ABSTRACT
Due to improvements in information and communication technology and growth of sensor technologies, Internet of Things is now widely used in medical field for optimal resource management and ubiquitous sensing. In hospitals, many IoT devices are linked together via gateways. Importance of gateways in modernization of hospitals cannot be overstated, but their centralized nature exposes them to a variety of security threats, including integrity, certification, and availability. Block chain technology for level monitoring in oxygen cylinders is a scattered record containing the data related to oxygen levels in the cylinder, patient's name, patient's ID number, patient's medical history, and all connected information carried out and distributed among the hospitals (nodes) present in the locality (network). Designing an oxygen level monitoring technique in an oxygen cylinder used as the support system for COVID-19-affected patients is a challenging task. Monitoring the level of oxygen in the cylinders is very important because they are used for saving the lives of the patients suffering from COVID-19. Not only the COVID-19 patients are dependent on this system, but this system will also be helpful for other patients who require oxygen support. The present scenario many COVID-19 hospitalized patients rely upon oxygen supply through oxygen cylinders and manual monitoring of oxygen levels in these cylinders has become a challenging task for the healthcare professionals due to overcrowding. If this level monitoring of oxygen cylinders are automated and developed as a mobile App, it would be of great use to the medical field, saving the lives of the patients who are left unmonitored during this pandemic. This proposal is entitled to develop a system to measure oxygen level using a smartphone App which will send instantaneous values about the level of the oxygen inside the cylinder. Pressure sensors and load cell are fitted to the oxygen cylinders, which will measure the oxygen content inside the cylinder in terms of the pressure and weight. The pressure sensors and load cells are connected to the Arduino board and are programmed to display the actual level of oxygen inside the cylinder in terms of numerical values. A beep sound is generated as an indicator to caution the nurses and attendants of the patients regarding the level of the oxygen inside the cylinder when it is only 15% of the total oxygen level in the cylinder in correlation to the pressure and weight. The signal with respect to the level corresponding to the measured pressure and weight of the cylinder is further transmitted to the monitoring station through Global System for Mobile communication (GSM). Graphical display is used at monitoring end to indicate the level of oxygen inside all oxygen cylinders to facilitate actions like 100% full, 80% full, 60% full, 40% full, 20% full which states that either the oxygen cylinder is in good condition, or requires a replacement of empty cylinders with filled ones in correlation to the pressure and weight being sensed by the sensors. The levels of the oxygen monitored inside the cylinder and other related data can also be stored on a cloud storage which will facilitate the retrieval of the status at any point of time, as when required by the physicians and nurses. These results reported, are valued in monitoring the level of the oxygen cylinder remotely connected to the patients, affected by COVID-19, using a smartphone App. This mobile phone App is an effective tool for investigating the oxygen cylinder level used as a life-support system for COVID-19-affected patients. A virtual model of the partial system is developed using TINKER CAD simulation package. In real time, the sensor data analysis with cloud computing will be deployed to detect and track the level of the oxygen cylinders. © 2023 Elsevier Inc. All rights reserved.
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The world has altered since the World Health Organization (WHO) designated (COVID-19) a worldwide epidemic. Everything in society, from professions to routines, has shifted to accommodate the new reality. The World Health Organization warns that future pandemics of infectious diseases are likely and that people should be ready for the worst. Therefore, this study presents a framework for tracking and monitoring COVID-19 using a Deep Learning (DL) perfect. The suggested framework utilises UAVs (such as a quadcopter or drone) equipped with artificial intelligence (AI) and the Internet of Things (IoT) to keep an eye on and combat the spread of COVID-19. AI/IoT for COVID-19 nursing and a drone-based IoT scheme for sterilisation make up the bulk of the infrastructure. The proposed solution is based on the use of a current camera installed in a face-shield or helmet for use in emergency situations like pandemics. The developed AI algorithm processes the thermal images that have been detected using multi-scale similar convolution blocks (MPCs) and Res blocks that are trained using residual learning. When infected cases are detected, the helmet's embedded Internet of Things system can trigger the drone system to intervene. The infected population is eradicated with the help of the drone's sterilisation process. The developed system undergoes experimental evaluation, and the findings are presented. The developed outline delivers a novel and well-organized arrangement for monitoring and combating COVID-19 and additional future epidemics, as evidenced by the results. © 2023 IEEE.
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The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) causes Covid-19, an infectious illness. A methodology was created to track the vaccination history of people with the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) that causes Covid-19, an infectious illness. The system operates on a Raspberry Pi processor that is designed to authenticate the vaccination records of individuals. The Vaccination Identification System consists of various components connected to the Raspberry Pi Zero 2W microprocessor, Pi camera, an LCD display, LED indicators, a buzzer, a DC servo motor, and a PCB converter. The proposed system grants access to vaccinated individuals and denies access to those who are not vaccinated.
ABSTRACT
In today's Era,various industries are settling up in India and tourism is one of them. Tourism being one of the leading industries in India has set up the benchmark within last few years. Talking about today's scenario, the tourism industry is facing a huge loss because of the deadly humanitarian disease "COVID-19"that came at the end of 2019. It had led to the LOCKDOWN nationwide, leading towards the downfall of the hotel and tourism industry. Global covid-19 pandemic has challenged this sensitive industry with unprecedented circumstances and repercussions. Although, after the second wave, the situation is becoming better day by day, the tourist visits at famous stations have increased rapidly that may be harmful for the country and virus may further spread to the country and there are several reasons for increase in the tourist visit at different parts of the globe. These reasons have been considered as criteria for the study. The main objective of this work is to find out the main reasons why people are getting attracted towards tourism. In this work an AHP approach been proposed to solve the above discussed problem. Total seven criteria's have been taken from expert opinions which have been considered for study. It has been found that the reason "Upcoming 3rd Wave"has the maximum impact than other reasons for increment of people at tourist places. © 2023 Author(s).
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COVID-19 has wreaked havoc on the global economy, supply chains, and government, posing an unparalleled health threat. The manufacturing sector was one of the most disruptive systems in the world at the time of the COVID-19 pandemic. Most manufacturing companies have faced a lock-down situation and are focusing on the production of essential products. Furthermore, COVID-19 has altered customer behavior. The short-term and long-term effects of COVID-19 on the manufacturing sector must be evaluated to hasten recovery and build preparedness measures should another such disruption occur. The limitations affecting the construction system during this period were discussed and prioritized in this study. The ambiguous nature of human thinking makes it difficult to evaluate the qualitative parameters;hence, it is preferred to incorporate an approach that converts the variables into triangular fuzzy numbers to better represent the values of the criteria. A fuzzy analytical hierarchical procedure (FAHP) is applied to evaluate the limitation criteria in an ambiguous environment. "Growing demand for existing products" is considered the heaviest limit after "financial stagnation" and "setback in logistics services." The study results will help the manufacturing company in formulating and implementing strategies to overcome the pandemic situation. © 2023 River Publishers. All rights reserved.
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Accurate diagnosis of SARS-CoV-2 infection is critical for the management of individuals with suspected COVID-19 diseases, as well as instituting public health measures. The experience gained over twoyears of the pandemic has led to a better appreciation of the scope and utility of various diagnostic modalities. Laboratory tests to diagnose COVID-19 in human beings can be broadly categorized as direct and indirect tests. In children (as in adults), RT-PCR is the current gold standard for diagnosis. RT-PCR detects footprints of the virus and its variants. However, its sensitivity is still less than desired. Rapid antigen tests are less accurate than RT-PCR, but the quick availability of results helps in outbreak control. Antibody tests can be used for retrospective diagnosis of infection, but currently available tests do not correlate with protection conferred by vaccination. The initial hype around chest computed tomography scans for diagnosis has now settled, and it is no longer considered a primary diagnostic modality. There are nonspecific changes in many hematological and biochemical parameters, which are more useful for monitoring disease progression than diagnosis. © 2023 Elsevier Inc. All rights reserved.
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BACKGROUND: COVID-19 vaccine is the mighty weapon opted by all the countries across the globe in an attempt to eradicate the fatal COVID-19 pandemic. The myths of the COVID-19 vaccine are spreading widely, causing a hindrance to this noble preventive measure. The prevalence of such myths among healthcare professionals may be toxic and deadly.AIM AND OBJECTIVES: To assess the knowledge, attitude, and practice of the healthcare professionals regarding the myths on COVID-19 vaccination and to demystify them.MATERIALS AND METHODS: An 18-item questionnaire evaluating knowledge, attitude, and practice based on the existing myths on COVID-19 vaccination was circulated through Google Forms (R) among 412 healthcare professionals of six disciplines belonging to a private university. The responses obtained were subjected to statistical analysis using the SPSS (R) 20 software package.RESULTS: A total of 385 health professionals participated in this study. The majority of them reported medium knowledge (165) and positive attitude (273) with the mean knowledge and attitude scores of 3.82 +/- 1.55 out of 6 and 4.3 +/- 1.58 out of 7, respectively. Even though 312 participants got vaccinated, 73 of them fai led to receive it. The knowledge scores showed a high statistically significant difference among the participants of different designations (p=0.001), but not with ge nder, field, and staff with different years of experience (p>0.05). The attitude scores were statistically different among participants of fields and designation (p<0.05) but not among genders (p=0.31) and staff with different years of experience (p=0.87). Knowledge and attitude scores showed a positive linear correlation and a high statistically significant difference (p<0.001).CONCLUSION: This study recommends more enhanced education programs on COVID-19 vaccination for health professionals and demands an improved knowledge, attitude, and practice among health professionals to achieve the goal of 100% vaccination so as to eradicate the COVID-19 pandemic.
ABSTRACT
Previously, there were physically operated hand dispensers that needed to be contacted every time we needed to apply the sanitizer. Due to the outbreak of the COVID-19, the importance of alcohol-based sanitizers has come up. As there are chances of spreading the viruses through contact surfaces, foot-operated dispensers have been developed to avoid contact between hands and hand dispensers. For the virus-infected people, their body temperatures may be high. Therefore, many organizations have been using infrared guns to record their body temperatures before they start working. To record their temperature, a manual presence is required. To replace these manual operations, an automated hand dispenser can be used. An IoT-based automated machine is designed to sanitize the hands with alcohol-based liquid without any contact with the prefilled sanitizer bottle. In connection to that, a temperature sensor is also employed within the dispenser machine to indicate the temperature of the person before they want to sanitize their hands. During the COVID-19 pandemic, most organizations were allowing their clients to work only after checking their body temperature and sanitizing themselves physically. Therefore, to avoid physical contact between the dispenser and people, a device that provides contactless operation has been developed, and further, it does not require any manual presence. While this device uses an ultrasonic sensor along with a temperature sensor to identify the existence of a hand and note the temperature of that hand, a microcontroller is also employed to control the operations. Subsequently, an LCD display is used to indicate the recorded temperature and to pump the alcohol-based sanitizer. A submersible DC motor pump is used, which is operated using a relay from the microcontroller (Granted Patent Ref.: AU 2020102940). © 2023 Elsevier Ltd. All rights reserved.
ABSTRACT
With the rise of the COVID-19 pandemic across the globe, people have come to understand the requirement of sanitation. However, other than the personal hygiene, sanitization of all the appliances (like mobile phone, wristwatch, wallet, eye wear, etc.) has become very important. Therefore, the requirement of germicides is being increased to sanitize all the appliances. A few germicides comprise chemical sanitization mechanisms and others devices are based on high radiant UV (ultraviolet) light. From the available literature, UV-based germicides are more efficient and effective in killing the harmful microorganisms. However, in the existing system the rate of disinfection is less, which makes this system lag. In general, the UV-based germicides use UV rays for the sanitization process. The UV rays are one of the forms of electromagnetic radiation with the wave lengths from 10 to 400nm. Typically, there are three types of UV rays, viz., ultraviolet A (UVA), ultraviolet B (UVB), and ultraviolet C (UVC) Moreover, UVA are longer waves, used as a black light through which microorganisms may be noticeable, while UVC are the shorter waves that kill the harmful microorganisms directly by destructing their DNA. Further, we have developed a germicidal system with greater rate of disinfection that is comparatively faster than the existing system, and it also includes the sanitization of our working environment too to disinfect the airborne organisms with greater accuracy. In the present invention, an IoT device that provides surface sanitization through microcontroller-based UV germicide is developed to reduce the disinfection time and air sterilization as well. © 2023 Elsevier Ltd. All rights reserved.
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Mucormycosis is one of the most rapidly fulminating fatal mycotic infections in human beings leading to necrosis and destruction of the involved structures. Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2, has been associated with a wide range of opportunistic bacterial and fungal infections. Increasing case of mucormycosis has been seen in patients affected by COVID-19. This article includes a case report on diagnosis, pharmacological, surgical management, and prosthetic rehabilitation of post-COVID mucormycosis.
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The global pandemic of coronavirus disease 2019 (COVID-19) causes severe respiratory problems in humans. The Chest X-ray (CXR) imaging technique majorly assists in detecting abnormalities in the chest and lung areas caused by COVID-19. Hence, developing an automatic system for CXR-based COVID-19 detection is vital for disease diagnosis. To accomplish this requirement, an enhanced Residual Network (ResNet) model is proposed in this paper for accurate COVID-19 detection. The proposed model combines the Depthwise Separable Convolutional ResNet and Pyramid dilated module(DSC-ResNet-PDM) for deep feature extraction. Employing the DSC layer minimizes the number of parameters to mitigate the overfitting issue. Further, the pyramid dilated module is used for extracting multi-scale features. The extracted features are finally fed into the optimized Medium Gaussian kernel Support Vector Machine classifier (MGKSVM) for COVID-19 detection. The proposed model attained an accuracy of 99.5%, which is comparatively higher than the standard ResNet50 and ResNet101 models. [ FROM AUTHOR] Copyright of Imaging Science Journal is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Introducction:-Covid 19 started out as a fast-spreading viral disease, in Wuhan in 2019. Soon, it spread across the globe and WHO declared it a Pandemic. Various countries took various measures to control its spread and transmission. By the time, countries recovered from it, a new wave would come along with different expressions and pathophysiology. When Covid 19 began, various health agencies in India started making protocols and standard ooperating procedures including conducting autopsies in COVID-19 infected bodies. Aims and Objectives:-Aim of our study is to analyze cause of death among all covid 19 positive cases brought for medicolegal autopsies from the time of lockdown for a period of one year. Our aim is to see if there were any factors which could have prevented these deaths. Material(s) and Method(s): A retrospective study of 1 year conducted from 25th March 2020 to 24th March 2021, (1st wave of Covid 19) was done in a tertiary care hospital in Bangalore. (Bowring and Lady Curzon hospital) Results: 39 Covid-19-positive unnatural deaths were handled with the youngest being 18 years old and the oldest beings 83. The majority turned out to be suicides (51.28%), then RTAs, falls, and natural death. The commonest method of suicide was hanging (35.89%), followed by poison consumption, and falling from a height. Conclusion(s): COVID-19 is a viral infection with variable clinical signs and variable fatality rates. There is much to learn about it. However, suicides in COVID-19 cases might not have ended death if some care, timely diagnosis, and treatment were provided.Copyright © 2023, Institute of Medico-legal Publication. All rights reserved.
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The wireless communication system very essential technology and have significant use after corona virus effect the world very badly. The Wi-Fi technology exhibits good wireless communication to provide internet facility but suffers with low antenna gain. This novel array proposed method with different dielectric material properties is used to enhancement the gain of the Wi-Fi antenna. The operating frequency of the proposed antenna is at 2. 5GHZ. This proposed method consist of Teflon dielectric material with dielectric constant of 2.02 has the gain of 8.4dbi, return loss of -30db and VSWR is 1.85, with loss tangent 0.0002. This proposed method compares with different dielectric material like kapton and fr-4 substrate but Teflon exhibit the good results. This proposed method work good for PCB antennas and flexible and wearable antennas with kapton substrate. © 2022 IEEE.
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Educational institutions and students find it a challenging task to complete the syllabus prescribed in the given period of academic year in compliance with the academic calendar, as they remain closed for an indefinite period due to the outbreak of Covid. Efforts are being made by them to chalk out ways n means to achieve the goal of completing the portions of syllabus well in time in spite of the hostile situation. Assurance of quality of learning is also a matter of prime importance for which the content has to be designed well and delivered in a professional manner. Most of the students face constraints in learning through online platform and as such it deserves high attention as to how the content is organized and presented before them so as to address such constraints and to make the learning effective. As the pandemic and subsequent restrictions led to the sudden change from conventional class room to online mode, teachers and students have faced much challenges. Most of the institutions couldn't rise to the occasion so as to formulate quality contents to deliver through online platform. Online learning can be made easy, efficient and productive if the experiences of students and learning are incorporated in the study. The findings of this study indicated that majority of the students evinced a positive attitude towards online classes in the wake of corona. The online learning was found to be advantageous as it provided flexibility and convenience for the learners. Students preferred well-structured content with recorded videos uploaded in university web-sites. They also indicated the need for interactive sessions with quizzes and assignments at the end of each class to optimize the learning experience. © 2022 IEEE.
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Serological assays used to estimate SARS-CoV-2 seroprevalence often rely on manufacturer cut-offs established based on severe cases. We conducted a household-based serosurvey of 4,677 individuals in Chennai, India from January to May, 2021. Samples were tested for SARS-CoV-2 IgG antibodies to the spike (S) and nucelocapsid (N) proteins. We calculated seroprevalence, defining seropositivity using manufacturer cut-offs and using a mixture model based on measured IgG. Using manufacturer cut-offs, there was a five-fold difference in seroprevalence estimated by each assay. This difference was largely reconciled using the mixture model, with estimated anti-S and anti-N IgG seroprevalence 64.9% (95% Credible Interval [CrI], 63.8-66.0) and 51.5% (95% CrI, 50.2-52.9) respectively. Age and socioeconomic factors showed inconsistent relationships with anti-S and anti-N IgG seropositivity using manufacturer cut-offs. In the mixture model, age was not associated with seropositivity, and improved household ventilation was associated with lower seropositivity odds. With global vaccine scale-up, the utility of the more stable anti-S IgG assay may be limited due to the inclusion of the S protein in several vaccines. SARS-CoV-2 seroprevalence estimates using alternative targets must consider heterogeneity in seroresponse to ensure seroprevalence is not underestimated and correlates not misinterpreted.
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The lung diseases will cause a significant negative effect on the human lungs in a severe manner. A person may suffer from this disease because of bacteria or viruses. The alveoli in the lungs, which are a portion of the lungs that are filled fluids, so the patients with Pneumonia have a low percentage of oxygen in their blood. According to the UNICEF survey, it killed about 880,000 children belonging to the age-group of 0-5 in the year of 2016. Due to the improper detection of the infection in the starting stage, the death rate of the persons increasing enormously. Lung diseases can be detected by radiologists by looking at or examining the chest x-rays very keenly. This process of examining is very costly and requires time. To reduce the time and increase the accuracy of detection, it is needed to prevent the intervention of man from examining the chest x-rays. It is a great idea to use the convolutional neural networks, which includes in the class of deep learning, for the detection of lung diseases. It works on extracting of features from chest x-rays which classifies them to detect lung diseases. Pre-defined architectures of CNNs, which are the state-of-The-Art algorithm and techniques of transfer learning is used in the project. In this study, a Transfer Learning strategy is utilized, in which a previously trained model is utilized to train on images of various lung disorders taken from the dataset, covering safe samples. Some examples of these lung diseases are lung opacity, viral pneumonia, and covid. © 2022 IEEE.
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The opportunity to live and take part in community life is a basic human right, and persons with disabilities (PwD) often need additional care and support to achieve this. This becomes a real challenge in a developing society. The goal of this research is to create a vision for the empowerment of people with disabilities and to pave the way for their independent living in a developing society. The study used a mixed design method. Analyzing data from various government reports resulted in a status analysis of disability in the state of Kerala, India. The study found that the gaps identified in the disability sector in Kerala were primarily in the areas of the availability of sustainable model programs, innovations, research, education, skill development, and employment coupled with an inadequate ecosystem for the implementation of projects and schemes. A qualitative study design was adopted. The participants were selected using the expert analysis technique of purposeful sampling and data was collected using an interview guide. The interview transcripts were analyzed using thematic analysis and are presented in a descriptive format. Despite the fact that the data in several government agencies are incomplete, it was encouraging to learn that several schemes to assist people with disabilities are being implemented. Local governments were responsive to disability even during disasters such as floods and the COVID-19 pandemic, but more planned approaches should be spearheaded. The vision for the future is targeted at achieving, among other goals, independent living for PwD. © 2023 SAGE Publications.
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Pulmonary artery pseudoaneurysms (PAPs) are uncommon entities consisting of contained rupture of the pulmonary artery and are a potentially fatal cause of hemoptysis. We describe two index cases of left lower lobe PAPs and arterial ectasia post-COVID-19 pneumonitis and their endovascular treatment with Amplatzer vascular plug, coils, and glue.Copyright © 2022. Indian Society of Vascular and Interventional Radiology. All rights reserved.
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In this paper, there are four distinct models utilized for the retrieval of CSPM from the Sentinel 2A/2B satellite imageries by using cloud computing techniques. In this study, a comparative analysis of different CSPM models was carried out at three different sites (Haridwar, Varanasi, and Hooghly). The study reveals that there are significant changes in CSPM in the Ganges in three different periods such as pre, during, and post-COVID. Noteworthy, fewer anthropogenic activities have generated important transformations in aquatic environments during the COVID. © 2023 IEEE.
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Background: COVID 19 has two-way interaction with Type II Diabetes Mellitus. First, patient with DM are more prone for developing severe COVID 19. Second, moderate to severe COVID 19 can present with new onset DM or may lead to hyperglycaemia and hyperglycaemic complications in Type II DM patients. In this report we present 4 cases of COVID 19 associated Hyperglycaemic Complication (3 with Diabetic Ketoacidosis and 1 with Hyperglycaemic hyperosmolar state). Method(s): Case Series of patients admitted to Thumbay Hospital, Ajman. Result(s): We report 4 cases of COVID 19 patients who presented to us with hyperglycaemic complications. There of them had features of Diabetic Ketoacidosis and one had Hyperglycaemic hyperosmolar state. All were treated with IV Insulin infusion and IV Fluids. COVID 19 infection was managed as per MOH protocol. All patients recovered well and were discharged in stable condition. Discussion(s): COVID 19 is associated with new onset DM or may lead to hyperglycaemic complications in patients with Type II DM. There are three pathophysiological processes which may be responsible for this finding. One, SARS-CoV-2 virus is known to enter the body through angiotensin-converting enzyme (ACE) II receptors in the pulmonary pneumocytes leading to infection and inflammation. Similar ACE-II receptors are also expressed in key metabolic organs and tissues, including pancreatic beta cells, adipose tissue, the small intestine, and the kidneys. Direct infection of pancreatic beta-cells with SARS-CoV-2 virus with beta-cell cell injury is likely the underlying mechanism for development of new onset diabetes and hyperglycaemia in existing diabetic patients. Such direct beta cell infection can cause hyperglycaemic complications in asymptomatic or mild COVID 19 as well. Two, moderate to severe COVID 19 is associated with hyperinflammatory immune response leading to marked rise in inflammatory mediators such as C-reactive protein and ferritin. Such hyperinflammatory response can also lead to hyperglyacemia in patients with diabetes mellitus. Three, corticosteroids are mainstay treatment of patients with moderate to severe COVID 19 and would definitely contribute to worsening of hyperglycaemia in these patients. Our patients presented to us with hyperglycaemic complications before initiation of any treatment. It is likely that such a situation would be due to direct infection and destruction of beta cells with SARS-CoV-2 virus infection. Conclusion(s): Type II Diabetes Mellitus patients are high risk of developing hyperglycaemic complications due to COVID 19. This can lead to increased morbidity and mortality. Patients with Type II DM should seek medical attention even if they have mild to asymptomatic COVID 19 to monitor for hyperglycaemic complication which can develop irrespective of severity of stage of illness.