Undergraduate YPEC 2021

UG18-Thermal camera temperature measurement system using embedded machine learning

Since 2019, COVID-19 has spread among different countries and seriously affected our daily life. To identify people with fever, there are several body temperature measurement methods on the market. However, these methods have different drawbacks on their efficiency, price, or privacy issue. Our project aims to use low-cost and portable hardware to build a body temperature measurement system. Our system has achieved 89.6% face detection accuracy, error of ±1.0°C in temperature readings, and a valid distance of 2.5 meters. The main difference between our system and the existing solution is that our system only captures low-resolution thermal images, and preventing privacy issues. The system captures thermal images through a thermal camera and passes them to a Raspberry Pi, and implements machine learning with the assistance of a USB accelerator in order to detect the position of the human face in the image. Finally, the target’s body temperature can be calculated.