Mobile Application Utilizing YOLOv8 for Real-Time Urban Traffic Data Collection
This paper presents a pioneering mobile application specifically designed to revolutionize the collection of urban traffic data. The application is engineered on the robust YOLOv8 platform for mobile devices, leveraging smartphone cameras to provide real-time observations of traffic conditions and v...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2025-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/01/e3sconf_icegc2024_00077.pdf |
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| _version_ | 1832098667372216320 |
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| author | Charef Ayoub Jarir Zahi Quafafou Mohamed |
| author_facet | Charef Ayoub Jarir Zahi Quafafou Mohamed |
| author_sort | Charef Ayoub |
| collection | DOAJ |
| description | This paper presents a pioneering mobile application specifically designed to revolutionize the collection of urban traffic data. The application is engineered on the robust YOLOv8 platform for mobile devices, leveraging smartphone cameras to provide real-time observations of traffic conditions and vehicle counts with a notable accuracy of 93%. The development environment includes Java Android, enhancing the app with cutting-edge functionalities such as YOLOv8 for precise vehicle type detection and Deep Sort for effective vehicle counting. Despite achieving high accuracy, the application encounters difficulties in accurately detecting motorcycles, which are often hidden behind larger vehicles. This research not only demonstrates the effectiveness of a sophisticated tool for traffic data analysis but also emphasizes the essential need for continuous improvements to tackle practical challenges encountered in urban settings. The findings signify a major progression in urban mobility research and advocate for advanced traffic management and planning strategies. |
| format | Article |
| id | doaj-art-fd59381e3b1c4db1a0fd9b45b3922224 |
| institution | Kabale University |
| issn | 2267-1242 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj-art-fd59381e3b1c4db1a0fd9b45b39222242025-02-05T10:46:25ZengEDP SciencesE3S Web of Conferences2267-12422025-01-016010007710.1051/e3sconf/202560100077e3sconf_icegc2024_00077Mobile Application Utilizing YOLOv8 for Real-Time Urban Traffic Data CollectionCharef Ayoub0Jarir Zahi1Quafafou Mohamed2LAMIGEP, EMSI Moroccan School of EngineeringLaboratory of Computer Systems Engineering (LISI) Department of Computer Science Faculty of Science Cadi Ayyad UniversityDepartment of Computer Science University of Aix-MarseilleThis paper presents a pioneering mobile application specifically designed to revolutionize the collection of urban traffic data. The application is engineered on the robust YOLOv8 platform for mobile devices, leveraging smartphone cameras to provide real-time observations of traffic conditions and vehicle counts with a notable accuracy of 93%. The development environment includes Java Android, enhancing the app with cutting-edge functionalities such as YOLOv8 for precise vehicle type detection and Deep Sort for effective vehicle counting. Despite achieving high accuracy, the application encounters difficulties in accurately detecting motorcycles, which are often hidden behind larger vehicles. This research not only demonstrates the effectiveness of a sophisticated tool for traffic data analysis but also emphasizes the essential need for continuous improvements to tackle practical challenges encountered in urban settings. The findings signify a major progression in urban mobility research and advocate for advanced traffic management and planning strategies.https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/01/e3sconf_icegc2024_00077.pdf |
| spellingShingle | Charef Ayoub Jarir Zahi Quafafou Mohamed Mobile Application Utilizing YOLOv8 for Real-Time Urban Traffic Data Collection E3S Web of Conferences |
| title | Mobile Application Utilizing YOLOv8 for Real-Time Urban Traffic Data Collection |
| title_full | Mobile Application Utilizing YOLOv8 for Real-Time Urban Traffic Data Collection |
| title_fullStr | Mobile Application Utilizing YOLOv8 for Real-Time Urban Traffic Data Collection |
| title_full_unstemmed | Mobile Application Utilizing YOLOv8 for Real-Time Urban Traffic Data Collection |
| title_short | Mobile Application Utilizing YOLOv8 for Real-Time Urban Traffic Data Collection |
| title_sort | mobile application utilizing yolov8 for real time urban traffic data collection |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/01/e3sconf_icegc2024_00077.pdf |
| work_keys_str_mv | AT charefayoub mobileapplicationutilizingyolov8forrealtimeurbantrafficdatacollection AT jarirzahi mobileapplicationutilizingyolov8forrealtimeurbantrafficdatacollection AT quafafoumohamed mobileapplicationutilizingyolov8forrealtimeurbantrafficdatacollection |