High-Level Project Summary
Our issue is the Climate Change Disasters, so we have chosen the most frequent one of them which is Floods ! After we have identified the top Marginalized countries which suffer from Floods,then we've started to think about some solutions by merging technology (like water level sensors) with mechanical solutions (like water-gate) to create the best way to drain water and mitigate the effects of Floods against the people and their buildings.
Link to Project "Demo"
Link to Final Project
Detailed Project Description
we help bring to light regions where marginalized populations are facing a higher burden from environmental hazards, lack of access to resources and opportunities, and design solutions to bring
We have used the Geocoded Disasters (GDIS) Dataset, v1 (1960 – 2018) through several steps:
We analyzed the data through which we were able to find the areas where most of the natural disasters such as floods, earthquakes and volcanoes occur.so we have chosen the most frequent one of them which is Floods !
Then we used the geographical maps to filter the countries and extract the poor countries in which these choirs occur, then we've started to think about some solutions by merging technology (like water level sensors) with mechanical solutions (like water-gate) to create the best way to drain water and mitigate the effects of Floods against the people and their buildings.
Space Agency Data
We have used the Geocoded Disasters (GDIS) Dataset, v1 (1960 – 2018) through several steps: We analyzed the data through which we were able to find the areas where most of the natural disasters such as floods, earthquakes and volcanoes occur. Then we used the geographical maps to filter the countries and extract the poor countries in which these choirs occur
Hackathon Journey
It's been a really geat exprience. We have learnt a lot as individuals and as a team, we learnt how to conduct research about a challenge we weren't familiar with. We've chosen this challenge particularly because it affects millions of people around the world. The challenge wasn't easy but we managed to overcome the obstacles through determination and strong team work.
References
-Data resources: Determing poor countries: https://www.arcgis.com/home/item.html?id=ae80331630cd4c91b4b7458e391d3b65
-Determining Areas prone to natural disasters: https://sedac.ciesin.columbia.edu/data/set/pend-gdis-1960-2018
-Tools Python
Jupyter nootbooks
Tags
#space_for_change #NASA #Satellite_Images #Climate_Change #Disasters #Floods #Nature #Countries #Technology #Sewage_Pipelines #AI #Machine_Learning #World_Health #Data_Analysis #python #Data_Visualization
Global Judging
This project has been submitted for consideration during the Judging process.