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

التفاصيل البيبلوغرافية
العنوان: Advancements in Solar-Powered UAV Design Leveraging Machine Learning: A Comprehensive Review
المؤلفون: R Hariharan, Saxena Archana, Dhote Vijay, S Srisathirapathy, Almusawi Muntather, Raja Kumar Jambi Ratna
المصدر: E3S Web of Conferences, Vol 540, p 02024 (2024)
بيانات النشر: EDP Sciences, 2024.
سنة النشر: 2024
المجموعة: LCC:Environmental sciences
مصطلحات موضوعية: resource, nav, rotor-driven, controllers, suav, flight endurance, Environmental sciences, GE1-350
الوصف: 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
French
تدمد: 2267-1242
Relation: https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/70/e3sconf_icpes2024_02024.pdf; https://doaj.org/toc/2267-1242
DOI: 10.1051/e3sconf/202454002024
URL الوصول: https://doaj.org/article/05dd9796f22e4c5d87e979ba18f167f3
رقم الأكسشن: edsdoj.05dd9796f22e4c5d87e979ba18f167f3
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:22671242
DOI:10.1051/e3sconf/202454002024