"Kaggle" entries

Hacking robotic arms, predicting flight arrival times, manufacturing in America, tracking Disney customers (industrial Internet links)

The next wave of manufacturing will be highly automated--and American. Also, a hardware hacking collective rehabilitated a pair of cast-off industrial robots.

Flight Quest (GE, powered by Kaggle) — Last November¬†GE, Alaska Airlines, and Kaggle announced the Flight Quest competition, which invites data scientists to build models that can accurately predict when a commercial airline flight touches down and reaches its gate. Since the leaderboard for the competition was activated on December 18, 2012,¬†entrants have already beaten the benchmark prediction accuracy by more than 40%, and there are still two weeks before¬†final submissions are due.

Robot Army (NYC Resistor) — A pair of robotic arms, stripped from their previous application with wire cutters, makes its way across the Manhattan Bridge on a bicycle and into the capable hands of NYC Resistor, a hardware-hacker collective in Brooklyn. There, Trammell Hudson installed new microcontrollers and brought them back into working condition.

The Next Wave of Manufacturing (MIT Technology Review) — This month’s TR special feature is on manufacturing, with special mention of the industrial Internet and its application in factories, as well as a worthwhile interview with the head of the Reshoring Initiative.

At Disney Parks, a Bracelet Meant to Build Loyalty (and Sales) (The New York Times) — A little outside the immediate industrial Internet area, but relevant nevertheless to the practice of measuring every component of an enormous system to look for things that can be improved. In this case, those components are Disney theme park visitors, who will soon use RFID wristbands to pay for concessions, open hotel doors, and get into short lines for amusement rides. Disney will use the resulting data to model consumer behavior in its parks. Read more…

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. Read more…

O'Reilly Radar Show 3/12/12: Best data interviews from Strata California 2012

Doug Cutting on Hadoop, Max Gadney on video data graphics, Jeremy Howard on big data and analytics.

Hadoop creator Doug Cutting discussing the similarities between Linux and the big data world, Max Gadney from After the Flood explains the benefits of video data graphics, Kaggle's Jeremy Howard looks at the difference between big data and analytics.