Study on Safety Training and Exam System Using Neural Network

The research addresses safety training and exam monitoring for power industry field workers, proposing a method based on facial behavior and posture recognition. By combining facial features with an improved neural network, a head behavior recognition system was designed, enhancing accuracy and real-time performance using deep information and Lie group spatiotemporal feature extraction. Posture recognition was improved through wireless body area networks and advanced neural networks, addressing signal transmission and classification issues. While the study achieved breakthroughs in accuracy and performance, it remains sensitive to environmental factors and has room for improvement in data processing and training efficiency. Future work could optimize algorithm robustness, improve system adaptability, and incorporate multimodal analysis for better recognition accuracy.