International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 05 | May 2022
p-ISSN: 2395-0072
www.irjet.net
ACCESS CONTROL SYSTEM USING FACE MASK DETECTION USING ARTIFICIAL INTELLIGENCE Nachiket Dhavale, Akshada Chavan, Nishant Bhosale Dept. of Computer Engineering Late G.N. Sapkal College of Engineering Nashik, Maharashtra, India- 422213 ---------------------------------------------------------------------***---------------------------------------------------------------------
Therefore, not only risk his own life, but also several people who might come into contact with this person knowingly/unknowingly. This module uses artificial intelligence to automatically detect a person with/without a mask and sets off an alarm when a person is detected without wearing a mask.
Abstract -The covid-19 pandemic, is causing a worldwide
emergency in health protection. This virus mainly targets our lungs and spreads through respiratory droplets which come out from he/she infected with coronavirus and give risk others. The transmission gets huge risk in public places or in crowded places. The after-lockdown period has seen increase in cases day by day as people have now stepped out of their home to resume their work and recreational activities. The natural human tendency is to be complacent and take off the mask when talking, working or after using it for a long time, just use it to relax and breathe properly. And as per the reports in India, only 14 percent of the population correctly wears their mask. So, our project that falls in the combined domains of Artificial Intelligence and the Internet of things. In this project, we propose a method to detect face masks on people and consequently control a person's access to a facility/premise. Our system uses computer vision to analyzed and determine whether the person in question is wearing a face mask or not. Further, the output of the recognition module/system will be used to control access/entry to a facility/premise. This system will be implemented on a real-time basis, meaning that it will control the aforementioned access in real time without having to make a person wait. This will be made possible with the help of microcontrollers/microprocessors such as the Arduino Uno. The model that is trained and used for detection will be stored locally to ensure real-time processing. This will help prevent people from entering public places such as malls, cinema theatres, offices, hospitals, schools, colleges, etc. without a mask.
2. OBJECTIVES • Face Mask Detection Model Training: A default OpenCV module was used for obtaining faces, followed by a Keras model for identifying face masks. • Detecting persons who aren't wearing masks: Using the database, an open CV model was trained to recognize the names of people who aren't wearing masks. The system is designed to regulate the motor that connects the doors in public areas such as malls, theatres, schools, parks, and other public spaces. This motor will not be able to open doors and let that individual in because of the face-mask detecting system.
3. BRIEF DESCRIPTION Because the offices/establishment is now open to the public, a mask detection module is required. As a result, persons can currently walk freely in and out of establishment/office locations. According to ICMR norms, everyone (Mandatory) must wear a face mask. It is a natural human instinct to put on the mask prior to inspection (in/out gate controlled by sentries) and remove it thereafter (just to relax and breathe easily). This is clearly a breach of safety precautions and Social Distancing rules. Body temperature can be monitored with a thermal thermometer at entry/points, and the status of the Aarogya setu app can be checked, but this does not guarantee that the person is Covid positive/negative. As a result, the person cannot move freely without wearing Masks. Moreover Sentries/guards cannot be stationed at every corner of the establishment to keep an eye on persons who remove their mask and stroll around freely unnoticed, expecting that no one will be able to capture them once they have passed through a sentryguarded gate. This module will detect if persons are entering the campus with or without a mask, and
Keywords: COVID-19, Face Mask, Image Processing, Computer Vision, Arduino Uno Artificial Intelligence, Micro controller.
1. INTRODUCTION The COVID19 pandemic has greatly affected people's lives, causing millions of people loss. Complacency tends to infiltrate people to adhere to restrictions/councils established for an extended time and subsequently, they manipulate their own diluted version of the instructions to better adapt to their comfort levels. Therefore, it sneaks into the trend to remove the mask according to their convenience and wear it again according to their comfort.
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