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Resonant Beam Charging (RBC) is a promising multi-Watt and multi-meterwireless power transfer method with safety, mobility andsimultaneously-charging capability. However, RBC system operation relies oninformation availability including power receiver location, class label and thereceiver number. Since smartphone is the most widely-used mobile device, wepropose a Mask R-CNN based smartphone detection model in the RBC system.Experiments illustrate that our model reduces the smartphone scanning time toone third. Thus, this machinelearningdetectionapproachprovidesanintelligentwaytoimprove the user experiencein wireless power transfer for mobile and Internet of Things (IoT) devices.

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