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  Published Paper Details:

  Paper Title

ADAPTIVE CONTROL OF TRAFFIC SIGNALS THROUGH AI TECHNIQUES

  Authors

  Mr.A Suresh,  D. Gangadhar,  D. Geethika,  G. Geethika,  A .Hepsibha

  Keywords

IR detection, Raspberry Pi, ZigBee, Sensor.

  Abstract


This paper is proposed with a plan to identify the crisis vehicle particularly the rescue vehicle by utilizing the signal produced from the crisis vehicle to the traffic signal control unit. Ambulances are normally found out by the alarm sound, yet in some time where the drivers in the shut vehicle couldn't hear the sound appropriately and furthermore there exists confusion in the path in which the rescue vehicle is showing up. Some time, the alarm is switched off to decrease the strain on the patients. The proposed framework would give an answer for this issue This framework utilizes a sensor that distinguishes the traffic density on the lane from the signal of the vehicle a ways off from the traffic signal to get out the traffic congestion on the lane and to give a quicker development of the crisis vehicle to serve the patients needing crisis. The lead of utilizing this framework is that signal have more high frequency and it is simple recognized from a good distance. We directed a study at various seasons of a day and furthermore at various climatic circumstances to study the detection of the signal from the ZigBee.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2303569

  Paper ID - 232975

  Page Number(s) - f5-f9

  Pubished in - Volume 11 | Issue 3 | March 2023

  DOI (Digital Object Identifier) -   

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

  E-ISSN Number - 2320-2882

  Cite this article

  Mr.A Suresh,  D. Gangadhar,  D. Geethika,  G. Geethika,  A .Hepsibha,   "ADAPTIVE CONTROL OF TRAFFIC SIGNALS THROUGH AI TECHNIQUES", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 3, pp.f5-f9, March 2023, Available at :http://www.ijcrt.org/papers/IJCRT2303569.pdf

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


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