  This paper presents the development of an intelligent system for the
detection of coronavirus using artificial neural network. This was done after
series of literature review which indicated that high fever accounts for 87.9%
of the COVID-19 symptoms. 683 temperature data of COVID-19 patients at >= 38C^o
were collected from Colliery hospital Enugu, Nigeria and used to train an
artificial neural network detective model for the detection of COVID-19. The
reference model generated was used converted into Verilog codes using Hardware
Description Language (HDL) and then burn into a Field Programming Gate Array
(FPGA) controller using FPGA tool in Matlab. The performance of the model when
evaluated using confusion matrix, regression and means square error (MSE)
showed that the regression value is 0.967; the accuracy is 97% and then MSE is
0.00100Mu. These results all implied that the new detection system for is
reliable and very effective for the detection of COVID-19.

Machine Learning;Artificial Intelligence