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The Development and Educational Evaluation of a Smart IoT Relay Baton with Accelerometer Technology

Year: 2025
Type: article
Abstract: Background. Relay performance depends on both individual speed and the efficiency of baton exchanges. However, conventional batons lack quantitative feedback to guide training. Objectives. This study aimed to develop and evaluate a Smart IoT Relay Baton equipped with an accelerometer to provide objective, real-time performance data. Materials and Methods. A modified R&D approach by Borg and Gall was used, involving needs analysis, system design, expert validation, small/large-scale trials, product revision, and finalization. The prototype used an accelerometer + NodeMCU ESP32, MQTT streaming, and a web dashboard. The participants were 241 sprint relay athletes (19–23 years). Baseline runs with conventional batons were followed by identical runs with the IoT baton. The outcomes included the measurement of transition time, entry speed, average acceleration, and team coordination (sync delay). The statistical analysis employed comprised using the Shapiro–Wilk test, paired t-tests, Cohen’s d, and Pearson correlations (α = .05). Results. Significant improvements were observed across all variables: transition time −9.97%, entry speed +9.85%, average acceleration +8.98%, and coordination +24.21% (all p < .05). Effect sizes were large to very large (d = 0.70–1.20). Correlations highlighted strong links between entry speed and acceleration (r = .74), as well as between transition time and coordination (r = .68). Conclusions. The IoT baton effectively supported coaches with accurate evaluations and strategic decision-making. These findings underscore the transformative role of IoT-based devices in advancing evidence-based sprint training. Furtherresearch should validate the tool in official competitions, integrate biometric and video-tracking technologies.
Authors: Cahyo Yuwono, Adi S, Tommy Soenyoto, Sri Indah Ihsani, Made Bang Redy Utama, Hilmy Aliriad, Khoiril Anam, Widya Hary Cahyati, Laily Mita Andriana, Mahenderan Appukutty
Language: English
Open Access status: gold
Estimated APC paid: $200
OpenAlex ID: W7106301658
FWCI: 2.198
Cites: 49
Cited by: 1
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