A survey on mobile sensing based mood-fatigue detection for drivers

Wei Tu; Lei Wei; Wenyan Hu; Zhengguo Sheng; Hasen Nicanfar; Xiping Hu; Edith C.H. Ngai; Victor C.M. Leung

doi:10.1007/978-3-319-33681-7_1

A survey on mobile sensing based mood-fatigue detection for drivers

Wei Tu^*
, Lei Wei
, Wenyan Hu
, Zhengguo Sheng
, Hasen Nicanfar
, Xiping Hu
, Edith C.H. Ngai
, Victor C.M. Leung

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

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’ moodfatigue 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 moodfatigue 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.

Original language	English
Title of host publication	Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers
Editors	Veronika Krutilova, Dagmar Cagáňová, Daniela Špirková, Julius Golej, Kim Nguyen, Radim Lenort, David Holman, David Staš, Pavel Wicher, Alberto Leon-Garcia
Publisher	Springer Verlag
Pages	3-15
Number of pages	13
ISBN (Print)	9783319336800
DOIs	https://doi.org/10.1007/978-3-319-33681-7_1
Publication status	Published - 2016
Externally published	Yes
Event	International Conference on Sustainable Solutions Beyond Mobility of Goods, SustainableMoG 2015 - Bratislava, Slovakia Duration: 13 Oct 2015 → 14 Oct 2015

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume	166
ISSN (Print)	1867-8211

Conference

Conference	International Conference on Sustainable Solutions Beyond Mobility of Goods, SustainableMoG 2015
Country/Territory	Slovakia
City	Bratislava
Period	13/10/15 → 14/10/15

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Mobile sensing
Mood-fatigue detection
Vehicular sensor application

Access to Document

10.1007/978-3-319-33681-7_1

Cite this

Tu, W., Wei, L., Hu, W., Sheng, Z., Nicanfar, H., Hu, X., Ngai, E. C. H., & Leung, V. C. M. (2016). A survey on mobile sensing based mood-fatigue detection for drivers. In V. Krutilova, D. Cagáňová, D. Špirková, J. Golej, K. Nguyen, R. Lenort, D. Holman, D. Staš, P. Wicher, & A. Leon-Garcia (Eds.), Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers (pp. 3-15). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 166). Springer Verlag. https://doi.org/10.1007/978-3-319-33681-7_1

Tu, Wei ; Wei, Lei ; Hu, Wenyan et al. / A survey on mobile sensing based mood-fatigue detection for drivers. Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers. editor / Veronika Krutilova ; Dagmar Cagáňová ; Daniela Špirková ; Julius Golej ; Kim Nguyen ; Radim Lenort ; David Holman ; David Staš ; Pavel Wicher ; Alberto Leon-Garcia. Springer Verlag, 2016. pp. 3-15 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST).

@inproceedings{d395a1c425ca4bd0baac611c742f5768,

title = "A survey on mobile sensing based mood-fatigue detection for drivers",

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{\textquoteright} moodfatigue 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 moodfatigue 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.",

keywords = "Mobile sensing, Mood-fatigue detection, Vehicular sensor application",

author = "Wei Tu and Lei Wei and Wenyan Hu and Zhengguo Sheng and Hasen Nicanfar and Xiping Hu and Ngai, \{Edith C.H.\} and Leung, \{Victor C.M.\}",

note = "Publisher Copyright: {\textcopyright} ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.; International Conference on Sustainable Solutions Beyond Mobility of Goods, SustainableMoG 2015 ; Conference date: 13-10-2015 Through 14-10-2015",

year = "2016",

doi = "10.1007/978-3-319-33681-7\_1",

language = "English",

isbn = "9783319336800",

series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",

publisher = "Springer Verlag",

pages = "3--15",

editor = "Veronika Krutilova and Dagmar Cag{\'a}{\v n}ov{\'a} and Daniela {\v S}pirkov{\'a} and Julius Golej and Kim Nguyen and Radim Lenort and David Holman and David Sta{\v s} and Pavel Wicher and Alberto Leon-Garcia",

booktitle = "Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers",

address = "Germany",

}

Tu, W, Wei, L, Hu, W, Sheng, Z, Nicanfar, H, Hu, X, Ngai, ECH & Leung, VCM 2016, A survey on mobile sensing based mood-fatigue detection for drivers. in V Krutilova, D Cagáňová, D Špirková, J Golej, K Nguyen, R Lenort, D Holman, D Staš, P Wicher & A Leon-Garcia (eds), Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 166, Springer Verlag, pp. 3-15, International Conference on Sustainable Solutions Beyond Mobility of Goods, SustainableMoG 2015, Bratislava, Slovakia, 13/10/15. https://doi.org/10.1007/978-3-319-33681-7_1

A survey on mobile sensing based mood-fatigue detection for drivers. / Tu, Wei; Wei, Lei; Hu, Wenyan et al.
Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers. ed. / Veronika Krutilova; Dagmar Cagáňová; Daniela Špirková; Julius Golej; Kim Nguyen; Radim Lenort; David Holman; David Staš; Pavel Wicher; Alberto Leon-Garcia. Springer Verlag, 2016. p. 3-15 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 166).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A survey on mobile sensing based mood-fatigue detection for drivers

AU - Tu, Wei

AU - Wei, Lei

AU - Hu, Wenyan

AU - Sheng, Zhengguo

AU - Nicanfar, Hasen

AU - Hu, Xiping

AU - Ngai, Edith C.H.

AU - Leung, Victor C.M.

N1 - Publisher Copyright: © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016.

PY - 2016

Y1 - 2016

N2 - 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’ moodfatigue 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 moodfatigue 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.

AB - 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’ moodfatigue 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 moodfatigue 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.

KW - Mobile sensing

KW - Mood-fatigue detection

KW - Vehicular sensor application

UR - https://www.scopus.com/pages/publications/84978215420

U2 - 10.1007/978-3-319-33681-7_1

DO - 10.1007/978-3-319-33681-7_1

M3 - Conference contribution

AN - SCOPUS:84978215420

SN - 9783319336800

T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

SP - 3

EP - 15

BT - Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers

A2 - Krutilova, Veronika

A2 - Cagáňová, Dagmar

A2 - Špirková, Daniela

A2 - Golej, Julius

A2 - Nguyen, Kim

A2 - Lenort, Radim

A2 - Holman, David

A2 - Staš, David

A2 - Wicher, Pavel

A2 - Leon-Garcia, Alberto

PB - Springer Verlag

T2 - International Conference on Sustainable Solutions Beyond Mobility of Goods, SustainableMoG 2015

Y2 - 13 October 2015 through 14 October 2015

ER -

Tu W, Wei L, Hu W, Sheng Z, Nicanfar H, Hu X et al. A survey on mobile sensing based mood-fatigue detection for drivers. In Krutilova V, Cagáňová D, Špirková D, Golej J, Nguyen K, Lenort R, Holman D, Staš D, Wicher P, Leon-Garcia A, editors, Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers. Springer Verlag. 2016. p. 3-15. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST). doi: 10.1007/978-3-319-33681-7_1

A survey on mobile sensing based mood-fatigue detection for drivers

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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