Driver Drowsiness Detection using Raspberry Pi

Preventing road accidents caused by drowsy drivers is crucial for road safety. To achieve this, drowsiness detection while driving is necessary. The detection process involves monitoring the driver's eye movements, head position, and facial expressions. The latest advancements in computer vision and machine learning enable the detection of drowsiness signs in real time. Our goal is to create a drowsiness detection system that alerts drivers before it's too late for an accident to occur. This system can be incorporated into vehicles, personal devices, providing a successful solution for reducing the threat of drowsy driving. In conclusion, the proposed driver drowsiness detection system using Raspberry Pi provides a reliable and cost-effective solution for enhancing road safety. By detecting and alerting the driver to their drowsiness, the system can prevent accidents caused by drowsy driving, reducing the risk of injuries and fatalities on the road.

Autorentext

Tejaswi Potluri est un bon chercheur en vision par ordinateur. Elle a publié 10 articles dans des revues réputées telles que Springer, Elsevier, Scopus, Web of Science. Elle a donné de nombreuses sessions dans des universités réputées sur la vision par ordinateur, le traitement vidéo et les pratiques d'enseignement et d'apprentissage.