IoT and Fuzzy Logic Applied to Smart Public Hall for COVID-19 Monitoring System

Abstract

Purpose: Since the breakout of COVID-19 pandemic, various preventive measures have been put in place by WHO to prevent the spread of this disease. However, some people are unaware or less likely to follow rules regarding hygiene, physical distancing, properly wearing of face mask and body temperature measurement. One of the best solutions to this challenge is the introduction of the internet of things (IoT) technology to assist in implementation of the preventive measures. This paper presents an IoT-enabled solution that uses Fuzzy logic controller to assess the risks of being COVID-19 infected and monitor environment conditions in the public hall to limit the spread of the coronavirus. 
 Methodology: The proposed model employed sensors to measure in real-time the body temperature, hand sanitization, wearing of face mask, room ventilation and IP camera controlled by Fuzzy logic controller for decision making. In addition, it uses raspberry-pi for processing and data transmission to the cloud, liquid crystal display (LCD) for displaying data and web application was developed for user interface. The resulting sensor measurements were simulated using MATLAB software and the system made automatic decisions.
 Findings: A prototype was implemented effectively and the results obtained from the system were fast, accurate, efficient and cost effective when compared to other commercially available systems.
 Unique Contribution to Practice: The actual practice for implementing the preventive measures require the presence of the health care personnel (HCP) which is time consuming and risky for HCP. Therefore, this system works autonomously and effectively in monitoring and controlling the implementation of the COVID-19 preventive measures in the public hall.