Artificial Intelligence-Based Drowsiness Detection
The physical and psychological demands of driving need the highest level of focus, making it the most dangerous employment. The spectrum of accidents related to tiredness in the modern era is complicated. Determining whether driver fatigue plays a role in accidents and the degree of physical and psychological discomfort that the drivers experienced is a difficult task without a tried-and-true method. Hence automatic drowsiness detection has become a major challenge froma research perspective. In this research, drowsiness detection has been implemented using Artificial Intelligence (AI). The method is derived by combining information from the image and data/log to provide a capable process for detecting sleepiness. This is supported by testing using many drivers with diverse environments to make the perfect method.
Authors
- Ayodeji Olalekan Salau (ORCID: https://orcid.org/0000-0002-6264-9783)
- T. Jagadesh
- J. Dhanasekar
- B. Gomathy
- Kanagasabai Balamurugan (ORCID: https://orcid.org/0000-0002-2286-1595)
- K. Satheesh Kumar (ORCID: https://orcid.org/0000-0003-3643-3644)
- M. P. (ORCID: https://orcid.org/0009-0003-2963-842X)
Institutions
- Afe Babalola University (NG)
- PSG INSTITUTE OF TECHNOLOGY AND APPLIED RESEARCH (IN)
- KPR Institute of Engineering and Technology (IN)
- Sri Eshwar College of Engineering
Publication Details
- Published
- 2024-11-26
- DOI
- https://doi.org/10.1109/nigercon62786.2024.10927319
- Citations
- 1
- Primary Topic
- Sleep and Work-Related Fatigue
- Type
- article
- Field-Weighted Citation Impact
- 0.51