The camera sees the entrance
The door is in the frame and people are seen in full as they pass. Most of the time the existing cameras are enough.
An “AI camera” has a processor inside that recognises people and vehicles in the image. The same recognition can be done by software that reads the image from the IP cameras you already have. Vizor does this for shops, pharmacies, warehouses and construction sites, and sends the figures in a report every day.
An AI camera does the analysis inside itself, with whatever functions the manufacturer built in. Software does the analysis on the image from your existing cameras and ties it to the business: to receipts, to hours and to locations. Asked the same question, the two give different answers.
Recognising people in the image is only the start. The value comes from what is done with it: hourly figures, compared with receipts and across locations. Each one has its own page, with examples.
By hour and by day, staff excluded, from the entrance camera.
ConversionVisitors set against the till receipts for the same hour.
Walk-outsIn the pilot pharmacies, one person in three leaves without a receipt.
QueueA phone notification when the queue passes the threshold you set.
ZonesThe attention map: the zones people avoid and the crowded ones, by day.
GateThe people who passed the site gate, against how many are invoiced.
For counting, the camera has to see the whole entrance; for conversion, the checkout area too. If no camera sees them, one or two ordinary IP cameras are added, with no special functions: the intelligence stays in the software, not in the camera.
The door is in the frame and people are seen in full as they pass. Most of the time the existing cameras are enough.
The door is cut off by the edge of the frame or hidden by a shelf. Sometimes moving or turning the camera is enough.
An ordinary IP camera is mounted above the entrance. For a single entrance, one is enough.
It depends on the camera’s angle and quality, which is why we don’t quote a brochure figure. In our pilot in two pharmacies, the average error was 1.5% per day in people counting and 1.7% against receipts.
What video analytics measures, which cameras it works on, what it costs and how accurate it is.
Read →Infrared beam, 3D sensor or your existing cameras: what each one measures and what it costs.
Read →Conversion by hour, bypassed zones and checkout queues, in every store in the chain.
Read →What Moldova’s new personal data law requires from a business with cameras: legal basis, notice, records.
Read →Cameras with a built-in processor that recognises people, vehicles or faces in the image. Based on it, the camera sends alerts: someone crossed a line, entered a zone or stayed too long in one place. The functions are the ones the manufacturer built in, and they differ from model to model.
Usually not. The software reads the image from the IP cameras you already have, of any brand, and does the recognition outside the camera. New cameras are needed only where no camera sees the entrance or the checkout area, and then ordinary IP cameras are enough.
It counts visitors by the hour, excluding staff, and sets them against the till receipts, which gives you the conversion rate. It shows the checkout queue, the zones people avoid and the moments when a product leaves without going through the till. The result arrives in a daily report covering all locations.
An AI camera gives you alerts and counts in its own app, with the functions of that particular model. Video analytics on your existing cameras gives you business figures: visitors against receipts, by the hour, compared across locations. The camera is bought once for each spot; the analytics is a monthly subscription per location, with no equipment to buy.
Yes, as long as they are IP cameras and their stream can be accessed over the network; the brand does not matter. Send us a snapshot from the entrance camera and within 24 hours we will tell you what can be measured on it.
Yes, under the conditions of Law No. 195/2024: a written purpose, a legal basis, informing people with a sign and a retention period for the footage. Counting produces aggregate figures from which no one can be identified. Facial recognition is a separate case: a facial template is biometric data and needs its own legal basis, written down before it is switched on. The details are on the page about Law 195/2024.
One day per location, without stopping the business. The first report arrives on the evening of the installation, and the figures are checked with manual counts in the first weeks.
We look at a frame from your entrance camera and write to you within 24 hours what video analytics can measure on it and what else would be needed, if anything.