ABSTRACT
Because of the world’s extreme interconnectivity, the next pandemic is likely only a flight away. Viruses like Ebola, NIPAH, Zika, and others have emerged and significantly impact people’s lives. Millions of people died because of these deadly viruses and still new viruses are coming into mankind every few years and taking so many lives. Currently, Coronavirus is an immediate threat to mankind. Each country is establishing a new set of laws and regulations to limit the Coronavirus effect. The most important thing for us to remember at this period is to wear a facemask at all times, maintain social distance, sanitize our hands, and do several other things. Despite the government’s intensified efforts, a small number of people continue to violate the rules and regulations. A chance to limit the virus’s spread in its early stages was neglected, with grave repercussions for many netizens. Facemask identification would be one of the most important aspects of our civilization to prevent the virus from spreading further. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The Covid-19 pandemic in the late 2019 caused the world to shut down. Even though it is recommended to reduce overcrowding it still cannot be avoided. This can cause the pandemic to spread even more, especially since offices, schools and colleges are slowly reopening. With image detection making huge breakthroughs in the last decade, modern image detection technologies can now be combined with the current hardware to combat problems like overcrowding, which massively spreads the pandemic. In this paper, the YOLO v4 algorithm has been used, which greatly speeds up the process of detection and improves the overall accuracy of the system. © 2022 IEEE.
ABSTRACT
The COVID-19 pandemic has led to many lifestyle changes, one of them being the mandatory use of face masks in public settings. Given the importance of masks, there are various types for people to use, such as cloth and N95. A proper mask must be used to protect oneself and others from the spread of the coronavirus. This paper proposes CoViMask, a face mask type detector that detects the type of mask that a person is wearing, and is trained using a custom-made dataset. Accuracy, precision and recall are used to evaluate the proposed method. The paper also mentions the application areas. The results obtained prove that CoViMask is efficient in mask type detection and may aid in controlling the spread of covid. © 2022 IEEE.
ABSTRACT
With the COVID-19 pandemic establishing its reign world-wide in the last two years with over 260 million cases and more than 5 million deaths, there has been an incessant need to quell the increasing fear and anxiety which has taken root in the minds of people. One way to do this has been to create an awareness about the global pandemic and arm people with a way to track various indispensable resources during these tough times. This paper discusses, in detail, the implementation of this idea - a real-time, COVID-19 resource tracker website which scrapes data from the most favored social media, Twitter and collates them to display the relevant information about the resources related to COVID-19;and provides vital particulars and facts about donation sites (in real-time) and general guidance in symptoms, treatments and precautions - integrated into an all-in-one website equipped with auto-completion feature and a handy navigation to increase its user friendly nature. © 2022 IEEE
ABSTRACT
The COVID-19 pandemic has already spread over 200 countries in a few months and taken a toll on many lives. At this critical time, there is a need to follow some precautions to control the virus spreading rapidly through direct and indirect contact. The World Health Organization (WHO) has already recommended the importance of face masks for protection from the virus. Hence, one of the prime changes we have had to incorporate in our lives is wearing a face mask. This work reports the development of Ag particles containing polydimethylsiloxane (PDMS) based e-skin sensor, which generates signals on touch (contact mode) or proximity (non-contact mode) near the sensor. These signals are retrieved using IoT. The signals indicate a person's presence, which activates face mask detection using deep learning. This model is an IoT and Machine Learning-based system. When a human touches or places a hand near the PDMS-Ag sensor, this model performs face masks detection. This model is also suitable for security purposes. Since controlling the number of new COVID-19 cases is the need of the hour, we are using face mask detection in this study. © 2021 IEEE.
ABSTRACT
The spread of COVID-19 contagion has to lead the world on a pause, because of its alarming rate. The only immediate solution was to practice social distancing and enforce lockdown. COVID-19 has declared an international emergency because it has been labeled pandemic, and different countries are still developing their vaccine. As far as now various countries with various governments have undertaken active plans and emergency measures to protect the public. The government and various health organizations are in charge of the survey. In fear of being affected, people tend to avoid hospital visits and circumvent the COVID-19 test. As of now, many Web applications are developed to avoid social interaction and community gathering. The COVID-19 test booking Web app provides the user to choose what, when, and where to take the COVID-19 test, it also helps the government health officials to maintain a safe database. This ensures the increase of COVID-19 test being taken and provides the individual proper safety and assurance. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
COVID-19 has devastated people's lives across the globe. Declining economy, job losses and market uncertainty have created restlessness in public. These unprecedented times have led to concerns about the future and fear of restricted income. To overcome these strenuous and tough times, individuals and families need to take certain vital steps in order to manage and monitor their budgets judiciously. Though COVID-19 will continue to have its adverse consequences globally, a few smart decisions may help common people maintain healthy and stable finances. So it's essential that we keep a track of the transactions every day. To do so, we’ve proposed a web application with the help of HTML and CSS to make it visually appealing. It is capable of tracking the minute transactions that we make. The main objective of this application is for the user to monitor their expenses. The user can store his income and expenses based on the transaction, date of the income or expense and the category of items. This could be achieved by linking the database (MySql) with the PHP script. We have developed a web based application which is used to manage a users daily expense in a more structured and organized manner. Thus, we can minimize the hand-operated computations which would’ve been involved otherwise and also track expenditure. This application asks the user to provide his income which is further split across various categories in order to calculate his total expenses per day, and these results will be stored for each user separately. We also included a feature to scan and store the images of the bill in the database which could be downloaded at any given point of time. In addition to this, we have integrated a calculator which is an optional feature for the user to do the extra calculations within the website rather than going for an external calculator. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Our globe is being impacted by a variety of calamities, some of which are natural and others which are manmade. The past decades have witnessed the occurrence of many types of natural and man-made disasters like Earthquakes, Tsunamis, Wildfires, EBOLA outbreak and currently COVID-19. These disasters have been claiming a lot of lives and in fact the number is very huge. Some lives could be saved if there is a better and faster aid in terms of help or immediate response from the officials or people nearby. Natural disasters cannot be controlled by humans but the number of deaths in other types of disasters could be controlled by us. Mainly, due to EBOLA and COVID-19 many people lost their lives because of lack of immediate support and aid. More than 10, 000 deaths were accounted for by the EBOLA outbreak and now due to COVID-19, one of the most destructive viruses that ever lived on the earth, recorded figures much higher than that of EBOLA, nearly 3.17 million people left this world as of now. Now in this pandemic situation many are losing their lives because of the scarcity in medical equipment and also no proper transportation especially ambulance service. To overcome this situation this application supports the person who needs help by sending emergency alerts to the surrounding people for seeking help. This SOS application is capable of saving many lives through which an immediate aid and support can be obtained from the nearby people. © 2021 IEEE.
ABSTRACT
The ongoing pandemic has caused several impacts on human life. Social media has become more popular during the pandemic, wherein people share all their thoughts and emotions. Due to the social distancing norms and other preventive measures, people are connecting with each other through this platform. This gave us an occasion to study the overall mental reaction of the public to this disease. To measure the region-wise sentiment value, we used the tweets associated with COVID-19 in this paper. This is then used for the model's training. Then, we generate the average emotion conveyed by each region. This can be beneficial in validating the psychological impact that COVID-19 had on the people, helping governments to take effective actions. The output as well as the COVID-19 guidelines and data are then represented in a website. © 2021 IEEE.
ABSTRACT
BACKGROUND: COVID-19 continues to inflict significant morbidity and mortality, particularly on patients with preexisting health conditions. The clinical course, outcomes, and significance of immunosuppression regimen in heart transplant recipients with COVID-19 remains unclear. METHODS: We included the first 99 heart transplant recipients at participating centers with COVID-19 and followed patients until resolution. We collected baseline information, symptoms, laboratory studies, vital signs, and outcomes for included patients. The association of immunosuppression regimens at baseline with severe disease were compared using logistic regression, adjusting for age and time since transplant. RESULTS: The median age was 60 years, 25% were female, and 44% were white. The median time post-transplant to infection was 5.6 years. Overall, 15% died, 64% required hospital admission, and 7% remained asymptomatic. During the course of illness, only 57% of patients had a fever, and gastrointestinal symptoms were common. Tachypnea, oxygen requirement, elevated creatinine and inflammatory markers were predictive of severe course. Age ≥ 60 was associated with higher risk of death and the use of the combination of calcineurin inhibitor, antimetabolite, and prednisone was associated with more severe disease compared to the combination of calcineurin inhibitor and antimetabolite alone (adjusted OR = 7.3, 95% CI 1.8-36.2). Among hospitalized patients, 30% were treated for secondary infection, acute kidney injury was common and 17% required new renal replacement therapy. CONCLUSIONS: We present the largest study to date of heart transplant patients with COVID-19 showing common atypical presentations and a high case fatality rate of 24% among hospitalized patients and 16% among symptomatic patients.
Subject(s)
COVID-19/epidemiology , Heart Failure/surgery , Heart Transplantation , Immunosuppressive Agents/therapeutic use , Aged , COVID-19/diagnosis , COVID-19/therapy , Female , Heart Failure/complications , Heart Failure/mortality , Hospitalization , Humans , Logistic Models , Male , Middle Aged , Risk Factors , Survival Rate , Treatment OutcomeABSTRACT
The Coronavirus (Covid-19) pandemic has spread towards all the seven continents. It’s very heart-breaking that we lost more than 1.87 million people to the virus and the virus have infected more than 86.5 million people worldwide. Being contagious disease, which can also be fatal, it spreads through various means. Lockdown was imposed on most countries for the safety of its citizens. People could only go out to fulfil essential needs like getting food items, medicines and for other essentials. Proper social distancing and wearing masks were made mandatory. Some shops were forced to close down due to overcrowding and some even went out of business. E-commerce thrived during this period. But this impacted a lot of people, especially local shop owners and small scale businessmen. The Locally Shopping Web App proposes a platform for these local shop vendors to engage their business online, with all the essential features that an ecommerce application should have. The customers can view and place orders from their local shops. Shops within a radius of 5km are identified by computing the Haversine distance of the nearby shop and customer’s current location coordinates, which is obtained through a map based interface. They can collect the items at a chosen time slot during checkout for a given shop for which a QR code based token is given. This token system can help us to prevent overcrowding for which at a particular time slot not more than the specified number of customers by the shopkeepers are present at the shop. This system would ensure that local shops don't go out of business, and proper social distancing is maintained so that none of our people get infected while meeting their daily needs.
Subject(s)
Coronavirus Infections , COVID-19ABSTRACT
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic continues to afflict millions of people worldwide. Patients with end-stage heart failure and left ventricular assist devices (LVADs) may be at risk for severe COVID-19 given a high prevalence of complex comorbidities and functional impaired immunity. The objective of this study is to describe the clinical characteristics and outcomes of COVID-19 in patients with end-stage heart failure and durable LVADs. METHODS: The Trans-CoV-VAD registry is a multi-center registry of LVAD and cardiac transplant patients in the United States with confirmed COVID-19. Patient characteristics, exposure history, presentation, laboratory data, course, and clinical outcomes were collected by participating institutions and reviewed by a central data repository. This report represents the participation of the first 9 centers to report LVAD data into the registry. RESULTS: A total of 40 patients were included in this cohort. The median age was 56 years (interquartile range, 46-68), 14 (35%) were women, and 21 (52%) were Black. Among the most common presenting symptoms were cough (41%), fever, and fatigue (both 38%). A total of 18% were asymptomatic at diagnosis. Only 43% of the patients reported either subjective or measured fever during the entire course of illness. Over half (60%) required hospitalization, and 8 patients (20%) died, often after lengthy hospitalizations. CONCLUSIONS: We present the largest case series of LVAD patients with COVID-19 to date. Understanding these characteristics is essential in an effort to improve the outcome of this complex patient population.