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Artificial Intelligence (AI) Applications in Aviation Sector

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Over the next few years, AI is expected to bring several breakthroughs in the aerospace industry by reducing costs, shortening design processes, eliminating duplication, experimentation, augmentation, support, production and Upgrade. AI developments could help the aviation and aerospace sectors improve their production methods. The aerospace industry, however, has limited the adoption of AI approaches, primarily due to a lack of access to high-quality data, a preference for simple models over complex models, and a need for more competent staff and partners to execute it effectively. However, the right partner could make AI a game-changing innovation impacting the productivity, efficiency, scale and speed of aerospace companies. The aviation sector uses machine learning, computer vision, robotics and natural language processing to benefit from AI. Predictive maintenance, pattern recognition, automatic scheduling, targeted advertising, and customer feedback analysis are some of the key benefits. Artificial Intelligence (AI) technology is dramatically improving flight operations and having a significant impact on the commercial aviation sector. The world’s leading airlines are adopting AI and other advanced technologies to deliver personalized services and improve customer experience. At the airport, self-service kiosks automate procedures and security checks. Moreover, these can be categorized as the tip of the iceberg, there are several other applications which have been highlighted below:

  1. Passenger Identification

Operational efficiency will increase among the ground workforce thanks to security scanners, machine learning techniques and biometric identification. Many US airports are using AI to identify potential threats at busy airports. Tools with AI capabilities have the ability to speed up the passenger identification process.

  1. Baggage control

Syntech ONE, an artificial intelligence platform to screen baggage for many conveyor belts, is set to be installed at Japan’s Osaka airport. Syntech One’s ability to detect potential dangers is enhanced by its compatibility with X-ray security system. Security personnel will be able to quickly and efficiently find illicit items through the use of automated baggage screening , which would significantly reduce the workload of security personnel.

  1. Design products

The aviation industry often favors affordable and reliable aircraft parts to reduce costs where possible. To create such components, automakers can combine generative structures with AI algorithms. Iterative design is a process in which technologists or architects iteratively produce a perfect product using design criteria as input data along with constraints and characteristics such as materials, available assets, and a specified budget . Advanced design programming can allow product designers to quickly evaluate various design ideas when paired with AI. Designers could use this innovation to create new lightweight and affordable products. AI can therefore help the aeronautical industry to optimize its design and production methods.

  1. Dynamic ticket pricing

If you’ve ever bought a plane ticket, you know it’s a once-in-a-lifetime experience. Different fares may apply for the same flight depending on your travel comparison tool. Departure time, destination, travel time and number of tickets available all affect prices. The price of a ticket can vary from minute to minute. This is because airlines use a practice known as dynamic pricing. It is a method of changing prices to the highest profit levels based on current market conditions. Dynamic pricing algorithms use sophisticated techniques such as machine learning and in-depth data analysis.

  1. Delay forecast

Delays are common and are mainly influenced by various variables. Modern ML-based applications can help airlines and airports around the world predict delays and notify customers quickly. Customers will have more time to change their travel plans or make other arrangements if necessary, which will significantly improve the user experience (UX) for the aviation industry.

  1. Efficient use of fuel

Aerospace industries place great importance on fuel quality, and even a slight decrease in aircraft fuel consumption can have a significant impact on a company’s profitability and sustainability.

Deploying AI-powered devices can lead to reduced fuel consumption. For example, a French startup, Safety Line’s machine learning app, can help pilots improve their climb paths before each flight. The bottom-up process uses the most gasoline, so improving this step results in significant financial savings.

  1. Supply chain management that works

The distribution network uses AI, which streamlines the aviation industry. Routine maintenance and repairs are more accessible to perform with better supply chain proficiency than manual compatibility. Since the date for repairs is usually known in advance, it also saves money and minimizes downtime. Automating data collection quickly improves supply chain management capability.

  1. Practices & Training

AI can be used to build formation in flight. AI simulations can be combined with interactive virtual frameworks to provide pilots with a complete simulation environment. Simulators with artificial intelligence capabilities can also be used to collect and evaluate academic data, such as biometrics, to develop personalized training programs based on students’ academic performance. This could prove to be a strong build point.

  1. Client satisfaction

In commercial aviation, customer satisfaction and quality of service are of vital importance. AI is one method airlines can use to increase customer engagement and deliver top-notch customer service. Artificial intelligence (AI)-based chatbots are automated systems that can provide real-time, human-like customer service. Online chatbots could help businesses by automating customer support. There are many ways to achieve this, including:

  • Tips to help customers make accurate and personalized purchases
  • AI-powered chatbots could offer prompt and courteous support.
  • Automatic assistance would still be available.
  • Customer interactions could be more productive.
  1. Maintenance planning

The world’s largest aircraft manufacturer, Airbus, is adopting artificial intelligence applications to increase the reliability of its aircraft repair procedure. A cloud-based tool called Skywise facilitates convenient data storage. The fleet continuously collects and logs huge amounts of data, analyzes it and saves it to a cloud server. AI and predictive analytics create a systematic method for the airline industry to choose an efficient procedure for aircraft maintenance.

Until now, AI in aviation has only been used on the ground. Machine learning has been used to find patterns and anomalies in massive data that has been converted from aircraft and engines. The aviation sector has only recently begun its journey towards AI; therefore, fully adopting AI will be difficult and may take some time. However, today the technology is developing at breakneck speed. For businesses to benefit from digital transformation, they must be fast, efficient, sustainable and productive. The implementation of AI will help the travel and aviation sectors. Delivering individualized customer experiences can be achieved by service providers using AI-powered chatbots, instant messaging apps, and other smart tools.

References:

  • https://www.analyticssteps.com/blogs/8-applications-ai-aerospace-industry
  • https://aithority.com/predictive/ai-applications-in-aviation-and-travel-industry/#:~:text=The%20aviation%20industry%20leverages%20AI,to%20improve%20overall%20customer%20experience
  • https://addepto.com/blog/fly-to-the-sky-with-ai-how-is-artificial-intelligence-used-in-aviation/#
  • https://www.techopedia.com/the-role-of-artificial-intelligence-in-the-aviation-industry/2/33247


Amreen Bawa is an intern consultant at MarktechPost. In addition to pursuing BA Honors in Social Sciences at Panjab University, Chandigarh, she is also an avid learner and writer, with particular interest in the application and scope of artificial intelligence in various facets of life.


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