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AW6 2020 Information Technology NEWS

All about data


Closing the data gaps to automate airport operations is vital to efficiency post COVID, writes Thorben Burghardt, ADB SAFEGATE’s vice president for gate solutions.

The new oil of the 21st century is a well-known metaphor used to express the increasing value generated by data.

In a recent study, IDC and Qlik have taken it a step beyond by declaring the implications of data to be those of the new
water. Many analogies can be made between data and water, such as the necessity for clarity and availability, and accessibility, without which viability is mitigated.

From data we derive information, often subsumed and simplified by the term Artificial Intelligence. Data has become the new integration layer for applications of multiple vendors.

Instead of deeply integrating (melting) heterogenous applicationsfrom different vendors, today’s integration starts with the data layer.

For airports, concepts like Total Airport Management or a Digital Apron cannot be achieved without data of high-integrity and efficient means of omni-channel data sharing.

The digital transformation to a data driven business is a bumpy road. How long this road actually is has become apparent during these COVID afflicted times where airport operations are preserved with minimal staff, revealing gaps between existing ‘integrated’ systems.

Closing gaps to automate the apron, for example, is vital to efficiency and a key challenge. This leads to changes in how, when and where decisions are taken.

A real-world example

Under normal conditions, ADB SAFEGATE is parking 50,000 aircraft a day with its advanced visual docking guidance systems (A-VDGS). The solution has operated relatively isolated since the late 1990s on a per gate basis, relying on a sizeable variety of (local) data, similar to a micro-cosmos.

In recent years, initiatives such as A-CDM have drastically changed the ‘how’ with decisions taken collaboratively, within one provider’s solution and integrated with other vendors’ solutions.

The availability of data on the macro-cosmos has moved the ‘when’, a decision is taken to a much earlier point of the turnaround process. Knowing the track of the aircraft expected at a gate, in combination with tracks of other aircrafts, allows predictive action rather than reaction.

Driven by the change to cloud technologies, ‘where’ a decision is taken has adapted in parallel. Today, ADB SAFEGATE processes approximately 40,000 messages for parking aircraft per gate, per month.

Monthly, 17 million messages and resulting gate decisions have moved from local environments to be processed in the cloud. This is not only a change in technology, but also in that data is now omnicentralised (partially centralised and partially de-centralised) and thus, so is the decision making.

Parallel adaptions of the how, when, and where, plus the shift in technology lead to the proverbial question: to where will this lead?

The axiomatic answer is to a smarter world driven by holistic intelligent decision making. I believe the answer to be simpler. When integrating on the data-layer, we do not necessarily need to know exactly where it will lead.

We publish and subscribe data according to our needs. We derive decisions from there, centrally or distributed, and share these decisions, of course, as new data – to which our stakeholders can subscribe. In this way, the evolution of the data-ecosystem becomes self-sustainable.

What is the next challenge?

The change described spans an interesting area of conflict between technological possibilities and expected legal certainty.

Integrated systems must be robust and able to make decisions on incomplete, fuzzy knowledge such as conflicting information, parties not publishing information, or insufficiently trained AI algorithms. Otherwise, workflows would constantly stall and require manual intervention.

For many this is the next challenge in the digital transformation of airports: relying on the new way of data processing and decision making while keeping the same level of legal certainty.

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