scholarly journals Facemask Detection With an Alarm System and Email Notification Using Deep Learning to Prevent Spread of COVID-19

Author(s):  
Vinita Sankla ◽  
Savitanandan Patidar ◽  
Vishal kushwaha ◽  
Ashish Bagwari ◽  
Rahul Tiwari ◽  
...  

Abstract COVID-19 is one of the most dangerous viruses which caused a pandemic in human life, not only in terms of direct casualties but also regarding socio-economic impact. The outbreak quickly spread around the world. The 1st anniversary of the global Corona virus pandemic gets passed away in 2021, but still, no way to tell how long the pandemic will continue. After analyzing a report by WHO of covid-19, to minimize the rate of covid-19 transmission, our national government advised citizens to wear face masks. A model using deep learning and MobileNetV2 for face mask detection is presented. This method was trained and checked on the real-time dataset. There are 3,833 images in the Medical Masks Dataset, including 1918 images of people wearing no mask and 1915 images of people wearing masks. We adopted OpenCV to detect faces in real-time from a live stream captured with our webcam. With the aid of computer vision and deep learning, we hope to classify whether or not the person in the video stream is wearing a face mask. If the camera captures a face without a mask an Email notification will be sent out to the administrator and the system alarm will ring.

Author(s):  
Prod. Roshan R. Kolte

Abstract: COVID-19 pandemic has rapidly affected our day-to-day life the world trade and movements. Wearing a face mask is very essentials for protecting against virus. People also wear mask to cover themselves in order to reduce the spread of covid virus. The corona virus covid-19 pandemic is causing a global health crisis so the effective protection method is wearing a face mask in public area according to the world health organization (WHO). The covid-19 pandemic forced government across the world to impose lockdowns to prevent virus transmission report indicates that wearing face mask while at work clearly reduce the risk of transmission .we will use the dataset to build a covid-19 face mask detector with computer vision using python,opencv,tensorflow,keras library and deep learning. Our goal is to identify whether the person on image or live video stream is wearing mask or not wearing face mask this can help to society and whole organization to avoid the transfer of virus one person to antother.we used computer vision and deep learning modules to detect a with mask image and without mask image. Keywords: face detection, face recognition, CNN, SVM, opencv, python, tensorflow, keras.


2021 ◽  
Vol 1916 (1) ◽  
pp. 012077
Author(s):  
M Sujaritha ◽  
S Kabilan ◽  
M Manikandan ◽  
S Nanda Kisore
Keyword(s):  

Author(s):  
Phakawat Pattarapongsin ◽  
Bipul Neupane ◽  
Jirayus Vorawan ◽  
Harit Sutthikulsombat ◽  
Teerayut Horanont

2020 ◽  
pp. 147-158
Author(s):  
Asantha Senevirathna

 COVID-19 pandemic has become a major crisis in 2020. The pandemic has claimed thousands of lives and is spreading a negative economic impact around the global economy. The pandemic has caused a devastating impact on human life in many of the countries without a clear distinction among developed or developing nations. Sri Lanka is facing the heat of the pandemic gradually since January and has taken various measures to combat the situation. The COVID-19 pandemic forwarded a greater challenge to Sri Lanka since the country has faced various disasters in the recent past and question marks remain about the government’s response. The Sri Lankan government response to the current COVID-19 crisis has been largely successful and is ranked among the best responsive countries in the world. This paper discusses Sri Lanka’s strategies in dealing with COVID-19 pandemic and possible future challenges related to the issue.


2021 ◽  
Vol 336 ◽  
pp. 07004
Author(s):  
Ruoyu Fang ◽  
Cheng Cai

Obstacle detection and target tracking are two major issues for intelligent autonomous vehicles. This paper proposes a new scheme to achieve target tracking and real-time obstacle detection of obstacles based on computer vision. ResNet-18 deep learning neural network is utilized for obstacle detection and Yolo-v3 deep learning neural network is employed for real-time target tracking. These two trained models can be deployed on an autonomous vehicle equipped with an NVIDIA Jetson Nano motherboard. The autonomous vehicle moves to avoid obstacles and follow tracked targets by camera. Adjusting the steering and movement of the autonomous vehicle according to the PID algorithm during the movement, therefore, will help the proposed vehicle achieve stable and precise tracking.


2021 ◽  
Vol 9 ◽  
Author(s):  
Sharnil Pandya ◽  
Anirban Sur ◽  
Nitin Solke

The presented deep learning and sensor-fusion based assistive technology (Smart Facemask and Thermal scanning kiosk) will protect the individual using auto face-mask detection and auto thermal scanning to detect the current body temperature. Furthermore, the presented system also facilitates a variety of notifications, such as an alarm, if an individual is not wearing a mask and detects thermal temperature beyond the standard body temperature threshold, such as 98.6°F (37°C). Design/methodology/approach—The presented deep Learning and sensor-fusion-based approach can also detect an individual in with or without mask situations and provide appropriate notification to the security personnel by raising the alarm. Moreover, the smart tunnel is also equipped with a thermal sensing unit embedded with a camera, which can detect the real-time body temperature of an individual concerning the prescribed body temperature limits as prescribed by WHO reports. Findings—The investigation results validate the performance evaluation of the presented smart face-mask and thermal scanning mechanism. The presented system can also detect an outsider entering the building with or without mask condition and be aware of the security control room by raising appropriate alarms. Furthermore, the presented smart epidemic tunnel is embedded with an intelligent algorithm that can perform real-time thermal scanning of an individual and store essential information in a cloud platform, such as Google firebase. Thus, the proposed system favors society by saving time and helps in lowering the spread of coronavirus.


Author(s):  
Shiv Kumar ◽  
Agrima Yadav ◽  
Deepak Kumar Sharma

The exponential growth in the world population has led to an ever-increasing demand for food supplies. This has led to the realization that conventional and traditional methods alone might not be able to keep up with this demand. Smart agriculture is being regarded as one of the few realistic ways that, together with the traditional methods, can be used to close the gap between the demand and supply. Smart agriculture integrates the use of different technologies to better monitor, operate, and analyze different activities involved in different phases of the agricultural life cycle. Smart agriculture happens to be one of the many disciplines where deep learning and computer vision are being realized to be of major impact. This chapter gives a detailed explanation of different deep learning methods and tries to provide a basic understanding as to how these techniques are impacting different applications in smart agriculture.


Author(s):  
Ismail Nasri ◽  
Mohammed Karrouchi ◽  
Hajar Snoussi ◽  
Abdelhafid Messaoudi ◽  
Kamal Kassmi

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