Big Data in Aviation: Big Data Analytics in Airline Industry

Last time, we talked about AI in aviation. In this article, we are going to take a look at a closely related subject. Big data in aviation is also an interesting aspect of this industry. Thanks to big data, aviation companies can make more informed decisions and predict diverse scenarios. How is big data in aviation working? And what kinds of information aviation companies and airlines process every day? Let’s find out!

In this article, we are going to show you how big data analytics works in the aviation industry. How airlines and other companies using aircraft are using big data and for what purposes. However, before we get to that, let’s think for a few seconds about the big data itself. What kind of information is available when it comes to big data in aviation?

Big data in Aviation

Did you know that even in the COVID-19 times, every day, there are over 145,000 flights[1] worldwide? That’s quite an impressive number, isn’t it? Thanks to tools like FlightRadar24, every person can for free track and see the details of each one of these 145,000 flights. Of course, there was a massive drop in flights around March and April 2020 (that’s when the first global lockdown started), but at the end of 2020 situation was pretty similar to the one in late 2019.

Source: flightradar24.com

Let’s think about these 145,000 flights. That’s a massive amount of big data that are being generated every day only by these planes. Each plane has its unique number, flight origin and destination, number of passengers, route, and terabytes of technical data regarding every single part and component that keeps the aircraft in the air.

Then we have the weather data. According to the Airports Council International (ACI)[2], there are over 17,000 commercial airports in the world. Every single one of these airports is vitally interested in weather data. Both airports and airlines want to know about the potential storm, heavy rain, fog, or any other weather phenomenon that could have an adverse impact on the airport’s work and planes’ routes.

Lastly, we have passenger data. That’s yet another significant source of big data for every airport and airline. Bear in mind that each passenger’s identity has to be verified. Each ticket contains information about the flight, seat, class, and personal data. Given that each flight can take 100-300 people, we can try to estimate that there are, on average, over 10 million people in the air every single day. These numbers can truly be mind-boggling. But we want to show you how big data in the aviation industry works.

There’s quite a lot going on every day.

Big data in aviation: logistics and transportation companies

So far, we’ve just barely scratched the surface. After all, there’s also the entire sector of transportation and cargo planes. Although these aircraft and companies operating them are also interested in the weather data, we deal with different kinds of big data in aviation.

Consider carriers using aircraft. Thanks to big data in aviation, these companies can easily schedule flights and predict delays based on weather data. But it goes further. After all, there’s the cargo data as well. Carriers need to estimate the demand for storage space in every plane so that they don’t fly half empty.

That’s why courier and logistics companies closely track information regarding parcels being sent via their company and optimize the number of products and parcels each plane can take. All of that information is tightly correlated with other customer data regarding packages, orders, and contracts. It’s all interconnected, making big data in aviation a vast and difficult to embrace subject.

How is big data analytics used in the Airline Industry?

As we’ve already talked a bit about big data in aviation, let’s now examine how it’s used and for what purposes. As always, there are two simple goals–to cut costs and improve efficiency. There can also be indicated the third goal–to improve user experience (UX). But to some extent, that’s also a way to improve efficiency, so we end up with two major objectives. How big data analytics allows aviation companies to reach them?

Big data in aviation increases user experience

First off, let’s talk about the customer side of big data in aviation. Airlines and airports use big data to improve customer service and UX in general. As there are significant operational gains, big data can also help airlines to enhance customer service. For starters, airlines, just like any other retail or e-commerce company, use big data to provide customers with personalized experiences and offers. The knowledge coming from big data can be used for cross-selling, upselling, and other additional services, like onboard refreshments tailored to current customers’ needs and preferences.

Big data in aviation can also be used to simplify the ticket purchasing process. And then there’s the check-in process. Not that long ago, you had to arrive at the airport at least 5-6 hours before the flight and manually go through the check-in process. Now, it’s usually available online, and you can do it yourself just with your ID.

At the end of the check-in process, you can download or print your boarding pass, and you’re almost ready to go. Naturally, baggage claim and security check have to happen the old way, but it’s still the massive simplification of this process.

Airlines also frequently use customer loyalty programs to increase UX. For example, AAdvantage is a loyalty program offered by American Airlines. When you participate in AAdvantage, you can collect points called miles and exchange them for flights for over 1,000 destinations worldwide.

Another interesting example of such a program is Miles & More. It’s a European customer loyalty program for frequent travelers. There are many airlines participating in this program, i.a., LOT Polish Airlines, Lufthansa, Swiss Airlines, Air Canada, Air China, Singapore Airlines, and SAS.

Airport navigation: augmented reality

Have you ever got lost at the airport? If so, you’re not the only one. Surely, it’s a non-standard application of big data in aviation, but it’s certainly worth talking about. Imagine a common situation: You’re late, and your flight takes off soon. You can’t miss it. You still have to find the baggage drop-off, check-in terminals, and finally, your gate.

If you’re for the very first time at this airport, it could take you too much time to figure everything yourself out. And in such a situation, augmented reality comes to the rescue!

Source: techcrunch.com

Imagine there’s a mobile airport app that can flawlessly guide you to your destination without unnecessary delays. This is what the Gatwick airport (in the UK) did. They created a mobile application fueled by augmented reality to help passengers navigate through gates, check-in points, and other crucial places throughout the airport. Their app uses two terminals with around 2,000 battery-powered beacons that help thousands of passengers find their way.

Safer planes and flights

In the first part of this article, we told you that every plane comes with terabytes of technical big data regarding every part, component, and software that allows each aircraft to operate at its full capacity without the risk of serious failures or glitches.

Thanks to big data analytics, engineers and maintenance staff can make sure each plane is in its top shape and can fly 100% safely. Of course, not every situation can be predicted, but the number of such unexpected scenarios can be limited to a minimum.

And what about flights? Thanks to weather big data, pilots and ATC teams can direct planes on routes with no turbulence zones or storms, making the flight itself more comfortable and safe.

Data4Safety

In September 2017, EASA (EU Aviation Safety Agency) started a new initiative known as Data4Safety or D4S. This program aims to collect and gather all big data that may support the management of safety risks in aviation at the European level. D4S experts are primarily interested in:

• Safety reports (or occurrences),
• Flight data (i.e., data generated by the aircraft via the Flight Data Recorders),
• Surveillance data (air traffic data),
• Weather data and several other types of information

The idea is to set up a predictive system whose ultimate goal is to help European aviation companies in “knowing where to look” and “seeing it coming”. In short, it’s big data analytics that allows aviation companies all over the world to increase the safety of planes and flights.

Cheaper maintenance

Safety is one thing. Keeping planes’ maintenance as cheap as possible is another. Airlines and companies managing aircraft try to lower repair and maintenance costs. The best way to achieve this objective is to implement big data analytics. As you already know, each plane comes with terabytes of technical information. It can be used to predict future glitches, prevent them from happening, and make the maintenance procedures more accurate and thorough. As a result, it is possible to lower costs related to maintaining an aircraft.

One of the companies using big data analytics this way is Boeing. With their Airplane Health Management (AHM) system, they can reduce maintenance costs and avoid flight delays and cancellations with access to real-time fault information from the airplane, combined with predictive tools[3]. In other words, they are using big data analytics to create a predictive model that improves their planes’ maintenance and prevents potential failures. Interestingly, their AHM system is fully operational even while the airplane is in flight.

EasyJet has taken a similar way, only here their ultimate goal was to decrease delays. In 2018, EasyJet announced a five-year predictive maintenance partnership program with Airbus. They are using Airbus’ data platform and machine learning in order to implement predictive maintenance so that potential malfunctions can be predicted and repairs conducted as quickly as possible.

Moreover, they decided to distribute spare parts within the network of maintenance points in order to support a quicker response when machine learning algorithms predict that a fault could happen. This way, repairs take less time and can happen without disrupting the company’s everyday work[4].

Tthe partnership of NASA and southwest airlines

Here’s another fascinating example of how big data analytics can increase the safety of air travel. Thanks to this partnership, Southwest Airlines have a more insightful view into their everyday operations and have access to a system that allows them to spot potentially dangerous irregularities and deviations.

According to Jeff Hamlett, the director of flight safety at Southwest Airlines Co.: “I think what we got out of this technology is the ability to ask, ‘What is normal?’ Because that turns out to be really powerful, and we can say ‘OK, we need to make this correction in our training,’ or ‘Maybe we need to adjust our concept of what the ideal is.’”[5]

Summary

It’s time to sum up our findings. Thanks to big data analytics in the aviation industry, everything that happens at the airport or on the plane can be facilitated and accelerated. Aircraft are safer and more fuel-efficient. The flights themselves are also much safer because intelligent algorithms can help pilots and air traffic control teams navigate through (or avoid altogether) turbulences and storms.

And finally, customers get a better, more tailored service. Thanks to improved ticket purchasing processes and custom-made customer loyalty programs, airlines, and airports all over the world can deliver demanded user experience (UX) and get more customers.

Although we still have to struggle with the pandemic, we truly believe that sooner or later, everything will be back to normal, and big data analytics in the aviation industry will flourish again. Even today, this technology significantly changes the entire industry. Imagine what will be possible in the coming years!

At Addepto, we deal with big data analytics every day. In fact, it’s our primary job. If you’re interested in big data analytics, even if you don’t work in the aviation industry, drop us a line! We will gladly help you implement this tremendous technology into your organization. Work with us and see how big data analytics can change your company into a quick, efficient, and cost-effective organization!

References

[1] Flightradar24. Total number of flights tracked by Flightradar24, per day (UTC time), 2019 vs 2020 vs 2021. URL: https://www.flightradar24.com/data/statistics. Accessed Apr 13, 2021.
[2] Aeronewstv. Video – How many commercial airports are there in the world?, 08.11.2015. URL: https://www.aeronewstv.com/en/lifestyle/in-your-opinion/2954-how-many-commercial-airports-are-there-in-the-world.html. Accessed Apr 13, 2021.
[3] Boeing Services. AIRPLANE HEALTH MANAGEMENT (AHM). URL: https://www.boeingservices.com/maintenance-engineering/airplane-health-management-ahm/. Accessed Apr 13, 2021.
[4] Josep Mele. EasyJet: Reducing Delays with Machine Learning. Nov 13, 2018. URL: https://digital.hbs.edu/platform-rctom/submission/easyjet-reducing-delays-with-machine-learning/. Accessed Apr 13, 2021.
[5] NASA Spinoff. Data Mining Tools Make Flights Safer, More Efficient. 2013. URL: https://spinoff.nasa.gov/Spinoff2013/t_3.html. Accessed Apr 13, 2021.