IoT-Based Automatic Corona Virus Detection and Monitoring System

2021 ◽  
pp. 229-241
Author(s):  
Dipak P. Patil ◽  
Amit Mishra ◽  
Tushar H. Jaware
Keyword(s):  
Monitoring System ◽  
Virus Detection ◽  
Corona Virus

scholarly journals Solar Powered Smart Dry Hand Sanitizer Dispenser Machine with Level Monitoring System

2021 ◽  
Vol 9 (VI) ◽  
pp. 4898-4901
Author(s):  
Purnima K. Burade
Keyword(s):  
Monitoring System ◽  
Distribution System ◽  
Virus Disease ◽  
Hand Washing ◽  
Cross Contamination ◽  
Hand Sanitizer ◽  
Corona Virus ◽  
The World ◽  
Solar Powered ◽  
Level Monitoring

Corona virus disease (Covid-19) is endangered in the world. Since the WHO declared it a pandemic and many cities are in lockdown, people have been unable to get out of their homes and thousands of people have already lost their lives. With the outbreak of the global Covid-19 crisis, hand washing and hygiene have become an absolute necessity in daily affairs. The Automatic Mist Based Sanitizer Distribution System is a very useful resource with level monitoring in the fight against corona virus. This contactless delivery system helps clean dry hands regardless of clean surfaces and helps reduce the spread of cross-contamination.

scholarly journals Seasonality of non-SARS, non-MERS Corona viruses and the impact of meteorological factors

2020 ◽  
Author(s):  
Olympia E Anastasiou ◽  
Anika Huesing ◽  
Johannes Korth ◽  
Fotis Theodoropoulos ◽  
Christian Taube ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Cloud Cover ◽  
Detection Rate ◽  
Meteorological Factors ◽  
Seasonal Pattern ◽  
Virus Detection ◽  
Virus Infections ◽  
Weather Factors ◽  
Corona Virus ◽  
Corona Viruses

Background: Seasonality is a characteristic of some respiratory viruses. The aim of our study was to evaluate the seasonality and the potential effects of different meteorological factors on the detection rate of the non-SARS Corona Virus detection by PCR. Methods: We performed a retrospective analysis of 12763 respiratory tract sample results (288 positive and 12475 negative) for non-SARS, non-MERS Corona viruses (NL63, 229E, OC43, HKU1). The effect of seven single weather factors on the Corona virus detection rate was fitted in a logistic regression model with and without adjusting for other weather factors. Results: Corona virus infections followed a seasonal pattern peaking from December to March and plunging from July to September. The seasonal effect was less pronounced in immunosuppressed patients compared to immunocompetent. Different automatic variable selection processes agreed to select the predictors temperature, relative humidity, cloud cover and precipitation as remaining predictors in the multivariable logistic regression model including all weather factors, with low ambient temperature, low relative humidity, high cloud cover and high precipitation being linked to increased Corona virus detection rates. Conclusions: Corona virus infections followed a seasonal pattern, which was more pronounced in immunocompetent patients compared to immunosuppressed. Several meteorological factors were associated with the Corona virus detection rate. However, when mutually adjusting for all weather factors, only temperature, relative humidity, precipitation and cloud cover contributed independently to predicting the Corona virus detection rate.

scholarly journals Corona Virus Detection Using Transfer Learning Technique

2021 ◽  
Author(s):  
Sangeetha Balachandran ◽  
Senthil Prabha R ◽  
Ravitha Rajalakshmi N ◽  
Srilam K
Keyword(s):  
Transfer Learning ◽  
Virus Detection ◽  
Corona Virus ◽  
Learning Technique

scholarly journals Positive Epstein-Barr virus detection in corona virus disease 2019 (COVID-19) patients

2020 ◽  
Author(s):  
Ting Chen ◽  
Jiayi Song ◽  
Hongli Liu ◽  
Hongmei Zheng ◽  
Changzheng Chen
Keyword(s):  
Epstein Barr Virus ◽  
Virus Disease ◽  
Acute Infection ◽  
Virus Detection ◽  
C Reactive Protein ◽  
Barr Virus ◽  
Reactive Protein ◽  
Corona Virus ◽  
Single Center Study ◽  
Epstein Barr

Abstract Background Since December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused an outbreak of corona virus disease 2019 (COVID-19) in Wuhan, China. The Objective of this study was to detect the EBV coinfection in COVID-19.Methods In this retrospective single-center study, we included 67 patients with confirmed COVID-19 in Renmin Hospital of Wuhan University from January 9 to February 29, 2020. Patients were divided into EBV seropositive group and seronegative group according to the serological results of EBV, and the characteristics differences between the two groups were compared.Results 67 COVID-19 patients were included in our study. The median age was 37 years, with 35 (52.2%) females. Among these COVID-19 patients, 37 (55.2%) patients were seropositive for EBV viral capsid antigen (VCA) IgM antibody. EBV seropositive COVID-19 patients had a 3.09-fold risk of having a fever symptom than EBV seronegative (95%CI, 1.11-8.56; P=0.03). C-reactive protein (CRP) (P=0.02) and the aspartate aminotransferase (AST) (P=0.04) in EBV seropositive COVID-19 patients were higher than that in EBV seronegative patients. EB seropositive patients had a higher portion of corticosteroid use than the EB seronegative patients (P=0.03).Conclusions EBV acute infection was found in COVID-19 patients. EBV seropositivity was associated with fever and increased inflammation. EBV reactivation may affected the treatment of COVID-19.

scholarly journals Prototype Social Distancing Reminder Using HC-SR04 Sensor At The Payment Counter Via A Smartphone

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Ferry Wahyu Perdana ◽  
Shazana Dhiya Ayuni ◽  
Arief Wisaksono ◽  
Syamsudduha Syahrorini
Keyword(s):  
Infectious Disease ◽  
Monitoring System ◽  
Public Spaces ◽  
Literature Study ◽  
Social Distancing ◽  
Reading Accuracy ◽  
Corona Virus ◽  
New Type

Starting from the beginning of March 2019 and even until the end of 2020, the Indonesian people are experienced prolonged suffering due to the emergence of a new type of infectious disease called Corona Virus 2019. Social Distancing is a program that aims to prevent the transmission of the COVID-19 disease as early as possible. In this research, the method used is the observation technique and literature study for the implementation of the HC-SR04 sensor as one of the distance sensors used for distance reminders implemented in public spaces using IoT as a monitoring system. The results obtained are the reading accuracy of the HC-SR04 sensor is quite accurate to 100% accuracy and when the HC-SR04 sensor detects less than 8cm (1meter real distance) then the DF Player will sound, the LCD will display a display “Jaga Jarak Anda! ", And there will be a notification"Peringatan: Kondisikan Jarak" on a smartphone that has the Blynk application installed.

scholarly journals Positive Epstein-Barr Virus Detection in Corona Virus Disease 2019 (COVID-19) Patients

2020 ◽  
Author(s):  
Ting Chen ◽  
Jiayi Song ◽  
Hongli Liu ◽  
Hongmei Zheng ◽  
Changzheng Chen
Keyword(s):  
Epstein Barr Virus ◽  
Virus Disease ◽  
Virus Detection ◽  
Barr Virus ◽  
Corona Virus ◽  
Epstein Barr

scholarly journals Corona Virus Detection and Classification with radiograph images using RNN

2021 ◽  
Vol 9 (2) ◽  
pp. 768-781
Author(s):  
Dr Moulana Mohammed, Et. al.
Keyword(s):  
Neural Network ◽  
Virus Detection ◽  
World Health ◽  
Screening Tests ◽  
Machine Learn ◽  
Early Screening ◽  
Corona Virus ◽  
The World ◽  
Multi Level ◽  
The Given

We’re working on detecting the symptoms of Corona virus, also known as Covid-19, in this project.COVID-19 is a highly infectious disease that has been declared a Pub- lic Health Emergency and a Pandemic by the World Health Organization.The virus has infected over 25 million people worldwide,which has killed over 840,000 people and threat- ened the lives of millions more. COVID-19 is characterised by a dry cough, sore throat, and a high temperature. It is critical to find quick and accurate results for Covid-19 at this time in order to stop it in its early stages and avoid it from being a problem. Deep learning concepts are being used to analyse and classify symptoms from radiograph im- ages.Chest radiographs are one of the early screening tests to assess the onset of disease since the infection seriously affects the lungs.In this proposal, we used a recurrent neu- ral network model combined with a multi-level thresholding technique to detect Corona virus. One of the machine learn- ing techniques for prediction is the RNN model. A Recur- rent Neural Network is used to decide if the given images belong to Covid-19 during the classification process. This implementation is based on a publicly available dataset of radiograph images.

Monitoring des Arzneimittelmissbrauchs 2006 bei Klienten von Suchtberatungsstellen (PHAR-MON)

2007 ◽  
Vol 53 (7) ◽  
pp. 65-77 ◽  
Author(s):  
Susanne Roesner ◽  
Heinrich Küfner
Keyword(s):  
Monitoring System

<span class="fett">Hintergrund und Zielsetzung:</span> PHAR-MON ist ein Monitoring-System, das die auf dem deutschen Markt befindlichen Arzneimittel in ihrer Bedeutung für die Entwicklung von Missbrauch und Abhängigkeit in Suchtberatungsstellen überwacht. </p><p> <span class="fett">Methodik:</span> Klienten ambulanter Beratungsstellen werden im Rahmen der Standarddokumentation zu ihrem Arzneimittelkonsum befragt und Fälle eines abhängigen Konsums, eines schädlichen Gebrauchs oder eines Missbrauchs in PHAR-MON dokumentiert. </p><p> <span class="fett">Ergebnisse:</span> Im Jahr 2006 wurden insgesamt 448 Meldungen von 276 überwiegend alkohol- und drogenabhängigen Klienten in das Monitoring einbezogen. Tranquilizer vom Benzodiazepin-Typ wurden in allen Klientengruppen mit Anteilen zwischen 29,1 % und 35,3 % am häufigsten dokumentiert. An benzodiazepinabhängige Klienten werden zunehmend auch Nicht-Benzodiazepin-Hypnotika verordnet. Bei opioidabhängigen Klienten war im Zeitraum der letzten fünf Jahre ein Anstieg im missbräuchlichen Substitutionsmittelkonsum von 14,9 % auf 33,8 % zu verzeichnen. </p><p> <span class="fett">Schlussfolgerungen:</span> Das Risiko gefährlicher Wechselwirkungen zwischen Arzneimitteln mit Alkohol und Drogen sollte stärker als bisher in die ärztliche Verordnungsentscheidung einbezogen werden.

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