Drowsiness detection system is a visual based system which will detect the eyes of the driver and classify it as awake or asleep in real time. The targeted customers predominately consist of commercial land transport companies, and is also available to general public. Since long distance transportations exhausts a lot of drivers which can lead to driver unexpectedly falling asleep can cause fatal accidents. In order to prevent this the Drowsiness detection system will immediately detect the state of the driver, if the driver falls asleep the system will immediately raise an alarm to alert the driver. The system’s interface will be through a web app which will display the camera feed and the status of the driver in real time. The system uses HOG [Histogram Oriented Gradient] for feature extraction of facial points recognition. Though there will some delay between the real time feed and the processed feed Our project aims in making it as fast as possible with minimum compute resources. This project is done using openCV, python, Dlib, boot.python.