Research Article
A Survey on Mobile Sensing Based Mood-Fatigue Detection for Drivers
@INPROCEEDINGS{10.1007/978-3-319-33681-7_1, author={Wei Tu and Lei Wei and Wenyan Hu and Zhengguo Sheng and Hasen Nicanfar and Xiping Hu and Edith Ngai and Victor Leung}, title={A Survey on Mobile Sensing Based Mood-Fatigue Detection for Drivers}, proceedings={Smart City 360°. First EAI International Summit, Smart City 360°, Bratislava, Slovakia and Toronto, Canada, October 13-16, 2015. Revised Selected Papers}, proceedings_a={SMARTCITY360}, year={2016}, month={6}, keywords={Mobile sensing Mood-fatigue detection Vehicular sensor application}, doi={10.1007/978-3-319-33681-7_1} }- Wei Tu
Lei Wei
Wenyan Hu
Zhengguo Sheng
Hasen Nicanfar
Xiping Hu
Edith Ngai
Victor Leung
Year: 2016
A Survey on Mobile Sensing Based Mood-Fatigue Detection for Drivers
SMARTCITY360
Springer
DOI: 10.1007/978-3-319-33681-7_1
Abstract
The rapid development of the Internet of Things (IoT) has provided innovative solutions to reduce traffic accidents caused by fatigue driving. When drivers are in bad mood or tired, their vigilance level decreases, which may prolong the reaction time to emergency situation and lead to serious accidents. With the help of mobile sensing and mood-fatigue detection, drivers’ mood-fatigue status can be detected while driving, and then appropriate measures can be taken to eliminate the fatigue or negative mood to increase the level of vigilance. This paper presents the basic concepts and current solutions of mood-fatigue detection and some common solutions like mobile sensing and cloud computing techniques. After that, we introduce some emerging platforms which designed to promote safe driving. Finally, we summarize the major challenges in mood-fatigue detection of drivers, and outline the future research directions.
