Design and Development of a Solar- Powered UAV Using IoT and Machine Learning

Abstract

The proposed solar-powered UAV utilizes photovoltaic panels to convert solar energy into electrical power to supply the onboard electronic systems, including the propulsion system and sensors. To enhance the UAV's performance, loT technology is employed to enable the communication and coordination of the UAV with other connected devices, such as ground stations and sensors. This allows for real-time data collection and analysis, as well as improved situational awareness for the UAV. To optimize the performance of the UAV, SVM is used as a machine learning algorithm for object detection and classification. SVM has been widely used in UAVs to detect and classify objects in aerial images, and has been proven to be effective in a variety of applications. The proposed design utilizes SVM to detect and classify objects of interest, such as crops, buildings, and infrastructure, and to assist in the navigation and control of the UAV. The design and development of the proposed solar-powered UAV involves several key components, including the solar panels, propulsion system, control system, and communication system.

Keywords

• design
• development
• solar-powered uav
• internet of things
• iot sensors
• machine learning
• ml algorithms