RouteReality: Building a Community-Powered Bus Tracker for Belfast When I first launched routereality.co.uk, the goal was simple: give Belfast and Northern Ireland bus users better, more accurate arrival predictions than the official sources provide. Unlike apps that rely solely on scheduled timetables or delayed GPS feeds, RouteReality is fully community-powered.

Users check predicted times, wait at the stop, and tap to report when the bus actually arrives. Every report feeds back into the system, refining predictions for everyone in real time.

Today, the site runs 24/7, covering 100+ routes and 17,000+ stops, with live updates constantly streaming in from real users across the country. But building and deploying a system like this one that people depend on every day was far from straightforward. Here are the main problems I encountered along the way, and how they shaped the project.

1. Keeping Real-Time Data Accurate When Users Are Always Reporting

The core of RouteReality is user-submitted arrival reports. In theory, more reports = better predictions. In practice, the live nature of the system creates immediate challenges.

Timing mismatches and outliers — People report arrivals at slightly different times due to boarding the bus, network delays, or simply tapping a second too early/late. Early on, a few bad reports could mess with predictions by minutes. I had to implement outlier detection (ignoring reports more than ~3 minutes off the median) and time window clustering to group reports for the same bus instance.

Duplicate or spam reports — With users constantly using the site, especially during peak commute hours, the same bus stop could receive multiple reports in seconds. Without careful deduplication logic (based on user session, location hints, and timestamp proximity), predictions would jump erratically.

Sparse data in the early days— When the user base was small, many stops had zero or one report per day. Predictions defaulted to timetable estimates, but users expected better. Bootstrapping accuracy required careful fallback logic and incentives to encourage early reporting.

**2. Scalability and Performance Under Constant User Load **Unlike a static site, RouteReality has users actively querying predictions and submitting reports at all hours. The system needs to handle concurrent reads/writes without lag, especially during busy periods.

Database pressure — Storing millions of timestamped reports requires a time-series-friendly setup. Early prototypes using a standard relational DB choked on write-heavy loads. Moving to a more scalable store (with proper indexing and partitioning by route/stop/day) prevented slowdowns.

Server costs and monitoring — Running 24/7 means no off-hours for heavy maintenance. Unexpected spikes in traffic (e.g., bad weather driving more bus usage) could spike costs or cause brief slowdowns. Setting up real-time monitoring dashboards became essential to catch issues before users noticed.

1. Live Deployment Nightmares: No Room for Downtime Deploying updates to a live system with constant user activity is unforgiving. Even a 30-second outage frustrates someone waiting at a rainy stop.

Zero-downtime deploys — Early deploys caused brief interruptions as the server restarted. Implementing blue-green deployments or rolling updates eliminated that pain, but required more infrastructure setup.

*Bug fixes under pressure *— A subtle bug in report aggregation once caused predictions to drift by 5+ minutes for a popular route during evening rush. Users noticed immediately and reported it (ironically helping debug). Hotfixes had to be rolled out without breaking ongoing sessions.

*Testing in production-like conditions *— Local tests missed real-world issues like network latency on mobile data, varied device clocks, or users in poor signal areas. Gradual rollouts and feature flags became my best friends.

Lessons Learned and What’s Next Launching RouteReality taught me that real-time, user-dependent systems are as much about people as technology. Community engagement is the biggest variable. The more people report, the better it gets, but getting that branch started requires patience and careful tuning.

Despite the challenges, the system is live, improving daily, and already helping commuters in Belfast and beyond. Future plans include better outlier handling, optional location-based reporting (with privacy controls), and deeper analytics to spot patterns (e.g., chronically late routes).

If you’re a regular user, thank you for every report. It directly makes predictions more accurate for everyone. And if you haven’t tried it yet, head to the journey page and start reporting. The more we all contribute, the better RouteReality becomes.

Always cross-check with official Translink sources, as RouteReality remains an independent community project.

Posted February 2026