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Title	Ips: Intelligent Parking System Using Yolo And Image Processing
ID_Doc	34158
Authors	Rani R.; Kumar S.; Pippal S.K.; Gund M.; Chaudhari U.; Agrawal R.; Dalsaniya M.; Verma L.
Year	2024
Published	International Journal of Transport Development and Integration, 8, 3
DOI	http://dx.doi.org/10.18280/ijtdi.080308
Abstract	Parking management systems often need to improve due to outdated infrastructure, inefficient manual processes, and the lack of automation, resulting in increased congestion and poor user experience. Traditional parking management systems, reliant on manual license plate entry and outdated payment methods, need help to meet modern demands. In response, this research introduces a novel Intelligent Parking System (IPS) that leverages automatic License Plate Recognition (LPR) with a YOLO model for real-time detection and recognition of vehicle license plates. By eliminating the need for sensors and manual data entry, our system enhances accuracy, reduces maintenance costs, and optimizes parking operations. Furthermore, integrating QR code-based payment simplifies and accelerates the payment process, reducing wait times and improving user experience. This approach addresses the growing need for scalable and adaptable parking solutions in smart city initiatives. Through this research, the IPS provides a scalable, intelligent alternative to conventional parking systems, contributing to smarter urban environments. Copyright: ©2024 The authors.
Author Keywords	deep learning; license plate recognition; object recognition; parking system; YOLO

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