Solar-Powered UAV Design Leveraging Machine Learning: A Comprehensive Review
Creator
Hariharan R.; Saxena A.; Dhote V.; Srisathirapathy S.; Almusawi M.; Raja Kumar J.R.
Description
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. The Authors, published by EDP Sciences, 2024.
Source
E3S Web of Conferences, Vol-540
Date
2024-01-01
Publisher
EDP Sciences
Subject
Controllers; Flight endurance; NAV; Resource; Rotor-driven; SUAV
Coverage
Hariharan R., School of Business and Management, CHRIST (Deemed to Be University), Bangalore Yeshwantpur Campus India, India; Saxena A., Department of Management, Uttaranchal Institute of Management, Uttaranchal University, Uttarakhand, Dehradun, India; Dhote V., Department of Computer Science and Engineering, IES College of Technology, IES University, Madhya Pradesh, Bhopal, 462044, India; Srisathirapathy S., Department of Mech, Prince Shri Venkateshwara Padmavathy Engineering College, Chennai, 127, India; Almusawi M., The Islamic University, Najaf, Iraq; Raja Kumar J.R., Department of Computer Engineering, Genba Sopanrao Moze College of Engineering, Maharashtra, Balewadi, India
Rights
Restricted Access
Relation
ISSN: 25550403
Format
Online
Language
English
Type
Conference paper

Collection

Conference Papers

Citation

Hariharan R.; Saxena A.; Dhote V.; Srisathirapathy S.; Almusawi M.; Raja Kumar J.R., “Advancements in Solar-Powered UAV Design Leveraging Machine Learning: A Comprehensive Review,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/18970.

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