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PARK-EZE: An IoT based Smart Parking System using DLSTM Prediction

Authors

  • Ankith Issac Dominic

    Albertian Institute of Science and Technology
    Author

  • Meera Johnson

    Albertian Institute of Science and Technology
    Author

  • Jaida Fathima

    Albertian Institute of Science and Technology
    Author

  • Alaina Benny

    Albertian Institute of Science and Technology
    Author

  • Amritha Soloman

    Albertian Institute of Science and Technology
    Author

Abstract

In response to escalating urbanization and vehicular
congestion, our project PARKEZE a Smart Parking System
introduces an innovative solution integrating IoT and DLSTM
(Deep Long Short Term Memory) technologies. By employing IoT
sensors for realtime data collection and DLSTM for predictive
analysis, the system PARK-EZE aims to revolutionize parking
management. This exploration delves into PARK-EZE’s design,
implementation, and transformative potential, elucidating its role
in creating smarter, more sustainable urban spaces. Through
comprehensive data analytics, PARKEZE seeks to alleviate
congestion and inefficient parking allocation, fostering efficient
urban mobility patterns. PARK-EZE represents a paradigm shift
towards efficiency, accessibility, and environmental stewardship
in urban environments.

Keywords:

PARK-EZE, Prediction, Real-time parking data
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Published

06-08-2025

Issue

Vol. 4 No. 1 (2024): IJERA

Section

Articles

License

Copyright (c) 2024 International Journal on Emerging Research Areas

Creative Commons License

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

All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

How to Cite

[1]
A. Issac Dominic, M. Johnson, J. Fathima, A. Benny, and A. Soloman, “PARK-EZE: An IoT based Smart Parking System using DLSTM Prediction”, IJERA, vol. 4, no. 1, pp. 1–5, Aug. 2025, Accessed: Aug. 18, 2025. [Online]. Available: https://ijera.in/index.php/IJERA/article/view/163