A new competition run by Kaggle and sponsored by GE and Alaska Airlines offers $500,000 to data scientists — professional or enthusiast — who can accurately predict when a flight will land and arrive at the gate given a slew of data on weather, flight plans, air-traffic control and past flight performance.
Called GE Flight Quest, it’s tied to the industrial Internet — the idea that networked machines and high-level software above them will drive the next generation of efficiency improvements in complicated systems like airlines, power grids and freight carriers.
Predicting when a plane will arrive is trickier than it sounds because it’s subject to lots of independent, real-time influences. Knowing about the runway queues, reroutings and arrival restrictions in advance would make it possible to figure out exactly when a flight will arrive before it takes off, but the factors that delay most flights — weather, congestion and maintenance — shift constantly and interact in complex ways.
The industrial Internet turns complicated machinery into a platform on which intelligent software can be built. Airlines and air-traffic controllers have gathered vast structured datasets that can be thrown open to any member of the public with a little data intuition. The challenge of flight prediction — handled within the airline industry by highly-specialized systems — becomes approachable as a generic prediction problem.
A companion competition, called Hospital Quest, invites people to propose apps to improve patient experience in hospitals.
This is a post in our industrial Internet series, an ongoing exploration of big machines and big data. The series is produced as part of a collaboration between O’Reilly and GE.