It was a hack-a-thon where we were challenged to help solve an environmental issue
recycling is a big problem where i live, probably the biggest issue excluding covid-19 (not long term though)
Everyone talks about personal habit changes that would help recycling rates but intuitively it's annoying for people to be told by clingy activists how they should live their lives. I personally fucking hate to be told that I'm not living a sustainable lifestyle. bottom line is that it is naive to expect people to change their behaviour. So, I decided that my solution wouldn't rely at all on telling people what to do.
So I studied physical bin distribution and frequency, and took a look at very successful cities in terms of recycling rate (seoul, vienna, san fran etc.). I found that in my subdistrict, not only were there not enough recycling bins (frequency), but also that they were placed in suboptimal areas, e.g. I found one in a dodgy back-alley and another within the least-visited corridor of the local wet market).
I created a mathematical model that would predict, based on factors such as income, population density, area of district etc., the ideal distribution of recycling bins in a chosen subdistrict where I live, the results for which would be illustrated on google maps. By that I mean each bin would be displayed on the map as a marker. My model would prioritize proven high-volume recycling bin locations (middle of thoroughfares, intersections) rather than low volume locations. i didnt have time to create a backend so its just a local website thats hosted on my github.