In response to the demand for high-quality electronic information talents in the mobile network industry, in the situation of artificial intelligence (AI) to promote technological innovation, this paper conducts an overall design in the target system, curriculum system, teaching platform, teaching mode and teaching case. The practice education mode of teaching practice, engineering practice, innovation practice, and enterprise practice, which aims to improve students’ ability to solve complex engineering problems, is constructed. The mode breaks geographical boundaries between schools and enterprises to build the through-through experimental teaching course system based on artificial intelligence and edge computing and design a medical image intelligent analysis system project case based on Mobile Edge Computing (MEC), which improves students’ practical ability, engineering design ability, scientific research innovation ability, enterprise practice ability and mobile network application capabilities. At the same time, the hardware portability of the edge computing platform provides good conditions for long-distance education and the mobile network. This method is a beneficial attempt to cultivate high-level, diversified, and creative electronic information talents.
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This work is supported by the National Natural Science Foundation of China (62001137); the National Key Research and Development Program of China under Grant 2018AAA0102702; the Natural Science Foundation of Heilongjiang Province (JJ2019LH2398); the Fundamental Research Funds for the Central Universities (3072020CFT0801). All of the authors declare that there is no conflict of interests regarding the publication of this article.
We would like to thank the reviewers for their useful discussions and suggestions.
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Hou, C., Hua, L., Lin, Y. et al. Application and Exploration of Artificial Intelligence and Edge Computing in Long-Distance Education on Mobile Network. Mobile Netw Appl (2021). https://doi.org/10.1007/s11036-021-01773-x
- Artificial intelligence
- Mobile network industry
- University-enterprise cooperation
- Through-through experimental teaching
- Long-distance education