@article{ref1,
title="Methods and tools for monitoring driver's behavior",
journal="Proceedings. International Conference on Computational Science and Computational Intelligence",
year="2022",
author="Jan, Muhammad Tanveer and Moshfeghi, Sonia and Conniff, Joshua and Jang, Jinwoo and Yang, Kwangsoo and Zhai, Jiannan and Rosselli, Monica and Newman, David and Tappen, Ruth and Furht, Borko",
volume="2022",
number="",
pages="1269-1273",
abstract="In-vehicle sensing technology has gained tremendous attention due to its ability to support major technological developments, such as connected vehicles and self-driving cars. In-vehicle sensing data are invaluable and important data sources for traffic management systems. In this paper we propose an innovative architecture of unobtrusive in-vehicle sensors and present methods and tools that are used to measure the behavior of drivers. The proposed architecture including methods and tools are used in our NIH project to monitor and identify older drivers with early dementia.<p /> <p>Language: en</p>",
language="en",
issn="2769-5670",
doi="10.1109/csci58124.2022.00228",
url="http://dx.doi.org/10.1109/csci58124.2022.00228"
}