Resonant Beam Charging (RBC) is a promising multi-Watt and multi-meter wireless power transfer method with safety, mobility and simultaneously-charging capability. However, RBC system operation relies on information availability including power receiver location, class label and the receiver number. Since smartphone is the most widely-used mobile device, we propose a Mask R-CNN based smartphone detection model in the RBC system. Experiments illustrate that our model reduces the smartphone scanning time to one third. Thus, this machine learningdetectionapproachprovidesanintelligentwaytoimprove the user experience in wireless power transfer for mobile and Internet of Things (IoT) devices.
@article{arxiv.2004.10021,
title = {Mask R-CNN Based Object Detection for Intelligent Wireless Power Transfer},
author = {Aozhou Wu and Qingqing Zhang and Wen Fang and Hao Deng and Sai Jiang and Qingwen Liu},
journal= {arXiv preprint arXiv:2004.10021},
year = {2020}
}