Advanced analytics and machine learning – the connected airport takes flight

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As restrictions on air travel begin to lift and the volume of air travelers starts to increase, airport operators will be leveraging an extensive range of innovative technologies in a bid to streamline passenger journeys, deliver more personalized experiences, and optimize operational capacity and efficiencies.

The key is data. By generating, analyzing and acting on a variety of new datapoints, airport operators are able to provide a host of innovative processes and services to improve operations. From mobile apps that help passengers navigate the facilities and services on offer prior to embarkation and stay updated on their travel arrangements, to self-service check-in and artificial intelligence (AI) powered customer service chatbots, the airport of today is evolving at breakneck speed.

On top of this, automation technologies help airport operators reduce queues and streamline passenger movements through key security controls, immigration and gate checkpoints. Data-powered services are also offering passengers a more frictionless journey experience.

The connected airport takes flight

The emergence of Internet of Things (IoT) smart sensors and facial recognition technologies means that today’s airport operators have access to huge volumes of data. What’s more, they are primed and ready to use a variety of cutting-edge solutions that will make it easier to leverage insight from this data to optimize their operational capabilities. These technologies promise to make airports and the surrounding infrastructure safer and more efficient than ever before.

Using AI algorithms and digital twin technologies, operators will soon be able to collate data from across their real-time airport and airline operations to visualize, simulate and predict with greater certainty exactly what is likely to happen next. Leveraging these insights, they’ll be able to trigger proactive responses to any anticipated event.

Sharing this operational data with other stakeholders, including airline operators, they’ll be able to monitor passenger numbers and identify their key characteristics, all of which will make it easier to turn around facilities faster and ensure that appropriate human and equipment resources are in the right place, at the right time.

Meanwhile, a growing number of connected and autonomous vehicles and robots are already making an appearance in airports around the globe.

Baggage and luggage: using analytics for just-in-time operations

One key area where transformational technologies are making an impact now for airports, airlines and ground handlers is by better tracking the billions of bags that are transported every year. This technology is already rolling out across the world and is set to make it easier for passengers to track their bag’s progress, from the moment they deposit it to the final delivery into their hands once they reach their end destination.

Following the 2018 introduction of IATA’s Resolution 753, which requires baggage to be tracked at key points – passenger handover to airline, loading to the aircraft, delivery to transfer area and return to the passenger – airports have been turning to data collection and analytics to enhance the entire extended chain of custody.

Alongside addressing the challenge of baggage mishandling, increasing the efficiency of their baggage operations and delivering an enhanced passenger experience, the introduction of these technologies has also enabled airports to work more closely with airlines to keep airplanes and passengers safer. Key to this is clamping down on the illicit activities of airside and landside personnel.

For example, analytics can spot unusual patterns such as bags unexpectedly entering the system on loading, or baggage handlers who are associated with baggage that is persistently misrouted. Consider items such as an extra bag surreptitiously checked into the baggage system by a bad-actor baggage handler after a passenger has boarded. The extra bag might contain goods for resale such as rare apparel, or items subject to high tariffs. When claimed by an accomplice at the destination, the passenger would never know about the illegal use of their identity nor would the airline know of its criminal exploitation. Analytics technologies identify this type of misuse by analyzing the anomalous patterns from the activity logs of the handlers and the bags themselves.

Tightening security controls

The adoption of machine learning and the integration of AI with airport security systems such as screening, perimeter security and surveillance is enabling airport authorities to initiate additional security layers designed to protect the safety of employees and passengers alike. This includes implementing enhanced risk-based screening measures, behavioral recognition and modeling systems and state-of-the art 3D checkpoint scanners, as well as using smart gates and enhanced facial recognition at every stage of a departing passenger’s journey.

Systems that can detect and pinpoint risky behaviors can be used to detect disgruntled passengers or airport/airline staff, all of which helps improve the detection of potential security threats.

Protecting critical assets

Clearly, as automated airside operations become a reality, airport management teams will increasingly be dependent on leveraging real-time data to reduce the variability of operational processes and improve performance.

Integrating operational silos to facilitate the real-time information flows that feed their complex adaptive systems – logistics, customer-facing services and airline operators – is just the start. Keeping such highly connected environments protected from external cyber threats that attempt to access assets will increasingly become a top priority if airport operators are to realize the benefits of their technology investments.

With airports considered critical infrastructure, a growing awareness of data – and its inherent risks – is a must-have.



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