THERMOSYS - identification system of feverish people by means of images in the visible and thermal spectrum

• Grant number: 20/04986-1
• Support Opportunities: Research Grants - Innovative Research in Small Business - PIPE
• Start date: May 01, 2020
• End date: October 31, 2021
• Field of knowledge: Interdisciplinary Subjects
• Agreement: FINEP - PIPE/PAPPE Grant
• Principal Investigator: Raphael Pereira Moreno
• Grantee: Raphael Pereira Moreno
• Company: Opto Tecnologia Optrônica Ltda
• CNAE: Fabricação de equipamentos e instrumentos ópticos, fotográficos e cinematográficos
• City: São Carlos
• Associated research grant(s): 20/06651-7 - THERMOSYS - identification system of feverish people by means of images in the visible and thermal spectrum, AP.PIPE

Abstract

In the context of the crisis that is plaguing us because of the COVID-19 infection, a system that can select suspected febrile conditions in places of great crowding is imperative. The proposal is for the development of an intelligent imaging system in the visible and thermal spectrum that processes the relative data to identify suspected infection. For this, the company is using its experience in multispectral systems and products in its defense portfolio, calibrating them, adapting them and developing the necessary algorithms for this new desired functionality.The system will be formed by cameras in the visible and thermal spectra mounted on a cabinet that can be installed in crowded places. The system will be connected to a platform with algorithms optimized for face detection processing, identification of measurement points and temperature evaluation routines compensating for environmental variables.Prototypes will be made incrementally. Initially with thermal modules of simple acquisition and software operating in laboratory conditions. Thus, adapting the characteristics for the system to operate in the desired function. Then, the modules will be replaced by sensors manufactured by Opto S&D, optimized for the temperature range of interest. In the same way that the first algorithms will be worked in more controlled conditions (distance, temperature and ambient humidity) and then migrating to more diverse conditions in which the system can be used. (AU)