Machine learning based thermal response study of university students under summer outdoor military training

Key Points

• Physiological stress levels increased significantly during outdoor military training sessions, indicating vulnerability to heat.
• Key metrics showed that students experienced temperature increases during training, averaging 4.2 degrees Celsius over two hours.
• Analysis of thermal response data utilized machine learning algorithms to predict heat stress outcomes in real-time.
• Findings highlight the importance of adaptive training protocols for university students engaged in outdoor activities.