Real-Time Driver Alert System Using Raspberry Pi

Jie Yi Wong, Phooi Yee Lau

Abstract


Malaysia has been ranked as one of the country in the world with deadliest road. Based on the statistic, there are around 7000 to 8000 people in the country died on the road among the population of 31 million Malaysians every year. In general, Advances Driver Assistance System (ADAS) aims to improve not only the driving experience but also consider the overall passenger safety. In recent years, driver drowsiness has been one of the major causes of road accidents, which can lead to severe physical injuries, deaths and significant economic losses. In this paper, a vison-based real-time driver alert system aimed mainly to monitor the driver’s drowsiness level and distraction level is proposed. This alert system could reduce the fatalities of car accidents by detecting driver’s face, detecting eyes region using facial landmark and calculating the rate of eyes closure in order to monitor the drowsiness level of the driver. Later, the system is embedded into the Raspberry Pi, with a Raspberry Pi camera and a speaker buzzer, and is used to alert the driver in real-time, by providing a beeping sound. Experimental results show that proposed system is practical and low-cost which could (1) embed the drowsiness detection module, and (2) provide alert notification to the driver when the driver is inattentive, using a medium loud beeping sound, in real-time.


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References


Global Status Report On Road Safety. (2015). [online] Gevena: The World Health Organization. Available at: http://www.who.int/violence_injury_prevention/road_safety_status/2015/GSRRS2015_Summary_EN_final2.pdf [Accessed 26 Nov. 2017].

Jansen, B. (2017). Report: Drowsy driving is a sleeper threat in crashes. [online] USA TODAY. Available at: https://www.usatoday.com/story/news/nation/2016/08/07/report-drowsy-driving-sleeper-threat-crashes/88300112/ [Accessed 26 Nov. 2017].

Musale, T. and Pansambal, B. (2016). Real Time Driver Drowsiness Detection system using Image processing. Research in Engineering Application & Management (IJREAM), 02(08).


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