دورية أكاديمية
Advancements in Solar-Powered UAV Design Leveraging Machine Learning: A Comprehensive Review
العنوان: | Advancements in Solar-Powered UAV Design Leveraging Machine Learning: A Comprehensive Review |
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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 |
تدمد: | 22671242 |
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DOI: | 10.1051/e3sconf/202454002024 |