AI-ENABLED REAL-TIME DRIVER MONITORING AND SAFETY SYSTEM USING ESP32

Abstract

Road accidents caused by driver fatigue, distraction, and unsafe driving behavior have become a major concern worldwide. To address this issue, this paper presents an AI-enabled real-time driver monitoring and safety system using ESP32 designed to enhance driver awareness and reduce accident risks. The proposed system utilizes an ESP32 microcontroller integrated with an ESP32-CAM module to capture real-time video of the driver and analyze facial features using Artificial Intelligence and computer vision techniques.The system continuously monitors driver conditions such as eye closure, yawning, and head movement to detect signs of drowsiness or distraction. When abnormal driver behavior is identified, the system immediately triggers alerts through a buzzer or warning notification, thereby helping the driver regain attention. Additionally, sensor modules can be incorporated to monitor environmental parameters or vehicle conditions, further improving system reliability and safety. The ESP32 platform provides a low-cost, compact, and energy-efficient solution suitable for real-time embedded applications in vehicles. By combining AI-based image processing with IoT-enabled microcontroller technology, the proposed system offers an effective approach for preventing accidents and improving road safety. The developed model demonstrates the feasibility of implementing intelligent driver monitoring systems in modern smart transportation environments.