The issue appears after the line forms
Waiting and drop-off are operational problems that sales and POS do not record.
Measure wait time, headcount, and crowding live. Evidence for staffing before a peak.
No identity, only queues and crowding
Waiting and drop-off are operational problems that sales and POS do not record.
Without weekday and hourly crowding records, staffing relies on experience.
saai queue measurement
Use existing CCTV to measure wait time, headcount, and crowding live. Alert staff before the threshold is crossed.
What it looks like
Queues and crowding. Act before the threshold.
Measure
People waiting and the estimated wait, live.
Alert
Staff hear about it before the threshold is crossed.
Guide
One line on customer signage: about 6 minutes.
3
People waiting
4 min
Est. wait
Customer signage
Crowding peak by day
Outputs
Four queue and crowding signals. What to check next at checkout.
Waiting time
How many minutes joining the line costs right now.
People waiting
How many are standing at the checkout.
Crowding cycle
The interval between the ebb and the flow inside the store.
Peak
The busiest point by weekday and hour.
* Figures are illustrative.
Sense, analyze and think
care senses it. insight analyzes it. agent proposes what to do next and connects it to the action.
What needs attention?
Real-time alert when a queue or crowding crosses its threshold
Why did it happen?
Waiting-time peaks and crowding cycles
What should we do?
Staff reallocation, extra counters or self-checkout routing proposed
Evidence for checkout and self-checkout planning.
Expected wait shown clearly.
Privacy by Design
Anonymization comes first. The SEAL engine
No video stored
Deleted after analysis, stats only
No originals kept
Source footage is never retained
No re-identification
Identity removed, flow only
Where it leads
Queue and crowding signals extend to footfall measurement and live detection alerts.
All functions