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

¹ Assistant Professor, School of Business and Management, CHRIST (Deemed to be University), Bangalore Yeshwantpur Campus India .
² Department of Management, Uttaranchal Institute of Management, Uttaranchal University, Dehradun, Uttarakhand, India .
³ Department of Computer Science & Engineering, IES College of Technology, IES University, Madhya Pradesh 462044 India, Bhopal .
⁴ Assistant Professor, Department of MECH, Prince Shri Venkateshwara Padmavathy Engineering College, Chennai – 127, India .
⁵ The Islamic university, Najaf, Iraq .
⁶ Associate Professor, Department of Computer Engineering, Genba Sopanrao Moze College of Engineering, Balewadi, India Email: ratnaraj.jambi@gmail.com, Pune, Maharashtra .

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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.