UPDATED 14:01 EDT / JULY 05 2013

It’s a Bird! It’s a Plane! It’s Su… Big Data?

Before you jump to conclusions that this article is about The Man of Steel and Big Data, it’s not, though that would be awesome, wouldn’t it?  Anyway, this is about Big Data and aviation.

Not many of us have put much thought in the things happening around us, let alone the data we produce over time.  Yes, each and everyone of us produce data.  We produce it by simply uploading media to our social networking accounts, updating our status, posting anything on the web, sending SMS, MMS, e-mails – everything we do online produces data someway or the other and the services we use use some form of analytics to make sense of the activities in which we partake.

And just like anything that has to do with computers and machines, the aviation industry also produces data and.  And with Big Data analytics, these massive data sets can be harnessed for a variety of perks.

Big Data in Aviation

 

Preventive maintenance

As noted in Wikibon’s “Big Data in the Aviation Industry,” data produced by engines and sensors that collect data such as temperature, humidity, air pressure, from the environment are analyzed so service providers can predict when parts should be changed before they break down.  By keeping track of the wear and tear of the components or parts of the plane and maintaining these parts according to set standards, malfunctions can be prevented and costly replacement of parts can also be reduced significantly.

If planes are maintained and kept in good working condition, airplane downtime can be prevented.  That means passengers won’t have to be bothered with as many delayed or cancelled flights because of technical difficulties due to engine troubles and whatnot.

Flight, passenger and airport tracking

Though you can prevent technical problems by regularly maintaining the aircraft, environmental occurrences is another factor that is quite tricky to predict.  One minute you have clear blue skies, the next minute you’re faced with rolling thunder, lightning and dark clouds.

With Big Data, a centralized system can be created that tracks the status of airports to determine whether they are in service, how many people are currently in the airport, if the runways are clear and if they are able to accommodate emergency landings.  The availability of such data can help prevent flight delays, assist in transporting stranded or transferred passengers, and even save lives.

Improved customer experience

Airports and airlines are open to feedback from customers but it is quite hard to track them when everything is written on paper.  If there’s a way for these data points to be available digitally, it will be easier to curate customer feedback and see what are the top concerns and areas they should improve upon.

Obstacles in Aviation Data Analytics

 

Volume

Each aircraft produces terabytes of data and the biggest obstacle in making Big Data work for the aviation industry is transferring collected data to a centralized system that can be accessed by respective airport or airline departments for analysis.

Security

Aviation data is very sensitive as it deals with millions of lives everyday.  The problem with putting aviation data in the cloud is that if it falls into the wrong hands, it will yield disastrous results.

“Cloud computing offers many benefits, but it can be vulnerable to threats if managed to common industry standards. As cloud computing uses insecure or mission critical applications increase, it is likely that more criminals will find new ways to exploit system vulnerabilities. To mitigate the threat of security breaches, cloud computing needs to invest heavily in risk assessment to ensure that the system encrypts to protect data, establishes a trusted foundation to secure the platform and infrastructure, and builds higher assurance in to auditing to strengthen compliance. Security concerns must be addressed to maintain trust in cloud computing technology,” Dr. Tulinda Larsen stated in her paper Cross-Platform Aviation Analytics Using Big Data Methods.


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