44% Reduction in Average Taxi-In Time achieved at Toronto Pearson International Airport

Requirements

Toronto Pearson required full situational awareness of the turnaround process at all 106 gates to achieve operational efficiencies and improve resilience while decreasing delays. They needed data to provide the single source of truth for their Airport Collaborative Decision-Making initiative to ensure effective collaboration with their airline partners while maintaining safety standards and reducing their environmental impact.

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Solution

Assaia's TurnaroundControl uses a combination of AI and computer vision to track exactly what is happening during aircraft turnaround in real time. The resulting data is used to highlight when turnaround subprocesses (like fueling or catering) are falling behind schedule and mitigative action can be taken immediately to minimize delays and to increase gate availability.

The system also creates highly accurate predictions of when an aircraft will depart as soon as it arrives. These early predictions allow the airport operational staff to flag potential gate conflicts earlier and make gate changes to avoid incoming aircraft having to wait for their gate. Less waiting means less kerosene consumption, lower costs, and reduced C02 emissions.

Deviations from the schedule and predicted delays are communicated to users via the solution’s alerting capability. This allows for an efficient operation as users no longer need to keep an eye on all ongoing departures but rely on the system to flag departures with issues and focus their efforts on these flights. This method of management by exception means airports and airlines can manage more flights with the same number of staff as they become more productive.

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