VehicleSense: A reliable sound-based transportation mode recognition system for smartphones

A new transportation mode recognition system for smartphones, VehicleSense that is widely applicable to mobile context-aware services is proposed. VehicleSense aims at achieving three performance objectives: high accuracy, low latency, and low power consumption at once by exploiting sound characteristics captured from the built-in microphone while being on candidate transportations. To attain high energy efficiency, VehicleSense adopts hierarchical accelerometer-based triggers that minimize the activation of the microphone of smartphones. Further, to attain high accuracy and low latency, VehicleSense makes use of non-linear filters that can best extract the transportation sound samples. Our 186-hour log of sound and accelerometer data collected by seven different Android smartphone models confirms that VehicleSense achieves the recognition accuracy of 98.2% with only 0.5 seconds of sound sampling at the power consumption of 26.1 mW on average for all day monitoring.

I. Introduction

We live in the world of smartphones where people interact with their smartphones for a significant time of a day, e.g., [1]. As people spend more time on their smartphones, they expect higher intelligence from the smartphones. In order to meet this expectation, researchers have come up with the concept of recognition systems that bring intelligence to smartphones, with which the surrounding contexts are comprehended to provide timely services to the smartphone users. There exist diverse recognition systems such as activity recognition [2], exercises recognition [3], transportation mode recognition [4], and touch-based identity recognition systems [5].