International Journal of Computer Techniques Volume 12 Issue 3 | Driver Drowsiness System with Early Detection
Driver Drowsiness System with Early Detection
International Journal of Computer Techniques – Volume 12 Issue 3, May – June 2025
Abstract
Drowsiness while driving remains a leading cause of road accidents. This paper reviews and proposes a **driver drowsiness detection system** utilizing **physiological signal analysis** and **real-time behavioral monitoring**, including facial feature tracking and sensor fusion. The integration of **non-intrusive electrodes** and improved sensing materials advances early intervention strategies for **driver fatigue detection**.
Keywords
Drowsiness detection, Driver Monitoring, Sleepiness detection, Eye tracking, Real-Time Detection, Driver Assistance System.
Conclusion
This paper underscores the role of **physiological sensing in detecting drowsiness** and the potential of **silver/silver chloride and titanium electrodes** in improving usability. To overcome inter-individual variability and standardization issues, future research must emphasize **cross-border protocols and real-world validation** to commercialize intelligent driver safety systems.
References
- Saini, V., & Saini, R. (2014). Driver Drowsiness Detection System and Techniques. IJCSIT, 5(3), 4245–4249.
- Ramzan, M. et al. (2019). A Survey on Drowsiness Detection Techniques. IEEE Access, 7, 61904–61919.
- Deng, W., & Wu, R. (2019). Real-Time Driver-Drowsiness Detection Using Facial Features. IEEE Access, 7, 118727–118738.
Post Comment