This presentation of AI ( Artificial Intelligence) technology in commercial aviation has brought some significant changes in the ways flights are being operated today. Engineers have found AI can help the aviation industry with machine vision, machine learning, robotics, and natural language processing.

1. ARTIFICIAL INTELLIGENCE IN AVIATION
SUBMITTED BY
K G Priyanka

2. CONTEXT
• Introduction to AI in aviation
• How AI is reshaping aviation industry.
• Advantages and Disadvantages of AI in Aviation industry
• Conclusuion

3. Introduction to AI in Aviation
Artificial intelligence has been found to be highly potent and
various researches have shown how the use of artificial
intelligence can bring significant changes in aviation.
Few airlines now use artificial intelligence for predictive
analytics, pattern recognition, auto scheduling, targeted
advertising, and customer feedback analysis showing
promising results for better flight experience.
To date, we can see AI being implemented by airlines for
facial recognition, customer Q&A, baggage check-in,
factory operation optimization, and aircraft fuel optimization.

4. How AI is reshaping aviation industry.
#1 Crew Management
Everyday airline crew managers have to manage
complex networks of people, including flight
attendants, pilots, and engineers. Rescheduling
any of the crew members can be cumbersome.
Multiple factors affect the decision of a manager,
such as availability, credibility, certifications,
and qualifications of the crew member.

5. #2 Flight Maintaince
Aircraft maintenance is a tough task, and if done
incorrectly, it can cost a fortune to the airlines.
It requires extensive planning and scheduling.
Unplanned aircraft maintenance can result in flight
delays or even cancellation. Experts predict that
AI, if implemented correctly, can save millions of
dollars.
AI-based predictive maintenance is slowly becoming
a trend in the global aircraft maintenance market.
It will help the maintenance engineers to predict
failures before they actually happen. Delta is
planning to reduce its number of flight
cancellations via AI-based predictive maintenance

6. #3 Ticketing Systems
Air ticket prices are calculated based on multiple
parameters such as oil prices, flight distance, purchase
date, competition, seasonality, the brand value of the
airline, and more. Some parameters change daily, such
as oil prices, which leads to a continuous change in the
ticket price.
The AI algorithm is the ultimate solution to this problem.
It will help airlines to calculate the most efficient
prices for every flight, which will help them remain
profitable and provide competitive pricing to their
customers.

7. #4 Simplify Communication
Air traffic control (ATC) is one of the most crucial
aspects of all flights. In the case of international flights,
the communication between a pilot and an air traffic
controller is usually cross-lingual and cross-cultural.
Even though both of them use English for communication,
their accent might be different, which can create
confusion. For example, it can be difficult for an Indian
pilot to understand the heavily accented English of a
European controller. Moreover, the communication channels
of ATCs are noisy, which makes it more difficult for the
pilot to follow.

8. #5 Passenger Identification
Delta Airlines announced on May 2017, they’re going
to invest $600,000 to build self-service bag drop
machines and kiosks for passenger identification. The
kiosk will have a built-in camera that will take
photos of customers at the time of check-in and match
it with their passport. Both the face recognition and
self-service baggage drop-off will leverage machine
learning algorithms to perform their tasks.

9. ADVANTAGES
1. Baggage Screening
Japan’s Osaka Airport plans to install Syntech ONE 200 – an AI platform to screen baggage for
multiple conveyor belts.Automated baggage screening will help security officials detect illegal items
quickly and effectively. Syntech One 200’s compatibility with the X-ray security system increases
its probability to identify potential risks.
2. Predictive Maintenance
Airbus, the leading aircraft manufacturer, is implementing AI applications to improve the reliability of
their aircraft maintenance process. Skywise, a Cloud-based application helps in an efficient data
storage. The fleet collects and records a vast amount of data in real-time, processes it and stores it
in the Cloud server. Predictive Analytics and AI develop a systematic approach for the airlines company
to decide an effective process for aircraft maintenance

10. DISADVANTAGES
While AI is promising for the future of the aviation industry, it has some pitfalls as well. First, AI is
quite expensive. All airlines might not be able to afford or invest in such new and expensive technology.
Second, it will take some time for implementation by the worldwide aviation industry.
MCAS software installed in jets was the key reason behind the fatal accidents. These incidents are an
eye-opener for the use of AI technology in the aviation sector.
Commercial aircrafts are complex systems, and pilot-less planes put into service is not an easy job.
Even if such systems exist, only a few people are willing to fly in fully-autonomous aircraft. A
survey done in 2018 has shown that just under thirty per cent of the US flyers are willing to fly on
autonomous aircraft.

11. CONCLUSION
Unlike the software industry, the risks of real life harms are exponentially
higher in the aviation industry. While other industries have started using
this technology long back, the adoption of AI in aviation has been one of
caution, and rightly so. As the aviation industry embraces the benefits of
artificial intelligence and machine learning, it must also invest in putting
in place checks and balances to identify, reduce and eliminate harmful
consequences of AI, whether intended or otherwise. As Silicon Valley reels
in ethical dilemmas, the aviation industry will do well to learn from
Silicon Valley while making a transition to a smart future. The aviation
industry known for its rigorous safety measures and processes may, in fact,
have a thing or two to teach Silicon Valley when it comes to designing,
adopting and deploying AI systems into live systems that have high-risk
profiles.

12. THANK YOU