Driver Distraction System using Face, Eye, Yawn And Pulse Detection
R.Naresh1, Dhruvil Patel2, Aaryan Krishna3
1R.Naresh*, Associate Professor, Department of Computer Science and Engineering at SRM Institute of Science and Technology, Kattankulathur.
2Dhruvil Patel, Pursuing Bachelor of Technology, Computer Science and Engineering at SRM Institute of Science and Technology, Kattankulathur.
3Aaryan Krishna, Pursuing Bachelor of Technology, Computer Science and Engineering at SRM Institute of Science and Technology, Kattankulathur.
Manuscript received on April 20, 2020. | Revised Manuscript received on April 30, 2020. | Manuscript published on May 10, 2020. | PP: 263-267 | Volume-9 Issue-7, May 2020. | Retrieval Number: F4736049620/2020©BEIESP | DOI: 10.35940/ijitee.F4736.059720
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Secure car driving is an important entity for safety and is the first priority for any automobile driver and is the main reason for designing a system which captures the state of the drivers eyes and his/her facial variations combined with pulse fluctuations, altogether they gives us parameters to decide whether the driver should be notified or not. Eye detection – more precisely it analyses the eyes and check if they’re closed or open using camera module the amount of frames during which eyes are closed is decided. When this number of frames is above a selected threshold, the drive will get a alert. Camera module periodically takes snaps so as to confirm safety. A true time system which captures the state of the driver which will benefit many of us round the globe.
Keywords: Camera Module, drowsiness, Viola-Jones Human Machine Interface, Face Detection, Eye detection, Yawn detection, Distraction Detection, Alert Sound, Hear Cascade , Arduino , pulse sensor.
Scope of the Article: Machine Learning