A RESULT ON SMART DRIVER MONITORING SYSTEM

Abstract

Road accidents caused by driver drowsiness and distraction are a serious safety issue. Existing systems mainly use basic eye detection, which is often inaccurate and cannot detect behaviors like yawning, head movement, or mobile usage. They also lack real-time monitoring and smart alert features. This project proposes a Smart Driver Monitoring System using Raspberry Pi, computer vision, and IoT. A USB webcam captures real-time video of the driver, and techniques using OpenCV and MediaPipe/Dlib analyze facial features such as eyes, mouth, and head position to detect drowsiness and distraction. When unsafe behavior is detected, the system generates alerts and can slow down or stop the vehicle for safety. It also provides live monitoring through a web based dashboard.