Design and Application of Track and Field Sports Teaching and Training Intensity Monitoring System Based on Wireless Sensor Technology

This study designs and validates a wireless sensor network (WSN) system for the objective, continuous quantification of training intensity in track and field. The system integrates wearable inertial and heart rate sensors, transmitting data via a low-power LoRa (Long Range) network to a cloud platform. Machine learning algorithms classify activities and compute intensity metrics like PlayerLoad™ and Training Impulse (TRIMP). In a 12-week study with 45 university athletes, the system’s intensity metrics show a strong correlation with blood lactate levels (r = 0.92, p < 0.01). The experimental group using the system demonstrates a 15.3% greater improvement in performance times and a 28% reduction in non-functional overreaching compared to the control group, confirming the system’s effectiveness for data-driven training optimization.