Contributing to Flood Early Warning Systems (FEWSs) through crowdsourceing And Machine learning to mitigate Disaster and promoting SGDs".

Historically from the 90% of disaster experienced globally related to weather and natural occurrence, flood has 47% in this report finding either due to extreme storm, rainfall or climatic change all over the world. Affecting  over 2.3 billion people globally ( UNSR 2015).
The problem of flooding this project is looking at is the two types of phenomenal flooding we have from Fluvial flood to pluvial which look into the one cause by human activities within the cities that can result to this type of flooding. The problem that is always seeking for a profound solution is the problem of flood risk management .

Yes we have some people leaving the team because of busy schedule with other programs but now we are stable with team member like kihindel and Emmanuel

We have work with the theory of change model to redefine our problem , which has helped us to understand better what our problems are and who is our stakeholders

we under that taken the problem global  would be a bigger process especially when it come to crowdsourcing, the changes made in this project is to consider few case areas in Nigeria that has the high risk of flooding and profound solution

we have research on the exiting publication relating to flood activities particularly in Nigeria and to point out the gaps in this project, what has been done and what has not been done.  

Our pitch has a better look now than before, 

We developed a persona to better understand the need of stakeholders we are building for.

United Nations, INGOs or Other Experts

Possible overlap with other team members

We understand the need to simplify of problem well.

Ask we were told to do so in week one

Feedback was to narrow our solution to more applicable solution.