My approach to the Uber Nairobi Ambulance Perambulation Challenge ;
To begin with, it was important to observe the possible causes of road accidents and the factors that influence these incidents.
I observed unsurprisingly that the Time of the day, Day of the week, Public Holidays, and weather conditions had a lot of influence on the accident patterns. You can check this out in more details here
Then I grouped the accident locations based on this and optimized the ambulance locations for each time of the day(3Hr window), Day of the week, Public Holidays, and extreme weather conditions using a gradient descent algorithm to minimize the closest ambulance location to each accident location.
Since these groups of data are overlapping, The tricky part was determining which group takes preference. For example, the Ambulance location obtained for All days 3-6 pm may perform better than the location obtained from a more specific set of data like Sundays 3-6 pm.
I'll be happy to answer questions or clarifications under this thread
Thanks a lot. It might inspire others to do the same. And congrats on winning!
Thanks for sharing. Great solution
Thank you very much for sharing! Congrats!