A distributed IoT-based timing system for athletic training: Improving accuracy with ESP32 peer-to-peer communication and Raspberry Pi coordination
Kiet, Bui (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025121637301
https://urn.fi/URN:NBN:fi:amk-2025121637301
Tiivistelmä
The aim of this study was to design and improve a smart timing system for athletic training using embedded IoT devices. The objective was to address communication delays, centralized dependency, and limited synchronization accuracy found in initial Raspberry Pi-based systems.
The system hardware underwent comprehensive modernization, incorporating 3D printed housing and robust waterproof UART ultrasonic sensors to enhance field durability. For visual and operational clarity, a 7-segment display was integrated to assign and display a unique identifier for each cone, and LED light strips were added for providing clear, color-coded direction indication. On the software side, critical connectivity issues were resolved, and the problematic UI drift that caused latency in the stopwatch function was successfully corrected. Communication between the central unit and the cones was reliably established using optimized TCP protocols, and microsecond-level clock synchronization across all devices was precisely implemented using the Network Time Protocol (NTP) to ensure accuracy.
The testing results confirmed that the connectivity and latency problems were successfully resolved. The system demonstrated significant improvements in timing accuracy and reliability compared to the initial de-sign. The distributed approach removed the single-point bottleneck, which enabled more scalable performance. The conclusion is that affordable, flexible, and precise training tools can be effectively adapted to a wide range of sports and exercise scenarios.
The system hardware underwent comprehensive modernization, incorporating 3D printed housing and robust waterproof UART ultrasonic sensors to enhance field durability. For visual and operational clarity, a 7-segment display was integrated to assign and display a unique identifier for each cone, and LED light strips were added for providing clear, color-coded direction indication. On the software side, critical connectivity issues were resolved, and the problematic UI drift that caused latency in the stopwatch function was successfully corrected. Communication between the central unit and the cones was reliably established using optimized TCP protocols, and microsecond-level clock synchronization across all devices was precisely implemented using the Network Time Protocol (NTP) to ensure accuracy.
The testing results confirmed that the connectivity and latency problems were successfully resolved. The system demonstrated significant improvements in timing accuracy and reliability compared to the initial de-sign. The distributed approach removed the single-point bottleneck, which enabled more scalable performance. The conclusion is that affordable, flexible, and precise training tools can be effectively adapted to a wide range of sports and exercise scenarios.