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Editorial Process - Peer Reviewed

Smart Traffic Vehicle monitoring and Signal Allocation using YOLO

    Authors

    • Ramkumar P 1
    • Sandeep P 1
    • Suganyadevi S 2

    1 Master of Computer Science, Sri Krishna Arts and Science College, Coimbatore

    2 Assistant Professor, Department of Computer Science, Sri Krishna Arts and Science College, Coimbatore

,

Document Type : Research Article

10.47392/irjash.2023.S028
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Abstract

The traffic control system in India is now inflexible to the continuously increas- ing number of vehicles on the road. Fixed traffic light timing systems are a poor method of controlling traffic flow. Traffic lights are the fundamental component in traffic flow control through predetermined waiting and going times. A smart approach to adjust traffic light timing based on the number of vehicles in each lane is part of an intelligent traffic system. The average journey and waiting time for passengers will be reduced while the safety, dependability, and speed of the traffic flow is all increased. Designing an effective automated Traffic Time Saving system is the goal.  The system is used for traffic management.  In this proposed application first takes a picture of the car. Images are first converted from RGB to grayscale, then the vehicle picture is retrieved using image segmentation. After applying segmentation to the ready image, neural networks determine whether or not individual section contains a car. The suc- cessful parts will be counted by a counter. Lastly, a Graphical User Interface (GUI) will show the appropriate times for each light color.

Keywords

  • Traffic Control system
  • Vehicle monitoring
  • YOLO object classification
  • Counting
  • Image segmentation
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International Research Journal on Advanced Science Hub
Volume 5, Issue 05S - Issue Serial Number 5
May 2023
Page 213-218
Files
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  • PDF 2.49 M
History
  • Receive Date: 28 February 2023
  • Revise Date: 12 March 2023
  • Accept Date: 16 March 2023
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  • Article View: 202
  • PDF Download: 77

APA

P, R. , P, S. and S, S. (2023). Smart Traffic Vehicle monitoring and Signal Allocation using YOLO. International Research Journal on Advanced Science Hub, 5(Issue 05S), 213-218. doi: 10.47392/irjash.2023.S028

MLA

P, R. , , P, S. , and S, S. . "Smart Traffic Vehicle monitoring and Signal Allocation using YOLO", International Research Journal on Advanced Science Hub, 5, Issue 05S, 2023, 213-218. doi: 10.47392/irjash.2023.S028

HARVARD

P, R., P, S., S, S. (2023). 'Smart Traffic Vehicle monitoring and Signal Allocation using YOLO', International Research Journal on Advanced Science Hub, 5(Issue 05S), pp. 213-218. doi: 10.47392/irjash.2023.S028

CHICAGO

R. P , S. P and S. S, "Smart Traffic Vehicle monitoring and Signal Allocation using YOLO," International Research Journal on Advanced Science Hub, 5 Issue 05S (2023): 213-218, doi: 10.47392/irjash.2023.S028

VANCOUVER

P, R., P, S., S, S. Smart Traffic Vehicle monitoring and Signal Allocation using YOLO. International Research Journal on Advanced Science Hub, 2023; 5(Issue 05S): 213-218. doi: 10.47392/irjash.2023.S028

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