Framework for Efficient Resource Planning in Pandemic Crisis - Petrovic, Nenad; Kocic, Djordje (Ss Cyril and Methodius University in Skopje, Faculty of Computer Science and Engineering, Republic of North Macedonia, 2020)
Pandemics have dramatic consequences, both taking human lives and ruining economy leading towards crisis worldwide. It has also been the case with COVID-19 pandemic since the beginning of this year. In this paper, we present a framework aiming efficient resource planning during the pandemic crisis, making use of modelling, simulation, predictions based on deep learning, linear optimization and blockchain. As a case study, we target the current COVID-19 pandemic. According to the achieved results, the proposed framework has not only huge potential in cost reduction, but also enables the proactive approach to tackle the pandemic which can save many lives as well.
Keywords: blockchain, deep learning, coronavirus, COVID-19, linear optimization, modelling, simulation