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Driver Safety Alert System using Machine Learning
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 183 - Number 8 |
| Year of Publication: 2021 |
| Authors: Manjusha Sanke, Pranjali Savaikar, Chaitravi Parab, Mangesh Gawas, Viraj Mhalshekar |
10.5120/ijca2021921375
|
Manjusha Sanke, Pranjali Savaikar, Chaitravi Parab, Mangesh Gawas, Viraj Mhalshekar . Driver Safety Alert System using Machine Learning. International Journal of Computer Applications. 183, 8 ( Jun 2021), 27-30. DOI=10.5120/ijca2021921375
Abstract
Road accidents majorly occur due to driver fatigue and drowsiness or lack of concentration. A Driver Safety Alert System Using Machine Learning has been introduced for reducing the number of accidents. This system has been developed to support three major modules such as Drowsiness Detection, Lack of Concentration Detection and Mobile Usage Detection. It monitors driver performance by analyzing facial expressions, driver movements and his overall behavior. This system is based on application of Image Processing. Driver's live video is decomposed into frames and image processing is performed on each frame. The main image processing tool used is OpenCV. Python has been used as coding language. Drowsiness Detection has been carried out by estimating eye aspect ratio. Detection of lack of concentration has been done by checking head position. Mobile Usage Detection is based on detection of object near the ear. A driver's unusual behavior while driving that leads to road accidents has been detected and approaches are proposed to overcome these constraints which include Drowsiness Detection, Lack of Concentration Detection and Mobile Usage Detection.
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