car safety alert and accident detection system.

Road accidents caused by driver drowsiness and delayed emergency response are major concerns in modern transportation systems.Fatigue reduces driver alertness, slows reaction time, and increases the risk of severe collisions.To address this issue, the proposed Car Safety Alert and Drowsiness/Accident Detection System aims to develop a real-time monitoring and alert mechanism that enhances vehicle and driver safety.The system utilizes a combination of camera-based facial monitoring and sensor technologies to detect early signs of driver fatigue such as prolonged eye closure, yawning, and head movement.Artificial Intelligence (AI) and image processing techniques are applied to analyze facial features and determine the driver's alertness level.If drowsiness is detected, the system immediately generates visual, auditory, or vibration-based alerts to warn the driver and prevent potential accidents.In addition to drowsiness detection, the system incorporates accelerometer and gyroscope sensors to detect sudden impacts or abnormal vehicle movements.In case of an accident, the system automatically sends an emergency alert along with GPS location details to predefined contacts or emergency services, ensuring faster medical assistance and response.This project integrates hardware components such as Raspberry Pi/ESP32, camera module, sensors, GPS, and GSM modules with software tools like OpenCV and AI-based algorithms.The proposed system is non-intrusive, cost-effective, and adaptable to different vehicle types.By combining driver monitoring, accident detection, and emergency communication, the system contributes to intelligent transportation systems and aims to reduce road accidents, save lives, and improve overall road safety.