Abstract
This paper implements a wisdom classroom management system. In response to the difficulties of traditional campus equipment management, this system can automatically collect the status of electrical appliances in the classroom and analyze the data to provide equipment status diagnosis and early warning functions. At the same time, the Raspberry Pi provides a visual 3D management interface for the terminal. In addition, the system also introduces the voice recognition function in deep learning to control the equipment in the classroom more conveniently.
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