• Dr.S.Viveka, Jeevitha S, Keerthana B, Lakshmi L, Monika M


CNN, Drowsiness, Face detection, Segmentation


Drowsy driving is a prevalent and a serious public health issue that deserves attention. Recent studies estimate that around 20% of car crashes have been caused by drowsy drivers. A person when he or she does not have a proper rest especially a driver, tends to fall asleep causing a traffic accident. Nowadays, one of the main goals in the development of new advanced driver assistance systems is trustworthy drowsiness detection. It is why the present project wants to realize a system that can detect the drowsiness of the driver, in order to reduce traffic accidents. For that system, it will take the processing of images through a camera which will focus on the driver. In that, it is going to analyze the changes that happen in the face and then will be processed through a program in order to detect drowsiness to send an alert to the driver. These methods are used in a wide range of applications, the image classification being one of the fields in which these are employed with success. After the face is detected using CNN, the region containing the eyes and mouth has to be separated. An image which taken inside a vehicle includes the driver’s face.




How to Cite

Dr.S.Viveka, Jeevitha S, Keerthana B, Lakshmi L, Monika M. (2022). DRIVER DROWSINESS DETECTION USING CNN. International Journal of Advanced Engineering Science and Information Technology, 10(6), 61–68. Retrieved from