Co-Yudh: A Convolutional Neural Network (CNN)-Inspired Platform for COVID Handling and Awareness

Abstract

The COVID-19 pandemic has been a menace to the World. According to WHO, a mortality rate of 1.99% is reported as of 28th November 2021. The need of the hour is to implement certain safety measures that may not eradicate but at least put a restriction on the rising number of COVID-19 cases all over the World. To ensure that the COVID-19 protocols are being abided by, a Convolutional Neural Network (CNN)-based framework “Co-Yudh” is being developed that comprises features like detecting face masks and social distancing, tracking the number of COVID-19 cases, and providing an online medical consultancy. The paper proposes two algorithms based on CNN for implementing the above features such as real-time face mask detection using the Transfer Learning approach in which the MobileNetV2 model is used which is trained on the Simulated Masked Face Dataset (SMFD). Further, the trained model is evaluated on the novel dataset—Mask Evaluation Dataset (MED). Additionally, the YOLOv4 model is used for detecting social distancing. It also uses web scraping for tracking the number of COVID-19 cases which updates on a daily basis. This is an easy-to-use framework that can be installed in various workplaces and can serve all the purposes to keep a check on the COVID-19 protocols in the area. Our preliminary results are quite satisfactory when tested against different environmental variables and show promising avenues for further exploration of the technique. The proposed framework is a more improved version of the existing works done so far.

Face Mask Detection in Smart Cities Using Deep and Transfer Learning: Lessons Learned from the COVID-19 Pandemic

“…obileNetv2: everal works employ MobileNetv2 [144,[147][148][149][150][151] and similar detectors such as NASNetMobile [152]. In [153], an FMD technique that employs MobileNetv2 as a basis and performs transfer learning has been proposed and tested on SMFD. In [154], a MobilNetv2-based FMD solution is developed and compared with YOLOv3.…”

Classification of Mask Use during a Pandemic using the CNN Algorithm with Voice Notifications

“…Problems occur because many people violate the 5M policy, one of which is wearing a mask. So this research created a system that can detect the use of masks, inappropriate masks and not on the face with sound notifications [5] [6] [7]. The goal is to be able to make people more comply with regulations and break the chain of transmission of Covid-19.…”