Artificial Intelligence (AI) Applications in Aviation Sector

Over the next few years, AI is projected to bring several breakthroughs in the aerospace industry by cutting costs, shortening design processes, eliminating duplication, experimenting, augmentation, support, production, and upgrading things. AI developments might help the aviation and aerospace sectors to enhance their production methods. The aerospace industry, however, has limited 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 proper partner might make AI a revolutionary innovation that impacts aerospace companies’ productivity, effectiveness, development, and speed. The aviation sector uses machine learning, computer vision, robotics, and natural language processing to benefit from AI. Predictive maintenance, pattern recognition, auto-scheduling, targeted advertising, and an analysis of client feedback are some of the key advantages. Artificial intelligence (AI) technology is greatly enhancing flight operations and having a significant impact on the commercial aviation sector. The top airline businesses worldwide are adopting AI and other cutting-edge technologies to provide individualized services and improve customer experience. At the airport, self-service kiosks automate procedures and security checks. Moreover, these can be categorized as just the tip of the iceberg, there are several other applications that have been highlighted below: 

1. Identification of the Passenger

Operational efficiency will increase among the ground workforce thanks to security scanners, machine learning techniques, and biometric identification. Many US Airports use AI to identify potential threats at busy airports. Tools with AI capabilities have the capability to hasten the passenger identification process.

2. Baggage inspection

Syntech ONE, an AI platform to filter luggage for numerous conveyor belts, is set to be installed at Japan’s Osaka Airport. The capacity of Syntech One to detect possible dangers is improved by its compatibility with the X-ray security system. Security personnel will be able to quickly and effectively find illicit things with the use of automated baggage screening that would reduce the workload of the security personnel dramatically.

3. Designing products

The aviation sector often favors affordable and reliable airplane parts to cut costs wherever 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 by using design criteria as input along with constraints and characteristics like materials, available assets, and a specified budget. Advanced design programming may enable product designers to evaluate various design ideas when paired with AI quickly. Designers could use this innovation to create new lightweight and affordable products. AI may therefore help the aircraft industry optimize its design and production methods.

4. Dynamic pricing for tickets

If you’ve ever purchased a flight ticket, you know that it is a unique experience. Different pricing may apply to the same flight depending on your travel comparison tool. The departure time, destination, length of the journey, and the number of available tickets all affect prices. The price of a ticket might vary minute by minute. That’s because airlines employ a practice known as dynamic pricing. It is a method of modifying pricing to the highest levels of profit based on the current market conditions. Dynamic pricing algorithms use sophisticated techniques like machine learning and extensive data analysis. 

5. Delay Forecast

Delays are frequent and are mostly influenced by various variables. Modern ML-based apps can assist airlines and airports worldwide predict delays and promptly inform customers. Customers will have more time to change their travel plans or make other arrangements if necessary, which will significantly improve UX (User Experience) for the aviation industry.

6. Efficient use of Fuel

Aerospace industries place a premium on fuel quality, and even a slight decrease in aircraft fuel consumption can significantly impact a business’s profitability and sustainability.

The deployment of AI-powered devices may result in a reduction in fuel use. For instance, a French startup, Safety Line’s machine learning application, can help pilots improve their climbing trajectories before each flight. The ascending process uses the most gasoline, so enhancing this stage results in significant financial savings.

7. Supply Chain Management that Works

The distribution network is using AI, which is streamlining the aeronautics industry. Maintenance and routine repairs are more accessible to perform with improved supply chain competency than manually compatible. Because the date of the repairs is usually known in advance, it also saves money and minimizes downtime. Automation of data collection allows for quick improvements in supply chain management capability.

8. Practices & Training

AI can be used to construct flight training. AI simulations can be combined with interactive virtual frameworks to give pilots a complete simulation environment. Simulators with artificial intelligence capabilities may also be used to collect and assess academic data, such as biometrics, to develop customized training regimens based on students’ academic performance. This could prove to be a strong building point. 

9. Customer Satisfaction

In commercial aviation, customer satisfaction and service caliber are vitally crucial. AI is one method airlines may employ to increase customer engagement and deliver first-rate customer care. Artificial intelligence (AI)-driven chatbots are automated systems that can provide real-time, human-like consumer service. Online chatbots could help businesses by automating customer support. There are numerous ways to accomplish this,  which include:

• Advice on how to help customers make accurate and personalized purchases
• AI-powered chatbots could offer prompt and courteous support.
• Automatic assistance would always be available.
• Customer interactions could prove to be more productive.

10. Maintenance Planning

The world’s largest maker of aircraft, Airbus, is adopting AI applications to increase the dependability of their aircraft repair procedure. A cloud-based tool called Skywise aids in practical data storage. The fleet continuously gathers and records enormous amounts of data, analyses it, and saves it on a cloud server. AI and predictive analytics create a systematic method for the airline industry to choose an efficient procedure for maintaining airplanes.

Until now, AI in aviation has only been employed on the ground. Machine learning has been used to find patterns and anomalies in massive data that have been downconverted from aircraft and engines. The aviation sector has only recently started its journey towards AI; therefore, fully embracing AI will be challenging and could take a while. However, today, technology is developing at a breakneck speed. For businesses to benefit from digital transformation, they must be swift, efficient, long-lasting, and productive. AI implementation will help the travel and aviation sectors. The provision of individualized client experiences can be achieved by service providers using AI-powered chatbots, instant messaging apps, and other intelligent 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

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