An Automated Facemask Detection For Covid-19 Using Viola-Jones Algorithm

Corona Virus Disease (Covid-19) is a label species of the Corona virus family. It can cause a variety of illnesses, from the ordinary cold to advanced respiratory syndromes like Middle-East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). This virus is highly contagious and spreads due to the droplets produced by coughing and sneezing. Though there are several ways to prevent the transmission of Covid-19, one of the most important and effective way is using a face mask or a face shield. In this paper, we constructed face mask detection framework using Viola-Jones algorithm in order to recognize whether an individual is wearing a mask or not. This algorithm includes the selection of Haar features of a face, integral image creation, adaptive boost training and cascading. An extensive study is carried out in order to analyze the performance of the proposed approach;we use a large facial image dataset from the publicly available MAFA dataset. The results indicate the proposed method can accurately identify face mask wearing images with a classifier accuracy of 98.26%, suggesting it might be useful in Covid-19 prevention. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

Integrated Cloud Security for Data Storage and Access

During the COVID-19 pandemic, cloud computing & storage emerged as a viable alternative to traditional storage systems. Almost all firms are transitioning from traditional modes of operation to online modes of operation. The vast majority of businesses have the long-term goal of moving all or a significant part of their operations to an online (Work-from-Home) format. There are various advantages to cloud computing and storage, including cost savings, mobility, platform independence, accessibility, and elasticity. However, security is the primary impediment to adopting cloud storage services, particularly cloud retrieving. To address the issue of cloud storage security, this research study has proposed a method for cloud storage data security. The suggested strategy makes use of integrated cryptographic techniques to monitor, secure user as well as data that is kept in the cloud storage systems. The method that has been suggested constantly checks user data by performing the sequence of securities. The performance of proposed security is measured by downloading and uploading data iteratively and analyzed by computing time taken for cloud operations. Thus, the proposed strategy not only secures data but also increases user confidence in cloud-based storage services. The proposed approach can be further researched for dynamic data and variable data sizes. © 2022 IEEE.