How long do your patients really wait before admission?
The wait patients experience is often very different from the one staff estimate. Measuring it anonymously, by time slot, helps adjust how reception is organised without identifying anyone.
Healthcare
VIDEO.MA measures waiting room occupancy, admission queues and visitor flows on a strictly anonymous basis, with on-site processing preferred. No facial recognition, no patient identification: only aggregated counts and durations.
The wait patients experience is often very different from the one staff estimate. Measuring it anonymously, by time slot, helps adjust how reception is organised without identifying anyone.
An overcrowded waiting room hurts patient comfort and puts pressure on staff, yet peaks are rarely quantified. Measuring occupancy helps spread appointments and reception resources more evenly.
Technical or restricted areas are hard to supervise continuously. Access alerts on these zones, without identifying anyone, let you react sooner and review how they are organised.
Healthcare & Clinics
Waiting room peaks are endured, with no real-time visibility to redirect patients or reinforce the front desk.
Time spent at the admissions or billing desk weighs on the patient experience, yet it is rarely tracked objectively.
Pharmacy, storerooms and technical areas must remain restricted to authorised staff, on sites with heavy traffic.
Decisions on reception hours or space layout lack reliable, anonymous attendance data.
VIDEO.MA
Anonymous count of people present in each waiting room, with alerts above a defined capacity.
Aggregated counts of entries and movements between departments, with no identification of individuals.
Estimated number of people queuing and wait times at admission or billing desks.
Detection of presence in a defined zone outside authorised hours, complementing existing access control and without identification.
Detection of presence or congestion in defined technical or equipment storage areas.
Aggregated comparison of measured attendance with scheduled appointment volumes, with no personal or health data.
Number of people present per room, counted anonymously by video.
Average time spent queuing at the desk, estimated from video without identification.
Anonymous entries per access point and time slot, derived from video.
Number of presence events detected in defined zones, by video.
Aggregated appointment volumes from your scheduling software, with no personal data, compared with measured occupancy.
Entries today
642
Waiting room A occupancy
28 / 40
Average admission wait
7 min
Restricted-area alerts
1
Activity per hour
Events
Review of spaces, existing cameras and privacy risks, to define a scope strictly limited to the necessary areas and indicators.
Setup of counting and alert zones, on-site processing preferred, masking or exclusion of sensitive areas and aggregated-only outputs.
Testing in one waiting room and one admissions desk to validate accuracy, with patients and staff informed beforehand.
Gradual extension to other areas and regular review of scope, retention periods and indicator relevance.
No. No facial recognition or biometric identification is used. The system detects anonymous silhouettes to produce counts and durations, with no link to any patient record.
On-site processing, on an Edge AI device installed in the facility, is preferred. Only aggregated indicators are sent to the dashboard, and the architecture is validated with your IT team and, where applicable, your data protection officer.
Reception areas, waiting rooms, desks, corridors and certain technical zones. Patient rooms, treatment rooms, consulting rooms and any space where patient privacy is at stake are excluded.
As data controller, the facility must complete the formalities required by Law 09-08 with the CNDP and inform the people concerned. VIDEO.MA can provide the technical documentation needed to prepare the filing.
Get a quote tailored to your sites, cameras and metrics.