Avinor integrates forecasting technology across airport network
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Posted: 8 September 2022 | International Airport Review | No comments yet
Avinor has revealed it will integrate a new forecasting technology, which will allow the operator to plan and optimise operations across all areas of the airport network.
Credit: Avinor
Norwegian airport operator Avinor has announced it will integrate a new forecasting technology, which will allow the operator to plan and optimise operations across all areas of their airports. In one of the most comprehensive machine learning programmes in the industry, the strategic collaboration aims to result in better passenger experiences across its 40+ airports and allow for more cost-effective and reliable operations.
Now more than ever, airports are operating in a very dynamic environment, increasing the need for planning to be more agile and backed by evidence-based data. The programme will effectively build data that reflects the processes of passenger and flight movements across each airport. This will enable service providers to continually improve performance by making automated and accurate predictions and putting actionable insights directly into the hands of staff, where and when they need it.
“To reach our strategic goals of delivering better services more sustainably and more efficiently, we must become a data-driven organisation,” said Abraham Foss, CEO of Avinor.
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The machine learning platform will mesh data from multiple third-party systems and IoT devices to accurately automate predictions for multiple operational services and use cases across all time horizons. The programme scope includes providing accurate forecasts and capacity planning for passenger and baggage flow, check-in, security, and border control resource planning. It can also be used to provide predictions for baggage handling, concession footfall, shuttle services and terminal services such as cleaning, passengers with reduced mobility (PRM) assignments and transfers. This will enable the airports to match the availability of services to demand at any time and proactively address any potential issues, improving both the passenger and staff experience while lowering the overall cost to serve.
The technology may also be used by Avinor to improve airside decision-making such as turnarounds, de-icing, gate allocations and maintenance planning. The prediction capability will extend between airports; if Avinor understands the impact of events in one airport on others in the Norwegian network, the operator can take early action to minimise disruption.
Related topics
Airport development, Big data, Digital transformation, New technologies, Passenger experience and seamless travel, Terminal operations