IoT based Face Mask Detection System
Minal Suresh Patil, Shital Telrandhe, Ajay Mawaskar, Rupesh Gharde, Abhishek A. Madankar, Manthan Sawarkar · 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS) · 2022
The COVID-19 virus was first reported in December 2019 in China. Since then, it has created havoc on global level by causing health and financial crisis. The novel corona virus is continuously evolving into new variants of virus and still spreading in every part of the world. The virus is spread mostly by the droplets transferring from the infected person to an uninfected person. The only direct method of preventing such transfer of droplets can be done by washing of hands, avoiding contact with nostrils, eyes and mouth. Only complete vaccination of citizens can help in containment of virus till then use of face mask and social distancing has been made mandatory by authorities. This project proposes a contactless face mask detection model based on machine learning and image processing technology. It will follow the protocols of social distancing. This project will be helpful in accurately identifying whether a person is wearing a mask properly or not. This model can be easily installed in the entrance of ATMs, malls, educational institutions, offices and in the entrance of public offices. Being a contact less model it will effectively reduce the need of having a manual way of detection and will reduce the spreading of disease to further people. It is highly effective and cheap model as all the tools required for this project are free of cost and easily available online. Proposed model can be easily used on low end computers like Raspberry Pi. The model will encourage people to continuously wear mask in correct manner.