NDLI: The drive fatigue pattern monitor for haul truck drivers in surface mining operations

Content Provider	IEEE Xplore Digital Library
Author	Enji Sun Nieto, A. Quanming Li
Copyright Year	2015
Description	Author affiliation: Pennsylvania State Univ., University Park, PA, USA (Nieto, A.) \|\| China Acad. of Safety Sci. & Technol., Beijing, China (Enji Sun; Quanming Li)
Abstract	Haul trucks are one of the most important transportations in the operations of large surface mines. The traffic accidents involved haul trucks result in serious damages on the vehicles, even the loss of the drivers' lives. Drive fatigue is one of the key features that cause traffic accidents in surface mining operations. The light varies and driver's behaviors in the cabin increase the difficulties of drive fatigue monitoring. This paper developed the haul truck driver fatigue monitoring prealarm methodologies using real-time, non-intrusive machine vision technologies. It detected and tracked the driver's face by using AdaBoost algorithm. It extracted the key features of driver's eyes by template matching algorithm. This paper improved the SNAKE algorithms in the monitored image processing and pattern recognition, which increased the efficiency of the fatigue detection under the light variations and different driver's gestures. It observed the eye's closure duration and calculated the cumulative total percentage of a particular time (PERCLOS) to determine the driver's fatigue status. This research was applied to a driver of the haul truck in a coal mine. The detection results indicate that it can identify the driver's fatigue. The further research of the drive fatigue monitoring will increase the reliability and reduce uncertainty in surface mining operations.
Starting Page	1329
Ending Page	1334
File Size	1101453
Page Count	6
File Format	PDF
e-ISBN	9781467376822
DOI	10.1109/FSKD.2015.7382136
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	surface mining fatigue monitoring Machine vision Gray-scale Fatigue Feature extraction Eigenvalues and eigenfunctions haul truck safety Face Monitoring Vehicles
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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