IoT based anti covid visitor management system using Raspberry pi zero W

Abstract

The Covid-19 health protocol is a regulation by government to feel safer doing activities during Covid-19 pandemic. Generally, spread of Covid-19 occurs in public places, one of which is a shop. By building an Internet of Things (IoT) system that is expected to be able to detect early on the potential for someone to contract Covid-19 by detecting body temperature and mask when entering a store. The study proposes the development of a visitor management system by utilizing a camera to detect faces and measure temperature using an infrared thermometer sensor that is triggered using an ultrasonic proximity sensor so that it can run efficiently on raspberry pi zero with limited resources. Face detection is carried out using the haar cascade classifier which is optimized to work in real-time on the raspberry pi zero and displays the results on the web interface which is also installed on the raspberry pi zero. The research proposes an integrated system that is low-cost using raspberry pi and tested in real shops. Shop owners can see people who have the potential for Covid-19 and customers who are wrong/not wearing masks, using IoT functions to send data between sensors so that shop owners can monitor website-based systems. From the test results, the success rate of tools and algorithms is 78.38% of data that successfully detects temperature and masks, then there are 29.62% of data that fail to detect masks and temperatures. The data is then recorded in a JSON file which will be displayed into a website-based information system.