INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
UTILIZING MACHINE LEARNING FOR THE DETECTION AND TRACKING OF VEHICLES
Authors Name:
Chaganti Vinod
, Chekuri Nagendra Varma Raju , Daggula Rakshitha , Dalavai Kullay , Mr. S. Ramdoos
Unique Id:
IJSDR2404100
Published In:
Volume 9 Issue 4, April-2024
Abstract:
This project introduces an innovative application of machine learning for traffic analysis, where users can upload traffic videos for automated vehicle speed detection and vehicle count estimation. Leveraging state-of-the-art machine learning models and computer vision techniques, our system aims to provide a user-friendly solution for monitoring traffic dynamics in real-time. The system begins by accepting user-uploaded traffic videos, which undergo preprocessing to ensure consistency and optimal performance. Through the integration of advanced object detection algorithms, vehicles within the video frames are identified and tracked across successive frames to calculate their speeds accurately. Additionally, the system employs robust vehicle counting algorithms capable of handling varying traffic densities and occlusions. By analyzing the detected vehicles in the video stream, the system provides users with an estimation of the total vehicle count, aiding in traffic flow analysis and infrastructure planning.
Keywords:
Traffic analysis, Machine learning, YOLO (You Only Look Once), Vehicle speed estimation, Vehicle count estimation, Real-time processing, Traffic congestion, Road safety, Traffic management amounts of video data, extracting valuable insights such as vehicle speeds
Cite Article:
"UTILIZING MACHINE LEARNING FOR THE DETECTION AND TRACKING OF VEHICLES", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.9, Issue 4, page no.722 - 727, April-2024, Available :http://www.ijsdr.org/papers/IJSDR2404100.pdf
Downloads:
000338171
Publication Details:
Published Paper ID: IJSDR2404100
Registration ID:210825
Published In: Volume 9 Issue 4, April-2024
DOI (Digital Object Identifier):
Page No: 722 - 727
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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