AI and tracking data: looking to other industries | SITA

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AI and tracking data: looking to other industries

Published on  07 May by Dr. Simon Tomlinson , Data Science Business Engagement Manager, Lancaster University
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Robot hand shaking human handThe combination of artificial intelligence (AI) and tracking data will increasingly enable organizations to optimize operations, introduce automation, utilize prediction tools and adapt what they do in real-time to avert disruption.

While this will provide benefits in practically any domain, I believe there are going to be many potential use cases for leveraging tracking data and AI tools in the air transport industry.

The application of these new technologies to the world of travel promises some exciting developments. But there is one piece of strong advice I would have right now for professionals in the air transport industry – and that is to keep a close watch on developments in other industries, and particularly manufacturing and infrastructure management.

Smart factories

In manufacturing, think of smart factories, for instance. The widespread use of sensors, in conjunction with AI controllers, enable these factories to optimize their performance by continually planning and monitoring the flow of components and can prevent disruption through pre-emptive repairs.

AI, IoT and energy supply

Here in Lancaster, our academics are involved in a range of projects that combine AI with Internet of Things (IoT) technologies that promise to have benefits across a range of industries. One of the most promising application areas has been the enhancement of the management of infrastructure and energy supply that can be achieved through innovation.

Using our own campus as our laboratory we have been able to gain a rich understanding of user behavior regarding energy consumption and have been able to model and plan our management response accordingly.

Improvements in infrastructure management that are both supported by IoT-enabled sensors and AI-based analytics promise benefits for both utility and communications companies. They are likely to be one of the key use cases for this combination of technologies. Specific applications will probably include the prediction of demand and the efficient pre-emptive scheduling of maintenance.

A richer understanding of the journey

Then, in air transport, there is the potential of AI and tracking in optimizing the passenger travel experience, which will be enhanced through a rich understanding of the journey and interactions at various touchpoints and with stakeholders along the way.  

Using journey tracking data to build a unified repository of customer experience data will enable an AI system to highlight patterns of delays and errors. In turn, this will enable steps to be taken to remove any issues identified.

Critical lessons

Clearly the development of a successful AI solution will rely on the cooperation of air transport professionals – from the CIO’s office to those responsible for commercial and operational functions – to leverage their domain expertise and understanding of business processes. This will ensure that appropriate data is collected and that permission is granted for these data to be used by a central system that will perform analytics and optimization.

As we see in SITA’s white paper, Intelligent tracking – A baggage management revolution, the application of AI and data tracking capabilities will bring great improvements to baggage handling and services.

There will be many more applications, and to realize the opportunities the industry would be well advised to consider the principles of Industry 4.0 (aka the fourth industrial revolution) as they relate to automation and data exchange in manufacturing technologies. 

These principles may be applied to air transport business processes, and of course it is likely that a fundamental shift will be required in organizations’ relationship with information and their views of process control.

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