Intelligent user interfaces for Industry 4.0: Improving workplace security by systematically applying machine learning and image processing to identify face mask usage

The word "expression" suggests intent. The term "express" can be connoted as implied or imputed within. An emotion might be just a glance at someone's face which denotes a reaction. Reaction brings expression. In other words, expressiveness by someone refers to the way of communicating one's feelings. According to research and surveys, humans use 55–57 percent of body languages, 38 percent of tones or tonal variations, and the rest as words to convey meanings in messages for communication. It is also a proven fact that a significant part of the expression is in the form of nonverbal communication. There is sufficient evidence in psychology, pharmacology, and other fields to justify the same. Humans generally communicate through verbal expressions in response to inputs received, which is essential for our daily lives. However, word meanings can sometimes be challenging to detect the purpose accurately thereby necessitating good face recognition. Therefore it would be prudent to have face recognition made automatically and also effectively. In the present study, a facial emotion detection system seems to work correctly. The paper combines A.I. with image processing for such detection. Here Face-recognition software may be able to show the emotions that were captured by a camera. This article offers features related to this detection that has a over 90% success rate. The COVID-19 pandemic redefined the safety protocols of industries necessitating strict adherence to ‘wearing face masks while at work’. The method shown in the paper can thus be used to ensure strict adherence by all employees in the new normal scenario evading any verbal instruction for such compliance.