Road safety is essential. Some reasons for road safety breaches include
keeping the vehicle in neutral mode, using a manual braking system, driver drowsiness,
and uncontrollable vehicle speed. Any technological development that enhances road
safety is utterly essential. This project synergizes road safety and vehicle security
through a unified solution. By combining a Drowsiness Detection System with an
Arduino Uno, a blink sensor, a CNN, and OpenCV, the system monitors driver
alertness by analyzing eye blink patterns. Simultaneously, a Neutral Gear Safety
Shutdown, utilizing OpenCV and a CNN, prevents unintended vehicle movements in
neutral gear, thereby enhancing overall safety. This paper demonstrates a holistic
approach, leveraging cost-effective components and advanced technology, to ensure
adaptability and effectiveness across diverse vehicles, addressing immediate safety
concerns and preventing potential accidents.
Keywords: Convolutional neural network, Gear recognition, Matchmaking algorithm, OpenCV.
