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Research Paper | Computer Science & Engineering | India | Volume 11 Issue 11, November 2022 | Rating: 4.8 / 10

Driver Safety Prediction System

Kalyan Raja K | Sahiti Adepu

Abstract: Safety is one of the most essential factors that one should look at while driving, that includes Driver's state of mind and ensuring that the Driver follows speed limits or ant further possible Dangers. Most of the accidents on the road can be avoided if early alerts can be given to warn the Driver about his exhaustion level. In this paper, a real - time driver safety prediction system is presented Which aims to detect driver's mental state to drive and to detect and recognize traffic signs and vehicles on the roads. In the proposed system, Detection, classification and recognition are performed using Convolutional Neural Networks (CNN) and OpenCV to identify the content of the traffic signs found and to detect the vehicles. And the driver's drowsiness is detected by extracting an eye feature called the eye aspect ratio. The applications of this real time system include tracking objects, video surveillance, pedestrian detection, people counting, self - driving cars, face detection and traffic sign recognition.

Keywords: OpenCV, Convolutional Neural Network, Eye Aspect Ratio

Edition: Volume 11 Issue 11, November 2022,

Pages: 1202 - 1204