Personal flight intelligence
Every flight becomes a better prediction.
I built AeroStats AI to turn my drone flight logs into something anyone can understand: where I flew, how the battery behaved, what conditions affected the flight, and how machine learning can improve the next prediction as more flights are added.
Import
DJI flight records become normalized telemetry.
Analyze
Battery, route, weather, GPS and signal are compared.
Learn
Models retrain as more real flights are added.
Built around my own data
From raw telemetry to evidence that the model works.
Each uploaded DJI log becomes a replayable flight story with maps, battery efficiency, weather context, and transparent model outputs that show what the system knows and what still needs more data.
Replay every flight
Map path, synchronized telemetry, event markers, and controls for reviewing exactly what happened.
Measure efficiency
Compare battery drain, speed, altitude, route efficiency, signal quality, and return margin.
Validate the ML
Train battery, risk, and anomaly models with transparent validation metrics and confidence limits.
Add flight context
Join weather by GPS and time so changing conditions become part of the analysis.
Telemetry pipeline