Real-Time Computer Vision-based System for Monitoring & Detecting Driver's Drowsiness & Fatigue
Parul Singh R , Anil Kumar Gupta
DOI Number:
face recognition; eye; consciousness detection; CNN; machine learning; OpenCV; Mobile App; Flutter; accident prevention
Usually, Driver's eye vision during driving plays a vital role in order to avoid any kind of road accidents, which is a huge number these days in the society we all live in [25]. NCBI claims that the total number of road accidents was 464,910 in India, and it causes 405 deaths and 1,290 injuries daily from 1,274 accidents in our country. So, this is the main reason that the alertness of the drivers during driving is the primary matter of concern to our society. The drivers' attentiveness is affected due to many reasons, like getting a fatigue attack during driving or Alcohol consumption, etc. If such cases exist, there is a likely chance of the vehicle to meet with an accident. So, In, order to avoid such kinds of accidents on the road, there should be some internal safety devices inbuilt in the vehicles initially. These devices should be capable of alerting and protecting the vehicle from the accident by warning about the danger of the particular vehicle to a responsible person. So, the system is developed to determine the alertness of the Driver via an eye region of the specific person using CNN Machine learning algorithm and OpenCV models and deploying the Machine Learning model in a mobile application.
Article Details
Unique Paper ID: 150928

Publication Volume & Issue: Volume 7, Issue 11

Page(s): 27 - 34
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