Can AI and robotics accelerate airport throu
INDUSTRY WATCH
By using a combination of machine learning, robotics and an escalation path to human intervention, airports can achieve cost leadership by focusing its human workforce on more complex tasks. The expected outcome for the airport would be extended airfield availability and more aircraft throughput generating higher aeronautical revenue per day explains Benedicte Hennebo.
In airports economics, throughput is paramount. Passenger throughput to improve travellers’ experience and hence in airport spending, but also aircraft throughput which generates amongst others landing, take off fees that vary based on aircraft size, capacity and weight. So put in simple terms, the more passengers pass through and airplanes land or take off, the more airports add to their topline.
To increase capacity, whilst considering constraints such as number and configuration of runways, weather constraints, traffic mix, airports have two choices: initiating a CapEx intensive additional runway construction like Gatwick Airport is currently considering or finding cost-effective measures to enhance runway uptime with a focus on incremental and sustainable improvements.
Use case for AI and robotics
In 2021 three passenger planes landed at the Birmingham Airport while a stepladder was left in the middle of the runway. Cracks, rubber deposits or water stagnation on the landing field can also cause fatal incidents if left unmaintained which is why regular inspections are required.
Runways and taxiways are subject to very strict and regular inspections as per ICAO Annex 14 limiting the time airports can fully operate. Those inspections are however a long and labour intensive process that could be improved by using robots and drones.
Runway scanning
With advancements in drone technology, airports can leverage aerial solutions equipped with thermal imaging and AI-powered object detection to make inspections faster, safer, and more accurate.
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