Balogun Hammed Opeyemi, first place winner in the Uber Nairobi Ambulance Perambulation Challenge, shares his winning approach

2 min readSep 16, 2021


We’d like to introduce Balogun Hammed Opeyemi, winner of the Uber Nairobi Ambulance Perambulation Challenge. Read on to see how he came out on top and learn from his approach.

Please introduce yourself to the Zindi community.

I am Balogun Hammed Opeyemi (Balogun) from Lagos, Nigeria. I have a Bachelor’s and Master’s Degree in Physics from Lagos State University and University of Lagos respectively. I am passionate about research and solving real-life problems.

Tell us about your solution for 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. Unsurprisingly, I observed 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 detail here.

Then I grouped the accident locations based on this and optimised the ambulance locations for each time of the day (3 hour window), day of the week, public Holidays, and extreme weather conditions using a gradient descent algorithm to minimise 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 3–6pm may perform better than the location obtained from a more specific set of data like Sundays 3–6 pm.

What sets your solution apart from the rest of the field?

I think what made the difference for me was:

1) running each grouping individually and observing how their optimised locations differed from the general location, and also how they performed during the validation and test period.

2) Choice of the validation period. After observing that accident locations were influenced by time and period. I chose a validation period that mirrored the test set.”

What do you think of the AI community in Africa?

The biggest area of opportunity for AI in Africa is the youth population. Their interest in the field, creativity, and recognition of the many roles AI can play to solve everyday problems will certainly lead to great innovations. I believe with communities like Zindi, the gap between African youths and the rest of the world has never been slimmer. And over the next few years, the great breakthroughs in AI will be led by Africans.

On Zindi, I’m looking forward to more state-of-the-art projects and competitions, as well as a more vibrant community. My feature request is a repository for notebooks, which would be very beneficial for beginners. (Note: until then, feel free to check out our GitHub for notebooks!).




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