SMART TRAINING KIT BERBASIS INTERNET OF THINGS SEBAGAI ALAT MONITORING KEBUGARAN FISIK ATLET BOLA VOLI - Renno Bagas Syahputra; Muhamad Syariffuddien Zuhrie; Lusia Rakhmawati; Agus Wiyono (Universitas Nusa Cendana, 2025)
The performance of volleyball athletes is greatly influenced by the speed and accuracy of their footwork in reaching the ball, especially during footwork training. This study aims to design a physical fitness monitoring device based on the Internet of Things (IoT) called STARK (Smart Training Kit) using the Neo M9N GNSS sensor and ESP32 microcontroller. Position coordinates, time, and speed data are collected in real-time at a sampling rate of up to 25 Hz, then stored on a MicroSD card in CSV format. The data is transmitted to the cloud via a gateway application for visualization through Google Sheets and Google Maps. Testing was conducted using a comparison method of speed and distance traveled, with the Haversine Formula as the benchmark. Test results show that higher sampling frequencies yield more detailed recorded data. The device demonstrates sufficiently stable accuracy during constant movement, though small errors increase as object speed increases. Thus, this tool can serve as an alternative for monitoring sports training and support a sports science approach through measurable and structured data.