AN ANALYTICAL AND EFFECTIVE SOLUTION TO SOCIAL PROBLEMS THROUGH ARTIFICIAL INTELLIGENCE AND TECHNOLOGIES
This article analyzes technological and scientific approaches developed to reduce road traffic accidents caused by fatigue and drowsiness among transportation operators. It covers devices based on EEG and ECG signals used to monitor drivers' attention levels, microsleep detection algorithms powered by artificial intelligence, and risk prediction methods through statistical and mathematical modeling. Based on the research results, the use of the Eye Aspect Ratio (EAR) — an index that determines the state of eye openness — is proposed as an effective solution to enhance driver alertness and reduce accident rates.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-04-25
- DOI
- https://doi.org/10.5281/zenodo.15284717
- Primary Topic
- Sleep and Work-Related Fatigue
- Type
- article
- Field-Weighted Citation Impact
- 0.00