Detecting driver drowsiness based on sensors-a review
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Multidisciplinary Digital Publishing Institute (MDPI)
2014
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my.unimap-333202014-05-06T05:11:48Z Detecting driver drowsiness based on sensors-a review Sahayadhas, Arun Sundaraj, Kenneth, Prof. Dr. Murugappan, M arurun@gmail.com kenneth@unimap.edu.my murugappan@unimap.edu.my Driver drowsiness detection Transportation safety Hybrid measures Driver fatigue Artificial intelligence techniques Sensor fusion Link to publisher's homepage at http://www.mdpi.com/ In recent years, driver drowsiness has been one of the major causes of road accidents and can lead to severe physical injuries, deaths and significant economic losses. Statistics indicate the need of a reliable driver drowsiness detection system which could alert the driver before a mishap happens. Researchers have attempted to determine driver drowsiness using the following measures: (1) vehicle-based measures; (2) behavioral measures and (3) physiological measures. A detailed review on these measures will provide insight on the present systems, issues associated with them and the enhancements that need to be done to make a robust system. In this paper, we review these three measures as to the sensors used and discuss the advantages and limitations of each. The various ways through which drowsiness has been experimentally manipulated is also discussed. We conclude that by designing a hybrid drowsiness detection system that combines non-intusive physiological measures with other measures one would accurately determine the drowsiness level of a driver. A number of road accidents might then be avoided if an alert is sent to a driver that is deemed drowsy. 2014-04-01T07:05:58Z 2014-04-01T07:05:58Z 2012 Article Sensors 2012, vol. 12(12), pages 16937-16953 1424-8220 http://dspace.unimap.edu.my:80/dspace/handle/123456789/33320 http://www.mdpi.com/1424-8220/12/12/16937 http://dx.doi.org/10.3390/s121216937 en Multidisciplinary Digital Publishing Institute (MDPI) |
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Universiti Malaysia Perlis |
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Malaysia |
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Universiti Malaysia Perlis |
| content_source |
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http://dspace.unimap.edu.my/ |
| language |
English |
| topic |
Driver drowsiness detection Transportation safety Hybrid measures Driver fatigue Artificial intelligence techniques Sensor fusion |
| spellingShingle |
Driver drowsiness detection Transportation safety Hybrid measures Driver fatigue Artificial intelligence techniques Sensor fusion Sahayadhas, Arun Sundaraj, Kenneth, Prof. Dr. Murugappan, M Detecting driver drowsiness based on sensors-a review |
| description |
Link to publisher's homepage at http://www.mdpi.com/ |
| author2 |
arurun@gmail.com |
| author_facet |
arurun@gmail.com Sahayadhas, Arun Sundaraj, Kenneth, Prof. Dr. Murugappan, M |
| format |
Article |
| author |
Sahayadhas, Arun Sundaraj, Kenneth, Prof. Dr. Murugappan, M |
| author_sort |
Sahayadhas, Arun |
| title |
Detecting driver drowsiness based on sensors-a review |
| title_short |
Detecting driver drowsiness based on sensors-a review |
| title_full |
Detecting driver drowsiness based on sensors-a review |
| title_fullStr |
Detecting driver drowsiness based on sensors-a review |
| title_full_unstemmed |
Detecting driver drowsiness based on sensors-a review |
| title_sort |
detecting driver drowsiness based on sensors-a review |
| publisher |
Multidisciplinary Digital Publishing Institute (MDPI) |
| publishDate |
2014 |
| url |
http://dspace.unimap.edu.my:80/dspace/handle/123456789/33320 |
| _version_ |
1643797136349855744 |
| score |
13.222552 |