AI-Based Car Parking Communication System for Enhancing Urban Traffic Management in Erbil, Kurdistan
DOI:
https://doi.org/10.23918/eajse.v11i3p5Keywords:
Parking Management, Artificial Intelligence, License Plate Recognition, YOLOv8, OCR, Smart City, ErbilAbstract
Urban traffic congestion and inefficient parking management remain pressing challenges in rapidly developing cities such as Erbil, Kurdistan. A common issue arises when parked vehicles block others, causing unnecessary delays, frustration, and potential conflicts. This study presents an AI-based car parking communication system designed to enable seamless interaction between vehicle owners in such situations. The proposed system integrates YOLOv8 for real-time license plate detection and Tesseract OCR for character recognition, while a Firebase database cross-reference detects plates to identify the corresponding vehicle owners. Once identified, the system automatically sends an in-app and email notification to the blocking vehicle’s owner, facilitating quick resolution. Developed using Flutter, the mobile application provides a multilingual, user-friendly interface supporting Kurdish, Arabic, and English. Experimental results demonstrate high detection accuracy and rapid response time, confirming the system’s effectiveness in reducing parking-related conflicts and improving overall urban traffic management in Erbil.
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Data Availability Statement: The data used in this research, including the AI training datasets and application code, is not publicly available due to confidentiality and privacy concerns. Access to the data may be granted on a case-by-case basis upon request and subject to approval by the authors.
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Copyright (c) 2025 Slvar Abdulazeez, Saia Hasan , Ahmad Shwan
This work is licensed under a Creative Commons Attribution 4.0 International License.
Eurasian J. Sci. Eng is distributed under the terms of the Creative Commons Attribution License 4.0 (CC BY-4.0) https://creativecommons.org/licenses/by/4.0/
