Table 1.

Chronological summary of the works to be compared with the proposed approach. The table shows the approach, the main highlights, and disadvantages. In addition, if any of these works related their application to an IoT system

Works	Approach	Advantages	Disadvantages	IoT system
Ayan and Ünver [1]	Transfer Learning + Fine-tuning	The authors used data augmentation	The number of images for training is 8.3 more than those used for testing	No
Kermany et al. [18]	Transfer learning	The authors effectively classified the images for macular degeneration and diabetic retinopathy. Also, it obtained satisfactory results for pneumonia, although this is not the focus of the article	The number of images for training is 8.3 more than those used for testing	No
Rahimzadeh et al. [27]	Concatenation of Xception and ResNet50V2	Concatenation of Xception and ResNet50V2	The authors use images from COVID-19. Consequently, classes become unbalanced	No
Chouhan et al. [4]	Five different pre-trained architectures + majority vote classification	The results indicate that deep learning methods can be used to simplify the pneumonia diagnosis process	The authors affirm the need to evaluate the most sophisticated deep networks. At work, only five nets were used	No