Data & Methodology
How Airlert synthesizes official systems with passenger signals.
1. Official Data Sources
Airlert’s foundational data relies exclusively on official aviation sources. The primary source is FlightAware's AeroAPI, which processes ADS-B (Automatic Dependent Surveillance-Broadcast) telemetry, radar data, and airline schedules to provide exact positional updates and phase transitions.
We also integrate direct FAA NAS (National Airspace System) feeds to capture broad operational constraints, including ground stops, ground delay programs, and airport-specific disruptions.
2. Markers: The Passenger Network
While official systems define the structural reality of a flight, they suffer from reporting latency—especially around the gate and tarmac. Airlert introduces a secondary data layer of community markers. This layer surfaces pre-defined disruption signals posted by passengers geographically bound to the flight's manifest.
Because these are structured signals (e.g., "missing crew", "late airplane", "traffic queue") rather than open-text chatter, they can be plotted cleanly alongside the official timeline.
3. Understanding Signal Types
To maintain precision and avoid overclaiming, Airlert actively categorizes events into three classes:
Confirmed Events
Hard telemetry points (e.g., wheels up, gate arrival time updated to 14:00 UTC). These are immutable facts provided by our integration with AeroAPI.
Passenger-Reported Signals
Disruption observations posted by users. In our methodology, these are considered "early signals." They are often directionally correct and can surface issues before official systems reflect a delay, but they wait on official systems for objective verification. See the AAL1678 Case Study.
Contextual Markers
Extremely localized passenger observations where verification is impossible via telemetry—for example, "gate occupied" upon landing. Because official radar cannot track gate occupancy seamlessly, these markers provide plausible situational context to enhance the timeline, but are not treated as hard proof.
Our approach to flight intelligence strictly segregates official telemetry from passenger context. We aim to equip travelers with the earliest possible signals without substituting community reports for immutable facts.