Hyperlocal Predictive Parking · Munich
Parkcast Lab
A prototype that predicts parking availability on a tiny, highly regulated patch of Munich using manually curated data, lightweight ML models, and a phone-style map interface.
About This Prototype
This is the in-progress Parkcast prototype for hyperlocal parking predictions in my neighborhood in Munich. Parking here is notoriously difficult, so I finally asked the real question: where do I have any chance of finding a spot at a given time? The interface uses a Leaflet map with a time slider and color-coded street segments, each representing the predicted parking availability for that segment.
The current version uses dummy logic for visualization purposes. In the next version, it will connect to the actual ML model and API that processes manually collected parking data.
Key Features
- ▸Street-Level Parking Predictions
- ▸Hyperlocal, Rule-Aware Map Overlay
- ▸Phone-Style Interactive UI
- ▸End-to-End ML Pipeline
Tech Stack
- ▸Next.js
- ▸Scikit-learn
- ▸React
- ▸FastAPI