Aircraft and Artificial Intelligence

F-35 FOD News

The development and use of Artificial Intelligence (AI) technology within the aviation industry have brought some significant changes in the ways aircraft are being operated and maintained.

Although still in its early stages, AI has been able to increase safety and efficiency at airport terminals with vision systems for facial recognition and passenger identification, computer learning capabilities for ticketing systems and customer interactions, and robotic inspections for security scanning and luggage check-in.

The learning capabilities of AI has also been used in the management of airline crews. Scheduling and rescheduling of crew members can be a complicated venture. The system must take into account multiple variables that affect the process, such as availability, rest time, certifications, and qualifications of each crew member. AI can seamlessly analyze all of the potential data to find solutions within minutes.

As AI technology accelerates, the aviation industry is being cautious with its introduction to the actual physical aircraft to ensure that the technologies are thoroughly tested and to put in place the proper checks and balances before handing the reins and control of aircraft to autonomous systems, especially on large passenger aircraft.

The testing must show that the AI systems can act at least as competent as humans in high-risk environments before replacing human thought processes in flight. As it exists, the introduction of AI in collaboration with human interaction has already proven to be a very successful partnership in the advancement of safety in aviation.

Aircraft Maintenance Prediction

One of the main uses of AI, as it relates to physical aircraft, is in the performance of aircraft maintenance. Aircraft maintenance is an ongoing process and it requires extensive planning and scheduling to manage the hundreds of precise tasks that need to be performed. AI is being used as a predictive maintenance tool to best manage the sequence of steps in which aircraft maintenance should be done and to predict potential failures of maintenance on aircraft.

With a large percentage of the aircraft delays being caused by unplanned maintenance, using AI allows maintenance technicians to tackle the problems earlier when it’s easier and less costly to perform to improve the reliability of aircraft maintenance.

The AI systems can collect and record a large amount of real-time data which can provide the technicians with the information to detect possible malfunctions and replace parts before any component failures actually occur.

AI can analyze data from an aircraft’s monitoring sensors from not only a single aircraft, but from all similar aircraft types in a fleet or across the globe to discover patterns or irregularities in the data that could suggest a systematic problem with that type of aircraft.

With AI predictive maintenance, airlines can save thousands of dollars in reduced expenses connected with any unplanned maintenance, such as expedited shipping of parts, overtime costs for maintenance technicians and costs associated with flight delays or flight cancellations due to maintenance issues.

Autonomous Aircraft

In today’s world with self-driving cars and semi-autonomous drones, the vision of self-flying and fully autonomous aircraft capable of taking long flights without a pilot is beginning to be shaped within the aviation industry.

Although there is still a long way to go, several major companies in the aviation hierarchy are starting to explore how to make it possible and are currently developing and testing the technological advancements that will be required.

Currently, AI has proven capable of reacting and adjusting to the knowledge and information that has been programmed into it from the data obtained from thousands of flights.

However, the automation will need to react to complex variables that are not specifically programmed in rare or unforeseen scenarios, such as unexpected and intense weather or turbulence or other in-flight emergencies that the thinking skills of a human pilot could correct.

In a three-dimensional flight emergency, the AI software needs to interpret and manage all of the data from the aircraft’s multiple sensors, environmental conditions, and emergency protocols to adjust the proper flight controls to keep the aircraft flying safe.

The goal will be to develop and use AI technology to make the autonomous aircraft even more reliable than human pilots and to ensure safe flights for future passengers.

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