ICCK Transactions on Mobile and Wireless Intelligence
ISSN: 3069-0692 (Online)
Email: [email protected]
Submit Manuscript
Edit a Special Issue
TY - JOUR AU - Haque, A.K.M. Fazlul AU - Akter, Nila AU - Heya, Shaznina Mahrin AU - Khan, Mohammad Fahim Asif AU - Akter, Taslima PY - 2026 DA - 2026/02/14 TI - An Intelligent Smart Parking Framework Using Machine Learning–Based Automatic License Plate Recognition for Enhanced Security JO - ICCK Transactions on Mobile and Wireless Intelligence T2 - ICCK Transactions on Mobile and Wireless Intelligence JF - ICCK Transactions on Mobile and Wireless Intelligence VL - 2 IS - 1 SP - 21 EP - 30 DO - 10.62762/TMWI.2026.886184 UR - https://www.icck.org/article/abs/TMWI.2026.886184 KW - smart parking KW - ALPR KW - machine learning KW - image processing KW - IoT automation AB - Urban parking inefficiency has become a critical challenge in modern cities, leading to increased traffic congestion, higher fuel consumption, and greater environmental impact. This paper proposes an intelligent smart parking management system that integrates hardware sensing, machine learning, and computer vision to enable real-time parking monitoring and automated vehicle identification. The system combines infrared sensors, camera modules, and microcontroller-based control with vision-based parking space detection and automatic license plate recognition (ALPR). Experimental results demonstrate that the parking space detection module achieves an accuracy of 93.97%, while the license plate recognition module attains 84.93% accuracy. Extensive testing under real-world conditions confirms the system's reliability and practicality. The proposed approach enhances parking space utilization, reduces parking search time, and offers a scalable, cost-effective foundation for future smart city parking infrastructure. SN - 3069-0692 PB - Institute of Central Computation and Knowledge LA - English ER -
@article{Haque2026An,
author = {A.K.M. Fazlul Haque and Nila Akter and Shaznina Mahrin Heya and Mohammad Fahim Asif Khan and Taslima Akter},
title = {An Intelligent Smart Parking Framework Using Machine Learning–Based Automatic License Plate Recognition for Enhanced Security},
journal = {ICCK Transactions on Mobile and Wireless Intelligence},
year = {2026},
volume = {2},
number = {1},
pages = {21-30},
doi = {10.62762/TMWI.2026.886184},
url = {https://www.icck.org/article/abs/TMWI.2026.886184},
abstract = {Urban parking inefficiency has become a critical challenge in modern cities, leading to increased traffic congestion, higher fuel consumption, and greater environmental impact. This paper proposes an intelligent smart parking management system that integrates hardware sensing, machine learning, and computer vision to enable real-time parking monitoring and automated vehicle identification. The system combines infrared sensors, camera modules, and microcontroller-based control with vision-based parking space detection and automatic license plate recognition (ALPR). Experimental results demonstrate that the parking space detection module achieves an accuracy of 93.97\%, while the license plate recognition module attains 84.93\% accuracy. Extensive testing under real-world conditions confirms the system's reliability and practicality. The proposed approach enhances parking space utilization, reduces parking search time, and offers a scalable, cost-effective foundation for future smart city parking infrastructure.},
keywords = {smart parking, ALPR, machine learning, image processing, IoT automation},
issn = {3069-0692},
publisher = {Institute of Central Computation and Knowledge}
}
ICCK Transactions on Mobile and Wireless Intelligence
ISSN: 3069-0692 (Online)
Email: [email protected]
Portico
All published articles are preserved here permanently:
https://www.portico.org/publishers/icck/