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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM12773

DRIVER ALERT AND MONITORING SYSTEM

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM12773

Volume:

6 |

5 |

May 2022

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM12773

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PKD

PROF. K.B DUBEY

AA

AKASH AWASTHI

APS

AKHAND PRATAP SINGH

AC

AKSHAY CHAUDHARY

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Abstract

Here ,we have proposed a system which detects the driver’s fatigue status by analysing the blinking and duration of eye closure and position of eye retina using video data without equipping their bodies with devices. When a driver is in a very state of ,the action of eye like frequency of blinking is different from those in normal condition. The aim of this proposed idea is to cut back the possibilities of accidents that will occur thanks to driver’s fatigue condition . To spot lethargy various factors are utilized like eye retina identification and facial element acknowledgement has been utilized. Here right away, propose a method for identifying driver sluggishness utilizing eye retina location of the driving force. This framework is used for ongoing issue which catches picture consistently and measures the condition of the attention as indicated by the predetermined calculation and provides cautioning whenever required. For tiredness discovery of the drivers the per conclusion estimation of eye is believed of. So when the conclusion of eye surpasses a particular sum then we effectively distinguish driver to be tired. For actualizing this framework we utilize a pair of libraries of OpenCv . The framework can reach 40 edges for every second for eye following, and so the traditional right rate for eye area and following can accomplish 99.4% on five test recordings. the correct rate for weariness identification is 100%, yet the traditional exactness rate for weakness recognition is 90%.

KEYWORDS

Driver fatigue OpenCV eye tracking

Cite This Article

PROF. K.B DUBEY, AKASH AWASTHI, AKHAND PRATAP SINGH, AKSHAY CHAUDHARY, "DRIVER ALERT AND MONITORING SYSTEM," International Journal of Scientific Research in Engineering and Management, vol. 6, no. 5, May 2022. https://doi.org/10.55041/IJSREM12773

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Publication Date

3/4/2022

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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