Information‐centric networking driven psychology recognition and health conduction of undergraduates

Abstract

It is considerably significant to recognize the psychology of undergraduates especially during the period of COVID‐19 outbreak. This letter proposes an Information‐Centric Networking (ICN) driven psychology recognition and health conduction method based on the active data collection mode, that is, all undergraduates submit their psychology data to manger without protest by the special sensor tool. Meanwhile, the involved undergraduates and the management center construct a large network model. In order to support the mobility of undergraduates, this letter exploits ICN paradigm to help the management and transmission of psychology data. In addition, this management center deploys Deep Belief Network (DBN) to analyze the submitted psychology data. Finally, this letter makes a practical simulation on campus, and the experimental results show that the proposed psychology control method not only has good recognition effect but also contributes to health conduction. To be specific, the proposed method can improve about 2.6% psychology recognition accuracy and decrease about 46.5% psychology recognition time.