Design and Development of a Public AI Referee Assistance System Based on Harmony OS Platform
The Hawkeye system was regarded as a successful and effective referee assistant in commercial applications. However, the high hardware investment and strong professionalism set up a physical hurdle in public application. In this sense, one AI referee assistance system is a small-scale system develop...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/7/2127 |
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| author | Jingjing Zhao Chang Zhu Bo Leng Jiantao Qi |
| author_facet | Jingjing Zhao Chang Zhu Bo Leng Jiantao Qi |
| author_sort | Jingjing Zhao |
| collection | DOAJ |
| description | The Hawkeye system was regarded as a successful and effective referee assistant in commercial applications. However, the high hardware investment and strong professionalism set up a physical hurdle in public application. In this sense, one AI referee assistance system is a small-scale system developed under the guidance of computer vision theory and technology, using deep learning-based object detection algorithms and computer graphics-related knowledge. Its main function is to use computer vision technology to make correct and fair judgments on controversial decisions in badminton matches. The AI referee assistance system uses the Harmony OS platform to build a frontend mini-program and uses the YOLOV5 algorithm to detect and track corresponding targets, ultimately achieving judgments both inside and outside the bounds as well as serving violations. In this study, it was found that the object detection model trained in this study performed well, with a prediction accuracy of up to 99%. For posture recognition, this study also utilizes the relatively mature MediaPipe algorithm, which ensures high accuracy of the entire intelligent referee system’s ruling and meets the needs of current students. This helps college students better participate in badminton training and competitions, further improving their enthusiasm for participating in sports and, to some extent, solving the problem of scarce referee resources. |
| format | Article |
| id | doaj-art-98bbf10795b64beca6880d03ed1a0ac3 |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-98bbf10795b64beca6880d03ed1a0ac32025-08-20T03:08:54ZengMDPI AGSensors1424-82202025-03-01257212710.3390/s25072127Design and Development of a Public AI Referee Assistance System Based on Harmony OS PlatformJingjing Zhao0Chang Zhu1Bo Leng2Jiantao Qi3Physical Education Teaching Department, China University of Petroleum (East China), Qingdao 266580, ChinaSchool of Information and Communication Engineering (SICE), University of Electronic Science and Technology of China, Chengdu 611731, ChinaCollege of Education, Beijing Sports University, Beijing 100091, ChinaCollege of New Energy, China University of Petroleum (East China), Qingdao 266580, ChinaThe Hawkeye system was regarded as a successful and effective referee assistant in commercial applications. However, the high hardware investment and strong professionalism set up a physical hurdle in public application. In this sense, one AI referee assistance system is a small-scale system developed under the guidance of computer vision theory and technology, using deep learning-based object detection algorithms and computer graphics-related knowledge. Its main function is to use computer vision technology to make correct and fair judgments on controversial decisions in badminton matches. The AI referee assistance system uses the Harmony OS platform to build a frontend mini-program and uses the YOLOV5 algorithm to detect and track corresponding targets, ultimately achieving judgments both inside and outside the bounds as well as serving violations. In this study, it was found that the object detection model trained in this study performed well, with a prediction accuracy of up to 99%. For posture recognition, this study also utilizes the relatively mature MediaPipe algorithm, which ensures high accuracy of the entire intelligent referee system’s ruling and meets the needs of current students. This helps college students better participate in badminton training and competitions, further improving their enthusiasm for participating in sports and, to some extent, solving the problem of scarce referee resources.https://www.mdpi.com/1424-8220/25/7/2127AI refereeobject detectionmotion monitoringsportsintelligent identification |
| spellingShingle | Jingjing Zhao Chang Zhu Bo Leng Jiantao Qi Design and Development of a Public AI Referee Assistance System Based on Harmony OS Platform Sensors AI referee object detection motion monitoring sports intelligent identification |
| title | Design and Development of a Public AI Referee Assistance System Based on Harmony OS Platform |
| title_full | Design and Development of a Public AI Referee Assistance System Based on Harmony OS Platform |
| title_fullStr | Design and Development of a Public AI Referee Assistance System Based on Harmony OS Platform |
| title_full_unstemmed | Design and Development of a Public AI Referee Assistance System Based on Harmony OS Platform |
| title_short | Design and Development of a Public AI Referee Assistance System Based on Harmony OS Platform |
| title_sort | design and development of a public ai referee assistance system based on harmony os platform |
| topic | AI referee object detection motion monitoring sports intelligent identification |
| url | https://www.mdpi.com/1424-8220/25/7/2127 |
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