Flow Analytics by AGC

Right now, someone in your terminal is standing in a queue with no idea how long it will take. And neither do you.

By the time a border queue complaint reaches you, passengers have been standing in it for a while, and you're finding out last.

A camera loses the count when people block each other. It doesn't tell you how fast the queue is growing or when it'll clear. Our solution does.

Flow Analytics by AGC uses LiDAR sensors to count and track people in real time. For border control, that means queue length, wait time, and buildup speed, per checkpoint, as it happens.

A space can feel crowded before it actually hits any “limit.” That’s usually when stress kicks in: people slow down, hesitate, bunch up. By the time it’s obvious, it’s already uncomfortable. What’s interesting with real-time data is you can catch that shift earlier, when it still looks “fine” on the surface. Because that early moment is where flow starts to break down, movement becomes less predictable, queues form faster, and small delays begin to stack up. Catching it earlier means smoother flow, without needing more space or more staff. See how Flow Analytics helps airports detect these shifts in real time: https://lnkd.in/egaeSHJR

In terminal planning, space is usually designed with balance in mind: clear zones, defined pathways, and expected passenger distribution across areas. Once operations start, passenger movement doesn’t always follow those planned paths exactly. People naturally gravitate toward certain routes, familiar entrances, or perceived shortcuts. Over time, this creates uneven usage across the terminal. Some areas carry more movement than expected, while others remain quieter, even if they were designed for similar capacity. For planning teams, what becomes important is understanding how a layout performs once exposed to actual movement patterns, not just theoretical distribution. Flow Analytics helps airport teams analyse real passenger movement patterns to support more informed terminal planning and design refinement: https://lnkd.in/egaeSHJR