sc 18: e7

Research Article

Review on Drowsiness Detection

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  • @ARTICLE{10.4108/eai.13-7-2018.165517,
        author={Apoorva Apoorva and D Khasim Vali and Rakesh K R},
        title={Review on Drowsiness Detection},
        journal={EAI Endorsed Transactions on Smart Cities: Online First},
        volume={},
        number={},
        publisher={EAI},
        journal_a={SC},
        year={2020},
        month={7},
        keywords={SVM, Drowsiness, ECG, EEG, EMG, Driver Fatigue Monitoring, adaboost},
        doi={10.4108/eai.13-7-2018.165517}
    }
    
  • Apoorva Apoorva
    D Khasim Vali
    Rakesh K R
    Year: 2020
    Review on Drowsiness Detection
    SC
    EAI
    DOI: 10.4108/eai.13-7-2018.165517
Apoorva Apoorva1,*, D Khasim Vali1, Rakesh K R1
  • 1: Computer Science & Engineering, Vidyavardhaka College of Engineering, Mysuru, India
*Contact email: Apoorvaradhakrishna500@gmail.com

Abstract

This paper relates the street mishaps that happen because of driver's drowsiness. Recent studies state that more disasters are caused due to doziness. Drivers can feel drowsiness due to sleep deprivation, continuously driving, drugs and medicines, and so on. Accidents caused due to doziness are more than drink driving. This paper traces many methods to detect drowsiness and alerts the driver. There are two approaches to detect drowsiness. First is physiologically based and another is behavioral-based. Also there are other approached used. Many technologies are used for detecting the weariness of the driver. It is a review paper of numerous advancements utilized by various scientists. In addition, human conduct can also be studied. Also, the discovery of drowsiness with eyes open is conceivable. In countenance detection technology, driver weariness recognition is one of the major possible businesses uses. Here how drivers can be alerted using different methods is discussed.