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  Published Paper Details:

  Paper Title

Smart and effective real-time management of street parking using CNN

  Authors

  M. Zahir Ahmed

  Keywords

CNN, Machine learning, Python, Smart street parking, signals

  Abstract


With the rapid development of society, travelers have become more popular in big cities, making it difficult to find a parking space. These stations are very expensive to manage and difficult in many cases, especially if there are many locations such as airports or commercial centres. Traffic congestion in the parking lot is a big problem that people face every day because while the number of vehicles is increasing, the parking space is not. The model takes all the available parking spaces in a place and based on the data obtained, it works to detect whether the parking space is empty or occupied by a car and provides the data sheet regarding the empty parking lot. In our system, we need to detect the station using CNN, RF and SVM. Here we need to draw boxes for full and empty boxes. Full parking areas are red, empty parking areas are green. The main problem of today's life is the increasing number of vehicles and the shortage of parking spaces. With the rapid development of the city, the number of vehicles in the city has also increased, and parking spaces in the city have become limited, which causes people to consume more fuel while looking for parking spaces. live and the engine continues to work until then. Traffic congestion in the parking lot is a big problem that people face every day because the number of vehicles increases while the parking space does not increase.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT1135632

  Paper ID - 266399

  Page Number(s) - 312-316

  Pubished in - Volume 2 | Issue 1 | February 2014

  DOI (Digital Object Identifier) -   

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

  E-ISSN Number - 2320-2882

  Cite this article

  M. Zahir Ahmed,   "Smart and effective real-time management of street parking using CNN", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.2, Issue 1, pp.312-316, February 2014, Available at :http://www.ijcrt.org/papers/IJCRT1135632.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


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