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arXiv · 2004.10021

Mask R-CNN Based Object Detection for Intelligent Wireless Power Transfer

Aozhou Wu·Qingqing Zhang·Wen Fang·Hao Deng·Sai Jiang·Qingwen Liu
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Abstract

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.

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Aozhou Wu, Qingqing Zhang, Wen Fang, Hao Deng, Sai Jiang, Qingwen Liu. 2020-04-19. Mask R-CNN Based Object Detection for Intelligent Wireless Power Transfer. https://arxiv.org/abs/2004.10021

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