This project was implemented as a way to detect the drowsiness issues of the drivers while they are driving. Even though applications to address those issues are already available with some of the vehicles from the leading automobile manufacturers in the world, their prices may exceed the affordable level of most Sri Lankans. That is where this application comes in handy and helps the local community to have a safe driving time. First, the placement of the pupil of the eye is extracted using computer vision technologies. Then those images were fed into a machine learning model to detect the movements of the pupil whether the person is drowsy or not based on the opening of the eyes. This method works even if the person is wearing a pair of spectacles. But this method won't be effective if the driver is wearing a pair of sunglasses. To address that issue, a body-tracking method was implemented. By using this method we can recognize the driver's head is failing down due to a sleepy situation. As an additional aspect, we have implemented a speed detector for the vehicle using an accelerometer. With these implementations, it can predict the drowsy moments and warn it to the driver. Even if the driver neglects those warnings and still keeps driving under sleepy conditions, a message will be passed to one of the drivers closed one asking to request not to keep driving.