“One of the biggest challenges on these projects
is figuring out what data you need to achieve these
goals,” says Jun Chen, PhD, senior lecturer at the
School of Engineering, University of Lincoln, Lincoln, England. He’s the project lead for a three-year,
£ 1 million airport big data project in Lincolnshire,
England. Locating data is just the first challenge.
Next comes building reliable systems to model factors such as aircraft movement and fuel consumption, which teams can then use to coordinate and
optimize air traffic and flight paths.
Dr. Chen’s project team is using algorithms
(some relying on machine learning) to calculate
optimal airport ground traffic. The goal is to shorten
the time to takeoff and reduce fuel consumption.
His team began by meeting with stakeholders from
airlines, airports, aircraft engine manufacturers and
universities to share their project model and discuss
terms for accessing the data. Once they saw the
value in what Dr. Chen’s team wanted to do, they
were excited to share the data, he says. His team is
now running simulations to validate the reliability
of various proposed models against the data and
to test travel models to see where efficiencies can
be gained to improve ground movement. “
Improving the efficiency of surface movement plays a key
Big Data in Flight
A lot can go wrong on flights: lost luggage, delays
on the tarmac, missed connections and canceled
flights, for starters. But these headaches could
diminish as project teams leverage reams of data to
improve every aspect of the travel process.
Around the globe, airports and airlines are sponsoring big data projects to alleviate airport congestion and make air travel more efficient. As airports
struggle to accommodate a growing number of passengers while operating at near maximum capacity,
innovative use of data could deliver big benefits.
John F. Kennedy International Airport in New
York, New York, USA is implementing integrated
planning software that uses big data and forecasting models to track visitor flow and flight
operations so the airport can better predict traffic patterns and adapt staffing levels in response.
Before, the team had been using one giant spread-sheet. Similar projects are already underway in
other cities. London, England’s Heathrow Airport
is using big data to better predict whether passengers will make their connections to avoid
flight delays. And airports in Sydney, Australia
and Copenhagen, Denmark are using sensors and
big data to reduce choke points by anticipating
foot traffic flows.
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