The week's pick
Reseach Article
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.
References
- Erik Coman, Zhiheng Fan, William Huynh, Daniel Marinetti: Software Requirements Specification for Pedestrian Collision Avoidance System.
- Jie Yi Wong and Phooi Yee Lau: “Real-Time Driver Alert System Using Raspberry Pi”,ECTI Transactions on Electrical Eng., Electronics and Communication, Vol.17, No.2 August 2019.
- BensuAlkan, BurakBalci, AlperenElihos and Yusuf Artan: “Driver Cell Phone Usage Violation Detection using License Plate Recognition Camera Images”, 5th International Conference on Vehicle Technology and Intelligent Transport Systems, 2019.
- Rafael A. Berri, Alexandre G. Silva, Rafael S. Parpinelli, Elaine Girardi and Rangel Arthur: “A Pattern Recognition System for Detecting Use of Mobile Phones While Driving”, Proceedings of the 9th International Conference on Computer Vision Theory and Applications, 2014.
- Younes Ed-Doughmi ,NajlaeIdrissi and Youssef Hbali : “Real-Time System for Driver Fatigue Detection Based on a Recurrent Neuronal Network”, Journal of Imaging, March 2020.
- G.N. Keshava Murthy and Zaved Ahmed Khan: “Smart Alert System for Driver Drowsiness Using Eegand Eyelid Movements”, Middle East Journal of Scientific Research · May 2013.
- Anurag De, AshimSaha, Dr. M.C Pal: “A Human Facial Expression Recognition Model based on Eigen Face Approach”, International Conference on Advanced Computing Technologies and Applications (ICACTA-2015).
- B. Mohana, C. M. Sheela Rani: “Drowsiness Detection Based on Eye Closure and Yawning Detection”, International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277-3878, Volume-8 Issue-4, November 2019.
- Rajasekar .R, Vivek Bharat Pattni , S. Vanangamudi : “Drowsy Driver Sleeping Device and Driver Alert System”, International Journal of Science and Research (IJSR),ISSN (Online): 2319-7064
- YingyuJi, Shigang Wang, Yang Lu, Jian Wei, and Yan Zhao: “Eye and mouth state detection algorithm based on contour feature extraction”, Journal of Electronic Imaging 27(5), 051205, Sep/Oct 2018.
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