Drowsy Detection in the Eye Area using the Convolutional Neural Network

Detection of a drowsy driver is an important aspect driving safety. For this reason, it necessary to have technology carry out early detection before fatigue occurs. Mainly focused on that occurs at night. Analysis can be done quickly and accurately. These conditions sent via data so they monitored analyzed in real time. The results the analysis by communication internet network. In addition, functions as warning used logging or records stored. This research does not discuss but makes prototype for detecting sleepy drivers. Prototype created using Convolutional Neural Network Algorithm. area eye testing carried with brightness level light. study, building detect signs algorithm. eye, different light levels. dataset study consists series images, which are divided into two classes, namely open eyes, closed eyes. After conducting training process Network, we get accuracy reaching 90%.