Smart classroom teaching is one of the new teaching methods. With the support of technology, teaching is carried out with the help of smart teaching tools to enhance teacher-student communication, enhance students’ learning autonomy, and provide new ideas for the realization of students’ deep learning. How to promote the overall intelligence of the teaching environment so that the teaching equipment can be used more efficiently and managed more effectively has become the main concern of schools. This article mainly studies the smart classroom system based on the Internet of Things technology and smart classroom. For temperature detection, we mainly use the DS18B20 chip to detect the temperature in the classroom. For the light intensity of the classroom, we use a photoresistor to collect the light data, and after amplification by the amplifier, the A/D sampling process of the single-chip microcomputer is used to obtain the light intensity, combined with the clock module to distinguish the influence of the classroom light. The data collection adopts the method of directly observing the source data, and the data format has not undergone secondary conversion, which ensures the accuracy of the source data. This test uses the USR-TCP232 network debugging assistant to debug the data collection. To optimize the safety and reliability of the system, dual-computer backup switching is adopted on the hardware, and process monitoring and management strategies are adopted on the software. At the same time, the amount of data interaction in the smart classroom is relatively large, so it is necessary to build a highly available cluster server, so that the system not only has a certain degree of stability, but also can quickly respond to users’ access requests. We can calculate that the average transmission time is about 10 ms, and 99.9% of the data transmission delay is less than 30 ms. The results show that the Internet of Things and smart classroom provide great convenience for future smart campus construction, daily teaching, and campus management and can also provide reference for the construction of smart classrooms in other universities.
Research on the Construction of Urban and Rural Planning Land Classification System and Land Type Identification Based on Multi-Source Data of Internet of Things
