Machine Learning Based Driver Distraction Detection


  • S. Mohan Kumar Dean and Professor, Department of Computer Science and Engineering, Nagarjuna College of Engineering & Technology, Bangalore, Karnataka, India.
  • T. Kumanan Professor, Computer Science and Engineering, Dr. M.G.R. Educational and Research Institute, Chennai, Tamil Nadu, India


Distraction is nothing more than a lack of consideration for healthy driving practices. Intended or accidental deviation of the focus from the driver side may be attention. The diversion by drivers can be identified as anything required to detect data for safe and secure control of the car by incidents, people inside or outside the vehicle that may be forced or appear to force the drivers to move their focus from a fundamental driving activity into another spot. The main cause of distraction for drivers is their competitiveness for events which reduce driving performance in road crashes. The solution to the above issue defined in this paper will help minimize the accident by road that is one of the major reasons for the driver's distraction. The driver also assesses whether or not the driver deliberately detects yawning, facial recognition, eye detection and finds whether or not the driver drank an alcoholic. The sensor can be used for alcohol detection. It is planned to ensure the safety of car passengers. For real-time object tracking, the hair cascade algorithm may be used.


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Center for disease control and prevention.

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