Face Recognition and Temperature Data Acquisition for COVID-19 Patients in Honduras

Abstract

Honduras health workers are reduced; doctors and nurses are getting infected by COVID-19. The primary purpose of this project is the design and development of software that performs facial recognition and temperature registration for patients. The incremental model was used to develop the software. The algorithm was trained with 5 images per face for the first test and 10 images per face for the second, with a total sample of 80 participants. At a maximum distance of 1.4 meters from the camera, the system obtained 72% and 82% accuracy for each of the tests. Finally, the authors conclude that the system can be implemented in health areas such as laboratories, hospitals, and clinics so that contact between patients and doctors can be reduced.