SingMonitor: E-bike Charging Health Monitoring Using Sound from Power Supplies

Abstract

In recent years, fire disasters caused by charging electric bicycles/moped (e-bikes) have been increasing, causing catastrophic loss of life and property; Worse still, existing fire warning systems are costly to install and maintain, and they work after the accident occurs. Some existing works propose using power meters or similar sensors in the power grid to monitor e-bike charging health. However, the use of additional equipment makes them challenging to deploy. Others can use the sound or electromagnetic signals emitted by e-bikes for monitoring, but they suffer from limited monitoring distance. To solve this problem, we propose SingMonitor, a scheme to remotely monitor e-bike charging status using mobile devices’ microphones. The charging e-bike generates a unique current signal, which is then transmitted through the power grid and drives the mobile devices’ power supply to generate sound, which is then captured by a microphone. Based on this principle and the proposed template matching method, SingMonitor can identify the e-bike charging status. Experiments show SingMonitor achieves an F1 score of 0.94 in identifying 10 e-bikes’ charging status, with a detection distance of 9m+.

Keywords

• e-bike
• power supply
• power factor correction
• template matching