‘Smart Travel’ system at Abu Dhabi airport under trial

Our Correspondent

Abu Dhabi International Airport (AUH) in the UAE capital is in the trial phase of a new enhanced ‘Smart Travel’ system, developed by Abu Dhabi Airports in partnership with ConvergentAI and powered by Artificial Intelligence. This is expected to shorten queues and streamline processes throughout the airport and give passengers a more seamless experience at the airport.

The new system employs big data, AI, and the rigorous modelling and assessment of passenger traffic to optimise a variety of processes from check-in and immigration counter staffing to passenger arrival and departure times.

As a part of the ongoing trial, select passengers travelling with Etihad Airways will be informed of the optimal time for them to arrive at Abu Dhabi International Airport. By staggering passenger arrivals, the new system will mitigate crowding, facilitate social distancing, and shorten queues. Overtime, as the AI-powered system continues to operate, it will become smarter and further streamline passenger journeys through the airport.

“By enabling passengers to quickly and seamlessly transition through check-in, immigration and boarding, we are providing them with more time to enjoy everything Abu Dhabi International Airport has to offer, from first-rate dining to superior duty-free offerings,” said Chief Information Officer at AUH John Barton.

The introduction of AI technology at Abu Dhabi International Airport is also benefiting airlines, retailers, and employees working at the airport in a variety of ways. By using AI to monitor real-time imagery of aircraft, special programmes are being developed to guide on-ground teams to complete certain actions, such as the unloading of luggage or the refuelling of an aircraft at optimal times.

AUH is also exploring the integration of AI into its safety and security systems, enabling the automated monitoring of camera feeds of the airport apron, the area in which aircraft manoeuvre and park. AI-equipped systems can be taught to detect irregular activity or objects and notify the relevant teams to address potential issues swiftly and efficiently.