STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Operating Systems Development & Trends

Android-Based Real-Time Driver Drowsiness Detection and Alert System

  1. Hajara Musa
  2. Muhammad Abubakar Sadiq
  3. Ali Ahmad Aminu
  4. Bitrus Gideon Mohzo
  5. Abubakar Adamu

Abstract

Traffic accidents cause millions of people to lose their lives every year. Statistics assert that most fatal accidents are due to driver drowsiness. So the rate of fatality due to accidents caused by drivers falling asleep is high. There have been various researches and developments on driver drowsiness and fatigue detection systems by industries and academic researchers over the years. However, the solutions produced are usually found on luxurious vehicles and are computationally expensive to be connected to embedded devices or mobile devices with operating systems such as Android. This paper proposes to a cost-effective and efficient driver drowsiness detection system that can be installed on mobile devices or smart embedded devices using state-of-the-art technological advancements in the area of machine learning and artificial intelligence to prevent or reduce accidents that occur due to drowsy driving.

Keywords

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