Enhanced Parking System

Authors

  • Sunil Bhutada  Department of IT, Sreenidhi Institute of Science and Technology, Yamnampet, Hyderabad, Telangana, India
  • Sanjay Kiran Chennoju  Department of IT, Sreenidhi Institute of Science and Technology, Yamnampet, Hyderabad, Telangana, India
  • Anvesh Gali  Department of IT, Sreenidhi Institute of Science and Technology, Yamnampet, Hyderabad, Telangana, India
  • Manikanta Reddy Makka  Department of IT, Sreenidhi Institute of Science and Technology, Yamnampet, Hyderabad, Telangana, India
  • Likith Chintala  Department of IT, Sreenidhi Institute of Science and Technology, Yamnampet, Hyderabad, Telangana, India

Keywords:

Data analysis, Data Visualization, Open CV, MatplotLib.

Abstract

The majority of parking lots are maintained manually by the human workforce, and there is a least automated system in place to manage the parking area appropriately. Drivers must circle the parking lot in search of a parking slot. This type of issue is most common in metro cities near retail malls, hospitals, and so forth. In this paper we develop a OpenCV model where when a car enters any of the parking lots the car driver can find the state of the parking lot, namely whether it is fully occupied, partially occupied, or unoccupied at the entry itself. And also in this paper we are going to extract car information and perform some data visualization and analyze that output.

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2022-06-30

Issue

Volume 9, Issue 3, May-June-2022

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Sunil Bhutada, Sanjay Kiran Chennoju, Anvesh Gali, Manikanta Reddy Makka, Likith Chintala "Enhanced Parking System" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 9, Issue 3, pp.382-385, May-June-2022.