Customizable Thresholds: The drowsiness detection thresholds are customizable, allowing for adaptation to individual driver preferences and varying road conditions. Efficient Performance: Our system ...

This project implements a drowsiness detection system using a Raspberry Pi, Pi Camera Module, and OpenCV. The system uses facial landmarks to detect if the user's eyes are closed for a prolonged ...

CAN Bus Module: Facilitates vehicle integration, allowing data sharing with other automotive systems. Alert Mechanisms: Buzzer, LEDs, and speakers provide real-time feedback based on the eye status.

In this project, we have thought of building a Driver Drowsiness Detection and Alerting System for Drivers using Arduino Nano, Eye blink Sensor, and RF Transceiver module.

We designed a smart Driver Drowsiness Detection System using Raspberry Pi and Python that will keep track of a driver's eye movement.

The aim of this project is to detect the drowsiness level of the driver in the vehicle, to warn the driver and to prevent possible accidents. Percentage Eye Closure (PERCLOS) and Convolutional Neural ...

The intention of this project is to create a prototype drowsiness detection system. This system works by means of monitoring the driver's eyes and sounding an alarm if he or she will become drowsy.