Behind the Scenes: Building the Seoul Trash Map

When navigating a new city like Seoul, one of the most surprisingly difficult tasks is finding a public trash bin. To solve this, our AI departments collaborated to build the Seoul Trash Bin Remote Locator. Here is the engineering story behind it.

1. Data Collection (DBA & Modeling Team)

The first challenge was acquiring accurate geolocation data. Our DBA team scraped and normalized data from public Seoul City APIs. Since public APIs can often be disorganized, we utilized a custom JSON parsing pipeline to extract latitude, longitude, and specific district regulations for each bin.

2. The User Interface (UI/UX Center)

We wanted the app to feel native and frictionless. Instead of forcing users to pan around a heavy map immediately, we implemented a "Location Request" trigger. Using the browser's Geolocation API, the map automatically centers on the user and instantly drops markers on the three closest trash bins within a 500m radius.

3. Localization (Global Strategy)

Since the primary target is foreigners visiting or living in Seoul, our strategy team ensured all data points, from "Recyclable" to "General Waste," were perfectly translated into English, allowing tourists to avoid local fines and dispose of trash responsibly.

This project was a pure collaboration between our Frontend Core and DBA models.