A predictable turnaround process thanks to: Turnaround Insights
To streamline the turnaround process and make it more predictable, Amsterdam Airport Schiphol has developed Turnaround Insights. This cutting-edge solution uses deep learning technology to translate camera images from the aircraft stands into usable data. This data, which provides insight into the various sub-processes, such as refuelling, pushback, cleaning and catering, will help us predict and prevent delays.
Understanding the turnaround process
The turnaround process starts from the moment an aircraft arrives at the gate and ends when it leaves the gate. In a short timespan, all kinds of activities have to take place in a relatively confined space: passengers disembark, the aircraft is refuelled and cleaned, baggage unloaded, maintenance carried out where necessary, and so on. This process is tightly organised: the slightest hiccup can be enough to cause a ripple of disturbances that leads to a flight being delayed. Needless to say, that’s something we at Schiphol want to avoid wherever possible. Data that provides valuable insights into turnaround can help prevent such problems.
Cameras at the aircraft stands
At the aircraft stand, cameras are positioned in order to collect a series of snapshots. An advanced algorithm (deep learning technology) then converts these snapshots into data and recognises specific elements of turnaround, such as the arrival of a baggage car or the hooking up of a tanker. This enables us to pinpoint the start and the end of each element and to measure the time in between. The resulting timestamps show the progress in the turnaround.
From proof of concept to broad rollout
In 2019 and 2020, on a proof of concept basis, Schiphol installed cameras at the aircraft stand at Gate E-19 with a view to developing the algorithm. This model was then validated and a feedback loop developed so that the quality of the algorithm could be continuously improved. Pier H was also equipped with cameras. In collaboration with future users, we are now validating the Pier H model. A plan is currently underway to further expand the number of piers with cameras.
Open data for partners
Using the data we gather with Turnaround Insights, we can both predict and prevent delays by making timely adjustments. To achieve this goal, we plan to share this sector data with all our internal and external partners working at the gate. This will enable us to cooperate on the basis of a single, verifiable truth to streamline our processes and make the operation predictable.
Read the previous blogs:
Is sustainable taxiing possible at a busy SchipholPublished on:
Thanks to the taxibot trial we know the prerequisites for sustainable taxiing. But more research was needed into the scalability of the concept.
Collaboration with Eco-Runner Team DelftPublished on:
The collaboration underlines the dedication we have towards sustainable mobility and fits our ambition to create the world’s most sustainable airports
Sustainable taxiing: Taxibot trialPublished on:
We carried out a Taxibot trial at Schiphol between March and August 2020. In this blog we tell you how that went and what we learned from it.