Author
Abstract
There is now a greater need for effective and safe parking solutions due to the growth in urbanization. To provide an anodyne parking experience, this article introduces an AI-driven parking management system that combines biometric authentication for gate control with Automatic Number Plate Recognition (ANPR) for vehicle classification. This paper will present an IoT-based automatic number plate recognition (ANPR) and biometric gate control system designed to optimize parking management through automated vehicle access. We suggested a biometric-integrated Internet of Things-based parking access management system with fingerprint recognition for user authentication. The system uses a Raspberry Pi 4 as its central controller and uses automatic number plate recognition (ANPR) to classify vehicles. Our suggested framework will utilize the camera to capture images of vehicles, then extract the license plate number and compare it to a database of permitted vehicles using ANPR software for vehicle classification and allocation. The system uses AI and IoT-based technologies to enhance security, automate vehicle entrances, and track real-time parking occupancy. Only registered users or authorized personnel are permitted to enter the restricted parking area. The proposed system is designed to operate in real-time, minimizing unauthorized access, reducing congestion, and enhancing overall parking efficiency. As a result of integrating with IoT systems, the solution will improve security and operational efficiency by enabling real-time monitoring, dynamic updates of parking availability, and logging of entry and exit events.
Suggested Citation
Iqra Yasmin*,Romiza Rubab,Muhammad Afzal,Javeria Rusool, 2025.
"AI-Driven Parking Management: ANPR-Based Entry & Biometric Gate Control,"
International Journal of Innovations in Science & Technology, 50sea, vol. 7(3), pages 1437-1452, July.
Handle:
RePEc:abq:ijist1:v:7:y:2025:i:3:p:1437-1452
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