Automatic Facial Mask Rule Violation Detection using Keras & Tensorflow to Limit COVID-19

COVID-19 is a pandemic disease that spread by itself coming in the contact of people. It was initially started from China and now it has been spread all over the world and many casualties have been occurred. Social distancing commonly known as physical distancing is a non-pharmaceutical approach through which it can be reduced. But social distancing only works when people started wearing mask because it can spread by sneezing even having distance among people. So wearing mask is mandatory to stop spreading this virus at its possible extent. In this paper, it has been intended to identify the people who are wearing mask or not. By the help of CCTV camera it can be recognized at the entrance of various public places such as mall, airport, railway station, mart and many more. If facial mask can be recognized effectively with high level of accuracy then it can become mandatory for people who are violating the rules. The proposed system uses Keras and Tensorflow model for identifying whether people are following the rule or not. Tensorflow is a deep learning methodology through which facial mask can be detected with all kind of situations. Proposed system is able to classify whether a person wear a mask or not, it is also able to identify whether people incorrectly wearing mask i.e. partial wearing. It is mandatory to identify whether people are properly using the mask or not. System identify this kind of situation and classified them accordingly. System uses hybrid technique by combining two algorithms i.e. keras and tensorflow. By combining both the systems it can be identified more precisely to identify the rule violations. Keywords: COVID-19, Facial Mask, Convolutional Neural Network, Classifiers, Machine Learning, Image Processing, Pattern Recognition.

Synonyms and Symptoms of COVID-19 and Individual and Official Actions against the Disease—A Brief Online Survey 6 Months into the Pandemic and on the Threshold of the Second Wave in Germany

To control the ongoing global pandemic due to SARS-CoV-2, we need to influence people’s behavior. To do so, we require information on people’s knowledge and perception of the disease and their opinions about the importance of containment measures. Therefore, in August 2020, we conducted an anonymous cross-sectional online survey on these topics in 913 participants in Germany. Participants completed a questionnaire on various synonyms and symptoms of corona virus and specified the importance they attributed to individual and regulatory measures. The virus was linked more closely with most synonyms and the discovery in China than with the places of the first larger European outbreaks. General (cold-like) symptoms, such as “cough” and “fever,” were more widely known than COVID-19-specific ones, e.g., “loss of taste and smell.” The widely promoted individual measures “distancing,” “hygiene,” and “(facial) mask wearing” were rated as highly important, as were the corresponding official measures, e.g., the “distancing rule” and “mask mandate.” However, the “corona warning app” and a “vaccine mandate” were rated as less important. A subgroup analysis showed broad agreement between the subgroups on nearly all issues. In conclusion, the survey provided information about the German population’s perception and knowledge of the coronavirus five months into the pandemic; however, participants were younger and more educated than a representative sample. To learn from the beginning and still ongoing pandemic and develop concepts for the future, we need more conclusive studies, especially on the acceptance of further specified lockdowns, the population’s willingness to be vaccinated, and the influence of misinformation on public opinion.

FORMULATION AND EVALUATION OF PEEL OFF GEL FACIAL MASK FROM ARABICA COFFEE FRUIT PEEL EXTRACT (COFFEA ARABICA L.)

Objective: The aim of this study was to obtain a peel off gel facial mask preparation from Arabica coffee fruit peel extract that meets the requirements and to determine the antioxidant activity of Arabica coffee fruit peel extract and peel off gel facial mask preparation from coffee fruit peel extract Methods: In this study, three formulations of peel off gel facial mask were made with 3 variations in the concentration of coffee fruit peel extract, namely F1 (1%), F2 (2%), and F3 (3%). Furthermore, the preparation was evaluated for 28 d of storage at room temperature (25-30 °C) and cold temperature (8 °C) which included organoleptic, pH, spreading ability, homogeneity, viscosity, dry time, and antioxidant activity. Results: The results of the evaluation showed that F1, F2, and F3 met the requirements which included organoleptic, pH, spreading ability, homogeneity, viscosity, and dry time. The antioxidant activity of the coffee fruit peel extract was very strong (IC50 17.36 µg/ml). The antioxidant activity in the peel off gel facial mask sample of formula F1 (IC50 75.63 µg/ml) and formula F2 (IC50 50.71 µg/ml) was strong, and for formula F3 was very strong (IC50 21.44 µg/ml). Conclusion: All formulas met the evaluation requirements, arabica coffee fruit peel extract and peel of gel facial mask preparation (F3) have very strong antioxidant activity.

Use of Artificial Intelligence for Face Detection with Face Mask in Real Time to Control the Entrance to an Entity

Due to the pandemic caused by Covid-19, daily life has changed significantly. For this reason, biosecurity measures have been implemented to prevent the spread of the virus as an effective way to reactivate economic activities. In this sense, the present paper focuses on real-time face detection as a measure of control at the entrance to an entity, thus avoiding the spread of the virus while recognizing the identity of workers despite the use of masks and thus reducing the risk of entry of individuals outside the organization. Therefore, the objective is to contribute to the security of a company through the application of machine learning methodology. The selection of methodology is justified due to the adaptation of the same according to the interests of this project. Consequently, algorithms were used in a progressive manner, obtaining as a result the control system that was intended, since each particularity of the face of the individual was recognized in relation to its corresponding identification. Finally, the results of this article benefit the security of organizations regardless of their field or sector. Keywords— Control, Detection, Facial Recognition, Facial Mask, Face recognition, Machine learning.

Social Distancing for Covid-19 Monitoring System

The battle of corona-virus and mankind is possible to be tackled as long as we maintain the basic norm of social distancing and wearing masks amongst ourselves as it is through our droplets from the respiratory tract that the virus spreads. With the increasing demand for man-force and people requiring to go to their workplaces post lockdown, it is very necessary that we save each other from the virus. In this project, we will go through a detailed explanation of how we can use Python, AI and Deep Learning to monitor social distancing at public places and workplaces are keeping a safe distance from each other by analyzing real-time video streams from the camera and also detect facial mask monitoring using OpenCV and Python. To ensure if people are following social distancing protocols in public places and workplaces, we wanted to develop a tool that can monitor if people are keeping a safe distance from one another, wearing masks or not by processing real-time video footage from the camera. People at workplaces, factories, shops can integrate this tool into their security camera systems and can monitor whether people are keeping a safe distance from each other or not along with that we detect facial mask monitoring using Python with help of haar-cascade algorithm to see whether a person is wearing a mask or not. We are also planning to include thermal screening detection to measure the temperature of the subjects, a dashboard which will display a live report of corona cases around the world. We will also include an alert system that will send a notification to the authorities if the social distancing is not followed or if the temperature exceeds the threshold. The authorities can take suitable measures to isolate the subject and thus prevent the spread of Covid-19.