Quickness Aspect Talent Identification (QATI) System Based on the Internet of Things

Identifying an athlete’s speed and quickness talent is a crucial stage in the world of sports that can determine an athlete’s success. However, in general, the athlete’s speed and quickness measurements are still done manually with a stopwatch, and then the results are written down in a book or paper. This study proposes a Quickness Aspect Talent Identification (QATI) system that uses Internet of Things (IoT) technology to identify athlete talent for quickness. This system is designed to obtain athlete quickness data by monitoring their movements through sensors placed at predetermined points and connected to a database via the Internet. The QATI system can help identify athletes that traditional talent identification methods might miss. The QATI system comprises four nodes, one controller, and a website-based information system. The node serves as an athlete’s goal point, which can be placed at four points. The controller will set the on–off combination on the node with an adjustable duration or run with a random algorithm. NodeMCU sends time measurement results to a Wifi or Bluetooth network server. The measurement results from each sensor on the node will appear on the website that has been created. The QATI application is proven to perform several configurations such as training mode, delay between devices, duration of on, the distance the device detects, and viewing indicators of the number of connected sensors. The QATI system is an innovative approach to talent identification that utilizes IoT technology to identify athletes for quickness.