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Why Hyderabad commuters skip the metro, and the no-code app I built to help

A psychology student with no coding background asked commuters why they avoid the metro, and found the answer was overcrowding. This is how I turned that insight into a no-code prototype using AWS PartyRock.

I’m a psychology student, not a coder. When I joined Environmental Hacks, I picked the Air track because I see the problem every day: Indian cities are getting more polluted, and a big reason is the number of petrol and diesel vehicles on the road. Many households own two or three.
My first assumption was that people avoid the metro because they don’t care. So I asked commuters why they drive. The answer wasn’t “I don’t like the metro.” It was overcrowding. People use the metro, but when it’s packed they go back to their own bikes and cars. So the fix isn’t only “build more metro,” it’s also helping people use the metro we already have more comfortably.
I built Metro vs Vehicle with AWS PartyRock, a no-code app builder. I described the app in plain English, and PartyRock generated the inputs and outputs. You enter a trip distance and vehicle type, and it shows an estimate of the CO₂ saved by choosing the metro, the money saved on fuel and parking, how fewer vehicles ease traffic and improve road safety, and tips for beating crowding at peak hours. I exported the PartyRock bundle and used an AI assistant (Claude) to turn it into a standalone HTML page that runs in any browser. The code is on GitHub:  BhaktaPrahalada/-metro-vs-vehicle: Commute comparison tool for Hyderabad, built with AWS PartyRock  .
I showed the idea to three commuters. All three found it helpful. One said [the first person’s comment in your words]. Another said it helps us see how much we are polluting the city. The third said that if public transport were much better, both travel costs and pollution could come down, and suggested that as the next addition. That is a very small sample, so I treat it as early feedback, not proof.
The figures in the app are rough estimates (emission factors per km, fuel prices, metro fares), not measured data, and there is no live crowding data yet. My next step would be connecting real crowd data from the metro operator.
Fewer personal vehicles means cleaner air, smoother roads and safer streets that are easier to manage. If the metro feels comfortable, people will choose it. I built this with no coding experience, which shows that anyone with a real problem and curiosity can start solving it.
# hackathon# ai# aws-partyrock
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