Contact person: Transit Analytics Visualization Platform

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Location: Dundas, Canada

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I need a fully-functioning, web-based platform that ingests both static and real-time GTFS feeds, processes them through a Python-driven pipeline, and turns the results into fast, interactive map views. The first milestone will zero-in on operations analytics, with route performance front and centre: dwell times, headway adherence, on-time performance, and speed profiles must be surfaced on maps with layered overlays so users can compare patterns in real time or jump back through historical slices.

The workflow I have in mind:

• Data ingestion & storage – automatic retrieval of multiple GTFS feeds (static and RT), cleaned and stored in a scalable database ready for high-volume queries.
• Analytics engine – Python modules that calculate route-level KPIs, refresh on a rolling schedule, and expose results through an API.
• Front-end visualisation – a responsive web UI that calls those APIs and renders route performance with Mapbox or Google Maps overlays, complemented by drill-down dashboards and exportable reports.

Acceptance will be based on:
• Map overlay that updates seamlessly as new real-time data arrives.
• Ability to filter by route, direction, date range, and time of day without noticeable lag (<2 s).
• Clean, commented Python code and deployment scripts ready for cloud hosting.

If you’ve tackled GTFS pipelines, map SDKs, and performance-minded UIs before, let’s talk about timelines and the best staging approach for incremental releases." (client-provided description)