Affiliation:
1. Christu Jyothi Institute of Technology & Science, Jangaon, Telangana, India
Abstract
The Driver Drowsiness Detection System is a sophisticated safety solution designed to mitigate the risks associated with driver fatigue and drowsiness while operating a vehicle. This project aims to develop an intelligent system capable of monitoring driver behavior and physiological signals in real-time, detecting signs of drowsiness, and issuing timely alerts to prevent accidents.
The system utilizes a combination of hardware sensors, including cameras, infrared sensors, EEG sensors, and heart rate monitors, to capture and analyze various indicators of driver drowsiness, such as facial expressions, eye movements, head gestures, body temperature, brainwave patterns, and heart rate variability.
Reference11 articles.
1. W.-B. Horng, C.-Y. Chen, Y. Chang and C.-H. Fan, "Driver fatigue detection based on eye tracking and dynamic template matching", Proc. IEEE Int. Conf. Netw. Sens. Control, vol. 1, pp. 7-12, Mar. 2004.
2. This paper, authored by W.-B. Horng, C.-Y. Chen, Y. Chang, and C.-H. Fan, presents a method for detecting driver fatigue using eye tracking and dynamic template matching. The authors proposed a system that monitors a driver's eye movements in real-time and compares them to predefined templates associated with fatigue indicators. By analyzing the deviation of eye movements from these templates, the system can infer the driver's level of fatigue.
3. M. Saradadevi and P. Bajaj, "Driver fatigue detection using mouth and yawning analysis", Int. J. Comput. Sci. Netw. Secur., vol. 8, pp. 183-188, Jun. 2008.
4. In this paper authored by M. Saradadevi and P. Bajaj, the authors propose a method for detecting driver fatigue by analyzing mouth movements and yawning patterns. The system monitors the driver's facial features, particularly focusing on mouth movements and instances of yawning, which are indicative of drowsiness or fatigue. By analyzing these facial cues, the system aims to accurately identify when a driver is becoming fatigued and alert them to take necessary breaks or rest. The research was published in the International Journal of Computer Science and Network Security in June 2008.
5. M. A. Assari and M. Rahmati, "Driver drowsiness detection using face expression recognition", Proc. IEEE Int. Conf. Signal Image Process. Appl. (ICSIPA), pp. 337-341, Nov. 2011.