Handbook for Implementing AI in Aviation (#21)

The extent to which Artificial Intelligence is used in everyday applications has increased enormously over the past year. This is no less true for the global aviation industry. However, in a world bound by regulations and safety requirements, knowing what to consider when implementing AI is helpful.

I've asked Dimitrios Ziakkas , Assistant Professor at 美国普渡大学 , to share his views. This autumn, he published a handbook on implementing AI in Aviation along with Lea Sophie Vink , Konstantinos Pechlivanis , and Abner Flores .

Dimitrios Ziakkas is an Assistant Professor at 美国普渡大学 ’s School of Aviation and Transportation Technology. He is an Airbus captain, instructor, and examiner with current A320, A330/350, and A340 type ratings. Dimitrios is a cross-cultural communicator, global citizen, and innovator with over 30 years of experience in worldwide military and civil aviation operations, integrating human resources planning – selection and recruitment aviation practices in multi-disciplinary research programs. His professional background is diverse, encompassing fields from history and the humanities to engineering and science. Dimitrios’ focus includes not only the history of aviation technological devices and processes but also the impact of technology on various aspects of life - politics, economics, science, the arts, and production organisation - and its role in the differentiation of individuals in society.

Implementation Guide for Artificial Intelligence in Aviation - A Human-Centric Guide for Practitioners and Organizations

By Dimitrios Ziakkas , Assistant Professor at Purdue University School of Aviation and Transportation Technology

In the vast expanse of human history, there have been moments that forever altered the course of our civilization. From the discovery of fire to the harnessing of electricity, these pivotal junctures have propelled humanity into new eras of innovation and progress. Today, we stand on the precipice of yet another transformative moment that promises to redefine how we navigate our world, both on the ground and in the boundless skies above. The following quick presentation of our book aims to build trust in implementing Artificial Intelligence (AI) in the Aviation ecosystem.

The Implementation Guide for Artificial Intelligence in Aviation is essential to the evolving ensemble around this historic juncture. Artificial Intelligence is revolutionizing the aviation industry by improving flight safety, operational efficiency, and customer experience. The EASA - European Union Aviation Safety Agency has published the Artificial Intelligence Roadmap 2.0, focusing on a human-centric approach to AI in aviation. AI techniques focus on Machine Learning, Deep Learning, Logic- and Knowledge-based approaches, enhancing traditional statistical methods. A human-centric approach is crucial for implementing AI, as humans excel in complex decision-making, emotional intelligence, adaptability, creativity, empathy, physical dexterity, and ethical reasoning.

Moreover, AI is transforming the aviation industry, particularly in flight training and operations. Pilots use virtual reality (VR) for cockpit procedural training, saving airlines and operators thousands of euros. AI-powered flight simulators train pilots in various scenarios, improving communication skills and enabling pilots to ask questions. However, accessibility and compliance with aviation regulations are crucial. AI integration in FSTD requires technical requirements, data verification, and data validation. The National Test Pilot School (USA) is integrating machine learning, augmented and mixed reality technologies to improve safety in flight tests. AI advancements like natural language processing and reinforcement learning enable immersive flight training for instructor-led and self-paced training.

Furthermore, AI is also improving weather prediction, flight planning, route optimization, and scheduling, enhancing pilot confidence and skill acquisition. Fatigue in aviation poses a significant threat to flight safety, and the Fatigue Risk Management System (FRMS) is implemented to manage it. Nevertheless, high fatigue levels among pilots suggest the need for improved strategies. AI can enhance FRMS by analyzing data, detecting fatigue signs, and developing mitigation strategies.

AI spearheads a groundbreaking transformation in air traffic management (ATM) by streamlining operations, leveraging predictive capabilities, and delivering invaluable recommendations. It is used in airspace management, decision support, flight path optimization, automated air traffic control, machine learning, and traffic prediction. Immersive technologies have the potential to significantly alleviate the workload of air traffic controllers, enhance safety measures, and drive operational efficiency to unprecedented heights. Nevertheless, we must acknowledge that there are indeed a multitude of challenges that persist within ATC0. These challenges encompass issues such as congestion, the intricacies of the airspace, unpredictable weather patterns, ensuring safety measures are upheld, mitigating environmental impact, addressing the ageing state of our infrastructure, fortifying cybersecurity protocols, and minimizing the occurrence of human error. AI is vital in Unmanned Aircraft Systems (UAS) and Drone Traffic Management. It empowers us with advanced technologies for traffic management, sense-and-avoid systems, autopilot systems, mission planning, and predictive maintenance.

AI is also used in airport operations management to optimize resource allocation and passenger flow. It can reduce congestion and waiting times, optimize energy usage, and predict maintenance needs. Moreover, AI-based chatbots and virtual assistants can improve the airline industry’s customer experience by providing personalized interactions, travel recommendations, and multilingual support. ?

Immersive technologies are paramount in driving predictive maintenance and condition-based monitoring for aircraft systems. AI applications are revolutionizing aviation repair operations and spare parts management, enhancing efficiency and cost-effectiveness. AI-MRO applications facilitate lean processes and the 6-Sigma philosophy in MRO operations.

Human-machine interaction (HMI) is crucial in AI-driven aviation and transportation systems, ensuring safe, efficient, and user-friendly transportation. It includes cockpit interfaces, air traffic management, autonomous vehicles, passenger experience, training, trust, transparency, and ethical considerations.

AI implementation in aviation requires a balance of ethical and legal considerations. Safety is paramount, and AI systems must be tested and certified to minimize system failures. Transparency is crucial for building trust, and AI algorithms must provide understandable explanations. Fairness is essential, and AI systems should ensure equal treatment for all individuals. Legal considerations include compliance with regulations, liability, intellectual property rights, data governance, and employment and workforce considerations.

The aviation industry can benefit from AI integration, but challenges like data quality, regulatory compliance, and cultural changes must be addressed. Successful AI implementation requires clear objectives, risk assessments, collaboration, robust data management, ethical considerations, and regulation compliance.

The story of artificial intelligence in aviation is not one of isolation but one of collaboration.

Throughout each chapter of our book, we explore the vast possibilities AI offers for aviation, from autonomous flight systems to predictive maintenance and air traffic management.

This guide is more than just a “first manual” of its kind. It serves as a gate for departure into the future that provides a precise flight plan to the collective effort of visionaries, engineers, pilots, and thinkers who have come together to chart a course toward a place where aviation and artificial intelligence are inextricably linked. It is a beam of light born out of boundless curiosity, unyielding determination, and the unwavering commitment to push the boundaries of human achievement toward a better future for all humankind.

The “Implementation Guide for Artificial Intelligence in Aviation – A Human-Centric Guide for Practitioners and Organizations” is a team effort of the aviation ecosystem.

Special Thanks to the Avion Full Flight Simulators team and primarily to Wouter Hollenga for his support.?For further reading, kindly visit: https://a.co/d/aokdBGA