Smarter Baggage Tracking with Real-Time Data

Air travel generates a constant stream of baggage events: check-ins, scans, loadings, and transfers.
The challenge? These events arrive in fragments, across systems, and at different times. Turning this noisy flow into a clear, reliable picture of where each bag is in its journey is anything but simple.

At OnBased, we solved this by building a stateful streaming pipeline on Databricks, powered by the latest Spark 4.0 technology. Instead of treating each baggage event in isolation, our system remembers the story of every bag — from check-in to arrival — and continuously updates it in real time.

What This Enables

Full lifecycle tracking – follow each bag across multiple flights and transfers.
Accurate event correlation – connect scattered scans into a single journey.
Dynamic enrichment – merge baggage data with live flight leg information as it happens.

Why It Matters

With the new transformWithStateInPandas API, our engineers can model complex rules in plain Pandas, making the system faster to build, easier to maintain, and more adaptable to new airline data sources.

The result: airlines gain real-time, lifecycle-aware baggage visibility — reducing mishandling, improving passenger experience, and unlocking smarter operational decisions.