Driver Fatigue Monitoring and Accident-Avoidance System

Abstract: The proposed driver fatigue and accident-avoidance system has aim to reduce the risk of accidents caused by the driver fatigue by integrating a monitoring software and warning alarm in vehicles. The system uses haar cascade classifiers to monitor the driver eye, mouth opening and head movement will be detected using haar cascade classifers which focus on the region of interests. Haar cascade classifier classifies the driver drowsiness level and create an alert based on that.  A machine learning algorithm classify the drivers drowsiness level as an alert once the system detects the drivers drowsiness level has exceeded a pre-defined threshold it will activates the warning system that can include visual, audito to prompt the driver to take the action. For instance, the warning system may issue an audible alert or vibrate the steering wheel to alert the driver. The proposed system can improve driver safety and lower the number of accidents caused by driver fatigue by providing a real-time warning system to alert drivers to their drowsiness level, helping them to take corrective action and avoid accidents. Furthermore, the system can be tailored to different driving conditions and integrated into various types of vehicles.

Keywords: ordering food, notifying the expiry date