Global warming and increasing heatwaves elevate the risk of exertional heat illnesses, particularly heatstroke, in endurance athletes and outdoor workers. This study developed and validated a wearable heatstroke warning system integrating physiological and environmental monitoring with a real-time web dashboard. The wrist- and finger-worn prototype comprised an ESP32 microcontroller and heart rate (MAX30101), skin temperature (MAX30205), ambient temperature and humidity (SHT31), and galvanic skin response (Grove-GSR v1.2) sensors with dual acoustic–visual alerts and WiFi transmission. Fifteen triathletes (18–39 years) completed 30 min of cycling in a climatic chamber: 0–15 min at 24 ± 1 °C, 70 ± 10% RH, and 16–30 min at 27 ± 1 °C, 90 ± 10% RH, with the workload rising from 40%HRmax by 10% every 10 min. Heart rate, estimated core temperature, ambient temperature, relative humidity, and GSR were recorded every 30 s and compared with standard devices using Spearman correlation (p = 0.01) and Wilcoxon signed-rank tests (p < 0.05). Heart rate, skin temperature (used a linear model to calculate core body temperature), ambient temperature, and humidity sensors showed fair–very good validity (r = 0.692, 0.995, 0.994, 0.952), while GSR was low (r = 0.298). No significant differences were observed for heart rate, skin temperature, and humidity (p > 0.05), but body temperature (p = 0.003) and GSR (p < 0.001) differed. The system showed promising validity for real-time heatstroke risk monitoring, with further refinement needed for skin temperature and GSR sensing.

This research has developed a heat stroke warning system prototype for athletes utilizing the following sensors: DHT22, GY-906-BAA MLX90614, MAX30102. The device calculates the heat stroke risk and notifies users. The data is recorded, stored, displayed on a free-access website which graphs body temperature, ambient temperature, humidity, heart rate and heat stroke risk, and provides notifications for athletes engaged in outdoor activities. The researchers recorded sensors data (n = 1) for two sessions (12 min/session) in a closed room, at the sixth-minute marker, with an air conditioner activated to observe the changes observed by the sensors. For accuracy, the researchers employed Criterion-Related Validity, comparing sensor against standard equipment measurement. For reliability, we utilized Test-Retest Reliability, comparing sensor data from the first and second measurements. Accuracy and reliability were evaluated using the Pearson Correlation Coefficient, with significance set at p < 0.01. The DHT22 sensor demonstrates very high accuracy (r = 0.923) in ambient temperature and (r = 0.774) humidity measurements. It showed no significant reliability (r = 0.489) in temperature and (r = 0.185) humidity measurements. The GY-906-BAA MLX90614 sensor exhibited very high accuracy (r = 0.923) and reliability (r = 0.866) in body temperature measurements. The MAX30102 sensor lacked significant accuracy (r = 0.179) and reliability (r = 0.171) in heart rate measurements. The development of accuracy and reliability of sensors are important for preventing heat stroke in future applications.