ABSTRACT
In the current pandemic situation, we need to follow certain precautionary measures to safeguard us from the deadly virus. We have been able to contain the virus to a certain extent through social distancing, by sanitizing ourselves and sterilizing the daily-use items. Monitoring the vitals like body temperature, oxygen saturation, and pulse rate has proven to be effective in diagnosing the fatal disease. In this proposed method, we have come up with a solution to help the user to keep a check on the important parameters mentioned above by incorporating various sensors like MLX90614 non-contact infrared temperature sensor, SpO2 sensor, pulse rate sensor, and ultrasonic sensor in a shirt- CoviGuard. The vitals are displayed on an IOT application called ThingSpeak. A buzzer is used to indicate if the user doesn't maintain the specified distance of 0.5 meters. © 2023 IEEE.
ABSTRACT
Uncollected filled bins during the COVID pandemic in hospitals and at home are a common issue these days. This becomes a source of community spread of COVID-19. Here the key issue is unsanitary waste management, which can be controlled by an efficient IoT-based smart bin system to present garbage level collected in bins in 'COVID' wards through the use of ultrasonic sensor which stops rubbish from overflowing from smart bins and a gas sensor to determine if any dangerous gases are emitted. The virus and pathogens are neutralized with the help of ultraviolet rays. A rechargeable battery that runs on a solar Piezo hybrid power charges the system. As a result, the bin tends to minimize the potential of infectious illness transmitted to healthcare professionals. Smart bins will prevent overflowing waste from the bins and also stop unsanitary conditions from prevailing nearby. It is a straightforward yet incredibly valuable concept. © 2023 IEEE.
ABSTRACT
Face recognition is now ubiquitous as an efficient and non-invasive method to verify identity. A facial recognition system works by comparison of a digital image or video frame showing a person's face with a database storing face images. Face masks are considered a required biosafety measure during this COVID-19 pandemic. Use of masks led to various issues to emerge and impact the functioning of earlier facial recognition algorithms and that has motivated our research. The construction of a real-time face recognition system that recognizes faces with and without masks is described in this paper. ResNet10 is used to perform the feature extraction. Then, to perform face detection and recognition, it is paired with a machine learning algorithm such as SVM. Without a mask, the maximum recognition accuracy is 99.40%, while with a mask, it is 98.30%. © 2022 IEEE.
ABSTRACT
Coronavirus has become one of the most deadly pandemics in 2021. Starting in 2019, this virus is now a significant medical issue all over the world. It is spreading extensively because of its modes of transmission. The virus spreads directly, indirectly, or through close contact with infected people. It is proclaimed that people should wear a mask in public areas as a counteraction measure, as it helps in suppressing transmission. A portion of the spaces, where the virus has broadly fanned out, is because of inappropriate wearing of facial cover. In crowded areas, keeping a check on facial masks manually is difficult. To automate this process, an effective and robust face mask detector is required. This paper discusses a hybrid approach using a machine learning technique called eigenfaces, along with vanilla neural networks. The accuracy was compared for three different values of principal components. The test accuracy achieved was 0.87 for 64 components, 0.987 for 512 components, and 0.989 for 1,000 components. Hence, this approach proved to be more promising and efficient than its counters. © 2022 Institute of Advanced Engineering and Science. All rights reserved.
ABSTRACT
Agonizing and debilitating pain is what most patients with chronic pancreatitis endure. Chronic pain often leads to depression and poor quality of life. Surgical decompression can result in permanent pain relief by reducing intraductal hypertension. Elective surgical procedures had to be postponed during the Covid-19 pandemic as the resources, including oxygen supplies, workforce, and ventilators, were dedicated to the service of Covid-19 patients. We present a case of 20 year-old-male suffering from severe abdominal pain due to chronic pancreatitis refractory to analgesic medications. Given the refractory pain and inability to proceed with surgery due to the pandemic, we subjected him to undergo splanchnic nerve block (SNB) with local anesthetic and steroid. SNB provided adequate analgesia and enabled the patient to tide over the crisis. To our knowledge, no case has been reported using a combination of local anesthetic and steroid in SNB for a patient with chronic pancreatitis.
ABSTRACT
Crowdfunding platforms like Kickstarter provide new product developers with a novel and readily accessible platform to interact with potential customers, seek funding, and gain valuable feedback from target users. Successful startup design processes are often praised due to startups’ agility and ability to adapt to changing markets under extreme resource constraints. The COVID-19 pandemic changed the market in a number of significant ways, and publicly available data on Kickstarter provides valuable insight into the fundamental ways that product developers adapt to volatiles markets created by a global crisis. Leveraging linguistic analysis, topic modelling, k-means clustering, and principal component analysis, startup data was analyzed to identify overarching trends in startup launch campaigns across years. Specifically, this work identifies emerging trends in the Kickstarter market in 2020 to understand how external factors affect launch practices. Subtle yet significant changes in Kickstarter campaigns show that new clusters of campaigns emerged during 2020, not present in prior years, indicating that product developers adapted language to meet the needs of a changing market. Findings motivate a more thorough investigation of the relationships between startup market trends and external events to build a deeper understanding of the fundamental ways developers adapt design processes due to external stimuli. Copyright © 2021 by ASME.