Image Processing Based Smart Violation Detection in College

2021 ◽  
pp. 567-571
Author(s):  
AL Chaitanya Krishna ◽  
B R Laya ◽  
BM Shravani ◽  
Pramilarani K
Keyword(s):  
Face Mask ◽  
World Health ◽  
Modern State ◽  
Automated Inspection ◽  
Automatic Tracking ◽  
Social Distancing ◽  
The World ◽  
State Of Affairs ◽  
Health Organization ◽  
Tracking Of Humans

According to statistics received via way of mans of the World Health Organization, the worldwide pandemic of COVID-19 has significantly impacted the arena and has now inflamed extra than 8 million humans worldwide. Wearing face mask and following secure social distancing are of the improved protection protocols want to be observed in public locations so one can save you the unfold of the virus. To create secure surroundings that contributes to public protection, we advocate a green laptop imaginative and prescient primarily based totally technique centered at the real-time automatic tracking of humans to locate each secure social distancing and face mask in public locations via way of means of imposing the version on raspberry pi4 to display hobby and locate violations via camera. After detection of breach, the raspberry pi4 sends alert sign to govern middle at kingdom police headquarters and additionally deliver alarm to public. In this proposed machine current deep gaining knowledge of set of rules had been combined with geometric strategies for constructing a strong modal which covers 3 factors of detection, tracking, and validation. Thus, the proposed machine favors the society via way of means of saving time and allows in reducing unfold of corona virus. It may be applied successfully in modern state of affairs while lockdown is eased to check out people in public gatherings, buying malls, etc. Automated inspection reduces manpower to check out the general public and additionally may be utilized in any place.

scholarly journals Social Distancing Perspektif Tasawuf Sebagai Konsep Perbaikan Diri di Era New Normal (Studi Pemikiran Al-Ghazali)

ESOTERIK ◽  
2020 ◽  
Vol 6 (2) ◽  
pp. 159
Author(s):  
Abdullah Abdullah
Keyword(s):  
World Health ◽  
Basic Difference ◽  
New Normal ◽  
Social Distancing ◽  
Religious Doctrine ◽  
Processing Data ◽  
Library Research ◽  
The Social ◽  
The World ◽  
Health Organization

<p class="06IsiAbstrak">The religion approach in realizing the new normal scenario in the pandemic era is urgent considering that religious doctrine is easier to accept and obey. So that it can be an effective step to prevent transmission. This research is qualitative research. This type of research is library research. The data collection method is done by reading and taking notes and processing data related to the social distancing perspective of Al-Ghazali's works of Sufism. This study found similarities between the social distancing perspective of the World Health Organization (WHO) and the social distancing perspective of Al-Ghazali's Sufism. This similarity is at least in two ways, first both emphasize the importance of maintaining distance from others, the second in the realm of strategy. The basic difference is in the realm of goals. The existence of this equation causes social distancing in the new normal era, the perspective of Sufism is important to offer and deserve to be published. and other things that underlie are two things, first, so that social distancing is not only maintaining immunity but also maintaining faith. The two social interaction strategies originating from religious doctrine will be easier to comply with given the ineffectiveness of government advice in implementing social distancing. Efforts to maintain one's consistency in implementing social distancing, there are three things that need to be considered, first to keep busy with positive things at home, second always to remember the dangers of interacting with the general public, third to minimize dependence on other people.</p>

scholarly journals The Challenge of Forecasting Demand of Medical Resources and Supplies During a Pandemic: A Comparative Evaluation of Three Surge Calculators for COVID-19

2020 ◽  
Author(s):  
Amina A. Kamar ◽  
Noel Maalouf ◽  
Eveline Hitti ◽  
Ghada El Eid ◽  
Hussain A Ismaeel ◽  
...  
Keyword(s):  
Comparative Evaluation ◽  
Healthcare Professionals ◽  
Healthcare Systems ◽  
World Health ◽  
Medical Resources ◽  
Social Distancing ◽  
The Social ◽  
The World ◽  
Health Organization

Ever since the World Health Organization (WHO) declared the new coronavirus disease 2019 (COVID-19) as a pandemic, there has been a public health debate concerning medical resources and supplies including hospital beds, intensive care units (ICU), ventilators, and Protective Personal Equipment (PPE). Forecasting COVID-19 dissemination has played a key role in informing healthcare professionals and governments on how to manage overburdened healthcare systems. However, forecasting during the pandemic remained challenging and sometimes highly controversial. Here, we highlight this challenge by performing a comparative evaluation for the estimations obtained from three COVID-19 surge calculators under different social distancing approaches, taking Lebanon as a case study. Despite discrepancies in estimations, the three surge calculators used herein agree that there will be a relative shortage in the capacity of medical resources and a significant surge in PPE demand as the social distancing policy is removed. Our results underscore the importance of implementing containment interventions including social distancing in alleviating the demand for medical care during the COVID-19 pandemic in the absence of any medication or vaccine. It is said that ″All models are wrong, but some are useful″, in this paper we highlight that it is even more useful to employ several models.  

scholarly journals Coronavirus outbreaks including COVID-19 and impacts on medical education: a systematic review

2020 ◽  
Vol 3 (2) ◽  
pp. 130
Author(s):  
Kelly Kelly ◽  
Lie Rebecca Yen Hwei ◽  
Gilbert Sterling Octavius
Keyword(s):  
Medical Education ◽  
Clinical Skills ◽  
World Health ◽  
Disease Spread ◽  
Social Distancing ◽  
Online Platforms ◽  
The World ◽  
Novel Coronavirus ◽  
Health Organization ◽  
Global Threat

Since the beginning of 2020, the world has been affected by the novel coronavirus COVID-19 pandemic. The virus’ infectious nature pushed all sectors to implement social distancing measures in an effort to limit its transmission, including the education sector. We searched PubMed and Science Direct on June 12th and found 24 papers that are relevant to our review. After the World Health Organization announced that COVID-19 is a global threat, various countries took a variety of measures to limit the disease spread such as social distancing, self-quarantine, and closing public facilities that hold large gatherings, including universities and schools. Hospitals started to prioritize services for COVID-19 cases. Medical education programs are also affected by this disease, but not continuing in-person classes outweighs any benefit from traditional teaching methods. The previous Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) pandemics have shown ways to shift medical education to online platforms. In the current pandemic, online meetings are being used to hold lectures, classes, laboratory practices, and clinical skills classes. For clerkship students, online platforms might not be feasible because this eliminates patient-doctor relationships, but it appears for now to be the only option. Some institutions have involved medical students in the frontlines altogether. We encourage all parties to constantly evaluate, review, and improve the efforts of continuing medical education, especially during this pandemic. Further research is needed to evaluate students’ performance after adopting e-learning and to discover the best methods in medical education in general and clerkship education in particular.

Face mask detection application and dataset

2021 ◽  
Vol 27 (2) ◽  
Author(s):  
Daniel Matthias ◽  
Chidozie Managwu ◽  
O. Olumide
Keyword(s):  
Disease Transmission ◽  
Face Mask ◽  
World Health ◽  
The World ◽  
The Face ◽  
Monitoring And Enforcement ◽  
Health Organization ◽  
Experimental Findings ◽  
Recognition Software ◽  
Deep Learning Model

The COVID–19 pandemic is, without any doubt, changing our world in ways that are beyond our wildest imagination. In a bid to curb the spiraling negative fallouts from the virus that has resulted in a large number of casualties and security concerns. The World Health Organization, amongst other safety protocols, recommended the compulsory wearing of face masks by individuals in public spaces. The problem with the enforcement of this and other relevant safety protocols, all over the world, is the reluctance and outright refusal of citizens to comply and the inability of relevant agencies to monitor and enforce compliance. This paper explores the development of a CCTV–enabled facial mask recognition software that will facilitate the monitoring and enforcement of this protocol. Such models can be particularly useful for security purposes in checking if the disease transmission is being kept in check. A constructive research methodology was adopted, where a pre-trained deep convolutionary neural network (CNN) (mostly eyes and forehead regions) used and the most probable limit (MPL) was use for the classification process. The designed method uses two datasets to train in order to detect key facial features and apply a decision-making algorithm. Experimental findings on the Real-World-Masked-Face-Dataset indicate high success in recognition. A proof of concept as well as a development base are provided towards reducing the spread of COVID-19 by allowing people to validate the face mask via their webcam. We recommend that the use of the app and to further investigate the development of highly robust detectors by training a deep learning model with respect to specified face-feature categories or to correctly and incorrectly wear mask categories.

scholarly journals How to Correctly Detect Face-Masks for COVID-19 from Visual Information?

2021 ◽  
Vol 11 (5) ◽  
pp. 2070
Author(s):  
Borut Batagelj ◽  
Peter Peer ◽  
Vitomir Štruc ◽  
Simon Dobrišek
Keyword(s):  
Visual Information ◽  
Service Providers ◽  
Face Mask ◽  
World Health ◽  
Detection Techniques ◽  
Face Images ◽  
The World ◽  
Public Behavior ◽  
Face Datasets ◽  
Health Organization

The new Coronavirus disease (COVID-19) has seriously affected the world. By the end of November 2020, the global number of new coronavirus cases had already exceeded 60 million and the number of deaths 1,410,378 according to information from the World Health Organization (WHO). To limit the spread of the disease, mandatory face-mask rules are now becoming common in public settings around the world. Additionally, many public service providers require customers to wear face-masks in accordance with predefined rules (e.g., covering both mouth and nose) when using public services. These developments inspired research into automatic (computer-vision-based) techniques for face-mask detection that can help monitor public behavior and contribute towards constraining the COVID-19 pandemic. Although existing research in this area resulted in efficient techniques for face-mask detection, these usually operate under the assumption that modern face detectors provide perfect detection performance (even for masked faces) and that the main goal of the techniques is to detect the presence of face-masks only. In this study, we revisit these common assumptions and explore the following research questions: (i) How well do existing face detectors perform with masked-face images? (ii) Is it possible to detect a proper (regulation-compliant) placement of facial masks? and (iii) How useful are existing face-mask detection techniques for monitoring applications during the COVID-19 pandemic? To answer these and related questions we conduct a comprehensive experimental evaluation of several recent face detectors for their performance with masked-face images. Furthermore, we investigate the usefulness of multiple off-the-shelf deep-learning models for recognizing correct face-mask placement. Finally, we design a complete pipeline for recognizing whether face-masks are worn correctly or not and compare the performance of the pipeline with standard face-mask detection models from the literature. To facilitate the study, we compile a large dataset of facial images from the publicly available MAFA and Wider Face datasets and annotate it with compliant and non-compliant labels. The annotation dataset, called Face-Mask-Label Dataset (FMLD), is made publicly available to the research community.

scholarly journals Ultra-Sensor Based Social Distancing Device

2021 ◽  
pp. 237-241
Author(s):  
K. Harshita ◽  
R. Moni Pravallika ◽  
T. Lakshmi Prasanna ◽  
Sk. Nazma ◽  
S. Parvathi ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
World Health Organization ◽  
Social Distance ◽  
Outdoor Environment ◽  
World Health ◽  
Localization Method ◽  
Social Distancing ◽  
The Social ◽  
The World ◽  
Health Organization

According to the world health organization, social distancing will be proven to be the only solution to fight with COVID-19. In this, an innovative localization method was proposing to track humans ‘position in an outdoor environment based on sensors is proposed with the help of artificial intelligence, this device is handy to maintain a social distancing. Duringcovid-19pandemicsituation, there is a need of maintaining social distance. If any person is approaching us, getting indication to maintain social distance is the need of the hour. Offices, public transports, grocery shops where the social distancing is mandatory. Since we can be cautious in front sideways to maintain the distance sensors are used in this model to alert the person to maintain social distance.

scholarly journals Manav Rakshak: Device to Help Maintain Social Distancing

2020 ◽  
Vol 9 (4) ◽  
pp. 2401-2403
Keyword(s):  
Minimum Distance ◽  
World Health ◽  
Social Distancing ◽  
The Social ◽  
The World ◽  
Precautionary Measures ◽  
Proactive Measures ◽  
Health Organization ◽  
Smart Wearable ◽  
Health Experts

Abstract: On March 11, 2020, the World Health Organization (WHO) confirmed COVID-19 a pandemic, in response to the more than 1,00,000 confirmed cases globally in more than 100 countries, and the persistent threat of spreading further. Presently, there is no medicine to cure or vaccine to prevent the spread of COVID 19. The only way to curb its menace is taking precautionary measures as advised by Health experts. Social distancing i.e. maintaining a minimum distance of 1-1.5 meter between two individuals is one of the proactive measures advised by WHO. In this paper, an ATMEGA (open source) based Smart wearable device “Manav Rakshak” is proposed. It can be worn while travelling outside home and will help in maintaining the social distancing thereby curb the spread of COVID-19.

scholarly journals Covid-19 Mask Detection

2021 ◽  
Vol 10 (2) ◽  
pp. 1319-1323
Keyword(s):  
Face Mask ◽  
Classification Model ◽  
World Health ◽  
Live Streaming ◽  
Public Places ◽  
The World ◽  
The Face ◽  
Health Organization ◽  
The Right ◽  
Facial Images

The corona epidemic poses a global health problem and therefore effective preventive measures are worn in public places,according to the World Health Organization (WHO). The COVID-19 epidemic has forced governments around the world to impose restrictions on the transmission of the virus. Reports show that wearing the right face while in public places and at work clearly reduces the risk of transmission. An effective and economical way to use machine learning is to create a safe environment for device setup. A hybrid model using the depth of the face mask detection machine will be introduced. The face mask detection databasecontains a mask and in addition to the facial images, we will use OpenCV to perform real-time facial detection from live streaming via our webcam. We will use the database to create a COVID-19 face mask detector from a computer view using Python, OpenCV, and Tensor Flow and Cameras. We aim to determine whether the person in the picture/video is wearing a face mask or not with the help of computer vision and in-depth reading and to show the same with caution. Steps to modeling are data collection, pre-processing, data classification, model testing, and modeling

scholarly journals Social distancing using IoT approach

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Mayuri Diwakar Kulkarni ◽  
Khalid Alfatmi ◽  
Nikhil Sunil Deshmukh
Keyword(s):  
World Health Organization ◽  
Target Object ◽  
World Health ◽  
Government Agencies ◽  
Technical Solution ◽  
Social Distancing ◽  
The People ◽  
The Social ◽  
The World ◽  
Health Organization

AbstractIn the coronavirus outbreak pandemic by COVID-19, the World Health Organization (WHO) has been issuing several guidelines through all government agencies. In line with those guidelines, social distancing in the population has been a major prevention practice, compelled by all government agencies worldwide. Despite strong recommendations to maintain at least one-and-a-half-meter distance between the persons, the guideline is not scrupulously followed. To overcome this situation, an IoT-based technical solution is proposed through this paper. PIR sensor is used for the detection of a target in the vicinity (1.5 m). Upon violation of social distancing norms, the system will trigger an audio alarm after the detection of the target object. The research paper model is prepared by considering the needs of the people. Many researchers are focusing on tracking affected persons, but few are focusing on the social distancing preventive. The suggested portable device will always notify the person who is violating the norm of 1.5 m. The proposed device will minimize the possibility of transmission and reduce the infection rate of COVID-19. The device uses a PIR sensor depending upon the applicability area of the human being.

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.

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