The optimal use of available airport capacity relies on technologies and solutions allowing airports to operate safely and efficiently. Better performance prediction is possible through big data analytics and artificial intelligence (AI), complemented by improved safety thanks to supporting tools and alert systems. Even though airport tools are under continuous evolution, AI is not fully incorporated yet. Many of the current operating methods around airports include manual processing, ad-hoc monitoring, data silos and segregated usage of data. In the context of AI, machine learning and other complementary technologies have matured in recent years, offering the possibility of making airport processes safer and more efficient.

The airport digital assistant (AP-DA) will bring and integrate AI technology capabilities across the whole spectrum of airport operations, in a balanced way, touching on both safety functionalities and operational throughput, airside and landside. Computer vision supports airport operators in detecting intrusions in restricted areas and in avoiding risks of collisions, while also contributing to the accurate calculation of aircraft turnaround processes and passenger flows. AI-enabled AP-DA will provide an alert system, helping to promptly take appropriate safety-related mitigation actions and achieve a more predictable airport operations plan (AOP). These alerts will be developed to support air traffic controllers, airport operations centre and airside frontline staff on certain tasks such as wildlife, foreign object and taxiway intrusion detection. In addition, the solution will support the airport operations centre to achieve a more predictable airport operations plan, enhancing the current process by incorporating: i) the calculation of the aircraft turnaround process, and ii) the prediction of the passenger at different airport check points, therefore consolidating terminal with airside operations.

The applicable regulations and existing standards have been identified for this solution, particularly those addressing artificial intelligence certification/development and system performance service specifications. In addition, the project has considered the latest reports regarding artificial intelligence from EASA and EUROCAE.

BENEFITS

• Safety: the automatic detection of FOD/wildlife and taxiway incursions will enable real-time resolution of events to improve safety through specific alerts for the different stakeholders involved, minimising the risk of incidents and events.
• Operational efficiency: the automatic and precise detection of wildlife/FOD and taxiway incursions, at the time of the event, contributes to reduced downtimes of runway and taxiway operations. AP-DA will also improve predictability through accurate predictions of the aircraft turnaround duration and passengers at different airport check points.
• Human performance: improve the situational awareness and decision-making of the airside and landside operations staff, supporting them in carrying out their tasks.
• Digitalisation: allow identifying taxiway incursions, FOD and wildlife at the runway operating environment, as nowadays the information comes from pilot reports, routine and non-routine airfield inspections. This allows having visibility and availability of the information related to taxiway incursions, FOD and wildlife presence and location in a digital way.
• Passenger experience: better alignment between needed resources and real demand at airport landside, improving passenger experience by reducing queues and delays.