UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 12 | Issue 10 | October 2025

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Published in:

Volume 10 Issue 5
May-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2305758


Registration ID:
512381

Page Number

h494-h501

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Title

Parking Space Finder Using Image Processing And Machine Learning

Abstract

Finding a parking spot has become difficult in many places all over the globe due to the rise in the number of vehicles on the road. The use of image processing and machine learning methods to count the number of accessible parking spaces in a particular location is one of many smart parking solutions that have been put forth to handle this problem. In this study, we show a clever parking system that counts the number of parking spots that are open in real-time by using machine learning and image processing methods to identify and discover available spaces. The suggested system consists of a camera network that records pictures of the parking area and an algorithm that analyses these images to find open parking spots. To extricate the parking spots from the recorded pictures, the image processing algorithm carries out a number of image enhancement and segmentation operations. The machine learning programme then examines these segmented pictures to categorise each parking spot as either empty or filled. For the ease of users, the system offers a real-time count of the available parking spots, which can be shown on electronic signage or sent to a smartphone application. The suggested clever parking system has a number of benefits over conventional parking systems. It can increase the effectiveness of parking administration, lessen traffic congestion, and make parking easier for travellers. In order to improve the total city infrastructure, it can also be combined with other smart city systems like traffic management, public transit, and environmental tracking systems.

Key Words

Smart parking, Parking space detection, parking occupancy monitoring, Real-time counting, Real-time counting, Traffic congestion

Cite This Article

"Parking Space Finder Using Image Processing And Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.h494-h501, May-2023, Available :http://www.jetir.org/papers/JETIR2305758.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Parking Space Finder Using Image Processing And Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. pph494-h501, May-2023, Available at : http://www.jetir.org/papers/JETIR2305758.pdf

Publication Details

Published Paper ID: JETIR2305758
Registration ID: 512381
Published In: Volume 10 | Issue 5 | Year May-2023
DOI (Digital Object Identifier):
Page No: h494-h501
Country: Lucknow, Uttar pradesh, India .
Area: Science & Technology
ISSN Number: 2349-5162
Publisher: IJ Publication


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