About the Post

Author Information

strategist, marketer, blogger, social and tech trend watcher, dog-lover | Follow on Twitter @socialrati

social business infographic

3 IoT Factors in Losing A Plane

As the headlines continue to report a lack of information about the mysterious Malaysia Airlines disappearance, one of the questions being asked is why crucial flight data like that recorded on an airplane’s black box is not transmitted off the plane in real-time? Why keep the data locked in a crash site that may or may not be found?

Every commercial plane is loaded with sensors that continuously collect data but this recent mystery highlights some interesting limits to our capabilities in what seems like the  limitless universe of the Internet of Things.

Malaysia Airlines: IoT Example

Three factors impact our evolving rationale for what data to collect, filter, analyze, store and transmit.

1) Technology

Advances in sensor technology mean we now have the ability to put a sensor on almost anything from a jet engine to your car keys.  Sensors make it possible to monitor billions of devices, people, and activities in real time.  While ecosystems are forming around sensors and the rest of our world, one technology challenge is slowing progress – data management.

Big data is the term for all of the data generated by the Internet of Things (IoT) but “big” barely describes the enormity of the challenge involved in collecting, filtering, querying, analyzing, and storing all of the available data that the universe of sensors makes available.   For example, a single jet turbine can produce several hundreds of terabytes of data per day.

Add to that all the data from the thousands of other sensors on a plane and multiply that by all the planes in a commercial fleet like Malaysia Airlines has, and the immense quantity of data becomes apparent.  Then, factor in the fact that streaming data will be mixed with historic data and re-streamed in the form of predictive data, and the data challenge grows exponentially.

Of course, there is a plethora of hardware and software, people-based and machine-based solutions to address the challenge but determining the right mix for a scalable strategy and executing that strategy are not small tasks.

2) Cost

Hand in hand with managing the data successfully is an associated cost with how much data you are managing and how actively it is being managed.  Real-time data can yield huge returns like providing airlines with early warning  alerts for repairs and and operational efficiency for fuel consumption.  But capturing everything and transmitting it in real-time can be expensive (upwards of tens of thousands of dollars per terabyte).  

Companies have to carefully prioritize the collection and analysis of their data. In the case of the data stored on the black box, history tells us that air crashes are relatively infrequent and the black box is recovered the majority of the time.  So, should airlines collect the data in black box but also transmit it in real-time given the low prevalence of situations in which the data is lost?  Maybe.  

The Malaysia Airlines flight disappearance is sure to have data policies being reviewed and revised.  And, in an era of real-time data, the parties involved in a crash — the airline, the families, the NTSB, the insurance companies, etc. — will be demanding faster access to the data.

3) Security

Another key factor is both technology and cost related — security.  Jeff Immelt, GE chairman and CEO is quoted as saying. “Our greatest challenge and opportunity is to manage and analyze [IoT] data in a highly secure way to deliver better outcomes for customers and society.”

While it is possible to overcome the challenges of data management and to make the business case for real-time data, there is also the security of that data to be considered.  Could terrorists hack a plane’s real-time feed and then reroute, disable, or destroy it?  Does passenger safety more often rely on instant data transmission or the more siloed and batched nature of existing data protocols?

What other IoT issues do you think are surfaced by the Malaysia Airlines disappearance? 

Additional Reading: @Wired How’s It Possible to Lose An Airplane in 2014?

Advertisements

Tags: , , , ,

2 Comments on “3 IoT Factors in Losing A Plane”

  1. haridasgowra March 11, 2014 at 11:35 pm #

    what a pic and well written………
    #wordpress!

    • Jill Richards March 12, 2014 at 12:33 pm #

      Thanks for your comment – I like your IT site too!

Socialize - Share your comments with the Socialrati!

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s

%d bloggers like this: