DETECTION OF FACE MASK USING DEEP LEARNING

2021 ◽  
Vol 1 (9) ◽  
pp. 161-168
Author(s):  
Manak Bansal ◽  
Manaswi Manaswi ◽  
Pankaj Kumar ◽  
Jyoti Kaushik
Keyword(s):  
Infected Individual ◽  
Face Mask ◽  
Practical Application ◽  
Public Places ◽  
Railway Stations ◽  
The Great Depression ◽  
Global Recession ◽  
Specificity And Sensitivity ◽  
Area Unit ◽  
Severe Health Problem

As we know, the COVID-19 pandemic additionally referred to as the coronavirus pandemic, is an ongoing pandemic of coronavirus sickness since 2019. This infectious disease was first detected in Wuhan, China in late 2019. Symptoms of COVID-19 are highly variable, ranging from none to severe health problem. The virus spreads chiefly through the air when individuals are close to one another. It transmits from an infected individual through the droplets as they breathe, cough, sneeze or speak and these droplets then enters another individual via their mouth, nose, or eyes. It might also spread via contaminated surfaces. Individuals stay infectious for up to 2 weeks and can spread the virus albeit they do not have symptoms. As of 1st November 2021, more than 200 million cases are confirmed, with more than 500 million deaths due to COVID-19. The pandemic has been the reason for global social and economic disruption, including the largest global recession since the Great Depression. The recommended preventive measures include social distancing, carrying a mask publicly, ventilation and air-filtering, hand washing, covering one‟s mouth when sneezing or coughing and self-isolation for individuals exposed. In present endeavour therefore, the author has attempted to make one thing associated with it, that's deciding whether a dividual is carrying a mask or not. The complete investigations area unit distributed in various chapters that embody the current thesis. The performance of our model will be evaluated in precision, accuracy, recall, specificity, and sensitivity that demonstrate the practical application of this model. The system performs with an accuracy of 99.88%, precision of 99.49%, sensitivity of 99.77%, and specificity of 99.6. Thus, this model tracks if people are using masks or not in real-time using a device camera. This model can be used with the current camera infrastructure to enable this tool which can be used in various public places such as markets or railway stations or offices etc. Keywords: Covid-19, Face Mask Detection, Convolutional Neural Network, MobileNetV2, Precaution.

scholarly journals Face Mask Detection System using Deep Learning

2020 ◽  
Vol 6 (12) ◽  
pp. 161-164
Author(s):  
Pinki and Prof. Sachin Garg
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Learning Algorithm ◽  
Detection System ◽  
Face Mask ◽  
Video Stream ◽  
Public Places ◽  
Railway Stations ◽  
Deep Learning Algorithm ◽  
Safety Guidelines

In the present scenario due to Covid-19, there is no efficient face mask detection applications which are now in high demand for transportation means, densely populated areas, residential districts, large-scale manufacturers and other enterprises to ensure safety. This system can therefore be used in real-time applications which require face-mask detection for safety purposes due to the outbreak of Covid-19. This project can be integrated with embedded systems for application in airports, railway stations, offices, schools, and public places to ensure that public safety guidelines are followed. To identify the person on image/video stream wearing face mask or not. If the person doesn’t wear a mask, the notification will be sent to the respected admin with the help of Python and deep learning algorithm by using the Convolutional Neural Network, Keras Framework and OpenCV.

FACE MASK DETECTION ALERT SYSTEM

2021 ◽  
Vol 1 (10) ◽  
pp. 364-368
Author(s):  
Samrat Bhardwaj ◽  
Neha Agrawal ◽  
M L Sharma
Keyword(s):  
Large Scale ◽  
Learning Algorithm ◽  
Face Mask ◽  
Video Stream ◽  
Alert System ◽  
Public Places ◽  
Railway Stations ◽  
Deep Learning Algorithm ◽  
Safety Improvement ◽  
Safety Guidelines

In the present scenario due to Covid-19, there are no efficient face mask detection applications which are now in high demand for transportation means, densely populated areas, residential districts, large-scale manufacturers and other enterprises to ensure safety. This system can therefore be used in real-time applications which require face-mask detection for safety purposes due to the outbreak of Covid-19. This project can be integrated with embedded systems for application in airports, railway stations, offices, schools, and public places to ensure that public safety guidelines are followed. To identify the person on image/video stream wearing face mask or not. If the person doesn’t wear a mask, the notification will be sent to the respected admin with the help of Python and deep learning algorithm by using the Convolutional Neural Network, Keras Framework and OpenCV. Keywords: Computer Vision, Object Detection, Object Tracking, COVID-19, Face Masks, Safety Improvement

scholarly journals A Survey on Covid Safety System

2021 ◽  
Vol 9 (11) ◽  
pp. 589-593
Author(s):  
Hinal Sodagra
Keyword(s):  
Body Temperature ◽  
Face Mask ◽  
Raspberry Pi ◽  
Infrared Sensor ◽  
Shopping Malls ◽  
Solution System ◽  
Public Places ◽  
Hand Sanitizer ◽  
Security Clearance ◽  
Python Programming

Abstract: In this paper a Raspberry Pi based automated solution system focused on the real-time face monitoring of people to detect both face masks and body temperature with the help of MLX90614 sensor has been proposed. This is implemented using Python Programming with OpenCV Library, TensorFlow, Dlib Module. A security clearance system is deployed that will allow that person to enter if they are wearing a face mask and their body temperature is in check with WHO guidelines. A programmed hand sanitizer apportioning machine is mechanized, non-contact, liquor-based hand sanitizer gadget. Liquor is essentially a dissolvable, and furthermore a generally excellent sanitizer when contrasted with fluid cleanser or strong cleanser, likewise it needn't bother with water to wash off since it is unpredictable furthermore, disintegrates in a split second after application to hands. It is too demonstrated that a convergence of >70% liquor can execute Covid in hands. Here, we have used IR sensor detects the hand put close to it, the Arduino Uno is utilized as a microcontroller, which detects the distance and the outcome isthe pump starts running out the hand sanitizer. Thus, the above said system will help the society by saving time and also helps in contaminating the spread of coronavirus. This can be implemented in public places such as colleges, schools, offices, shopping malls, etc. to inspect people. Keywords: Deep Learning, Open CV, Keras, Python, Tensor Flow, Computer Vision, Raspberry Pi, COVID-19, DLib, Arduino, Sensor, Sanitizer, Infrared sensor

Research of High-Speed Railway Running Economic Benefit Based on Gray Model

2012 ◽  
Vol 253-255 ◽  
pp. 1273-1277
Author(s):  
Xue Dong Du ◽  
Na Ren
Keyword(s):  
Data Analysis ◽  
Prediction Model ◽  
Economic Benefit ◽  
High Speed ◽  
Accurate Prediction ◽  
Gray Model ◽  
Practical Application ◽  
High Speed Railway ◽  
Railway Stations ◽  
Train Operation

The research of high-speed railway running economic benefit is important to timely know well the train operation state for the railway administration. A prediction model of high-speed railway running economic benefit is proposed in this article based on Gray model. The Gray model is a good example to make accurate prediction of the development of matters. According to the data analysis of Beijing and Shanghai railway stations, we can know that the result of prediction model is accurate, so the prediction based on Gray model is scientific and reasonable in the practical application.

The Global Recession of 2007–2009: The Moral Factor and Jewish Law

2010 ◽  
pp. 403-428
Author(s):  
Aaron Levine
Keyword(s):  
United States ◽  
The United States ◽  
Mortgage Market ◽  
Jewish Law ◽  
Subprime Mortgage ◽  
The Great Depression ◽  
Global Recession ◽  
United States Economy ◽  
Moral Factor ◽  
Home Mortgage

This article focuses on the recent global recession that raged the world and in particular the United States with special reference to Jewish law. In December 2007, the United States economy plunged into the longest and deepest downturn since the Great Depression. The driving force behind the recession was the widespread failure of the subprime mortgage market, the segment of the home mortgage market extending loans to households with impaired credit histories and with little or no documentation of income. The collapse of that sector occurred in a rapid succession of events beginning with the fall of Countrywide Financial in January 2008. This article further moves to explain the moral factor pervading the recession and analyses the situation as per Jewish law. The central relevant moral dictum of Jewish law is the Imitatio Dei principle, which says that, in our interpersonal conduct, we should emulate the various attributes of mercy.

scholarly journals Introduction: Household Finances under Pressure: What is the Role of Social Policy?

2011 ◽  
Vol 11 (1) ◽  
pp. 67-68
Author(s):  
Ricky Joseph ◽  
Karen Rowlingson
Keyword(s):  
Social Policy ◽  
Budget Deficit ◽  
Financial Inclusion ◽  
Coalition Government ◽  
Asset Building ◽  
Trust Fund ◽  
Household Finances ◽  
The Great Depression ◽  
Global Recession

This themed issue examines household finances within the context of the 2007 banking crisis, which triggered the biggest downturn in many global economies since the Great Depression in the 1930s. The effects of this crisis and subsequent global recession were still unfolding at the time the articles of this issue were submitted to the journal. The election of the coalition government in May 2010, and its emergency budget aimed at reducing the nation's budget deficit, precipitated the biggest reduction in public sector funding in living memory. Rising unemployment and the increasing cost of living means that for many households even greater strain has been placed on their finances. Other developments, such as the winding-up of the Treasury Financial Inclusion Taskforce and the axing of asset building policies, for example the Child Trust Fund and Saving Gateway, had, to some, signalled an end to the consensus in government that had been built up around the financial inclusion agenda, and had left a big gap in social policy.

scholarly journals Realtime Face-Mask Detection on Raspberry Kit

2021 ◽  
Vol 9 (8) ◽  
pp. 2076-2083
Author(s):  
Kalyan Chakravarthi. M
Keyword(s):  
Face Recognition ◽  
Recognition Performance ◽  
Real Life ◽  
Face Mask ◽  
Recognition System ◽  
Primary Concern ◽  
Public Places ◽  
Life Problems ◽  
Promising Area ◽  
The Face

Abstract: Recognition from faces is a popular and significant technology in recent years. Face alterations and the presence of different masks make it too much challenging. In the real-world, when a person is uncooperative with the systems such as in video surveillance then masking is further common scenarios. For these masks, current face recognition performance degrades. Still, difficulties created by masks are usually disregarded. Face recognition is a promising area of applied computer vision . This technique is used to recognize a face or identify a person automatically from given images. In our daily life activates like, in a passport checking, smart door, access control, voter verification, criminal investigation, and many other purposes face recognition is widely used to authenticate a person correctly and automatically. Face recognition has gained much attention as a unique, reliable biometric recognition technology that makes it most popular than any other biometric technique likes password, pin, fingerprint, etc. Many of the governments across the world also interested in the face recognition system to secure public places such as parks, airports, bus stations, and railway stations, etc. Face recognition is one of the well-studied real-life problems. Excellent progress has been done against face recognition technology throughout the last years. The primary concern to this work is about facial masks, and especially to enhance the recognition accuracy of different masked faces. A feasible approach has been proposed that consists of first detecting the facial regions. The occluded face detection problem has been approached using Cascaded Convolutional Neural Network (CNN). Besides, its performance has been also evaluated within excessive facial masks and found attractive outcomes. Finally, a correlative study also made here for a better understanding.

scholarly journals The mask dilemma: unmasking the myths and facts

2020 ◽  
Vol 8 (1) ◽  
pp. 453
Author(s):  
Varsha Narayanan
Keyword(s):  
Health Care ◽  
Economic Burden ◽  
Disease Transmission ◽  
Scientific Evidence ◽  
Face Mask ◽  
Mass Vaccination ◽  
Morbidity And Mortality ◽  
Public Places ◽  
The People ◽  
Practical Guidelines

Coronavirus 2019 (COVID-19) has been spreading across the globe in 2020 with most countries being affected significantly in terms of the number of infected cases, morbidity and mortality, as well as health care and economic burden. Currently the most important individual and community measures for curtailing disease transmission are social distancing, hand sanitization and wearing of masks in public. It is important to advocate wearing masks in an effective and balanced manner and dispense supportive scientific evidence as well as practical guidelines and information in the community. Till the event of mass vaccination for COVID being available, improving the awareness, compliance and acceptance of the people towards proper wearing of a face mask when in public places, can be the most effective way for several countries to control transmission of COVID. 

scholarly journals Face Mask Detection in Real-Time using MobileNetv2

2021 ◽  
Vol 10 (6) ◽  
pp. 104-108
Author(s):  
Mohamed Almghraby ◽  
◽  
Abdelrady Okasha Elnady* ◽  
Keyword(s):  
Real Time ◽  
Face Mask ◽  
Stochastic Gradient Descent ◽  
Training Dataset ◽  
Optimization Approach ◽  
Public Places ◽  
Application Systems ◽  
Develop Software ◽  
Video Feed ◽  
Maximal Peak

Face mask detection has made considerable progress in the field of computer vision since the start of the Covid-19 epidemic. Many efforts are being made to develop software that can detect whether or not someone is wearing a mask. Many methods and strategies have been used to construct face detection models. A created model for detecting face masks is described in this paper, which uses “deep learning”, “TensorFlow”, “Keras”, and “OpenCV”. The MobilenetV2 architecture is used as a foundation for the classifier to perform real-time mask identification. The present model dedicates 80 percent of the training dataset to training and 20% to testing, and splits the training dataset into 80% training and 20% validation, resulting in a final model with 65 percent of the dataset for training, 15 percent for validation, and 20% for testing. The optimization approach used in this experiment is “stochastic gradient descent” with momentum (“SGD”), with a learning rate of 0.001 and momentum of 0.85. The training and validation accuracy rose until they reached their maximal peak at epoch 12, with 99% training accuracy and 98% validation accuracy. The model's training and validation losses both reduced until they reached their lowest at epoch 12, with a validation loss of 0.050% and a training loss of less than 0.025%. This system allows for real-time detection of someone is missing the appropriate face mask. This model is particularly resource-efficient when it comes to deployment, thus it can be employed for safety. So, this technique can be merged with embedded application systems at public places and public services places as airports, trains stations, workplaces, and schools to ensure subordination to the guidelines for public safety. The current version is compatible with both IP and non-IP cameras. Web and desktop apps can use the live video feed for detection. The program can also be linked to the entrance gates, allowing only those who are wearing masks to enter. It can also be used in shopping malls and universities.

scholarly journals Comparison of an Air-Fed Mask System with Hospital-Issued Personal Protection Equipments for Dental Aerosol Protection During the COVID-19 Pandemic

2021 ◽  
Vol 15 (1) ◽  
pp. 742-747
Author(s):  
John B. Bridgman ◽  
Andrew L. Newsom ◽  
David J. Chrisp ◽  
Abi E. Estelle ◽  
Mark Saunders
Keyword(s):  
High Speed ◽  
Infected Individual ◽  
Face Mask ◽  
External Source ◽  
Low Flow ◽  
Test Model ◽  
Viral Shedding ◽  
Dental Instruments ◽  
Test Conditions ◽  
The Face

Aim: A pilot study was conducted with the aim of developing a system to protect the eyes, nose, and mouth from the aerosol generated from a high-speed dental handpiece during the COVID-19 pandemic. Background: The SARS-CoV-2 virus is known to be present in the saliva of an infected individual during the contagious viral shedding phase of the disease. The use of rotary dental instruments places oral health practitioners at risk of contracting COVID-19 from infected individuals. In particular, it is very difficult to protect the mucous membranes of the face against the extremely fine aerosol produced from a high-speed dental handpiece. Objectives: This study aimed to develop and test a novel PPE system for use during the COVID-19 pandemic. An air-fed spray-painting mask was used under a plastic hood to protect against the aerosol from a high-speed dental handpiece. This was found to be superior compared to hospital-issued N-95 masks and eye protection in our test model. Methods: Subjects donned various forms of PPE whilst using a high-speed dental handpiece in a confined cubicle. The efficacy of each form of PPE was evaluated by adding fluorescein to the water coolant supply line of a high-speed dental handpiece before checking for facial contamination with an ophthalmology slit lamp. Results: Under our test conditions, the N-95 mask did not prevent nasal and mouth contaminations, but the combination of an air-fed mask with a sealed hood prevented these contaminations. Although goggles worn tightly did prevent contamination, the air-fed mask system was far more comfortable and did not fog up. Discussion: Under the rigorous test conditions of our model, we found hospital-issued PPE ineffective. We also found the single strategy of using positive airflow into a face mask ineffective, even with extremely high levels of airflow. Complete protection was only achieved reliably by the combination of physically sealing off the face from the surrounding airspace and using the air-fed system to provide an external source of air to breathe. We effectively made the clinical equivalent of a dive bell helmet. The air-fed mask is supplied by a standard dental air compressor and is simple to install for someone familiar with the technical aspects of compressors. The compressor does not rely on a filter and proves effective with cheap and easily accessible disposable items. Conclusion: Under rigorous testing conditions, the developed air-fed mask system with a sealed hood on low flow performed better than hospital-issued PPE against high-speed dental aerosol protection. The developed system protects the operators from the air of the room contaminated with aerosol and brings in safe air from the outside for them to breathe.

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