(untitled) (Jurnal Teknologi (Sciences & Engineering), 2021)
The unprecedented outbreak of novel coronavirus 2019 (COVID-19) globally has a huge impact to our daily life in numerous ways. To effectively minimize the spread of the virus, early symptom detection is crucial, especially in closed environment with high human traffic areas which post higher chances of human-to-human transmission. Body temperature measurement has been identified among the vital monitoring parameters. However, current available temperature monitoring mechanism is costly, limited to single individual and limited to locally without integrating to cloud and database. This led to difficulty in effective surveillance for suspicious COVID cases. Hence, the purpose of this paper is to introduce an end-to-end Internet of Things-enabled application for thermal monitoring as an early signal detection and screening method. This work integrates Raspberry Pi, thermal sensor, LCD display, buzzer, and LED light with Raspbian and Restful API for device-to-cloud communication. The system implemented is capable for user identification, body temperature remote monitoring and warning signal for fever symptoms. The result of this real-time system is capable to detect and screen the suspected contagious person in an organization effectively. Future works on integrating face recognition with machine learning and artificial intelligent enhancement.