elebrating 100 years of operation in 2025, Brisbane Airport Corporation (BAC) is currently executing the largest transformation in its history, investing over AUD $5 billion in capital upgrades as it modernizes existing facilities and builds new terminals. Anthony Tully-Smith, ICT Business & Finance Applications Manager, Technology, Brisbane Airport Corporation leads a team who are looking after nearly 300 SaaS applications – including essential CCTV and airport operating systems to flight information displays. Get the inside story on Brisbane Airport Corporation’s AI-powered technology overhaul: https://www.riverbed.com/customer-sto…

By Deb Gayen Reporter

UK airports are using artificial intelligence to help keep passengers moving.

AI-powered systems are helping to cut delays, especially in ground transport to and from airports, by tracking inbound flights and predicting late arrivals.

Aviation technology research suggests these systems can reduce airport ground transport delays by up to 20 per cent during disruption.

The impact is most visible in airport mobility, where timing failures can cascade quickly.

The technology gains come as major UK airports like Heathrow, Gatwick and Luton approach pre-pandemic passenger levels, putting further pressure on ground transport coordination.

1ST Airport Taxis, based in the UK, is among the firms using proprietary AI-supported technology that links real-time flight data to vehicle dispatch.

The AI system reduces airport pickup times by predicting delays, monitoring live flight data and adjusting dispatch in real time.

It also keeps drivers and passengers updated about road conditions and disruptions.

This results in more reliable and efficient airport pickups, particularly during peak travel periods.

Experts say as traffic continues to grow at the UK’s busiest airports, predictive technology is becoming central to maintaining reliability for time-sensitive travellers.

The Civil Aviation Authority confirmed that passenger numbers are nearing pre-Covid-19 figures at major hubs.

source : https://www.london-now.co.uk/news/25761322.uk-airports-like-heathrow-gatwick-using-ai-cut-delays/

Denver International Airport participated in a pilot program to test new security screening technology that uses artificial intelligence. The HEXWAVE System was created by Liberty Defense.

by Gustavo Pina Director of SITA Lab

Gus Pina is the Director of SITA Lab, the company’s strategic research and development arm. Created in 2008, SITA Lab explores new technology. It drives innovations for the air transport community, working independently and in partnership with others on pilot projects in robotics, big data, AI, wearable technology, and many others.

With 25 years in the IT industry, Gus has always been passionate about transforming business processes with emerging technologies. Prior to SITA, Gus spearheaded key roles in digital transformations across FedEx, Delta Air Lines, and Macy’s. We spoke to him to determine what drives SITA’s innovation roadmap.

The evolution of AI in chatbots

The last year has seen significant announcements and global public attention towards emerging Artificial Intelligence (AI) and Large Language Model (LLM) platforms like ChatGPT. Capturing both the public’s imagination and sparking fears around the rapid evolution of these transformative technologies, many industries are now speculating over the future of their products and services in a shifting technological landscape.

Chatbots and virtual assistants are among the most common use cases of customer-facing generative AI in the air transport industry. The rise of chatbots and virtual assistants expanded in the 2010s with the likes of Siri and Alexa. Like many other customer-facing industries, the air transport industry started leveraging the trend for AI-driven chatbot customer services.  

Before the availability of generative AI technology, chatbots were relatively limited in capability and required significant investment in development, training and tuning. Generative AI, and in particular LLMs such as ChatGPT, can make the user experience much richer without the resource of expensive machine learning training. They also provide a much broader knowledge base to work from.

Back in 2017, a small percentage of airlines and airports used AI-driven chatbots. We predicted that by 2020 68% of airlines and 42% of airports would have plans to adopt AI-driven chatbot services offering customer support. 

Our latest Air Transport IT Insights finds that the adoption of AI will continue to increase: airlines (76%) and airports (68%) are planning major programs, or R&D, for AI by 2025. 

Some of these programs today are directly customer-facing. For example, Etihad plans to use AI to enable passengers to book flights: Etihad Becomes The Latest Airline To Embrace AI Chatbots (simpleflying.com).

Clearly, while AI, and generative AI, are still relatively new, they have the potential to transform travel. 

Harnessing AI in the air transport industry today

As a global IT and communications provider for the travel and transport industry, we continuously explore and leverage emerging technologies to transform business models and processes – to help the industry reduce costs, overcome operational hurdles, and improve the passenger experience.

Starting with our SITA Lab innovation team and expanding across our product portfolios, we thrive on solving the industry challenges of today and tomorrow. SITA Lab explores new technology and drives innovations for the air transport community, working independently and in partnership with others on pilot projects in robotics, big data, AI, wearable technology, and many others.

While there are risks, generative AI’s opportunities for the air transport industry are immense. As part of our continuing work around AI, we are exploring numerous use cases to streamline processes, drive new operational insights and improve collaboration between airlines, airports, governments, and other stakeholders.

For instance, much process interaction between these stakeholders is through text-based document exchange (for legacy reasons). LLMs make it possible to extract meaning and intent from these human-readable documents into machine-readable and interpretable information. This bridge from human-readable text to digital computer interfaces will enhance greater collaboration and knowledge sharing, speeding up processes and enhancing industry efficiencies.

Today, we use AI, including machine learning, for data analytics, in several ways. See a few examples outlined below: 

(1) We offer SITA OptiClimb® as part of our SITA OptiFlight® suite of solutions, the industry’s only machine-learning solutions that analyze aircraft data and weather to optimize fuel and flight paths. The SITA OptiClimb® solution, aimed at airlines, delivers fuel savings of 5% for each flight while reducing annual CO₂ emissions by thousands of tons and operational costs by millions of dollars.

(2) Our SITA WorldTracer® Lost and Found Property leverages machine learning and several other emerging technologies to solve the global multi-million lost property problem by handling lost and found issues promptly and accurately, reuniting passengers with their lost property, and ensuring GDPR compliance. 

The technology behind the solution searches a global database of images and descriptions to match the found item to a missing item report. The solution uses image recognition to identify details such as the missing item’s brand, material, and color. It also recognizes similar words in the description to make a definitive match. 

Lost and Found Property cuts the cost of repatriating lost items by 90%. Airline employees can register a found item, create a missing item report, and validate a match in under two minutes. The solution also dramatically speeds up the time taken to find and return found items, with 60% of these items returned within the first 48 hours.

(3) Our border technologies are leveraging AI too. For example, we use it in our biometric identification technologies that support more modern border control procedures to increase security, improve border agencies’ operational efficiency, and generally provide a more pleasurable immigration experience for the traveler. 

We use AI to rapidly improve the performance of face recognition software to a point where they meet and even exceed the performance of other biometric modalities, such as iris and fingerprint, while being more convenient. A combination of more powerful edge processors with machine learning models is enabling face recognition on devices like mobile phones and smart security cameras.

(4) In our SITA Lab, we are developing next-generation digital assistants that leverage LLMs to create much richer chatbot-type interfaces than the first-generation chatbots. These bots have access to a combination of airport manuals, passenger points of interest, and real-time operational data. These assistants can be deployed at the airport to augment existing information service desks or within airline and airport apps.

We are also developing digital assistants to assist with airport operations systems. The assistant can provide advice on routine operational decisions, freeing up time for the airport staff to deal with more complex scenarios.

(5) AI is being used to help us resolve our airport customers’ technical issues, enhance communications, and increase customer self-service through virtual agents.

Here at SITA, we see great potential for generative AI across the entire travel and transport industry and we will leverage more of it to improve the effectiveness of our solutions and services to support the industry.

Assessing the risks of AI

There are many opportunities that we are exploring with AI. Of course, AI has several potential risks, from privacy violations to discrimination.

In addition to the traditional machine-learning risks, generative AI brings a new category of risk. The most commonly known is when ChatGPT ‘hallucinates’ and provides answers that sound convincing but are wrong or just invented. In the case of LLMs, careful use of Prompt Engineering and limiting the LLM to a specific data source (such as an airport’s operations manual) can prevent this from happening.

Until trust in these systems is established, it is important to have a human in the decision-making process and to build guardrails to autonomous systems.

source : https://tinyurl.com/49j6d3wk

Artificial intelligence (AI) has become a game-changing technology in an array of industries. The aviation industry is no exception. AI is transforming airport operations because of its capacity for processing massive volumes of data, analyzing patterns, and making smart decisions. Artificial intelligence in airline industry solutions is transforming the future of airports by boosting security and enhancing passenger experiences. 

Airlines are therefore looking into how artificial intelligence might assist them in meeting customer needs and enhancing operational effectiveness, speed, and overall experience. Let’s take a closer look at some of the primary ways AI is affecting airport operations and promoting a more comfortable, effective travel experience.

What is artificial intelligence?

Artificial intelligence (AI) is the simulation of human intellect in computers. It has been designed to imitate and duplicate human cognitive processes like learning, reasoning, problem-solving, perception, and decision-making. With the help of artificial intelligence (AI), robots (machines) can carry out jobs that would normally need human intelligence. AI-enabled machines can process massive volumes of data, spot patterns, and make predictions or even take actions based on that knowledge.

Smart Security

The use of Artificial Intelligence is revolutionizing how airport security is implemented, which is a key priority. Security camera data can be analyzed by AI algorithms in real-time, automatically spotting suspicious activity and potential threats. AI-powered facial recognition technology enables airports to precisely identify passengers and improve the security screening procedures. AI can also scan a lot of data from many sources, such as passenger IDs and travel records, to find high-risk people or suspicious patterns, which helps security efforts.

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 Maintenance Planning

To guarantee continuous operations, efficient maintenance of airport equipment and infrastructure is essential. AI-based predictive maintenance systems may track and examine data from multiple sensors integrated with important machineries, such as escalators or baggage handling systems. Artificial Intelligence can forecast maintenance requirements by seeing patterns and anomalies, averting equipment breakdowns, and cutting down on downtime. This proactive approach aids airports in cost-saving, operational efficiency, and seamless passenger experience.

Also Read: What is Online Check-In

Advanced Baggage Handling

Airports and travelers both experience great inconvenience as a result of lost or damaged luggage. The entire procedure, from check-in to retrieval, may be automated with AI-powered baggage handling devices. Artificial Intelligence can precisely detect, track, and classify luggage using computer vision and machine learning algorithms, guaranteeing that they arrive at their intended location. Airports can improve passenger experiences and streamline their operations by reducing mistakes and delays.

Personalized Passenger Experiences

Airports may now offer individualized services to the demands of specific passengers thanks to Artificial Intelligence. AI-powered virtual assistants can communicate with travelers and give them real-time flight updates, gate information, and airport directions. AI chatbots can respond to frequent questions, cutting down on wait times at customer care counters. Artificial Intelligence may also evaluate passenger information, including travel history and interests improving the overall trip experience. Flight booking websites can also use it to help passengers find cheap flight deals and also help with their queries. 

Ticketing Systems

The cost of an airline ticket is determined by a number of factors, including fuel prices, travel distance, date of purchase, competition, peak season, airline brand value, and others. Some factors, such as fuel costs, change daily, causing the ticket price to fluctuate over time. The best solution to this issue is an AI algorithm. It will assist airlines in determining the most cost-effective prices for every flight, enabling them to continue operating profitably and providing customers with competitive costs.

Artificial intelligence in airline industry has transformed airport operations and has made considerable improvements in security, maintenance, and other areas. The fad has only started. AI has the ability to improve airports by making them more cutting-edge, effective, and passenger-focused centers, changing the face of air travel for the better. 

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source : https://www.indianeagle.com/traveldiary/artificial-intelligence-in-airline-industry/

Airlines and airports in China are embracing artificial intelligence and automation to provide the hyper-personalised self-service experience their passengers are demanding, a new report reveals.

Airlines and airports in China are embracing artificial intelligence and automation to provide the hyper-personalised self-service experience their passengers are demanding, a new report reveals.

According to the SITA 2019 China IT Insights, shared today, China’s airlines and airports are using these technologies to expand mobile services and automating the journey with self-service every step of the way.  
 
A key technology that is attracting investment is artificial intelligence (AI).

SITA’s China IT Insights reveals that 88% of both airlines and airports are planning major programs, or R&D, with AI by 2022 and they are focusing on virtual agents and chatbots.

This investment matches the demands from passengers; SITA’s research of passengers in China shows that 64% of them want a digital travel concierge.

Already nearly half (43%) of airlines in China have AI-driven chatbot customer services and the planned investment should see the availability of them rising quickly over the coming years.

May Zhou, vice president and general manager of SITA China, speaking at the SITA China Air Transport IT Summit in Nanning, said: “China’s airlines and airports have a strong record in embracing technology and automation to drive efficient operations and high levels of passenger services. Now they are moving to the next level where they will harness artificial intelligence to deliver more services, faster and to more people.”

For passengers of China’s airlines and airports, self-service has reached a strong level of maturity, but a step-change is coming as biometrics is being adopted.

Today, 27% of airports have self-boarding gates using biometrics with travel documents but in just three years this will jump to 66%. And more than half of the airports have plans for secure single biometric tokens for all touch points by 2022.

Airlines too are committing to self-boarding gates using biometrics with ID, 60% are planning to use them driving a secure and seamless passenger experience right through the airport with the next three years.

Zhou added: “The adoption of self-service by passengers across China has been very encouraging for airlines and airports. At SITA, we see many in the industry who are now ready and planning to add biometrics to bring self-service to the next level.”

Mobile services are vital to meet China passengers’ demands and by 2022, all airlines and 93% of airports are planning investments in them.

Services including flight discovery, airline offers, check-in and flight status notifications via mobile are already provided by all airlines. One fifth are also using mobiles to sell newspapers, magazines and movies/TV to passengers.

Airports too are investing in mobile services to offer a more personalised experience for passengers. Services including, notifications about flight and airport status, and customer relationship management are well established and are offered by up to 81% of airports.

Keeping the passenger informed and connected is not only what China’s airports are providing via mobile, they are also facilitating mobile payments.

Close to three quarters enable passengers to buy airport services and allow cashless payments via mobile. This hyper-personalised service via mobile confirms it as a vital tool for China passengers.

The report highlights that blockchain technology is another key area of investment for airlines, today only 24% have major programs, or R&D, planned but this is set to jump to 80% by 2022. This is in line with the recent trends and commitments to blockchain technology in the country.

source : http://www.airport-world.com/news/general-news/7428-china-s-airports-embracing-ai-and-automation-new-report.html

Hitachi Vantara, the digital infrastructure and solutions subsidiary of Hitachi, is applying new artificial intelligence technologies to help airlines and airports solve some of their greatest challenges.

The Silicon Valley-based company’s technology aims to eliminate travel delays caused by congestion at check-in, security, retail and aircraft boarding areas.

Hitachi Vantara has developed solutions that combine computer vision with video analytics and machine learning to help airline and airport staff identify when and where congestion and delays are occurring and take action to address them.

The solution is already being piloted by a major US airline, and Hitachi Vantara hopes to implement the technology at more US airports in time for the 2020 holiday season.

The Lumada Video Insights solution uses lidar to produce a 3D visual model of the airport and the movement of travelers, equipment and luggage in real time.

The solution also applies video analytics tools to analyze the movement of travelers and luggage throughout an airport – while maintaining passenger privacy and without capturing any personally identifiable information. Comparing the actual movement of travelers to ideal models can then help airline and airport staff to identify issues and take action to streamline passengers’ travel experiences from the moment they check in to the moment they are safely in their seat with baggage stowed.

Potential use cases for Lumada Video Insights include streamlining check-in and security lines; providing travelers with more time to shop or relax in the lounge; and proactively managing overhead luggage space on aircraft.

source :

Indeed, KLM’s vigorous digital transformation strategy is largely due to recognising and leveraging the advantages of modern technology. Debie, who will speak in the Premium Conference at FTE-APEX Asia EXPO 2019 (12-13 November, Singapore), explains: “Digital transformation does not just mean replacing paper with apps. For us it means getting the right information to the right people at the right time to enable well-informed decision-making in an increasingly complex environment, supported by digital tooling.

“Key to this is to be truly data-driven, working from a single-source-of-truth and applying cutting-edge technology and algorithms to make sense of the complex operations.”

AI, machine learning and advanced optimisation

KLM is currently investing heavily in building automated decision-making tools to improve operations. In June last year, the airline embarked on a unique partnership with Boston Consulting Group (BCG) which has the potential to “revolutionise global airline operations”.

The project is a result of a close collaboration between KLM Operations Decision Support and Operations frontline teams, BCG’s consulting team, and members of BCG Gamma, an artificial intelligence and advanced analytics entity of data scientists, data engineers and software developers, who have developed a solution based on artificial intelligence, machine learning, and advanced optimisation that addresses all elements of the airline operations, while having a positive impact on customer experience and operating costs.

With these tools, KLM and other airlines will be able to tackle the most complex decisions pertaining to fleet, crew, ground services and network, with a focus on breaking down the typical silos across these departments. Earlier this year, Brazilian low-cost carrier GOL became the first airline customer of the KLM-BCG joint venture which will help GOL deliver better on-time performance to its customers while maintaining low costs.

Fostering an engineering culture

As Director Engineering & Architecture for the Department of Operations Decision Support (ODS) at KLM, Debie is responsible for creating and maintaining a cohesive overall architecture and technological vision for the products and platforms developed at ODS, but also for other clients within the partnership between KLM and BCG.

“I help teams within ODS and BCG/KLM teams at Partnership clients to build their products in accordance with the architectural vision,” he explains. “Additionally, I’m responsible for ensuring that we maintain high engineering standards in our development efforts. I provide development and architecture guidelines, coach teams and participate in recruitment efforts. A major focus area is to foster an engineering culture within the department that leads to acquiring and maintaining more engineering and data science talent.”

Together with his team, Debie has developed a suite of advanced optimisation tools for the Operations Control Centre to help set up robust schedules by implementing smart tail assignment, manage and solve disruptions, and help with decision-making. He points out: “This has led to huge savings in non-performance costs.”

Additionally, KLM has rolled out apps to more than 18,000 members of the airline’s frontline staff – from gate agents to captain and crew – to ensure they are all looking at the same information. “These apps provide the frontline staff not only with accurate real-time insights into the operation, but also gives them access to advanced predictions to see what’s ahead and guide their next actions.”

At the heart of its decision-making tools are KLM’s data platforms based on cutting-edge big data technologies. “Our goal is to provide people tools with a single-source-of-truth to guarantee we’re all looking at and acting upon the same information. To make decision in an integral way, we give each employee insight into the same possible tradeoffs built upon the same logic.”

The benefits for passengers are clear too – minimising the impact of disruptions through real-time updates, reducing baggage delays and personalising information that has been provided to the customer through digital channels.

In the longer term, Debie says that deep learning is very much on the agenda. “We want to dive more into deep learning and related technologies to improve the impact of our predictive models and optimisation models. We’re also looking into microservices architecture to improve decoupling across our tools. At the same time, one of the most pressing issues on our agenda is to bring the optimisers closer together in terms of decision-making. We want our optimisers to communicate with each other to ensure the best integral decision-making for our operations,” he said.

This ambition to be at the forefront of innovation has defined KLM as one of the leading airlines in the past century. Looking ahead, Debie says: “We got through the first 100 years by virtue of our pioneering and entrepreneurial spirit and of course through innovation. I’m confident that this spirit will help us in the next century as well.”

KLM Royal Dutch Airlines’ Daan Debie will be speaking at FTE-APEX Asia EXPO, 12-13 November, Singapore, where he will discuss why the airline is heavily investing in building automated decision-making tools for its operations, what problems are being solved with those tools, and the challenges it faces in pushing innovation and adapting to a new way of working

source : https://www.futuretravelexperience.com/2019/10/klm-pioneering-approach-artificial-intelligence-new-technology/?utm_source=Future+Travel+Experience+Newsletter&utm_campaign=8489c9a6b3-fte_nl_081119_REST&utm_medium=email&utm_term=0_c306aa3edf-8489c9a6b3-90811369