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A mobile covid vaccination strategy using mobile vans powered by real time logistics data and modular decision making framework.

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SoumavaBanerjee/TheCleverWorld_fullstack_hack21

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Easy Jabber

License Community Website

A basic GitHub repository with documentation and code of Easy Jabber,a self-proposed solution to 2021 Hackathon conducted by IIIT PUNE. Solutions here is mainly a common platform using GeoJson to connect the Authorities(Vaccine Drive Creators/Government) and Users through a data-driven location tracking platform. This web application will enable the one in need to connect with the vaccination points in a much optimised manner.

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Contents

Short description

What's the problem?

In the current situation, there are mainly two broad categories of problems that are widely faced in the vaccination scenario. First is overcrowding and second is wastage of vaccines. The necessity of vaccination isn’t unknown to anyone now, thus a definite is solution is the need of the hour.

How can technology help?

In this pandemic situation, technology can help managing the resources and reaching out the needy ones in a smarter and time efficient manner, contributing to the larger welfare. It not only reduces overcrowding but also helps in optimized time management.

The idea

The User will register themselves with authentic credentials and will be able to select a nearest vaccination standpoint with in 3kms of their home location. A day prior the user will be informed with their allocated stand point and other vital details with an approximate time slot division based on their age group. On D-day, the users will agin be notified 30mins prior the Van arrives and right from then, the users will be able to track the live-location of their vans. This will also decrease the work of the authority side, populating the stand points based on population density using the heat map.

Live demo

Project website

Built with

  • React
  • Redux
  • React-map-gl
  • NODE JS and Express
  • MongoDB

Authors

  1. Shubham Dutta
  2. Prasun Das
  3. Soumava Banerjee
  4. Sohini Chakraborty

LICENSE

This project is licensed under the Apache 2 License - see the LICENSE file for details.

Acknowledgments

  • Based on real time applications.

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