For decades, airport operations have been too vast, too complex, and too cumbersome to manage in any manner other than reactive – i.e.: responding to issues after they’ve already arisen. However, AI is finally pulling the pieces of the technological puzzle together so that even the world’s biggest and busiest international airports can reliably predict and resolve operational issues before they adversely impact flight times.
4 Prominent use cases of AI that herald the rise of predictive airport operations
Maintenance: While the integration of new technologies, platforms and general infrastructure can undoubtedly cause disruption to a 24/7/365 airport, maintaining existing assets is often the bigger and more resource-intensive battle. From ground support vehicles to security systems and even the humble baggage carousel, equipment breakdowns result in backlogs and delays, not to mention potential safety risks. AI-powered predictive maintenance can analyse historical operational data alongside asset lifecycle data, find and isolate issues before they reach critical levels, and then flag them for engineering teams to resolve in a timely manner, or even automate the response when appropriate.
Passenger security and verification: Any manual checks at security gates and immigration control are always prone to slow or inaccurate processing times, and a sharp snowballing of delays when large numbers of passengers converge. With the rising proliferation of biometrics-based verification (face and fingerprint scans, etc) such manual checks and their associated inefficiencies are being phased out. However, maximising the predictive security potential (i.e.: spotting and eliminating security threats or capturing wanted criminals before they can cause any harm) means integrating all passenger security and verification processes under an AI-empowered platform that collectivises this data, feeding it to human security agents who have the ability to judge the situation and formulate the optimal response. This combination of computational power and human empathy/situational awareness is essential for predictive security, rather than reacting to incidents as they arise.
Flight management: The business of consistently guiding all inbound and outbound flights, all landings, turnarounds and takeoffs, is the bread and butter of efficient airport operations. While human ATC operators will always be needed to safely direct flights, AI now lends its raw data-processing power to optimally guide the more routine elements of these processes. AI allows for real-time situational awareness of flight statuses, the automation of elements including gate assignment, certain ground handling ops (refuelling, staircasing, etc) while feeding a constant stream of the most useful operational data to human operators who can make better decisions faster, predicting and resolving issues before they can unfold.
Passenger processing: Security will always remain a deeply complex and potentially charged aspect of airport operations. This means they will always need human oversight and a deft human touch. However, the more routine elements of passenger processing can be vastly improved with AI systems that track passenger movements from the moment they enter the airport – or even before they set foot inside. When AI provides airport management teams with a full overview of exactly where passengers are bottlenecking, this allows for predictive responses that may range from assigned more human assets to a temporary situation, to a long-term expansion of parking spaces, check-in desks, security lanes, self-service kiosks, walkways or whatever is needed to accommodate better, safer passenger processing.
Exemplar airports – From reactive responses to predictive ops
Frankfurt Airport (FRA) – Germany: FRA is one of Europe’s busiest airport hubs, welcoming 44.5 million passengers from January to September 2023. While passenger numbers have been rising, physical expansion of the airport is not a viable option. Instead, Fraport, the airport operators, turned to Saudi Airport Exhibitor SITA to implement its Smart Path biometric solution, which enables all 90 airlines serviced at FRA to deploy facial recognition technology at every step along the passenger journey. This has led to a 30% improvement of passenger processing times at FRA, and complements its expanding use of AI to optimise all airport operations.
Dubai International Airport (DXB): The Emirates Airline Authority announced last year that Dubai airports including DXB would begin to use AI solutions from Swedish company Saab in their air traffic control operations. Currently under installation, the system will allow ATC operators to work from a single screen being fed every aspect of real-time flight data, weather and radar, all collated into one place. AI is also essential in Dubai airport’s coordination of ground-based assets, such as security, police, fire, ambulance and border control staff.
AI is the key to predictive airport operations
Impressive as these early forays into AI are for leading airports, they represent only a fraction of the technology’s overall potential to elevate operational efficiency and safety. As AI embeds itself into a wider range of airport operational elements, it will become a force multiplier – boosting the capabilities and response times of all airport assets whether they are managing things on the ground or in the air.
