Ways Machine Learning is Reshaping Commercial Flights

Fremont, CA: Artificial intelligence is becoming increasingly important in the aviation business. It may hold the secret to a faster recovery after a pandemic. Consider how its area of machine learning is already influencing common elements of travel, such as ticket pricing, point-to-point routing, fuel usage optimization, and biometric boarding.

• Dynamic ticket pricing

The airline sector is known as one of the most sophisticated in terms of employing complicated pricing techniques. The majority of passengers want to get the cheapest airline tickets available. Airline companies, on the other hand, strive to maximize their profits. Both sides can take advantage of machine learning algorithms in their pursuit of the best bargain.

• Route planning

When evaluating route and frequency demand for individual city pairs, carriers must examine hundreds of criteria, especially with the surge in point-to-point travel. Meanwhile, demographics, industry linkages, time of week and day, season, holidays, events, fuel price, and other factors all influence whether or not a route will be lucrative and when it will be successful.

ML can handle far more data than traditional analytical techniques for determining the best routes and timetables. It can assess both leisure and business travel demand by analyzing search engine data, booking agent data, social media postings and comments, and recruiting and professional sites.

• Onboard sales and food supply

What a person eats and drinks on an aeroplane varies tremendously, not just from person to person and kind of travel, but also by location and time of day. Every year, 20percent of the food supplied by in-flight catering gets wasted.

Carriers must study prior onboard sales data and alter their products to reduce food waste and financial losses. The more personalized the in-flight experience, the more complex algorithms airlines will require to perfect the supply vs. demand snack problem.

• Fuel consumption

Fuel and labor are the most expensive operational expenditure for an airline, accounting for over a quarter of total expenses. Not only that, but aviation accounts for around 2.4 percent of worldwide CO2 emissions from fossil fuels. Better estimations for how much fuel is necessary for a certain flight is required to become more efficient. Here comes machine learning.