Drowsiness Detection System
Suriya Kumar S1, Kishor R2, J.Kalaivani3

1Kishor R*, Student, B.Tech, Computer Science Engineering course in SRM Institue of Science and Technology.
2Suriya Kumar M, Student, B.Tech, Computer Science Engineering course in SRM Institue of Science and Technology.
Dr.J.Kalaivani, Assistant Professor in the Department of Computer Science and Engineering from SRM Institute of Science and Technology.
Manuscript received on March 30, 2020. | Revised Manuscript received on April 05, 2020. | Manuscript published on April 30, 2020. | PP: 1341-1343 | Volume-9 Issue-4, April 2020. | Retrieval Number: D8489049420/2020©BEIESP | DOI: 10.35940/ijeat.D8489.049420
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Melbourne is one of the liveliest cities in the world. It has a well efficient transport system, supported by a vast network of trams. Therefore, the mental health and stress level of the tram drivers plays a crucial role in the safety of the passengers. The issue of fatigue and drowsiness in the tram drivers are mostly due to their work-time and the most common thing is that the drowsiness occurs during the work time itself. This drowsiness is a risk for everyone including those who are not travelling in the tram. The current system that is used to prevent the drivers from falling sleeping is called the deadlock system. In this system the driver keeps his foot on a pedal at all times. Whenever the driver lifts his foot from the pedal the tram stops moving. Considering the technologies that are currently implemented in the vehicles seems to be insufficient. More over the driver gets uncomfortable when he keeps his foot onto the lever for a long time during long working hours. We have used OpenCV in python to create a program which monitors the eyes of a person and ensures that they keep the eyes open. The developed algorithm uses python libraries to detect any abnormality in the time interval between blinks and the extent of openness of the driver’s eyes. When an abnormality is detected the driver receives an alarm on his phone indicating driver drowsiness.
Keywords: Micro-controllers ,Open CV, Raspberry Pi