International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 05 | May 2022
p-ISSN: 2395-0072
www.irjet.net
Driver Alert Control & Accident Prevention System Keshav Mittal1, Manu2, Anmol Tomar3 1,2,3INFORMATION
TECHNOLOGY DEPARTMENT, MIET MEERUT ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - It is big problem for drivers to make aware of real-time needs in the automated system. At present, there are still
unresolved issues such as the driver's head tilts and the image size of the eyes large enough. This fact-finding paper outlines an effective way to solve these driver's sleep detection problems in a system on the basis of the image processing techniques. This technique violates common sleep deprivation methods making it like real, using face and optics recognition to establish the driver's eye position; then using a tracking system by keeping track of optics. Finally, after that we can see the driver's drowsiness. Test results show that it complies with analysis.
1. INTRODUCTION Various many researches have been done to measure driver drowsiness. Research on the image analysis and pattern - visual technology has become widely accepted. While identifying a sleepy condition in a driver we should do the following: a. Face identification & face tracking. b. optic area & optics tracking. c. Identifying the optics condition . d. Driver sleep detection (see Fig.1) It is efficient way to get the driver sleepy but when it comes to using the automated system the concept has changed. In getting sleepy, the important problem is accuracy and immediate detection. The purpose of research paper is to increase the prototype of the sleep alert warning system. Our complete recognition and awareness can be based on device design to accurately reflect the open and closed world of the driver in real time. through continuous eye tracking, it may be seen that symptoms of inflammatory fatigue may appear early to distance themselves from spontaneous. This discovery can be made using a series of eye pictures and movements of the face and head. Observing eye movements and edges for detection may be used. Hitting tools when drivers fall asleep and giving them warning warnings about threats, or even controlling vehicle movements, have been a challenge to good education and development.
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