ABSTRACT
The important reasons for the rapid spread of the novel coronavirus (2019-nCoV) was the lack of awareness of infected individuals about their health due to the 14 day incubation period of the virus and the subsequent un-intentional transmission, large scale ignorance of social distancing guidelines, and improper sanitary precautions and health. In this paper, we describe the development process of a system based solution for individuals to do Covid-19 susceptibility test using the SpO2 oxygen level detection test, to detect symptoms with higher levels of accuracy. We also discuss various other implementation features to prevent the unaware spread of the virus including providing details to the user regarding government guidelines related to containing transmission of the virus, alerts to the user about periodic maintenance of sanitary guidelines, social distancing, and notifying the user on non-compliance of above features. Finally, we discuss possible future extensions to stricter the measures taken up by the user to prevent any mistakes- like a front-camera based mask authentication approach, and alerting the user on entering crowded areas based on Bluetooth crowd sensing. Also, this system will be further developed into a mobile application.
ABSTRACT
The coronavirus disease (later renamed as COVID-19) originated in Wuhan, China and now has spread throughout the world. Many methods have been implemented so as to bring the condition under control, however it has been a difficult task to predict when the number of cases will start decreasing. Hence, we are trying to predict, using the Susceptible-Exposed-Infectious-Removed (SEIR) model, when the number of cases in India will start decreasing. The implementation will start on district/city level, then to the state level and then the country level. We are going to develop a WebApp, which will maintain a dashboard of the active cases, cured cases, and the death cases daily of India. We are trying to train the model on the data from a city/country where there was a significant decrease in the cases, to check our model's accuracy. We are expecting to get a probable period of time when the cases will decrease on an average all across India.