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  Published Paper Details:

  Paper Title

REAL-TIME VEHICLE DETECTION, TRACKING AND COUNTING USING DEEP LEARNING AND YOLO BASED DETECTORS

  Authors

  Priyanka D,  Vaishnavi Girish,  Tejaswini C S,  Gagana S,  Krupesha D

  Keywords

Computer Vision; Traffic-flow; Open CV; Vehicle Detection; Vehicle Track; Vehicle Count.

  Abstract


In most cities across the world, traffic congestion is a serious issue that has turned into a nightmare for the locals. It is brought on by signal delays, improper traffic light timing, etc. Traffic light delays are hard-coded and traffic has no bearing on it. Consequently, there is a growing need for systematic quick automatic systems to optimize traffic control. The majority of city traffic is starting to seriously interfere with daily living. Thus, many strategies are considered in order to control the traffic. We apply techniques from image processing in our system to calculate the traffic density. Every road needs to have cameras installed; these cameras are always monitoring the flow of traffic on that specific route. whereby data is processed to identify traffic density, notify the relevant department, and trigger automatic completion of the required actions. In addition to easing the traffic congestion, we also implemented a Yolo-based module for ambulance feasibility, allowing the ambulance to manage the traffic light in the designated region.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT24A3026

  Paper ID - 254246

  Page Number(s) - i613-i624

  Pubished in - Volume 12 | Issue 3 | March 2024

  DOI (Digital Object Identifier) -    http://doi.one/10.1729/Journal.38629

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Priyanka D,  Vaishnavi Girish,  Tejaswini C S,  Gagana S,  Krupesha D,   "REAL-TIME VEHICLE DETECTION, TRACKING AND COUNTING USING DEEP LEARNING AND YOLO BASED DETECTORS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 3, pp.i613-i624, March 2024, Available at :http://www.ijcrt.org/papers/IJCRT24A3026.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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