IoT based Drowsiness Detection with Automated Vehicle Control

A major danger to road safety, drowsy driving is a prominent cause of accidents globally. Drowsy driving is thought to be the cause of 100,000 crashes in India each year, accounting for 1,550 fatalities and 40,000 injuries. We suggest a comprehensive system that blends sound, seat vibration, and a brake mechanism to identify and prevent cases of drowsy driving in order to solve this problem. To determine the driver's level of wakefulness, the system uses sophisticated monitoring techniques, such as analysis of the driver's eye movements and head posture. Early indicators of drowsiness are recognized by the system, which then activates numerous alerts, including an alarm, seat vibration, and braking, to quickly warn the driver and prevent accidents. We carried out experiments using carefully chosen datasets from Kaggle, which cover a range of driving conditions, to assess the efficacy of the proposed method. We also cite a study by the National Highway Traffic Safety Administration, which found that using a similar sleepy driving detection technology significantly reduced the number of drivers falling asleep at the wheel by 45%.