Skip to content
IRIS NEURALContact
Back to public transport

CAM-97

Station car park

The station car park in mid-morning, seen from the lamp post at the entrance: rows of cars almost full, the entry barrier at the back and two cars sitting across the line, taking up two spaces each.

The station car park in mid-morning, seen from the lamp post at the entrance: rows of cars almost full, the entry barrier at the back and two cars sitting across the line, taking up two spaces each.
CAM-97IRIS VisionLive

Turn on IRIS Vision

AI-generated image

CAM-97 · 1 ZONE · 24 h

What IRIS understands

What it recognises in this scene

  • badly parked
  • parking rows
  • barrier

What this camera gives back

Nobody gets an alert here. Here you get numbers.

  • 78%Occupancy
  • 42Free spaces
  • 5Badly parked
  • 4 h 20 minAverage stay
  • 09:00Peak hour
  • 520Total today

The figures on this screen are an example from the illustration, not any client's measurement.

The series, not one figure

One number says nothing. A curve does.

Occupancy by time slot

  • Occupancy
Occupancy by time slot
SlotOccupancy
0622%
0878%
1086%
1284%
1482%
1680%
1861%
2038%
2219%

The figures on this screen are an example from the illustration, not any client's measurement.

How the counting works

Counting is not something you ask for. You draw a line.

An area is painted over the rows of spaces. Inside it IRIS looks at two things: how many spaces have a car on them and how long each car has been in its own. A car sitting half in one space and half in the next is flagged separately, because it takes two and pays for one. Where the rows are and where each space ends cannot be written in a sentence: it has to be painted onto the image, once, and from then on the figure repeats the same way every month. And a warning about the screen: the 78% occupancy you see here is an example from the illustration, not any client's measurement.

  • car park zone · Dwell zone

What changes

What changes for whoever runs the station

A station car park is two businesses sharing the same ground, and almost nobody knows how much of each there is. One is the person who leaves the car at seven and picks it up at eight in the evening because they took the train: one space, the whole day. The other pulls in for twenty minutes to drop somebody off. With the area in place, the manager sees the real mix by time band and knows whether spaces are genuinely short or whether it is turnover near the entrance that is missing. With that he sets tariffs, decides where the short-stay zone goes and whether an extension is needed at all. And badly parked cars stop being an anecdote people tell: they become a number tracked month by month.

What people usually ask

Does IRIS read the number plates in the car park?

No, this camera does not read plates: it measures the space, not the car. The clock starts when a space becomes occupied and stops when it frees up, and that alone gives the average stay without knowing whose vehicle it is. It is the simplest way to answer the question that matters — how many park all day and how many for twenty minutes — and the one that needs the least data. If a particular site needed plate reading for access control, that is a different system and a different conversation: it is agreed in writing beforehand, with its purpose and its retention period.

What does IRIS count as a badly parked car?

Badly parked means whatever the drawn rule says it means, no more and no less. Because the spaces are painted onto the image, IRIS knows where each one ends: a car straddling two spaces, or standing outside any space but inside the area, gets flagged. There is no opinion and no intent in it: there is a geometry and a vehicle on top of it. That makes it arguable in the good sense — you can show the illustration and see why that figure came out — and it makes it comparable, because the line around the space is the same in January as in August.

Does this work at night or in a covered car park?

It works if there is enough light and the camera does not move, and both conditions are checked on site before installing. At night, with a car park's normal lighting, occupancy measures well because a parked car is a large, still object; what degrades first is telling a badly parked car when shadow covers the line on the ground. Under cover there is less light and more pillars in the way, so where the camera goes matters a great deal and sometimes two are needed. If a particular car park is not good enough to measure with confidence, we say so before rather than after, and any figure published carries that condition stated.

A different case every time

We won't just tell you. We'll show you.

It is a summary of the real screen: it plays by itself, step by step, and shows only the path of one case. The actual tool has far more than fits in here.

  1. You ask
  2. IRIS searches
  3. It shows you
IRIS NEURAL
30ES
IRISDirectoGrabacionesGISIncidencias3996SituaciónCasosLPRAutomatizacionesIRIS DATA
Ask a question or make a request…Send
IRIS · Infinity Neural

And the best part

Nobody covers the night shift:the camera that is already on covers it.

It does not tire, it does not blink and it does not go for coffee. What happens at night is understood just as it would be at midday, and whoever is on duty hears about it while it is happening.

Tell us your problem and we will say whether IRIS understands it, or not yet.

We reply the same working day.