Birds are smart but the aviation industry is using AI to outsmart them
If you are looking for examples of advanced technologies being put into action, the aviation industry is a prime example. The two main aircraft manufacturers, Boeing and Airbus, both have already had fully digitized R&D ecosystems as part of their manufacturing processes for around five years. More recently, companies have been investing in AI to tackle everything from production quality issues to reducing the time it takes for new designs to come to market. However, AI can support much more than just manufacturing. The technology is also being used in novel ways across a range of scenarios from aftersales through to airport operations and air traffic control.
Airbus itself is looking at how different forms of AI can support different teams. It is implementing large language models (LLMs) and generative AI to ensure it provides the best possible support to its customers once they have purchased their planes. Earlier this year, the manufacturer announced that its aftersales team now has access to a generative AI tool which is making complex documents more accessible. Team members can ask natural language questions from customers and receive answers quickly sourced from a range of different technical documents. Maintenance staff can now check Standard Operating Instructions using natural language when performing routine checks on aircraft, such as confirming the correct torque setting for a given bolt.
By 2035 there are expected to be 50% more flights than there were in 2012, bringing the total number to just under 15 million flights per annum. Managing the ever-increasing number of airborne aircraft is a challenge for air traffic controllers globally. This increase in traffic compounds certain issues and even small process delays can snowball at scale.
One such issue is the time it takes to update the route of the flights that are already in the air, for example, if a flight is diverted due to poor weather conditions or if a flight needs to join a holding pattern before landing. In 2017, the time it took for a flight to be rerouted was one minute, however, the amount of time it takes to share the new route to an aircraft has doubled year-on-year. To combat this, air traffic controllers are utilizing AI and digital tools to improve operational efficiency in airports through faster analysis of data from a disparate range of sources, like weather forecasts, aircraft sensors and flight plans. AI is being used to increase the speed with which air traffic controllers can assess the risk factor associated with the conditions in which a plane might land, giving teams more time to make the safest decisions.
Additionally, air traffic controllers in the U.K. have recently gained access to ‘Project Bluebird’, a digital twin of airspace across the U.K. which is being used to test how AI can be further integrated into air traffic management decisions to reduce delays, ease congestion around busy airports like Heathrow and conserve fuel by routing aircraft along more efficient routes. With safety a priority, being able to test new ideas in the digital realm first is key to ensuring any issues are ironed out before they are rolled out.
Some airlines are also utilizing AI to reduce the amount of fuel used by their aircraft. Alaska Airlines is using Flyways AI to suggest optimal flight paths by analyzing data such as weather, wind, turbulence, airspace restrictions and traffic density. Using the platform helped conserve 1.2 million gallons of fuel in 2023 alone.
AI is also being used by airport operations crews to keep aircraft safe from collisions with birds or drones as they take off and land. Traditionally, managing wildlife, especially birds, around runways has been a manual effort, requiring a lot of time and labor. While solutions like kites in the shape of birds of prey exist, birds are intelligent and will quickly learn if the threat is not real and return to the runway.
The Edge Company, part of the Lenovo AI Innovators program, is working with airports like Dhaka International on an AI-powered long-term solution. Using computer vision, the system is not only able to spot, count and track birds but also classify their species, something that is difficult for ground crews or legacy radar-based to do at scale. The system can be integrated with a bio-acoustic bird dispersal system (BDS) which triggers predator-specie-specific distress calls, a noise that the birds cannot ignore. The ground crew can then follow up and clear any remaining birds as necessary. Given that the FAA estimates that 15% of bird strikes have a serious impact on aircraft, this system greatly improves passenger safety, as well as reducing delays while preserving wildlife and mitigating environmental impact
With 2024 predicted to see air passenger volumes exceed pre-pandemic numbers, the need for technologies to support aviation staff with crucial safety and efficiency initiatives is high. Intelligent implementations of AI are already proving their value, ensuring passengers get to their destinations on time and without issue, while supporting airlines in reducing their fuel consumption and thereby emissions.
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