基于边缘学习和联邦学习的新冠肺炎(COVID-19)高校防控管理模型研究

COVID-19 University Prevention and Control Management Model Based on Edge Learning and Federal Learning

作为新冠肺炎疫情所有信息的重要入口,互联网成为这次疫情主要的“信息源”平台。在这场疫情阻击战中,能否以计算机技术为依托,融合多种算法深度挖掘和实时跟踪全网数据,从高校管理侧打造防疫战线,发挥计算机技术战“疫”价值?本文运用了边缘学习和联邦学习两项计算机技术,设计出一个针对高校新冠肺炎疫情防控的管理模型。通过边缘计算能够迅速得出分析结果,从而精准实施新冠肺炎防控措施。通过联邦计算可以在保证每位师生的信息安全前提下,快速分析高校所收集的师生数据,从而及时安排相应的防疫措施,避免新冠肺炎疫情进一步扩散。

As an important entrance to all the information about the corona virus disease,the internet has become the main"information source"platform for this epidemic.In this epidemic blocking battle,can we rely on computer technology,integrate multiple algorithms to deeply mine and track the entire network of data in real time,build an epidemic prevention front from the management side of universities,and bring the value of computer technology to the epidemic?This paper used edge learning and federal learning to design a management model for the prevention and control of corona virus disease in universities.The edge learning calculation can quickly obtain the analysis results and quickly implement the corona virus disease prevention measures.Through the federal learning technology,under the premise of ensuring the information security of each teacher and student,analysis can be made based on the teachers and students’data collected by universities,so as to reasonably arrange corresponding preventive measures and prevent the further spread of the corona virus disease epidemic.