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Smart Passenger Flow Pilot

In the aviation transport domain, significant, double digit savings potentials cannot be found anymore in aerodynamic improvements or more efficient engines. Instead, the use of Integrated Intelligent Information will allow to increase the predictability and coordination between the stakeholders involved in all airport processes, and therefore to free up significant savings potentials. During this project, we are going to validate how Big Data technology might help to achieve them.

This pilot is focused on understanding the passenger flow within the airport, enabling a better understanding of its impact on other airport processes, such as aircraft, security and retail. By acquiring new insights on how passengers behave, this pilot will potentially:

  • Predict aircraft delays due to late passengers.
  • Improve the transfer process, anticipating the detection of those passengers who might miss the connections,
  • Support the scheduling of daily operation and resources required in security areas, taking into account parameters not yet considered and detected through the application based on big data exploitation principles,
  • Allow the creation of new business models based on data driven decision making in retailing. This way:
    • Managers can anticipate passenger preferences and behaviours to their arrival, while the time to react is increased and it enables thus the provision of customized offers
    • Dynamic adaptation of marketing strategies to the expected passenger typology per time slot
    • Insight based exploitation of the current business and approach to new market niches.

Besides the operational efficiency, passenger satisfaction will be also significantly increased through an efficient use of resources, which will allow to better assume the demand in peak hours by assigning systems and workforce where needed based on real time situation analysis, and offering tailored services according to customer segmentation.