The problem
When capacity becomes a problem
Counting by eye isn't enough
At peak times nobody has time to count who comes in and who goes out. And a manual count leaves no history.
You find the limit once it's passed
A full waiting room or an overcrowded venue gets noticed when customers start to complain, or to leave.
Every area has its own limit
The store as a whole can be quiet while the waiting area, the counter or one dining room is already full.
How it works
How capacity control works
Occupancy is calculated from the people detected in each area, with staff excluded, and updated in real time.
We set up the store and its areas
The whole store, the waiting area, a dining room or the counter: each area has its own occupancy.
We update the counters live
People present and entries reach the dashboard in real time, as they happen.
You set the thresholds
For each area you choose the limit and how often to check it; the rules follow the store's opening hours.
You get the alert
When occupancy goes over the threshold a notification arrives by email and in the notification centre, and the breach stays marked on the chart.
What you measure
What you measure with occupancy
Real-time counters
People present and entries, updated live in the dashboard.
Average and peak occupancy per area
How many people there are on average and at the busiest moment, area by area.
Occupancy heatmap
Occupancy by day and hour, and by zone, to see when areas fill up.
Capacity alerts
Thresholds per area, email and in-app notifications, severity levels and an alert history.
Opening hours
Metrics and alerts calculated only while the store is open.
An example
Saturday afternoon, a 20-seat waiting area
A counter-service shop sets an alert at 16 people, to leave some margin before the limit.
- Alert sent
- 4:25 pm, by email and in-app
- Occupancy at 4:30 pm
- 17 people
- Peak of the day
- 19 people, at 5:10 pm
Illustrative example.
Who it's for
The same metrics, read through the questions of your industry.
Retail & chains
People in the store and in each department during sales, events and extended openings.
Privacy
We measure flows, not people.
Only anonymous, aggregated data
Numbers leave the store, not images.
No identification
Demographic data only in aggregate, optional, and enabled only after an assessment with your DPO.
Staff are not counted
Employees are automatically excluded from every number.
In-store processing, EU hosting
Images stay on site; aggregated data is hosted in Europe.
Frequently asked questions
With the cameras covering entrances and areas: Kontrol Flow counts the people present, excludes staff and updates the counters in the dashboard in real time.
Yes. Set a threshold for the store or for a single area and get a notification by email and in the notification centre when it's exceeded. You choose how often it's checked, as often as every 5 minutes.
Yes. Each area, from the waiting area to the counter, has its own average and peak occupancy and can have its own alert threshold.
No. You set each store's opening hours and metrics and alerts take them into account, so you don't get pointless notifications out of hours.
Related solutions
People counting
Unique visitors and entries per door, hour by hour, from the IP cameras you already have, with staff excluded.
Queue and wait time
Average, median and P95 wait from waiting area to counter, queue, walk-outs and alerts.
AI-powered retail analytics that respects privacy. Transform your store's video feeds into actionable insights.
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