The technological revolution is advancing by leaps and bounds and the use of the software is already part of the management structures of all industries. The aviation industry is not far behind and has seen many advances in this area in recent years. What is its application? Why is AI going to change the industry?

The most promising applicable technology is artificial intelligence, which is defined as the combination of algorithms designed to create machines that have the same capabilities as humans. A technology that still seems distant and mysterious to us, but which has been present in our daily lives for a few years now. What are the reasons for introducing this type of technology in the sector, and what benefits can it bring? 

In general, airlines use manufacturers' data that are identical for all aircraft of the same type. However, as an aircraft ages, its performance is affected and it experiences a reduction in engine thrust and an increase in fuel consumption.

Despite ageing aircraft, manufacturers, flight management systems and flight preparation software providers continue to use manufacturer models that do not correspond to actual performance. This can reduce accuracy and negatively affect fuel efficiency, directly affecting CO2 emissions.

The European Commission has launched the EU-funded "PERF-AI" project, which focuses on applying machine learning technologies to flight data in order to identify performance changes for each aircraft and provide airlines with updated data to enable them to operate more efficiently. 

In other words, it is based on identifying suitable machine learning algorithms and testing their accuracy and capability by performing statistical analysis of flight data. In addition, the project developed mathematical models to optimise actual flight trajectories in relation to the aircraft's true performance and thus minimise fuel consumption during flight.

AI will also play a key role in the development of new ATM/U-space services, as new airspace users (high-level vehicles, low-level drones) seek to enter already busy and complex airspace. AI will also increase security and cyber resilience through the provision of new conflict detection, traffic advisory and resolution tools.

Quest for efficiency

The PERF-AI team applied machine learning to aircraft parameters that are recorded on quick access recorders and black boxes, and collected on every flight to update aircraft performance data. "The ultimate goal was to use the performance models obtained through machine learning to optimise flights, as the available data is more accurate and variable," explained Pierre Jouniaux, CEO and founder of Safety Line, a Paris-based start-up offering innovative solutions for safe and efficient aviation operations. As a result, we can identify the best operating conditions for pilots, so they can fly more efficiently.

The project partners recreated a complete aircraft performance model based solely on aircraft data that corresponds to the physical behaviour of an aircraft. They then tested the model on an engineering flight management computer. The results confirmed that it was possible to update any aircraft performance model and provide pilots with more accurate and robust information. An important benefit is that pilots can load less fuel for flights. The results were used to create several optimisation algorithms that required few computing resources to run on devices such as a tablet or latest-generation monitors, already present in most aircraft.

Reducing the carbon footprint of aviation

In recent months, the effect of the carbon footprint of aviation on our environment has become a hot topic, both in the private and commercial sectors. In fact, almost all airlines now offer passengers the option of paying a premium to offset the C02 emissions of their flights. The use of sustainable fuels is also gaining momentum, although they are only consumed at a miniscule percentage compared to traditional fuel. 

OEMs that need to use more accurate data to assess aircraft performance have the most to gain from this technology. Airlines that want to improve aircraft operations and, at the same time, reduce fuel consumption and CO2 emissions also have much to gain.

In conclusion, the application of this type of technology in the transport sector is set to increase and an example of this trend can already be seen in the automotive industry. It is also one of the fastest ways for companies to meet the SDGs (Goal 13: Climate Action, Goal 9: Industry, Innovation and Infrastructure). Artificial intelligence is positioned as one of the most promising technologies that can generate more changes in a few years within the sector.

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