scholarly journals Real-Time Implementation of AI-Based Face Mask Detection and Social Distancing Measuring System for COVID-19 Prevention

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Safa Teboulbi ◽  
Seifeddine Messaoud ◽  
Mohamed Ali Hajjaji ◽  
Abdellatif Mtibaa
Keyword(s):  
Real Time ◽  
Vision System ◽  
Close Contact ◽  
Public Health Problem ◽  
Confidence Score ◽  
Face Mask ◽  
Physical Distance ◽  
Measuring System ◽  
Social Distancing ◽  
The World

Since the infectious coronavirus disease (COVID-19) was first reported in Wuhan, it has become a public health problem in China and even around the world. This pandemic is having devastating effects on societies and economies around the world. The increase in the number of COVID-19 tests gives more information about the epidemic spread, which may lead to the possibility of surrounding it to prevent further infections. However, wearing a face mask that prevents the transmission of droplets in the air and maintaining an appropriate physical distance between people, and reducing close contact with each other can still be beneficial in combating this pandemic. Therefore, this research paper focuses on implementing a Face Mask and Social Distancing Detection model as an embedded vision system. The pretrained models such as the MobileNet, ResNet Classifier, and VGG are used in our context. People violating social distancing or not wearing masks were detected. After implementing and deploying the models, the selected one achieved a confidence score of 100%. This paper also provides a comparative study of different face detection and face mask classification models. The system performance is evaluated in terms of precision, recall, F1-score, support, sensitivity, specificity, and accuracy that demonstrate the practical applicability. The system performs with F1-score of 99%, sensitivity of 99%, specificity of 99%, and an accuracy of 100%. Hence, this solution tracks the people with or without masks in a real-time scenario and ensures social distancing by generating an alarm if there is a violation in the scene or in public places. This can be used with the existing embedded camera infrastructure to enable these analytics which can be applied to various verticals, as well as in an office building or at airport terminals/gates.

scholarly journals Practicing in a pandemic

2020 ◽  
pp. 10.1212/CPJ.0000000000000882 ◽  
Author(s):  
Christopher G. Tarolli ◽  
Julia M. Biernot ◽  
Peter D. Creigh ◽  
Emile Moukheiber ◽  
Rachel Marie E. Salas ◽  
...  
Keyword(s):  
Real Time ◽  
Virus Disease ◽  
Social Distancing ◽  
The Past ◽  
Corona Virus ◽  
The World ◽  
Patient Preparation ◽  
Ongoing Care ◽  
Remote Care

Neurologists around the country and the world are rapidly transitioning from traditional in-person visits to remote neurologic care because of the corona virus disease 2019 pandemic. Given calls and mandates for social distancing, most clinics have shuttered or are only conducting urgent and emergent visits. As a result, many neurologists are turning to teleneurology with real-time remote video-based visits with patients, to provide ongoing care. Although telemedicine utilization and comfort has grown for many acute and ambulatory neurologic conditions in the past decade, remote visits and workflows remain foreign to many patients and neurologists. Here, we provide a practical framework for clinicians to orient themselves to the remote neurologic assessment, offering suggestions for clinician and patient preparation prior to the visit; recommendations to manage common challenges with remote neurologic care; modifications to the neurologic exam for remote performance, including subspecialty-specific considerations for a variety of neurologic conditions; and a discussion of the key limitations of remote visits. These recommendations are intended to serve as a guide for immediate implementation as neurologists transition to remote care. These will be relevant not only for practice today, but also for the likely sustained expansion of teleneurology following the pandemic.

scholarly journals Coronavirus-A Global Emergency

2020 ◽  
Vol 32 (2) ◽  
pp. 138-142
Author(s):  
Md Abdul Ahad
Keyword(s):  
Sore Throat ◽  
Close Contact ◽  
Specific Treatment ◽  
Face Mask ◽  
Human Coronavirus ◽  
Over The Counter ◽  
Hand Sanitizer ◽  
The World ◽  
Medicine Today ◽  
Over The Counter Medicines

Introduction:Coronavirus is a highly infectious contagious virus producing pandemic throughout the world with highmorbidity and mortality. Discussion: Right now, there is no vaccine to prevent human coronavirus infections. But you mayable to reduce your risk of getting or spreading an infection by-washing hands often with soap and water for at least 20seconds, use an alcohol-based hand sanitizer that contains at least 70% alcohol if soap and water are not available. Avoidingtouching your face, nose, or mouth with unwashed hands, use of face mask, avoiding close contact with people who aresick, there is no specific treatment for coronavirus. Conclusion:Treatment aims to relieve the symptoms. Most people willget better on their own. However, you can relieve your symptoms by-taking over-the-counter medicines for pain, fever, andcough. Using a room humidifier or taking a hot shower to help ease a sore throat and cough. Getting plenty of nutritiousdiet, drinking fluids and taking rest. Medicine Today 2020 Vol.32(2): 138-142

A compendium of evidence related to ‘social distancing’measure in view of the spread of COVID-19 pandemic

Healthline ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 120-124
Author(s):  
Anuradha Shah ◽  
Kunal Shah
Keyword(s):  
Public Health ◽  
Close Contact ◽  
Physical Distance ◽  
Physical Contact ◽  
Definitive Treatment ◽  
Infected Person ◽  
Social Distancing ◽  
Influenza Pandemics ◽  
Health Measures

With no definitive treatment in place to date for the COVID-19 pandemic, reliance on public health measures is of utmost importance. Social distancing requires maintaining a physical distance of at least one meter between people and reducing the number of times people come into close contact with each other. Modeling evidence from past influenza pandemics and current experiences with COVID-19 indicates the role of SD in delaying the spread of the virus by reducing the probability that uninfected person will come into physical contact with an infected person.

Covid-19 and Older Adults: The Paradox of Control Measures

2021 ◽  
Vol 8 (3) ◽  
pp. 303-305
Author(s):  
Anthony Obinna Iwuagwu ◽  
Christopher Ndubuisi Ngwu
Keyword(s):  
Mental Health ◽  
Older Adults ◽  
Well Being ◽  
Face Mask ◽  
Control Measures ◽  
Infection Prevention And Control ◽  
Public Health Issue ◽  
Social Distancing ◽  
Main Challenge ◽  
The World

It is no longer news that Covid-19 pandemic has become a major public health issue around the world and affected day to day activities of public life. Medical experts around the world were overwhelmed by the Covid-19 virus outbreak and for a long time were unable to provide a vaccine or any pharmaceutical treatment. Countries were therefore forced to adopt unprecedented Infection Prevention and Control (IPC) measures to mitigate the spread and impact of the virus. These measures which are non-pharmacological includes, social distancing, social isolation, lockdown, constant washing of hands, wearing of face mask and protective gloves etc. However, these measures aimed at protecting the health care systems, have had some side effects on the health and well-being of older adults. In this letter, we have highlighted social distancing as the main challenge and a paradox for older peoples wellbeing during the Covid-19 pandemic outbreak. The merits of the IPC measures notwithstanding, its long and short term consequences for the mental health of older adults calls for concern. Among other recommendations, professionals of ageing and geriatrics are recommended to help set a balance in IPC measures and mental health of older people in this Covid-19 era.

scholarly journals Helping the Blind to Get through COVID-19: Social Distancing Assistant Using Real-Time Semantic Segmentation on RGB-D Video

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5202
Author(s):  
Manuel Martinez ◽  
Kailun Yang ◽  
Angela Constantinescu ◽  
Rainer Stiefelhagen
Keyword(s):  
Real Time ◽  
Semantic Segmentation ◽  
Physical Distance ◽  
Assistive Devices ◽  
Prototype System ◽  
Blind People ◽  
Audio Feedback ◽  
Daily Lives ◽  
Social Distancing ◽  
Depth Cameras

The current COVID-19 pandemic is having a major impact on our daily lives. Social distancing is one of the measures that has been implemented with the aim of slowing the spread of the disease, but it is difficult for blind people to comply with this. In this paper, we present a system that helps blind people to maintain physical distance to other persons using a combination of RGB and depth cameras. We use a real-time semantic segmentation algorithm on the RGB camera to detect where persons are and use the depth camera to assess the distance to them; then, we provide audio feedback through bone-conducting headphones if a person is closer than 1.5 m. Our system warns the user only if persons are nearby but does not react to non-person objects such as walls, trees or doors; thus, it is not intrusive, and it is possible to use it in combination with other assistive devices. We have tested our prototype system on one blind and four blindfolded persons, and found that the system is precise, easy to use, and amounts to low cognitive load.

scholarly journals Implementing a real-time, AI-based, people detection and social distancing measuring system for Covid-19

2021 ◽  
Author(s):  
Sergio Saponara ◽  
Abdussalam Elhanashi ◽  
Alessio Gagliardi
Keyword(s):  
Body Temperature ◽  
Embedded System ◽  
Smart Cities ◽  
Close Contact ◽  
Ground Truth ◽  
Measuring System ◽  
Surveillance Video ◽  
People Detection ◽  
Social Distancing ◽  
Thermal Cameras

AbstractCOVID-19 is a disease caused by a severe respiratory syndrome coronavirus. It was identified in December 2019 in Wuhan, China. It has resulted in an ongoing pandemic that caused infected cases including many deaths. Coronavirus is primarily spread between people during close contact. Motivating to this notion, this research proposes an artificial intelligence system for social distancing classification of persons using thermal images. By exploiting YOLOv2 (you look at once) approach, a novel deep learning detection technique is developed for detecting and tracking people in indoor and outdoor scenarios. An algorithm is also implemented for measuring and classifying the distance between persons and to automatically check if social distancing rules are respected or not. Hence, this work aims at minimizing the spread of the COVID-19 virus by evaluating if and how persons comply with social distancing rules. The proposed approach is applied to images acquired through thermal cameras, to establish a complete AI system for people tracking, social distancing classification, and body temperature monitoring. The training phase is done with two datasets captured from different thermal cameras. Ground Truth Labeler app is used for labeling the persons in the images. The proposed technique has been deployed in a low-cost embedded system (Jetson Nano) which is composed of a fixed camera. The proposed approach is implemented in a distributed surveillance video system to visualize people from several cameras in one centralized monitoring system. The achieved results show that the proposed method is suitable to set up a surveillance system in smart cities for people detection, social distancing classification, and body temperature analysis.

scholarly journals Gastro Coronavirus: A new era

Mediscope ◽  
2020 ◽  
Vol 7 (2) ◽  
pp. 117-125
Author(s):  
Md Abdul Ahad
Keyword(s):  
Close Contact ◽  
Specific Treatment ◽  
Face Mask ◽  
High Morbidity ◽  
Human Coronavirus ◽  
Over The Counter ◽  
New Era ◽  
Hand Sanitizer ◽  
The World ◽  
Over The Counter Medicines

Coronavirus is a highly infectious contagious virus producing pandemic throughout the world with high morbidity and mortality. Right now, there is no vaccine to prevent human coronavirus infections. But you mayable to reduce your risk of getting or spreading an infection by-washing hands often with soap and water for at least 20 seconds,using an alcohol-based hand sanitizer that contains at least 70% alcohol if soap and water are not available, avoiding touching your face, nose, or mouth with unwashed hands,use of face mask, avoiding close contact with people who are sick.There is no specific treatment for coronavirus. Treatment aims to relieve the symptoms. Most people will get better on their own. However, you can relieve your symptoms by-taking over-the-counter medicines for pain, fever, and cough&plenty of nutritious diet, drinking fluids and taking rest. Mediscope Vol. 7, No. 2: July 2020, Page 117-125

scholarly journals Face Mask Detection System

2021 ◽  
Vol 9 (VII) ◽  
pp. 1400-1402
Author(s):  
Yatharth Khansali
Keyword(s):  
Real Time ◽  
Detection System ◽  
Face Mask ◽  
World Health ◽  
Public Places ◽  
The World ◽  
The Face ◽  
Time Requirements ◽  
Health Organization ◽  
Protective Mask

COVID-19 pandemic has affected the world severely, according to the World Health Organization (WHO), coronavirus disease (COVID-19) has globally infected over 176 million people causing over 3.8 million deaths. Wearing a protective mask has become a norm. However, it is seen in most public places that people do not wear masks or don’t wear them properly. In this paper, we propose a high accuracy and efficient face mask detector based on MobileNet architecture. The proposed method detects the face in real-time with OpenCV and then identifies if it has a mask on it or not. As a surveillance task, it supports motion, and is trained using transfer learning and compared in terms of both precision and efficiency, with special attention to the real-time requirements of this context.

scholarly journals An Integrated Approach for Monitoring Social Distancing and Face Mask Detection Using Stacked ResNet-50 and YOLOv5

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 2996
Author(s):  
Inderpreet Singh Walia ◽  
Deepika Kumar ◽  
Kaushal Sharma ◽  
Jude D. Hemanth ◽  
Daniela Elena Popescu
Keyword(s):  
Social Distance ◽  
Surveillance System ◽  
Integrated Approach ◽  
Face Mask ◽  
Safety Measures ◽  
Social Distancing ◽  
The People ◽  
The World ◽  
Video Feed ◽  
Key Aspects

SARS-CoV-19 is one of the deadliest pandemics the world has witnessed, taking around 5,049,374 lives till now across worldwide and 459,873 in India. To limit its spread numerous countries have issued many safety measures. Though vaccines are available now, still face mask detection and maintain social distance are the key aspects to prevent from this pandemic. Therefore, authors have proposed a real-time surveillance system that would take the input video feed and check whether the people detected in the video are wearing a mask, this research further monitors the humans for social distancing norms. The proposed methodology involves taking input from a CCTV feed and detecting humans in the frame, using YOLOv5. These detected faces are then processed using Stacked ResNet-50 for classification whether the person is wearing a mask or not, meanwhile, DBSCAN has been used to detect proximities within the persons detected.

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