Artificial intelligence application to improve the performance of distance learning servers during the coronavirus pandemic threat period

Abstract

As of early 2020, almost all countries are fighting the coronavirus pandemic by implementing the rigorous restrictions recommended by the World Health Organisation to help reduce the number of infections as much as possible. The restrictions also apply to members of the academic community. The universities have suspended all teaching activities - except online. Most universities have introduced solutions for distance learning. However, organisation of distance education requires appropriate technological infrastructure. Providing the right IT infrastructure is not an easy challenge, because network devices and network servers note record-breaking peak loads during this time. It seems that there are potentially many possibilities of using artificial intelligence to improve the performance of distance learning platforms, information systems and network infrastructure in this difficult and demanding period. Examples of such use of artificial intelligence applications are presented in this article. The paper shows that the use of artificial intelligence to improve the operation of distance learning servers is potentially possible in many areas. It is also worth noting that the application of artificial neural networks and LSTM neural networks for this purpose seems very promising. The presentation of sample experiments and obtained results in this article seems to confirm this thesis.