Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM64663
Volume:
10 |
6 |
Jun 2026
Pages:
1-4
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Computer Science and Engineering
Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering
Computer Science and Engineering
Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering
Computer Science and Engineering
Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering
Computer Science and Engineering
Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering
Computer Science and Engineering
Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering
Computer Science and Engineering
Avinashilingam Institute for Home Science and Higher Education for Women, School of Engineering
Urban parking management has become a critical challenge in modern cities. Traditional parking systems rely heavily on manual processes, causing inefficiencies, human errors, and traffic congestion. This paper presents a Smart Parking System that leverages Number Plate Recognition (NPR) using EasyOCR—an Optical Character Recognition (OCR) technology—combined with a web-based dashboard for real-time monitoring and slot management. The proposed system captures vehicle number plates via a camera, automatically extracts the plate text using EasyOCR, assigns parking slots, and records entry and exit times in a SQLite database. A Flask-based web application serves as the backend, while an HTML/CSS dashboard provides administrators and users with real-time visibility into slot occupancy. The system supports up to 35 parking slots, prevents overbooking, and minimizes manual intervention. Experimental results demonstrate high accuracy in plate recognition under standard conditions, significant reduction in parking time, and improved overall parking management efficiency. The system is scalable and can be enhanced with Image Sensor,AI-based prediction, and cloud storage for smart city deployments.
KEYWORDS
This paper presented the design, implementation, and evaluation of a Smart Parking System with Number Plate Recognition using EasyOCR and a Flask-based web dashboard. The system successfully automates the key aspects of parking management—vehicle detection, slot allocation, real-time monitoring, and record maintenance—while minimizing human intervention. The proposed system addresses critical shortcomings of traditional parking methods, including manual data entry errors, lack of real-time visibility, and inefficient space utilization. Experimental results demonstrated over 91% OCR accuracy under standard conditions, sub-second response times for slot allocation, and consistent database integrity across all test scenarios. The modular architecture ensures ease of maintenance and extensibility. Future integration with IoT hardware, AI prediction models, and cloud infrastructure will further enhance the system's capabilities, making it a viable component of next-generation smart city infrastructure.
[1] A. Javaheri and Sai Sneha, "Evaluating the Impact of Smart Parking Systems on Parking Violations," IEEE Access, 2024. [Online]. Available: https://ieeexplore.ieee.org/document/10758649/ [2] A. O. Elfaki and W. Messoudi, "A Smart Real-Time Parking Control and Monitoring System," Sensors, vol. 23, no. 24, p. 9741, MDPI, 2023. [Online]. Available: https://www.mdpi.com/1424-8220/23/24/9741 [3] A. Ditta, M. M. Ahmed, and T. Mazhar, "Number Plate Recognition Smart Parking Management System using IoT," Measurement: Sensors, vol. 37, Elsevier, 2025, DOI: 10.1016/j.measen.2024.101409. [4] G. Pradhan and M. R. Prusty, "Advanced IoT-Integrated Parking Systems with Automated License Plate Recognition and Payment Management," Scientific Reports, Springer Nature, 2025. [Online]. Available: https://www.nature.com/articles/s41598-025-86441-w [5] M. Arora and A. Jain, "Automatic Number Plate Recognition System Using Optical Character Recognition," International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), 2019.
Publication Date
6/8/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
3
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...