Deep Learning Based Solar Cell Recognition for Optical Wireless Power Transfer

Autor:	Huang, Sida, Wu, Yuanting, Nguyen, Dinh Hoa
Rok vydání:	2024
Předmět:	Electrical Engineering and Systems Science - Image and Video Processing Electrical Engineering and Systems Science - Systems and Control
Druh dokumentu:	Working Paper
Popis:	Optical wireless power transfer (OWPT) is a technology that wirelessly transmit light energy from an optical transmitter to an optical receiver, usually a solar cell. In order to achieve the highest transmission efficiency, the solar cell receiver should be accurately aligned with the optical transmitter. Hitherto, only a few works have been existed for solar cell recognition in presence of complex backgrounds. In this paper, we employ a deep learning approach based on Yolov5-Lite for the solar cell recognition purpose, due to its lightweight, fast and easy to deploy on hardware characteristics. Our tests show a high accuracy of the employed deep learning model with the highest F1 score of 91% and mAP of 94.8%. Therefore, this deep learning model is highly promising for use in OWPT systems to precisely align optical transmitters and solar cell receivers. Comment: In Proceedings of The International Council on Electrical Engineering (ICEE) Conference 2024
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2410.14096 Zobrazit plný text záznamu View this record from Arxiv