Driver Drowsiness Detection Using Smartphone

Abstract

Abstract: Transition state between being awake and asleep is called drowsiness. Driver drowsiness is the major cause of traffic crashes and financial losses. This abstract presents a mobile technology using smartphones to visual indicators of driver drowsiness, allowing the possibility of making drowsiness detection systems more affordable and portable. This technology uses the front camera of a smartphone to capture images of drivers, and then uses smartphone vision algorithms to detect and track the face and eye of the drivers. Eye blinks are then detected as indicators of driver drowsiness. A simulated driving study showed that drowsy drivers differed significantly in the frequency of and eye blinks, compared to when they were attentive. The smartphone-based Driver-Drowsiness detection technology may have important applications in reducing drowsiness-related improving driving safety. This abstract describes the steps involved in designing and implementing a driver drowsiness detection system based on smartphone. It combines off the-shelf smartphone components for eye state (open vs. closed) classification. Preliminary results show that the system is reliable and tolerant to many real-world constraints. Driver drowsiness is a highly problematic issue which impairs judgment and decision making among drivers resulting in fatal motor crashes. This describes a simple drowsiness detection approach for a smartphone with Android / IOS application using Android Studio 4.4.2. & Mobile Vision API for drowsiness detection before and while driving. Quick facial analysis were performed to check drowsiness before the driver starts driving. Facial analysis was undertaken by eye blinking duration. Blinking duration is used to indicator for drowsiness. A performance accuracy of drossiness detection proved to be around 90%.