Automatic Early Detection System of Feverish Infectious Diseases in Indoor Public Areas
Leonardo Gianto, Titan H. Rukmana, Steven I. Surya, Yoanes Bandung · 2023
This paper introduces a 3-layer IoT architecture designed to automatically detect and identify individuals with feverish infectious diseases in indoor public areas. The architecture comprises the sensing layer, edge computing, and cloud computing components. Sensor modules capture facial images and body temperature, which are wirelessly transmitted to an edge device through MQTT for identification using machine learning techniques. Subsequently, the data is forwarded to a cloud server through HTTPS for storage, feedback generation, and presentation to authorized users. Each subsystem is meticulously designed to meet its specifications. We conclude the prototype's design and implementation are successful within a controlled condition. The proposed system is also viable for future developments such as attendance management, airport security, and others. However, the design and implementation process also exhibits certain limitations, notably concerning the reliability and uptime of the sensory module.