PROTOTYPE OF MASK RECOGNITION AND BODY TEMPERATURE IN REAL TIME WITH AMG8833 THERMAL CAM SENSOR FOR COVID-19 EARLY WARNING BASED ON MINICOMPUTER

Malik, Muchamad and Burhanuddin, Aan and SETYOADI, YURIS PROTOTYPE OF MASK RECOGNITION AND BODY TEMPERATURE IN REAL TIME WITH AMG8833 THERMAL CAM SENSOR FOR COVID-19 EARLY WARNING BASED ON MINICOMPUTER. KURVATEX.

Text PROTOTYPE OF MASK RECOGNITION AND BODY TEMPERATURE IN REAL TIME WITH AMG8833 THERMAL CAM SENSOR FOR COVID-19 EARLY WARNING BASED ON MINICOMPUTER.pdf Download (3MB)

Abstract

On April 19, 2020, the Republican Covid Task Force declared that the Covid-19 pandemic was a national disaster in Indonesia. At that time it was confirmed that there were 6575 cases and an increase of 5.23% compared to the previous day, then there were 5307 people in treatment which increased by 5.55% compared to the previous day, it was reported that 582 people died, which increased by 8.79 % compared to the previous day, and 686 recovered patients. WHO reports that the case fatality rate (CFR) or the death rate of Covid-19 cases in Indonesia reached 8.3%, which is twice the world's CFR. In this study, the main focus is to detect masks and body temperature used by visitors with various variations of masks on the market today, and next is to control the servo motor according to the detection conditions whether using a mask in real-time. Based on research on the system that has been tested, it shows that the components used to generate heat are very effectively used and can work as expected, and the MobilenetV2 method applied to the Raspberry Pi as the brain of the system can work as expected and has an accuracy rate of 99%. The AMG8833 sensor can read effectively at a maximum distance of 30 cm, the temperature reading deviation level is 0.1⁰C.

Actions (login required)

View Item