• Nehul Chaudhari
• Prathamesh Raut
• Sarang Satpute
• Umang Sangani
• Prof. Amit Uttarkar

The corona-virus COVID-19 pandemic is a global health crisis. Covid-19 virus is transferred between two people through the airborne transmission. One of the effective protection methods is wearing a face mask in public areas, which has been imposed as a compulsory measure to prevent the transmission all over the world . Also, temperature and oxygen level monitoring are the additional ways of monitoring of visitors. Manual monitoring of the face mask, temperature and oxygen level in congested and thronged places is a tedious task. The corona-virus epidemic has given rise to an extraordinary degree of worldwide scientific cooperation. Machine learning and Deep Learning can help to tackle Covid-19 pandemic in many ways. . Existing face detection system needs more enhancement and modifications to solve real world problems. In this paper we have implemented face-mask detection using the CNN algorithm and MobilenetV2 architecture, and we have also implemented face-recognition over the mask in our system. We are going to use Open-CV to do real-time face detection from a live stream via a camera, and then we are going to pass these frames(images) to our mask detector classifier to find out if the person is wearing a mask or not. After performing mask detection, the system will perform facerecognition over the mask to identify the visitor. Then we have used MLX90614 infrared temperature sensor for temperature check and MAX30100 Pulse oximeter for oxygen level check. ViAC will be highly beneficial for contact-less monitoring purpose and thus reducing the risk of guards to get infected and eliminating the tedious task of monitoring visitors. We have achieved 98% accuracy in face-mask detection.

Machine Learning, Neural Network, Deep Learning, Convolutional Neural Network, Computer vision

"Implementation of Visitor Analysis for Covid-19 using Machine Learning and IOT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 7, page no.a366-a371, July-2021, Available :http://www.jetir.org/papers/JETIR2107046.pdf

"Implementation of Visitor Analysis for Covid-19 using Machine Learning and IOT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 7, page no. ppa366-a371, July-2021, Available at : http://www.jetir.org/papers/JETIR2107046.pdf