Development of a Prototype Self-Controlled Car Using Computer Vision and Machine Learning Technologies

  • Unique Paper ID: 160171
  • Volume: 9
  • Issue: 12
  • PageNo: 1298-1301
  • Abstract:
  • The paper in the journal describes the creation of a prototype self-controlled car system that makes use of computer vision and machine learning. To record and analyze video data, the system makes use of a Raspberry Pi camera and the OpenCV framework. The system could find and follow things on the road using frame-by-frame analysis. The infor-mation gleaned from the detected items is then used by an Arduino Uno and a motor driver to independently control the vehicle's movement. The C++ programming language is used to implement the system, and it goes through an extensive amount of testing. Results show that, when compared to a human driver, the self-controlled automobile prototype performs with an increased level of accuracy, dependability, and activity.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{160171,
        author = {Dr. Vijit Srivastava and Rohit Kumar Pal and Himanshu Ranjan Shrivastav and Vikas Gupta},
        title = {Development of a Prototype Self-Controlled Car Using Computer Vision and Machine Learning Technologies},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {12},
        pages = {1298-1301},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=160171},
        abstract = {The paper in the journal describes the creation of a prototype self-controlled car system that makes use of computer vision and machine learning. To record and analyze video data, the system makes use of a Raspberry Pi camera and the OpenCV framework. The system could find and follow things on the road using frame-by-frame analysis. The infor-mation gleaned from the detected items is then used by an Arduino Uno and a motor driver to independently control the vehicle's movement. The C++ programming language is used to implement the system, and it goes through an extensive amount of testing. Results show that, when compared to a human driver, the self-controlled automobile prototype performs with an increased level of accuracy, dependability, and activity.},
        keywords = {Raspberry Pi, Arduino Uno, Open CV Frame work, Frame by Frame Analysis},
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 9
  • Issue: 12
  • PageNo: 1298-1301

Development of a Prototype Self-Controlled Car Using Computer Vision and Machine Learning Technologies

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