Design of Smart Classroom Monitoring Platform Based on Convolutional Neural Networks
This paper proposes a design of a smart classroom monitoring platform based on Convolutional Neural Networks(CNN),aiming to achieve intelligent recognition of student behavior.The overall design architecture of the platform includes the integration of components such as network cameras,Wi-Fi,servers,displays,and behavior recognition models.In the experimental stage,image data is collected through web crawlers to construct a dataset,and CNN is used to identify student behavior,including multiple states such as gaming,speaking,and sleeping.The experimental results show that this method has good recognition performance and can accurately identify different states of students.
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