Download Project Document/Synopsis
Driver drowsiness and fatigue are significant causes of road accidents. Every year, they increase the number of deaths and fatalities worldwide. A module for an advanced driver assistance system is presented in this system to reduce the number of accidents caused by driver fatigue and thus increase transportation safety; this system deals with automatic driver drowsiness detection based on visual information and Artificial Intelligence.
The proposed OpenCV algorithms effectively find and help to normalize human faces while causing the majority of accidents related to vehicle crashes. The algorithm begins by detecting heads on color images using color and structure deviations in the human face and background. Several faces and body gestures, including tiredness in the eyes and yawning, are regarded as signs of drowsiness and fatigue in drivers. These characteristics indicate that the driver’s condition is poor.
One of the most common causes of accidents is driver drowsiness and fatigue. Each year, the number of people killed in such accidents rises around the world. In Driver Drowsiness Detection System, to log in to the system the admin can log in with a username and password. The admin can view the list of all the users and also can view their logs.
The user has to register their account and log in using a username and password. Using Open CV, the system will detect eye closure or yawning actions in real-time. If it finds any, it will draw a red rectangle and add a log to the table. The user can view their logs with details in My Logs.
- It can quickly detect drowsiness.
- The system can distinguish between normal eye blinks and drowsy eye blinks.
- It can operate in low-light conditions and while the driver is wearing spectacles.