Idea
Climate change disaster aid map
Purpose
With the increase of natural disasters due to climate change, this map aims to predict what aid will be needed before the disaster happens so that the aid is already in place.
Coordinate aid
Help communities be resilient to natural disasters/ reduce suffering caused by natural disasters
How it works
Using AI, Machine Learning and satellite forecasts
Need to know type of infrastructure and population information
Working with the UN and aid charities like red cross
Long-term predictions- Educate at risk communities on survival techniques
Short-term- placing aid near to where the disaster is going to happen to shorten the time taken to deliver aid
Why solution would be good
How it addresses the UN sustainability goals
3) Good health and wellbeing → medical resources, first aid
9) Industry, Innovation and Infrastructure → learning and protecting
10) Reduced inequalities → aid can be close and accessible to all
11) Sustainable cities and communities → surviving climate change
13) Climate Action
17) Partnerships between UN and other natural disaster charities → coordinate aid so not all in 1 place
Displaying Information
Interactive map?
Platform?→ identify closest and most suitable organisations allowing them to collaborate and coordinate response
Categories of aid required: medical, sanitation, infrastructure, repair, fire
Alert system?
#Sustainability #Infrastructure #Coordination #NaturalDisaster #Aid #HumanitarianResponse #Resilience #ClimateChange #ClimateAction #UNSDGs #PlanningAhead #AI #SDG3 #SDG9 #SDG10 #SDG11 #SDG13 #SDG17 #InternationalCollaboration #Designathon2022 #DisasterPreparedness #D22025
This makes complete sense to me! I would think its a case of the data all being there, just not connected and wrestled into something useful. I dont have much to add as you seem to have thought most fo this through quite well - but perhaps find some analogues of similar platforms. WHat do they look like, what data streams do you need to plug into and more importantly how to validate the algorithm with each real event so you could get better over time.
Amazon, for example, ships things to local warehouses in anticipation for order based on data analysis before someone has even ordered it. The logistical trigger points for your idea will have a similar logic and maybe there is something to be gained by exploring how they do it?
Finally I would think it would be useful to reach out to people in this field, both in the field and in academia, to see what they suggest as a way of adding more detail into the plan
Good luck!