Aviation technology is moving rapidly. It can be hard to keep up with the latest and greatest technology in the field of aviation. An article in the New York Times asked, Are people ready to travel on a flight without a human pilot? People reacted in different ways. Some people shared their knowledge about the aviation industry. Many of them said that driverless cars are possible, but driverless planes sound absurd, as it is safer to be on the road than on the air. Technology is emerging in a whole new way with automation, AI, and robots. The question is, do we have the technology to run an AI-driven pilot? This will take years of R&D and testing to become fully pilotless.
Analyzing traveler behavior
Today airlines do use AI, data science, and machine learning to automate or speed up operations. It is very important for an aviation company to understand traveler demand and how to price flights. Thousands of factors affect this, like the time of the week/day when a passenger travels, holiday, seasonality, events, demographics, fuel price, etc. Analysts can use traditional statistical methods, but data science helps to get more easy and sophisticated methods to accomplish the demand analysis. Airlines can use traveler behavioral data by checking traveler’s online search data, social media chats, posts, and data from professional networking sites and finding out their chances of traveling to a specific location. PrivateJetScanner.com used machine learning-based clustering to group together many destinations based on their similarity. They considered many factors like the month of travel, time of the reservation, how long people stay at the destination, and many more. Some of the results were really surprising. For example, the cities considered ideal as a romantic destination were more often visited by single travelers, and proximity to a destination may be more important than the city itself. Festivals, events led to a rise in short term demand. Thus revenue teams can rely on event data to raise fares for a specific time period and benefit from rising demand. Many airlines use a ranking algorithm that matches historical flight bookings with event data to reveal how an event can affect traveler demand. Many people may prefer snacks and foods during their flight, but some skip their meals during traveling. Airlines must estimate how many snacks and drinks they onboard to deliver to the customers without wasting any food. Cabin waste is a serious environmental issue. Thus data scientists figured out that flight boarding early morning has very different food demands than one flying at night. Algorithms are created to predict the demands and help airlines save a significant amount of money. And do the right thing for the environment at the same time.
The planes contribute a huge amount to the global CO2 emission due to the use of fossil fuels, and it is increasing year by year at a significant rate. Thus airlines are looking to improve their fuel efficiency. Airlines also invested a lot of money on jet fuels. Airlines need to predict how much fuel they need. The best solution was to have an analytical tool. Scientists made time series algorithms and neural networks that could produce fuel consumption forecasts based on a number of trips, fuel prices, and time periods. These new solutions reduced the time to calculate the predictions and also made them more accurate..
Biometrics and facial recognition
Today airlines also use facial recognition systems and biometric technology as a boarding option. The equipment scans travelers’ faces and matches them with photos stored in their databases, which are collected from their passports, visas. In this way, travelers can have an easy, quick, and hassle-free identification process and provide a better customer experience. Biometric gates are used by several airlines at the airport.
Airlines use data science and machine learning to evaluate passenger demand, use data insights to optimize aircraft ground handling and fueling, and improve passenger experience in the airport with biometric boarding. In this way, we can hope that the technology-driven aviation industry will be more profitable, efficient, and effective.