@article{ref1,
title="Reliable identification of vehicle-boarding actions based on fuzzy inference syste",
journal="Sensors (Basel)",
year="2017",
author="Ahn, DaeHan and Park, Homin and Hwang, Seokhyun and Park, Taejoon",
volume="17",
number="2",
pages="s17020333-s17020333",
abstract="Existing smartphone-based solutions to prevent distracted driving suffer from inadequate system designs that only recognize simple and clean vehicle-boarding actions, thereby failing to meet the required level of accuracy in real-life environments. In this paper, exploiting unique sensory features consistently monitored from a broad range of complicated vehicle-boarding actions, we propose a reliable and accurate system based on fuzzy inference to classify the sides of vehicle entrance by leveraging built-in smartphone sensors only. The results of our comprehensive evaluation on three vehicle types with four participants demonstrate that the proposed system achieves 91.1%∼94.0% accuracy, outperforming other methods by 26.9%∼38.4% and maintains at least 87.8 %accuracy regardless of smartphone positions and vehicle types.<p /> <p>Language: en</p>",
language="en",
issn="1424-8220",
doi="10.3390/s17020333",
url="http://dx.doi.org/10.3390/s17020333"
}