Development of Intelligent Information System to Screen the Wearing of Masks by Machine Learning Combined with the Internet of Things

Abstract

The objectives of this research are: 1) to analyze, design and develop an intelligent information system to screen the wearing of masks by machine learning combined with the internet of things, and 2) to determine the effectiveness of the development of intelligent information system to screen the wearing of masks by machine learning combined with the internet of things. Data used in machine learning are 700 pictures of faces of people without masks, 750 pictures of faces of people wearing masks. The research tools consisted of development tools, experimental tool and data collecting tool. Development tools include the arduino IDE teachable machine and visual studio code. Experimental tool is the intelligent information system to screen the wearing of masks by machine learning combined with the internet of things developed with HTML, JavaScript, CSS, and C++. Data collecting tool is system efficiency evaluation form. Research methodology can be classified into 6 steps: 1) preliminary study, 2) system requirements determination, 3) system design, 4) system development, 5) system testing, and 6) system evaluation by three purposively selected experts. The findings from this research are: 1) the intelligent information system to screen the wearing of masks by machine learning combined with the internet of things can be performed well, and 2) the efficiency of the proposed system evaluated by three experts is in highest level (x =4.74, S.D.=0.33).