• Rushabh Dedhia
• Mayank Dand
• Aditya Akhave
• Prof.Bhakti Sonawane

The paper presents a system to detect drowsiness among E-Learners which will help the learners enhance their knowledge efficiently and correctly. A system needs to be designed that would tweak according to the drowsiness of the learners. It analyses visual features from the learner’s facial images having unique features such as Eye Blinks. The system detects for drowsiness by calculating the EAR ratio of both the eyes and also calculates the number of blinks done by the learner. If drowsy behavior is observed then appropriate steps to remove drowsiness, will be invoked by our system. The idea behind this system is to increase the level of concentration of the learner.

Drowsiness, E-Learning, Face Detection, Eye Aspect Ratio (EAR) ratio, Eye Blinks, Alert System, Timeline extraction.

"Drowsiness Detection in E-Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.360-365, April-2019, Available :http://www.jetir.org/papers/JETIR1904454.pdf

"Drowsiness Detection in E-Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp360-365, April-2019, Available at : http://www.jetir.org/papers/JETIR1904454.pdf