Prevention of the Spread of Viral Disease Using Artificial Intelligence from Data Obtained by UAVs

University of Pardubice, Faculty of Economics and Administration, Institute of System Engineering and Informatics, Studentská 84, 532 10 Pardubice, Czech Republic

^* Corresponding author: katerina.prihodova@student.upce.cz

Abstract

Research background: One of the significant globalization consequences is a threat of rapidly spreading communicable diseases. In recent months, COVID-19 has spread worldwide. It is a highly infectious disease, which is manifested mainly by fever, respiratory problems, muscle pain and fatigue. Therefore, there is a need to reliable monitor people’s body temperature. If the monitoring process takes places in enclosed spaces, the procedure may be performed at the entrance to the building. However, the problem occurs in public spaces. Therefore, to solve this problem, we propose the use of a drone with a thermal camera for scanning people in public spaces and subsequent evaluation using classification methods.

Purpose of the article: The aim of this article is to create a model for sensing and measuring the body temperature of people in public spaces so that the global impacts of COVID-19 on the economy and society are reduced.

Methods: To monitor large areas, it is necessary to have suitable methods for obtaining quality data. One of the methods for obtaining data with the high spatial resolution is the use of UAVs with a planned flight. Artificial intelligence methods will be used for the classification of persons; their representatives are, e.g. convolutional neural networks.

Findings & Value added: The proposed model of sensing and subsequent classification of people into groups (normal body temperature, elevated body temperature). The output of the model will help to monitor the spread of infectious diseases (the condition is a symptom - increased body temperature) in today’s globalized world.