Abstract
Photoelectric sensor, with its high sensitivity and global instantaneous communication ability, has become an important technical support in intelligent higher education. The background of this research is the rapid development of higher education, the rapid progress of intelligent technology and the popularization and application of 5G computing network. This paper investigates how photoelectric sensors can be used to achieve more efficient teaching and learning methods in intelligent higher education. A 5G computer network model including initial mapping model and migration mapping model is constructed. The initial mapping model compresses and encrypts the data before sending, and converts it into a format suitable for transmission in the network, ensuring the security and transmission efficiency of the data. The migration mapping model performs secondary processing on the data when it arrives at the receiving end and converts it into the format acceptable to the receiving end to ensure that the data can be properly received and processed. The findings suggest that photoelectric sensors can be used for real-time monitoring and feedback during the teaching process to provide more accurate assessment results, thereby improving the quality of teaching, and can also be applied to virtual laboratories and distance education to provide students with a wider range of practical and learning opportunities.
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Lu, C. Application of optoelectronic sensors based on 5G computing networks in the development of intelligent higher education. Opt Quant Electron 56, 348 (2024). https://doi.org/10.1007/s11082-023-06002-1
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DOI: https://doi.org/10.1007/s11082-023-06002-1