PASSME Breakthrough 1 focuses on reducing passenger build up in various areas of the airport, such as check-in, by forecasting the movements of passengers in an airport terminal. The forecast predicts the expected demand and use of certain airport operations thirty minutes ahead of time, improving the management of passenger flow.
These forecasts enable airport staff to adapt airport capacity and services, such as staffing, to the anticipated passenger demand at various points, such as security and border control. Furthermore, these forecasts allow for improved information systems and mobile applications for passengers, using the increasing desire among passengers for new mobile services to help better manage their journey. For example, forecasting could help provide live information about a passenger’s flight and how they may reach various airport locations. By collecting and sharing this information the PDF system can facilitate improved decision making by both airports and passengers.
A Passenger Demand Forecast, or PDF, system, allows this type of passenger forecasting to be carried out. This system uses real-time sensors to provide information on the detection and tracking of individual passengers. Input from advanced sensors at the airport will be obtained, for example, through WiFi, Bluetooth and video cameras, as well as from adaptive personalised devices (cf. Breakthrough 4). While ensuring privacy and data protection legislation, this information is then used to forecast a passenger’s behaviour throughout their journey through the airport.
Overall, this breakthrough provides a novel solution for managing passenger flows through a real-time passenger-orientated system, allowing forecast passenger demands to be met and, consequently, reducing travel times.