This document discusses building a scalable infrastructure to process and visualize near real-time public transportation data from Switzerland. It proposes acquiring data from APIs, storing it in Kafka and Elasticsearch, transforming it using Akka actors, and visualizing it through a React frontend. The system was able to handle 30x more trains with only 15% CPU usage, showing it is performant and scalable. The document concludes by discussing additional analysis that could be done on the historical transportation data.