Nick Woods has a vision: he wants to develop the world’s most intelligent airports. This vision isn’t just a long-term dream — Woods is already putting his ideas into practice.
“I think we’re well on the way,” said Woods, CIO at MAG Group, the largest UK airport operator that runs Manchester, London Stansted, and East Midlands Airports.
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“When I look around the world, lots of airports are doing cool things. However, I think our approach to emerging technology differs from many other organizations.”
Woods told ZDNET how he’s working with startups, using machine learning, and combining data insight with sensor data to make airports more efficient and staff more productive. Here’s how his team is developing the AI-enabled future of air travel.
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1. Supporting new business models
Woods said MAG spends a lot of time thinking about how it will make the most of emerging technology, particularly AI.
Nick Woods: “We’re being thoughtful about where we buy and build.”
MAG Group
“We’re being thoughtful about where we buy and build,” he said. “We’ve partnered with up-and-coming airport tech suppliers.”
Woods said some of the organizations MAG works with are startups. However, many of the partnerships are with companies in the scale-up phase.
“We’re co-investing with them to develop their products,” he said. “We’re showing them how to operationalize the technologies and proving them on the ground.”
Woods said that approach allows both parties to co-invest in technology and have a joint go-to-market strategy where the organizations can resell their solutions to other airports.
He gave the example of a close working relationship with Copenhagen Optimization, a technology specialist with a cloud-based system called Better Airport that can be used to improve airport operations.
“It’s a machine-learning platform, and we feed it all our turn-up data, flight schedule information, and historical data, which allows us to predict what the flight schedule will look like on the day based on the last flight getting back into the airport.”
2. Identifying performance improvements
Woods said his organization uses the insight from the Better Airport platform with other technologies to hone flight schedules and other operational areas.
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“We’re constantly monitoring what’s happening, updating the plan, and firing that out to everyone in the group,” he said.
The optimization of the planning engine takes place on the Google Cloud Platform. MAG then uses machine learning to update its algorithms continually. Real-time data is fed into these systems using AWS services.
The group also uses Veovo’s Passenger Flow Management technology to add insights from a combination of LiDAR, 3D Stereo cameras, and the airports’ Wi-Fi infrastructure to understand the movement of passengers through the terminals.
Woods said they can use this data to create a real-time view of how passengers flow through the building and can then work to boost internal processes.
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“We can look at where they’re gathering and getting congested, how busy the e-gates are at immigration, and how productive the various check-in desks are – and then we can start taking action to open more desks.”
3. Automating seasonal planning
Woods said the next phase in AI-led operational efficiency will focus on using MAG group’s technology platform to assist with seasonal planning activities.
The introduction of emerging technology involves a big cultural shift. Traditionally, professionals in the air control tower manually plan for the busiest weeks of the season in summer and winter.
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Now, with the help of all the data Woods’ team is collecting, AI and machine learning are supporting a move to automation.
“We’ve proven the software can do that work more optimally than the human can. And we’re now in a live test where we’re proving that we can do better on-the-day planning through the software as well,” he said.
Woods recognized that introducing automation involves focusing on “hearts and minds”. People must be shown how automation benefits staff, the organization, and passengers.
“We can then say the human role becomes an overseeing role, and we can manage the exceptions,” he said.
“We can manage when things go wrong and have the options to make changes, such as directing an aircraft to park at an alternative stand.”
4. Enhancing customer services
Woods said the insight his team collects isn’t just used to boost internal operations. The next stage will focus on using AI to improve passenger experiences.
“We’re starting to think about how we put that insight into the hands of the customer,” he said.
“So, we’re now working with AWS on using their large language model and Bedrock generative AI technologies to have better dialogues with customers around flight updates.”
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Woods gave the example of sending retail offers to passengers while waiting for their flights to take off or vouchers for tourist attractions at their destinations.
MAG is also working with AWS to use one of their new computer vision models.
“It’s essentially a self-training algorithm to start looking at, ‘Can I monitor what’s happening on the stand as the aircraft arrives? Has the cleaning started yet, and have the bags started being removed?'” he said.
“Some companies – from landing and turning the aircraft around – get off into the air again in 25 minutes. That’s an incredibly tight turnaround time. If we know passengers have started disembarking, and fuelling has finished, we can get much more predictive in improving on-time performance for the aircraft.”
5. Encouraging a focus on processes
Woods said one of the benefits of embracing emerging technology is that it’s helped to change how his team partners with the business.
Like many other organizations, Woods said IT projects at MAG were technology-led traditionally. People identified a business problem and looked for technological solutions.
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Focusing on AI has helped to create a new process-driven approach to innovation. The success of that approach will make it easier to justify more innovation in the future.
“We looked at the people in the process first and said right, ‘We’ve understood that process, we’ve made that as good as it can be, and then we’ve worked out the technology we need to underpin that process and make it work even better.'”
Woods said his team has proven the benefits of that shift in approach during the past few years. He said they’ve shown the long-term benefits from AI will be delivered by partnering with the rest of the business.
“Technology-led change doesn’t usually land well,” he said. “Instead, you need to think about how you partner with the business to understand what they want, what they need, what their priorities are, and then work with them to co-create better solutions that deliver the benefits. That’s a big change.”
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Source: Robotics - zdnet.com
