Natural disasters occur all over the world and it is can be considerably difficult to estimate the cost of repairing and supply relief to a given area. We hope that our estimator will make it easier to get an idea of the costs associated with providing relief to any given natural disaster.
What it does
It currently takes the latitude and longitude of a selected area and estimates a state-wide cost to repair a given area suffering from a given natural disaster. We currently are able to display the wealth factor of every state.
How We built it
We built the frontend for our website using react. We then used flask to create the backend. We the used the Google Platform for kubernetes, and finally we used MongoDB for our database.
Challenges We ran into
We faced a lot of challenges in DevOps. It ranged from not getting Azure kubernetes to work properly and forcing us to switch to Google-Cloud-Platform all the way to our domain not properly working for reasons beyond our comprehension. We then proceeded to face challenges in our front end that included making our map interactable
Accomplishments that We're proud of
We were able to create an intractable map that has a properly scaling marker. The marker can be moved upon clicking the map. We were also able to actually host our website (which we felt impressed with after all the difficulties we had to overcome).
What We learned
We learned how to use MongoDB, and learned a lot of techniques for debugging DevOps.
What's next for Geo-based Disaster Relief Calculator
We plan to increase the scalability of our project. We need to implement the different equations to calculate the different types of damaged with the different natural disasters. Then we also need to calculate the different types and number of businesses operating in a given radius. It currently operates on a macro-scale but we have created the tools to allow us to operate much more locally. We also plan on using machine learning tools (such as Azure) to allow us to make even more accurate estimates and possibly even estimate vulnerability of a population with respect to aspects like age.