Airports globally are experiencing unprecedented challenges as airlines are grounding aircraft in response to the sharp decrease in demand. Read our first guide on how to best overcome COVID-19’s impact on airport operations planning – social distancing, volatile schedules, and limited budgets.
orecasts passenger and baggage volumes and corresponding arrival curves at various touchpoints across the terminal. Provides an automated planning flow in real-time while machine learning ensures continuous data-driven improvement.
Allocates check-in counters and queue area using its unique Queue Vision feature to reduce flow area bottlenecks and secures optimized use of check-in infrastructure.
Generation of lane opening plans at security checkpoint(s) and the corresponding demand for staff based on passenger presentation.
Transforms in real-time a forecasted passenger arrival curve into optimized desk opening plans and resultant demand for border control staff.
Allocates baggage make-up positions considering any early baggage storage and secures optimized use of infrastructure. Allocation of baggage reclaim belts provides balanced use of reclaim belts, thereby improving the passenger flow.
In development. It will allocate stands and gates, considering all constraints and forecasts estimated times and aircraft links using machine learning. Thanks to the Horizon 2020 funding, the solution will be taken to the next level, which includes refining the machine learning components and advancing Better Airport®’s aircraft allocation solution.