There are 1.24 million traffic accidents every year with 2.4% caused by drowsy drivers. In that context, several methods for drowsiness detection have been developed. Nevertheless, despite the huge amount of researches, the several devices on markets, and car systems; it is not clear which method is the most appropriate, what sensors are the most useful and least intrusive. This study, shows a systematic literature review of the most recently and relevant methods.
|Number of pages||10|
|Journal||CEUR Workshop Proceedings|
|State||Published - 2020|
|Event||6th Iberoamerican Conference of Computer Human Interaction, HCI 2020 - Arequipa, Peru|
Duration: 16 Sep 2020 → 18 Sep 2020
Bibliographical noteFunding Information:
? Supported by INNOVATE-PER?, Universidad la Salle and X-traplus.
Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
- Drowsiness Detection
- Fatigue Detection