According to IOT for all, airlines are facing various problems today. One is to implement advanced technology in the business. Despite many problems, the aviation industry may enter the fourth industrial revolution.

Emerging technologies such as AI, Internet of things and AR / VR are reshaping the aviation industry from inside to outside.

Among the emerging technologies, the application of AI in the aviation industry is still in its early stage. So far, we have seen that airlines use AI to implement face recognition, customer Q & A, baggage check-in, factory operation optimization and aircraft fuel optimization. But AI has more potential than that. It can completely change the operation mode of airlines. The following are some use cases of AI.

1. Unit management

Every day, airline crew managers have to manage a large number of personnel, including flight attendants, pilots and engineers. Adjusting the scheduling of any crew member will be very troublesome. The decision of the manager is determined by many factors, such as whether the crew is available, credit, qualification and so on.

Boeing’s jeppensen solved this problem with AI technology. Their AI based crew scheduling system takes into account all the above aspects and can effectively manage the crew.

2. Aircraft maintenance

Improper maintenance will bring great losses to airlines. It requires extensive planning and scheduling. Unscheduled aircraft maintenance can lead to flight delays or even cancellations. Experts predict that if AI is implemented correctly, a lot of costs can be saved.

AI based predictive maintenance is slowly becoming a trend in the global aircraft maintenance market. It will help maintenance engineers predict aircraft faults in advance.

3. Ticketing system

The calculation of ticket price is based on multiple parameters, such as oil price, flight distance, purchase date, competition, seasonality, airline brand value, etc. Oil prices and other parameters are changing every day, resulting in constant changes in ticket prices.

AI algorithm is the ultimate solution to this problem. It will help airlines calculate the most effective price for each flight, which will help them maintain profitability and provide customers with competitive pricing.

4. Passenger identification

Delta Airlines announced in May 2017 that it would invest US $600000 to build self-service baggage checking machines and passenger identity authentication equipment. The device has a built-in camera that can take pictures of passengers during check-in and compare them with their passports. Machine learning algorithms are used in face recognition and self-service baggage check-in.

5. Customer service

In September 2017, United Airlines announced its cooperation with Alexa, Amazon’s AI tool. The two sides have created a skill called “united” for Alexa. As long as customers add “united” skills, they can ask any common questions through voice instructions. For example:

“Alexa, ask about the status of United 595.”

“Alexa, let United check in my flight.”

“Alexa, ask if United 675 has WiFi.”

Alexa’s natural language makes customers feel like they’re talking to real people.

6. Simplify communication

Air traffic control (ATC) is one of the most critical aspects of all flights. If it is an international flight, the communication between pilots and air traffic controllers is often cross linguistic and cross-cultural. Even if both sides communicate in English, their accents may be different, which will cause confusion. For example, Indian pilots may have difficulty understanding European air traffic controllers with a strong accent. In addition, the noise of ATC communication channel is large, which makes it more difficult for pilots to hear clearly.

Thanks to Airbus’s AI gym project, they have developed a machine learning algorithm that can not only remove noise in real time, but also provide a complete text record of air traffic control personnel’s audio.

Responsible editor; zl

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