Solutions · Vehicle analytics

BrainWhale Vision

Computer vision reads the video stream and turns it into events a person can act on: which vehicle passed, whether the belts were fastened, what the plate was. Instead of hours of footage the operator gets a list of facts with snapshots.

What it recognises

MODULE 01

Licence plate (ANPR/LPR)

Automatic plate capture on the stream, day and night, in motion and in dense traffic. The plate is normalised into a single format, so search works even when the reading is not perfect.

MODULE 02

Seatbelt

Detects separately whether the driver and the front passenger are belted. It works through the windshield and stays robust to glare on the glass.

MODULE 03

Body colour

Colour of the vehicle body — a search attribute that works even when the plate is unreadable: dirty, obscured or out of frame.

MODULE 04

Make and model

The make of the vehicle from the image. Together with colour and plate it gives a description precise enough to find a specific car in the archive.

How it works

The chain is the same for every module: a frame arrives, the detector finds the vehicle, the recognisers read the details, and the result becomes an event with a snapshot.

01
Frame
A frame comes from the camera stream or from the camera itself. Not every frame is analysed — sampling is enough and it saves computing power.
02
Detection
The detector finds vehicles in the frame and cuts out what matters: the plate area, the windshield.
03
Recognition
Each fragment goes to its own model: plate text, belt state, colour, make. A reading below the confidence threshold is marked unknown rather than guessed.
04
Event
The result is written to the database together with the snapshot, the camera and the timestamp, and if a rule matches it raises an alert.
# event example
plate "M BW 2024"
seatbelt driver: no · passenger: yes
colour white
make Toyota
camera cam-07 · 14:32:11
✔ Recognition runs on a graphics card: frames are processed in tens of milliseconds, so a checkpoint camera is handled in real time.

What the operator sees

A web interface is part of the delivery — it opens in a browser and needs nothing installed on the workstation.

Recognition log
All passages with snapshots, filters by plate, date, camera, colour and make.
Map and tracks
Cameras on a map and the path of a specific vehicle between them.
Summary
Counts by day, by camera and by violation — where and when belts are ignored.
Watchlists and alerts
A plate from the list or an unbelted driver raises an alert at the moment of passage.

Where the events go

Events are not locked inside the analytics. They go to BrainWhale VMS next to the live video and the archive, or into your existing Milestone XProtect — the modules install there as a plugin.

Video surveillance system →

See it on your own camera

We connect a module to your camera and show plate and seatbelt recognition in real time.