Abstract:

The project made in the field of computer engineering to develop a system for driver drowsiness detection to prevent accidents from happening because of driver fatigue and sleepiness and also include features. The report proposed the results and solutions on the limited implementation of the various techniques that are introduced in the project. Whereas the implementation of the project give the real world idea of how the system works and what changes can be done in order to improve the utility of the overall system. Furthermore, in order to help further optimization in the mentioned field to achieve the utility at a better efficiency for a safer road(Drowsiness detection system along with :Hump detection, Speed limit ,SMS alert(along with geolocation of vehicle),Pedestrian detection.

Keywords:
Driver drowsiness;
eye detection,
Hump detection,
Speed limit,
SMS alert(along with geolocation of vehicle),
Pedestrian detection ,
Machine learning,
Open-cv

Objective:
Using machine learning algorithm it shows result for detection of drowsiness ,eye detection, pedestrian detection, speed limit, SMs alert. And the system uses open-cv for face detection .and the system uses machine learning algorithm that is convolutional neural network to classify facial features to determine if the driver is exhibiting signs of drowsiness. and pedestrian detection, speed limit, SMS alert.