Driver Fatigue Detection Using Eye Tracking and Steering Wheel Unit System
Journal: International Journal of Research in Information Technology (IJRIT) (Vol.1, No. 4)Publication Date: 2013-04-30
Authors : B.C.Muruga kumary Vinoth James;
Page : 72-79
Keywords : Fatigue Detection; Fatigue Warning; Eye tracking system; Real time fatigue detection; Driver monitoring system;
Abstract
The main idea behind this project is to develop a nonintrusive system which can detect fatigue of the driver and issue a timely warning. Since a large number of road accidents occur due to the driver drowsiness. Hence this system will be helpful in preventing many accidents, and consequently save money and reduce personal suffering. This system will monitor the driver’s eyes using camera and by developing an algorithm we can detect symptoms of driver fatigue early enough to avoid accident. So this project will be helpful in detecting driver fatigue in advance and will gave warning output in form of sound and seat belt vibration whose frequency will vary between 100 to 300 Hz. Moreover the warning will be deactivated manually rather than automatically. So for this purpose a deactivation switch will be used to deactivate warning. Moreover if driver felt drowsy there is possibility of sudden acceleration or de acceleration hence we can judge this by Plotting a graph in time domain and when all the three input variables shows a possibility of fatigue at one moment then a Warning signal is given in form of text or red color circle. This will directly give an indication of drowsiness/fatigue which can be further used as record of driver performance.
Other Latest Articles
- Urea formaldehyde and Alkylated urea formaldehyde review paper
- Hybrid Compression Using DWT-DCT and Huffman Encoding Techniques for Biomedical Image and Video Applications?
- SECURE COMMUNICATION OF SECRET DATA USING STEGNOGRAPHY?
- IMAGE SEGMENTATION FOR TUMOR DETECTION USING FUZZY INFERENCE SYSTEM?
- THE CLOUD- CHANGING THE INDIAN HEALTHCARE SYSTEM?
Last modified: 2013-05-17 00:17:30