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Driver drowsiness is a leading cause of road accidents, especially during night or long-distance driving.This project envisages the design of an IoT-based Driver Sleepiness Prevention System using face detection to detect the drowsiness of the driver in real time. The system uses a camera module connected  to a Raspberry Pi to track facial characteristics such as closure of the eyes and yawning constantly using computer vision techniques through OpenCV and dlib libraries. When the system detects drowsiness or fatigue, it triggers a buzzer and LED indicators to give a warning to the driver instantly. In addition, real time data such as the status of drownsiness, runtime of the system, and triggers of the alarm are stored in an SQLite database to monitor and analyze the data. Visual indication is also given through the use of an LCD display, so the system becomes more interactive in nature. This project uses the Agile development approach, allowing iterative improvement in planning, design, implementation, and testing processes. The system is intended to be cost-effective, timely, and reliable and is proposed to prevent accidents caused by the driver’s sleepiness and promote road safety through the use of real-time detection and alarming techniques.