Research on Laboratory Construction and Management Based on Internet of Things and Deep Learning

Author:

Cao Min

Abstract

A computer laboratory intelligent management and control system based on Internet of Things technology and deep learning is proposed to address the shortcomings of traditional university laboratory management.The system adopts the main embedded technology, mobile communication technology, wireless sensor technology and database storage technology in the Internet of Things technology, laboratory areas and equipment, identify and collect relevant data, monitor abnormal conditions in real time, and alarm. At the same time, the user is provided with a preview of the experimental content and a demonstration of the results through the handheld client APP. The experimental results show that: when the system is powered by 0.35A current, the total system power is about 3W. The NTC thermistor used has a B value of 3435. Under normal temperature, T2 = 298.15K,R = 10KΩ,R0 = 10KΩ. The current temperature value can be calculated according to the value obtained after the analog-to-digital conversion of the microcontroller. The output frequency of the humidity detection circuit is measured by the single-chip microcomputer, and the current ambient humidity can be obtained by substituting the result into the above formula, that is, when the output frequency dimension of the circuit is 6853Hz, the ambient humidity is 40%. Through the application of this system, the inefficient and extensive manual management method of the computer experimental teaching center is completely solved, so that it can bring more intelligent and efficient services to the teachers and students of the whole school, so as to comprehensively promote the experimental teaching of the school.

Publisher

Scalable Computing: Practice and Experience

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