Detection System of Drowsiness for Car Driver Using Image Processing Completed with Multi Level Safety

Abstract

The rate of road traffic accidents in the 38th and 39th week of 2020 has increased. Many factors influence the occurrence of accidents, one of the reasons is that the driver is sleepy. The parameters used to determine the condition of drowsiness are identifying the condition of the eyelids. With this identification, an image processing system can be utilized by applying the Haar Casecade Classifier and Circular Hough Transform methods with Find Countur using HSV parameters. The detection uses a camera with the driver's eye input, if the image detected is a drowsy eye, the system will wake up the driver by turning on a sound alarm, besides this system is equipped with an SMS gateway feature that will be sent to the driver's relatives, that the driver is sleepy. Message notification sent contains the condition and location of the rider. Based on system-wide testing, this system has a success rate of 100% against HSV1, 96% against HSV2 and HSV3, 89% against HSV4, and 88% against HSV5 on eye detection results and response time. The resulting error is because the lighting at a certain distance is not match with HSV set, the system experiences a freeze due to the buzzer sound delay that is too long and the performance of the PC is also less than optimal.