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  Published Paper Details:

  Paper Title

MONITORING DRIVING BEHAVIOR THROUGH DEEP LEARNING TOOLS AND FUZZY INFERENCEING

  Authors

  Sneha Hitali,  Megha Rani Raigonda

  Keywords

driving behavior, CNN, distracted activity

  Abstract


Drivers are meant to concentrate on driving, but they pay more attention to their surroundings, and they are overconfident in their driving abilities and underestimate the impact of distraction activities on driving performance. The distracted activities include using cell phones in the car, fetching items in car, talking with passengers. In this experimental work the driver head posture is examined to know whether the driver is concentrating on his frontal view. The danger level is indicated using the fuzzy logic to determine the risk level in real time. Based on vehicle speed, it is an excellent method for detecting unsafe road conditions in a timely manner. The Convolutional neural network model is best suitable to detect driver distraction more reliable than training model that only collect data in simulation experiment. We additionally confirmed that our device can offer well timed signals when drivers are performing

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2112129

  Paper ID - 213234

  Page Number(s) - b283-b286

  Pubished in - Volume 9 | Issue 12 | December 2021

  DOI (Digital Object Identifier) -   

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

  E-ISSN Number - 2320-2882

  Cite this article

  Sneha Hitali,  Megha Rani Raigonda,   "MONITORING DRIVING BEHAVIOR THROUGH DEEP LEARNING TOOLS AND FUZZY INFERENCEING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 12, pp.b283-b286, December 2021, Available at :http://www.ijcrt.org/papers/IJCRT2112129.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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