Responding Faster to Queues in Restaurants and Cafés
Queue video analytics helps spot overload in till areas and sends the manager a signal with a time and location. It measures people counts, zone occupancy or observable waiting. At Busted, we choose the metric around the venue's layout and available camera angles.
What to define in advance
A group near a till may include people queuing to order, waiting for a drink and already served. Combining them produces a metric that explains little. We therefore separate entrance, ordering, payment and pickup zones as far as the camera allows.
Next, agree what normal operation looks like. Morning café traffic and quiet restaurant hours may need different trigger conditions. Include overload duration so brief gatherings do not cause unnecessary notifications.
People counts or waiting time
People counts are easier to interpret as zone load. Waiting time requires tracking a visitor's entry into and exit from the queue. Dense traffic, occlusion and crossing routes make this harder.
The pilot establishes which metric is more stable. Sometimes a signal that the till area has been overloaded beyond a threshold is enough. If individual waiting times are needed, they become a separate performance criterion.
What the manager does after an alert
A notification is useful when linked to a clear action: checking open tills, reallocating team tasks or investigating a stalled operation. The recipient and response process depend on the venue and are agreed alongside the metric.
A shift report shows overload periods, duration and distribution by hour. Comparing these with order counts helps teams discuss workload and shift planning.
Getting started
An assessment needs recordings under normal and peak load, a till and pickup layout, and a description of current service. Busted helps choose zones and metrics, then tests them at one location. Comparing venues makes sense after event definitions are consistent.