It’s no surprise Artificial Intelligence is once again high on the list of top trends in aviation in 2020. It was arguably the biggest story in technology for most of the 2010s but, as we enter a new decade, the question is: how much innovation is still on the horizon and how much is now a reality?
Reviewing the travel industry landscape, we can see elements of machine learning are already actively disrupting the experience for the better. We celebrate the successes of our customers and partners in every release of a new smart product or service. Why? The machine learning powering AI models and traveler experience applications depends on layers and layers of data and analytics. Something our 400+ Cirium employees care about deeply.
That machine learning is transforming practically every stage of the travel experience. Continue reading for more on interesting examples to date…
There’s no denying Panasonic Avionics is the trailblazer brand that has transformed the in-flight entertainment and customer service experience beyond recognition. As reported by Wired, Panasonic Avionics utilized advanced machine learning and deep learning algorithms to create its commercial aviation platform, NEXT Cloud. This technology enables airlines to serve up the food and the films passengers want – and customize the in-flight experience from seating to Wi-Fi quality – all drawn from the insights from passenger data provided by the NEXT Cloud.
Some airlines are raising the bar even higher. For example, Delta Air Lines plans to test a “binge button” enabling passengers to watch entire seasons of their favorite shows uninterrupted. It’s also launching entertainment recommendation features with personalized options based on previous viewing behaviors.
Predicting best-price air fares
AI is also giving consumers knowledge of the best time to buy and book – offering maximum value for money. No surprises that the mighty Google was the powerhouse behind the first enhanced travel content and shopping experiences. Google Flights, the brand’s flight search engine launched back in 2016, now notifies fliers as to when airfares will expire. Hopper, which has access to 50 trillion price itineraries, enabling the company to build models to determine how prices change over time, is also on the money. The travel app now predicts prices with 95% accuracy up to one year in advance, making it a major hit with savvy travelers.
Smarter online booking
So, you think you know what you want? Well, AI knows better. With recommendation engines designed to pre-empt your next steps – and every need – AI has created faster and more seamless booking experiences. For example, when searching on MakeMyTrip or Expedia for flights to a specific city, you’ll be offered several accommodation options for your stay. Meanwhile, Booking.com offers alternative destinations for your next trip.
The most significant innovations in security systems – designed to make security procedures both safer and faster – have been powered by AI. When it comes to improving airport operations and the customer experience, biometric screening is the game changer that’s now being introduced by airports worldwide. Last year, the US Transportation Security Administration introduced new computed tomography (CT) scanners, which use AI to help target threats, at Los Angeles International Airport (LAX), John F. Kennedy (JFK) and Phoenix (PHX) airports. This month, Philadelphia International Airport (PHL) began a 45-day pilot of biometric screening technologies at three international gates to help U.S. Customs and Border Protection (CBP) process departing passengers.
The opportunities for machine learning are endless. Essentially, it can be used to improve and enhance all aspects of logistics, from automating how airports adapt in times of disruption/cancellations to managing daily passenger flow. Frankfurt Airport is currently using machine learning to predict aircraft arrivals. This is an area we are especially interested in. Plenty more to come here.
Dynamic trip pricing & forecasting
It’s not just about airlines and airports. AI is used to track changing prices and suggest the best price for a complete trip, enabling Online Travel Agents (OTAs) to offer automated recommendations based on a wide range of factors, including affordability. AI applications can forecast where travelers would want to go and then present ads that can cater to targeted customer groups. This has been made possible by predictive analytics developed on machine learning algorithms.
A vast range of new revenue management and pricing solutions have since emerged, created by specialist RM tech companies, PMS providers, and by OTAs themselves.
And what about when you’ve arrived at your destination? How about a snappy virtual tour guide on your smartphone? Samsung reaped the data riches of AI to launch Bixby Vision back in 2017. Built into the Samsung camera, Bixby Vision is an image search feature that sees what your camera sees. Designed to be a pocket tour guide, it helps travelers translate a sign, order lunch, or scan a famous landmark to learn more about it. Bixby Vision’s capabilities have since expanded as has this sector with other brands wading in.
AI is also assisting airport workers to move heavy luggage at a swifter pace. Delta Air Lines has partnered with Sarcos Robotics to trial the exoskeleton – a robotic vest designed to help cargo workers lift and transport heavy luggage easily and efficiently.
Airports, including Hong Kong Airport, are also implementing smart RFID tracking to have AI enhance how they view luggage traffic. The data captured can provide insights into better operational flow, to avoid congested areas or adjust schedules to better balance the high-demand areas.
How does Cirium data relate to AI?
How and where do we come in? Good question. Artificial intelligence powering the traveler experience is made up of layers and layers of data and analytics. While we aren’t the ones developing traveler-facing AI, our customers are. Our customers – some of the biggest brands and entrepreneurs around the globe – make giant strides in AI innovations, in part because of how they harness industry data.
Our air travel data plays a key role in machine learning, from which AI models and applications are built.
And here’s the important detail: the more historical data you have, the more complex and sophisticated are the systems you can create. This means if you want to build something bright for the future, you need smart data from the past.
Cirium not only has the most comprehensive current and real-time data lake, but also the world’s largest volume of historical data. This is what makes us the leading go-to source for quality travel data to power machine learning. How did we get here? Watch the video below or read more about us.
Our customers are enriching their data with our historical data to enhance their models. Watch this space for more details and case studies coming soon.
You can find more content like this here. You can also interact with Cirium’s aviation data and analytics–covering global fleets, airline schedules, aviation asset values and flight status– visit Cirium Ideas.