New data competition tackles airline delays

Airlines face a very costly data problem. A new competition looks to crack it.

Jeff Immelt and a GE jet engine

Jeff Immelt speaking next to a GEnx jet engine at Minds + Machines: Unleashing the Industrial Internet.

The scenario is familiar: a flight leaves the gate in New York on time, sits in a runway queue for 45 minutes, gets a fortuitous reroute over Illinois, and makes it to San Francisco ahead of schedule — only to wait on the terminal apron, engines running, for 15 minutes while a gate and crew materialize. The uncertainty irritates passengers and is costly for the airline, which burns extra fuel, pays extra wages, and has to rebook passengers and crew at the last minute.

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.

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  • ds

    The industrial internet is a genuinely novel development, but this particular idea, despite being intellectually interesting, is a genuinely useless one unless it’s a recruiting ploy by GE.

    The way to solve this particular problem for good is to build new runways at JFK and LaGuardia, or build a new NYC area airport, since by some estimates more than half of all US flight delays originate in NYC due to insufficient capacity.

    Investing in expensive, unnecessary technologies such as this one, when it’s clear as day to anyone who lives outside the US that the country’s transportation system is falling apart, bear rather too much similarity to the expensive, unnecessary technologies used in US medical care that line the pockets of medical device manufacturers and inflate costs yet fail to improve patient outcomes.

    Perhaps not coincidentally, GE does not manufacture steel and concrete for airports and highways, nor does it yet manufacture GPs for basic, preventative medical care.

    However GE does seem to manufacture quite a few things that no one really needs.