Special Vehicle Classification Algorithm-Based System for Dedicated Parking Zone Violation Detection in South Korea
To address the problem of managing dedicated parking zones arising from the increasing number of electric vehicles and vehicles for the physically challenged, this paper proposes a license plate recognition (LPR)-based parking control system that combines the YOLO and MobileNet algorithms. These two...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10833648/ |
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| author | Hyunseong Park Kapyeol Kim Incheol Jeong Jungil Jung Jinsoo Cho |
| author_facet | Hyunseong Park Kapyeol Kim Incheol Jeong Jungil Jung Jinsoo Cho |
| author_sort | Hyunseong Park |
| collection | DOAJ |
| description | To address the problem of managing dedicated parking zones arising from the increasing number of electric vehicles and vehicles for the physically challenged, this paper proposes a license plate recognition (LPR)-based parking control system that combines the YOLO and MobileNet algorithms. These two algorithms are designed for real-time object detection and efficient preprocessing, respectively, and can operate in real time in resource-constrained edge-device environments. In tests using data from more than 51,000 vehicles, the system achieved an accuracy rate of 95.76% in classifying electric vehicles and 97.18% in classifying vehicles for the physically challenged. The average CPU and RAM utilizations of the system were 34.54% and 45.04%, respectively. In addition, the processing time per image was recorded as approximately 1.04 s, demonstrating its potential to run reliably on edge devices. These results are expected to facilitate the efficient resolution of parking management problems in smart cities and effective operation of parking zones reserved for electric vehicles and vehicles for the physically challenged. |
| format | Article |
| id | doaj-art-89fd2f85e4754be89ef2834bfa3c2f69 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-89fd2f85e4754be89ef2834bfa3c2f692025-01-21T00:02:30ZengIEEEIEEE Access2169-35362025-01-01137883790110.1109/ACCESS.2025.352686210833648Special Vehicle Classification Algorithm-Based System for Dedicated Parking Zone Violation Detection in South KoreaHyunseong Park0https://orcid.org/0000-0001-8300-2869Kapyeol Kim1Incheol Jeong2Jungil Jung3Jinsoo Cho4https://orcid.org/0000-0002-8119-8068Department of IT Convergence Engineering, College of IT, Gachon University, Seongnam-si, Republic of KoreaDepartment of IT Convergence Engineering, College of IT, Gachon University, Seongnam-si, Republic of KoreaDepartment of IT Convergence Engineering, College of IT, Gachon University, Seongnam-si, Republic of KoreaPCT Company Ltd., Seongnam-si, Republic of KoreaDepartment of Computer Engineering, Gachon University, Seongnam-si, Republic of KoreaTo address the problem of managing dedicated parking zones arising from the increasing number of electric vehicles and vehicles for the physically challenged, this paper proposes a license plate recognition (LPR)-based parking control system that combines the YOLO and MobileNet algorithms. These two algorithms are designed for real-time object detection and efficient preprocessing, respectively, and can operate in real time in resource-constrained edge-device environments. In tests using data from more than 51,000 vehicles, the system achieved an accuracy rate of 95.76% in classifying electric vehicles and 97.18% in classifying vehicles for the physically challenged. The average CPU and RAM utilizations of the system were 34.54% and 45.04%, respectively. In addition, the processing time per image was recorded as approximately 1.04 s, demonstrating its potential to run reliably on edge devices. These results are expected to facilitate the efficient resolution of parking management problems in smart cities and effective operation of parking zones reserved for electric vehicles and vehicles for the physically challenged.https://ieeexplore.ieee.org/document/10833648/Artificial intelligencebounding boxlicense plate recognition (LPR)MobileNetoptical character recognition (OCR)video processing |
| spellingShingle | Hyunseong Park Kapyeol Kim Incheol Jeong Jungil Jung Jinsoo Cho Special Vehicle Classification Algorithm-Based System for Dedicated Parking Zone Violation Detection in South Korea IEEE Access Artificial intelligence bounding box license plate recognition (LPR) MobileNet optical character recognition (OCR) video processing |
| title | Special Vehicle Classification Algorithm-Based System for Dedicated Parking Zone Violation Detection in South Korea |
| title_full | Special Vehicle Classification Algorithm-Based System for Dedicated Parking Zone Violation Detection in South Korea |
| title_fullStr | Special Vehicle Classification Algorithm-Based System for Dedicated Parking Zone Violation Detection in South Korea |
| title_full_unstemmed | Special Vehicle Classification Algorithm-Based System for Dedicated Parking Zone Violation Detection in South Korea |
| title_short | Special Vehicle Classification Algorithm-Based System for Dedicated Parking Zone Violation Detection in South Korea |
| title_sort | special vehicle classification algorithm based system for dedicated parking zone violation detection in south korea |
| topic | Artificial intelligence bounding box license plate recognition (LPR) MobileNet optical character recognition (OCR) video processing |
| url | https://ieeexplore.ieee.org/document/10833648/ |
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