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VehicleSense: A Reliable Sound-based Transportation Mode Recognition System for Smartphones - Presennted at IEEE WoWMoM 2017

So far, there have been no previous works with a satisfying performance in terms of a latency, a recognition accuracy and an energy efficiency at the same time. VehicleSense achieves all of these performances simultaneously by utilizing the unique characteristics of a sound of vehicles and implementing accelerometer-based trigger systems.

IEEE WoWMoM (World of Wireless  Mobile and Multimedia Networks) is a conference in the areas of wireless, mobile, and multimedia networking as well as ubiquitous and pervasive systems,
which is run by rigorous papers of 9 pages.

[ ABSTRACT ]
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.

Spectrogram of Bus SoundSpectrogram of Subway SoundSpectrogram of Taxi Sound

[ Spectrogram of Bus Sound, Taxi Sound, and Subway Sound (from left to right) ]

system overview

[ VehicleSense system overview ]