The Safety Scanner
Ensure proper mask usage while avoiding human contact and possible exposure.
Pitch Video
Thesis Statement
The Safety Scanner detects whether a mask is being worn properly when entering public places. It utilizes a sophisticated neural network to determine what portion of the face is covered and communicates the information to a LED display.
Abstract
As the pandemic progressed it was necessary to wear masks whenever in public to prevent the spread of COVID-19. At times it could be tedious and even unsafe to have a designated checker ensuring that all entering a public space wear their masks properly. To make entering public spaces safer and make mask checking more efficient, we developed a face mask detection system called The Safety Scanner. We utilized machine learning to craft a neural network and train it on a dataset of thousands of pictures. A facial recognition algorithm was then applied to the trained model which can then analyze a continuous feed. As new strains of the virus emerged, proper mask usage in public places only became more essential. The Safety Scanner eliminates the risk of transmission in public places while also making the need for a human checker stationed at entrances obsolete. Unlike similar tools, The Safety Scanner is inexpensive, easily accessible, and user-friendly. It can be used in markets, airports, hospitals, schools, and more. It is easy to install and use, even for young children. The Safety Scanner is a vital tool to keep everyone safe until the pandemic ends.