Face Mask Wearing Detection for Entrance Authorization

Authors

  • Hidayah Samian
  • Munirah Ahmad Azraai UTHM
  • Mohd Ridhwan Abdul Rani UTHM
  • Azmanirah Ab Rahman UTHM

Keywords:

Standart Operating Procedures, Ministry of Health, Liquid Crystal Display

Abstract

Face Mask Wearing Detection Device for Entrance Authorization is to discipline each individual to wear a face mask. It is one of the easiest methods to lower the rate of corona virus infection and save lives. This novel Coronavirus (2021- nCoV) is very easy to affect every individual and it can also be fatal especially to individuals with chronic diseases such as asthma, high blood pressure, heart failure and many more. Therefore, this study aims to ensure that face mask wearing detection devices for entry into premises can help reduce the rate of Novel Coronavirus (2021- nCoV) infection in premises or public places by ensuring customers comply with Standard Operating Procedures (SOP) set by the Ministry of Health (MOH). For example, when a customer enters a premises, this device will detect the customer’s face whether they are wearing a face mask or not. This device can also help to comply with the maximum limits of customers in the premises. This project aims to build a facial recognition device. The project uses technology designed as an individual aid and follows the SOP at this critical time. The project was developed using the Engineering Design Process development model which has four phases namely (1) identifying the problem, (2) making possible solutions, (3) prototype development and (4) testing and evaluating the product. The results show that the developed product can work well. In addition, three experts also agreed that this product can help discipline each individual to wear a face mask. However, in terms of design, this product still has room for improvement so that the quality of this product can be enhanced. In this writing, on the whole the developed product is able to function well and achieve the set objectives.

Downloads

Published

04-10-2022

Issue

Section

ELECTRIC AND ELECTRONIC

How to Cite

Samian, H., Ahmad Azraai, M., Abdul Rani, M. R., & Ab Rahman, A. . (2022). Face Mask Wearing Detection for Entrance Authorization. Research and Innovation in Technical and Vocational Education and Training, 2(2), 257-268. https://publisher.uthm.edu.my/periodicals/index.php/ritvet/article/view/7154