Home|Journals|Articles by Year|Audio Abstracts
 

Research Article

EEO. 2020; 19(3): 4506-4512


Machine Learning In Driver Surveillance

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




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.

Key words: Fatigue Detection, Alcohol intoxication, Arduino, UNO, Open Cv Application






Full-text options


Share this Article


Online Article Submission
• ejmanager.com




ejPort - eJManager.com
Refer & Earn
JournalList
About BiblioMed
License Information
Terms & Conditions
Privacy Policy
Contact Us

The articles in Bibliomed are open access articles licensed under Creative Commons Attribution 4.0 International License (CC BY), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.