Machine Learning In Driver Surveillance

Authors

  • Sharmila.P
  • Sai Kaavya Sree.M
  • T.P.Rani

Keywords:

Fatigue Detection, Alcohol intoxication, Arduino, UNO, Open Cv Application

Abstract

Road accidents are often caused by drunken driving and drowsiness. This paper detects the drowsiness of the driver. In addition the system also detects alcohol consumption by the driver. The main goal of this proposed system is to reduce the number of accidents due to driver's Drowsiness and alcohol intake. This increases the transportation safety. This system also makes use of a USB camera and Alcohol sensor (MQ-135)by which alcohol intake is detected and drowsiness of the driver is also monitored. Open CV, a machine learning software examines vision-based applications. It is the one which detects the driver's drowsiness. The idea comes with an application which helps to track the drowsiness and also alert the passenger and the owner if the driver is drunk. This will perform tasks like notifying and the customer with alarm by a mobile application. The ultimate aim of this system is to design a feasible system that decreases the fatal accidents caused by the drowsiness of the driver and can also display the percentage of alcohol consumed by the driver

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Published

2023-12-21

How to Cite

Sharmila.P, Sai Kaavya Sree.M, & T.P.Rani. (2023). Machine Learning In Driver Surveillance. Elementary Education Online, 19(3), 4506–4512. Retrieved from https://ilkogretim-online.org/index.php/pub/article/view/6584

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