IOT-Based Smart Helmet for COVID-19 Detection and Management

Abstract

Covid-19 is one of the pandemics that has shocked the world. Having originated from China, the virus rapidly spread across many countries of the world. There was a need to come up with mechanisms to manage the spread of the virus. The traditional methods of temperature capture through thermal handheld gun thermometers were tedious and exposed the officers to the same virus. Therefore, due to technological advancement, the Internet of Things has been widely used with smart devices being developed. This study proposes an IoT-enabled smart helmet that scans individuals for high temperatures using a thermal camera, identifies individuals by capturing their images using an optical camera, and sends alerts and information to authorized officers’ decision-making and further action. For instance, they would notify the identified individual and give guidelines on how to self-manage based on the COVID-19 management guidelines such as quarantine, exercise, self-distance, handwashing, sanitizing, and dietary needs. The integration of technologies in the smart helmet application is beneficial in addressing safety measures and enhanced healthcare and monitoring of patients. For instance, in crowded areas, manual testing can be challenging hence the need for a contactless screening. The implications in real-time data analysis, concurrency, Human-Computer Interaction, remote monitoring, data security, and interdisciplinary collaboration have enhanced operation and decision-making. The knowledge, once tested, will form the basis for advanced research and implementations in various domains such as manufacturing industries. The methodology involved data capture (input), processing, and output. Materials used include thermal and optical cameras for data input, GSM and Google location applications, Arduino IDE, and mobile phone applications. The study used simulation at a mall's entry point and captured the temperature of 8 individuals. Out of the 8 individuals, 3 had high temperatures whereas the rest registered normal temperatures. Temperature measurements were verified by healthcare personnel through a second measure of temperature.