Road accidents remain a significant global concern, causing injuries and fatalities primarily due to driver drowsiness, alcohol consumption, and the lack of real-time monitoring systems. This paper presents an AI-Assisted Driver Safety and Monitoring System designed to enhance road safety through intelligent detection and alert mechanisms. The proposed system integrates multiple sensors, including the MQ2 gas sensor for alcohol detection, the ADXL345 accelerometer for motion and tilt analysis, and a vibration sensor for collision detection. An ESP32-CAM module is utilized for real-time video streaming and image-based processing to detect driver drowsiness. The system employs AI-based decision-making to analyze both sensor data and visual inputs, enabling early detection of abnormal conditions. Upon detection, alerts are generated through a buzzer and mobile notifications, and live monitoring is enabled. The proposed system aims to prevent accidents proactively rather than reacting after occurrence, thereby improving overall driver safety and reducing accident risks.
Babypriya et al. (2026) studied this question.