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Universitas Hasanuddin
Research output:Contribution to journalArticlepeer-review

Car Driver Drowsiness Recognition Android-Based System

Indrabayu

Iop Conference Series Materials Science and Engineering

Published: 2019Citations: 2

Abstract

Abstract The growth of the number of vehicles in Indonesia especially in terrestrial mode is also offset by the increasing number of accidents. One of the main causes of traffic accidents is due to drivers who driving in drowsiness. This condition leads to loss of concentration and even awareness of the driver. The drowsiness recognition system built into android smartphone platforms which owned by almost all walks of life, can help the community and government in providing direct warning especially to motorists while driving in a drowsy state. The method used is the Haar-Cascade Classifier to detect the driver's face and utilize the detectable face size ratio to create ROI in the mouth area. Then the using of the FindContour algorithm to find contours in dark areas when the mouth is open because it evaporates. The size of the contour will be compared to the Mouth ROI size for the drowsy driver's decision. System creation using Android Studio with C ++ and Java programming languages, as well as OpenCV libraries for Haar-Cascade and FindContour. Based on the test to 10 respondents, the accuracy of the system recognizes sleepiness on the driver reached 88.7% during the day.

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Haar-like featuresSciences
Android (operating system)Sciences
Computer scienceSciences
Cascading classifiersSciences
Android applicationSciences
JavaSciences
Facial recognition systemSciences
Face detectionSciences
Artificial intelligenceSciences
Computer visionSciences
Real-time computingSciences
Classifier (UML)Sciences
Pattern recognition (psychology)Sciences
Operating systemSciences
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