Integration of YOLOv5 Algorithm and OpenCV in Innovative Smart Parking Management Approach
The problem of automatic parking lot identification and vehicle detection in open areas is becoming increasingly important due to the increase in the number of vehicles in Indonesia, particularly in big cities, resulting in difficulties in finding parking spaces during peak hours. In this condition,...
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| Format: | Article |
| Language: | English |
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Ikatan Ahli Informatika Indonesia
2024-06-01
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| Series: | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) |
| Subjects: | |
| Online Access: | https://jurnal.iaii.or.id/index.php/RESTI/article/view/5728 |
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| author | Akmal Hidayah Hidayah Sitti Zuhriyah Billy Eden William Asrul Yuyun Yuyun Esa Prakasa |
| author_facet | Akmal Hidayah Hidayah Sitti Zuhriyah Billy Eden William Asrul Yuyun Yuyun Esa Prakasa |
| author_sort | Akmal Hidayah Hidayah |
| collection | DOAJ |
| description | The problem of automatic parking lot identification and vehicle detection in open areas is becoming increasingly important due to the increase in the number of vehicles in Indonesia, particularly in big cities, resulting in difficulties in finding parking spaces during peak hours. In this condition, drivers often have to compete for parking spaces. This research aims to develop a smart parking system that integrates YOLOv5 and OpenCV algorithms. This approach thoroughly combines both algorithms to identify parking spaces and detect vehicles in real time in various parking scenarios. It is carried out in an open area with reference to parking conditions at the BRIN Bandung office. This study collected data from three different parking lot conditions, namely empty, partially occupied, and full. In each condition, the system successfully detected the parking lots and vehicles accurately. The novel contribution of this research is the development of a smart parking system that uses an integrated approach, providing an effective solution to the challenges of parking lot availability and vehicle detection. Using the advantages of both algorithms, we successfully created a system that can identify parking spaces and detect vehicles accurately and efficiently under various parking circumstances. Therefore, this research makes a significant contribution to the development of smart and adaptive parking management technology. |
| format | Article |
| id | doaj-art-a1edd4735834408287a442e361e2fd79 |
| institution | Kabale University |
| issn | 2580-0760 |
| language | English |
| publishDate | 2024-06-01 |
| publisher | Ikatan Ahli Informatika Indonesia |
| record_format | Article |
| series | Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) |
| spelling | doaj-art-a1edd4735834408287a442e361e2fd792025-01-13T03:33:46ZengIkatan Ahli Informatika IndonesiaJurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)2580-07602024-06-018341342210.29207/resti.v8i3.57285728Integration of YOLOv5 Algorithm and OpenCV in Innovative Smart Parking Management ApproachAkmal Hidayah Hidayah0Sitti Zuhriyah1Billy Eden William Asrul2Yuyun Yuyun3Esa Prakasa4Universitas HandayaniUniversitas HandayaniUniversitas HandayaniBadan Riset dan Inovasi NasionalBadan Riset dan Inovasi NasionalThe problem of automatic parking lot identification and vehicle detection in open areas is becoming increasingly important due to the increase in the number of vehicles in Indonesia, particularly in big cities, resulting in difficulties in finding parking spaces during peak hours. In this condition, drivers often have to compete for parking spaces. This research aims to develop a smart parking system that integrates YOLOv5 and OpenCV algorithms. This approach thoroughly combines both algorithms to identify parking spaces and detect vehicles in real time in various parking scenarios. It is carried out in an open area with reference to parking conditions at the BRIN Bandung office. This study collected data from three different parking lot conditions, namely empty, partially occupied, and full. In each condition, the system successfully detected the parking lots and vehicles accurately. The novel contribution of this research is the development of a smart parking system that uses an integrated approach, providing an effective solution to the challenges of parking lot availability and vehicle detection. Using the advantages of both algorithms, we successfully created a system that can identify parking spaces and detect vehicles accurately and efficiently under various parking circumstances. Therefore, this research makes a significant contribution to the development of smart and adaptive parking management technology.https://jurnal.iaii.or.id/index.php/RESTI/article/view/5728smart parkingyolov5opencvvehicle detectionparking space identificationobject recognition technology |
| spellingShingle | Akmal Hidayah Hidayah Sitti Zuhriyah Billy Eden William Asrul Yuyun Yuyun Esa Prakasa Integration of YOLOv5 Algorithm and OpenCV in Innovative Smart Parking Management Approach Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) smart parking yolov5 opencv vehicle detection parking space identification object recognition technology |
| title | Integration of YOLOv5 Algorithm and OpenCV in Innovative Smart Parking Management Approach |
| title_full | Integration of YOLOv5 Algorithm and OpenCV in Innovative Smart Parking Management Approach |
| title_fullStr | Integration of YOLOv5 Algorithm and OpenCV in Innovative Smart Parking Management Approach |
| title_full_unstemmed | Integration of YOLOv5 Algorithm and OpenCV in Innovative Smart Parking Management Approach |
| title_short | Integration of YOLOv5 Algorithm and OpenCV in Innovative Smart Parking Management Approach |
| title_sort | integration of yolov5 algorithm and opencv in innovative smart parking management approach |
| topic | smart parking yolov5 opencv vehicle detection parking space identification object recognition technology |
| url | https://jurnal.iaii.or.id/index.php/RESTI/article/view/5728 |
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