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nCOVID19 - A Tracker and Preventive measures

The spread of the pandemic expanded exponentially prompting a serious ruin in the brains of the individuals.

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nCOVID19 - A Tracker and Preventive measures

The spread of the pandemic expanded exponentially prompting a serious ruin in the brains of the individuals.

The problem nCOVID19 - A Tracker and Preventive measures solves

The individuals with typical influenza and cough or even awful inhale like side effects alarm a great deal in the ongoing flare-up of the pandemic and moves into the condition of hypertension and wretchedness. Our application underpins the improvement in the personal satisfaction of the individuals by demonstrating a portion of the bits of knowledge of various types of infection and whether they should visit a specialist and for day or two on the off chance that typical influenza like inclinations is there, at that point our foundation teaches individuals about the ongoing medicinal services and preventive measures to be taken during the equivalent. In the event that the issue continues for a limited period, at that point it would divert a message in the content box portraying the prudent moves that ought to be made quickly as a matter of course with the goal that circumstance may not turn out to be a lot of more awful. The application additionally delineates a tracker model which notes down all the cases all through the globe and furthermore advices individuals for the quick activities on the itinerary items and strategies of self-isolate to stem the spread of the infection making the threating such massive masses.

This application can likewise be utilized by the administration of India , taking as an official preventive measure and furthermore to spread the words among the general population and to teach the appropriately and more in a viable manner.

Challenges we ran into

While integrating the web-application making it responsive was a challenging task.
The use of data for plotting the data using plotly was time consuming as the the information which we got through the pasrer using a javascript function through the datasets of JOHN HOPKINS UNIERSITY was an effective challenge.
The integration of mapAPI for the mobile application and the integration to the app using Apple.SwiftAPI Key.
The disease prediction model could be much better machine learning model with enhanced data sets so that accuracy touches the apogee but keeping in account of time as well as deployment we focused on a simple model.
The future scope of the problem may be focused on some of the other outbreaks and guide people on the same through the medium of Digital India.

Technologies used

Discussion