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AI in Sports

Time / Place:

⏱️ 10/8 (Fri.) 21:00-21:25 at Online Track 2


In the recent years, mobile technologies and Internet of Things (IoT) have become popular in many fields. Therefore, AI is widely applied in daily life by using various data collection approaches. Sport is a typical field applying AI to enhance performance and reduce injury. AI is impacting nearly every major sport event such as Olympic Games and professional sport like NBA and MLB. It is clear from the direction of this trend that coaches and athletes are demanding more AI technology to help them developing smarter training method. In this respect, AI in sport won’t be much different than its applications in other fields. Sensor-based system or video-based system are 2 applications of AI in sports that hold great promise for future growth. AI can make the most benefits out of those data collected in sport field or training site, if the algorithm is appropriate to determine the right key factors for athletes and coaches. It’s important to note that most of the applications of AI in sport are still in a pilot phase. In order to reach the need to go beyond just tracking data to converting it to meaningful insights that actually help athletes meet their performance goals. Combined AI technology and sport science domain knowledge is essence for future development of AI in sports.

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  • 相子元 Tzyy-Yuang Shiang Website:
  • Institute of Exercise & Sport Science, National Taiwan Normal University / Distinguished Professor
  • 現任:
    • 台灣師大 運動競技學系 研究講座教授
    • 運動科技大聯盟 召集人
    • 國訓中心 運動科學 總召集人
    • 美國賓州州立大學 (Pennsylvania State University) 機械工程 (生物力學) 博士
    • 生物力學
    • 運動科學
      • Sports Biomechanics
      • Exercise & Sports Science
      • BioMedical Engineering

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