Construction of IIoT-Based Smart Education Environment and Innovation of Practical Teaching Mode for Teacher Training Students

In view of the challenges faced by traditional teaching models in the context of digital transformation of education, this study proposes to build a smart education environment based on the industrial Internet and innovate the practical teaching mode of normal students. The research adopts hierarchical system architecture to integrate data collection, edge computing and cloud computing technologies, and focuses on optimizing the support vector machine algorithm to achieve educational data classification and anomaly detection, with an accurate rate of 93.7%. Experimental results show that multimodal data fusion improves the analysis accuracy by 15%, and the real-time feedback delay is controlled within 200 ms, which effectively supports teaching evaluation and behavior analysis.