Voice-Enabled Traffic Sign Recognition and Alert System using ML : A Review

Authors

  • Prof. V. S. Nalawade  Department of Computer Engineering, SBPCOE, Indapur, Pune, Maharashtra, India
  • Tanuja G. Jagtap  Department of Computer Engineering, SBPCOE, Indapur, Pune, Maharashtra, India
  • Priyanka B. Jamdar  Department of Computer Engineering, SBPCOE, Indapur, Pune, Maharashtra, India
  • Shubham I. Kadam  Department of Computer Engineering, SBPCOE, Indapur, Pune, Maharashtra, India
  • Rutuja S. Kenjale  Department of Computer Engineering, SBPCOE, Indapur, Pune, Maharashtra, India

Keywords:

Convolutional Neural Network, GTSRB Dataset, Traffic Signs, voice alerts.

Abstract

The "Voice-Enabled Traffic Sign Recognition and Alert System" is an innovative application of machine learning and computer vision technologies aimed at enhancing road safety and driver awareness. In today's fast-paced world, the ability to promptly recognize and respond to traffic signs is crucial to prevent accidents and promote responsible driving. This project introduces a novel system that employs a camera installed in a vehicle to capture real-time images of the road. These images are then processed using advanced computer vision algorithms to detect and classify traffic signs. Furthermore, the system utilizes natural language processing to provide voice alerts to the driver, ensuring that they are informed about important traffic signs, speed limits, and other crucial information without taking their eyes off the road.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-10-30

Issue

Volume 9, Issue 10, September-October-2023

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Prof. V. S. Nalawade, Tanuja G. Jagtap, Priyanka B. Jamdar, Shubham I. Kadam, Rutuja S. Kenjale, " Voice-Enabled Traffic Sign Recognition and Alert System using ML : A Review" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 10, pp.211-216, September-October-2023.