Inferring Smartphone Positions Based on Collecting the Environment's Response to Vibration Motor Actuation

Abstract

Smartphones have become ubiquitous in recent years and offer many useful services to their users, such as notifications about incoming calls and messages, or news updates in real-time. These notifications however do not consider the current user's and phone's context. As a result, they can disturb users in important meetings or remain unnoticed in noisy environment. In this paper, we therefore propose an approach to infer the phone's context based on its vibration motor. To this end, we trigger the phone's vibration motor for short time periods and measure the response of its environments using the built-in microphone and/or accelerometers.Our evaluation shows that leveraging accelerometers allows to recognize the current phone's context with an accuracy of more than 99%. As a result, our proposed solution outperforms our previous work based on played and recorded ringtones in terms of classification performance, user annoyance, as well as potential privacy threats.