Detection & AI
Detection runs on your own hardware and picks up movement, people and vehicles, faces, license plates, and sounds. The results become events you can browse, get notified about, and search.
How detection works
Detection is layered:
- Motion runs continuously and cheaply. It just notices that something changed.
- When a trigger fires, the heavier AI wakes up. It runs object detection (people, vehicles, animals), then looks closer at what it found: faces on the people it sees, license plates on the vehicles, and a semantic fingerprint for search. Motion is the usual trigger. A detected sound wakes the AI too, and so can another sensor, for example a door contact.
While an event is active, the heavier analysis (objects, faces, plates, and search) switches to the camera's high-resolution stream for sharper crops, then drops back to the lighter stream once the scene goes quiet.
What you can detect
- Motion — movement in the frame.
- Objects — people, vehicles, and animals.
- Faces — recognize known people and group unknown ones.
- License plates — read plate numbers.
- Audio — sounds like glass breaking, alarms, or a dog barking.
- Semantic search — find moments by describing them in words.
- Find an object — click a person or vehicle and get the moments that show it.
- AI descriptions — a written summary of what happened.
- Episodes — related sightings across cameras told as one story.
Plugins do the work
Detection is provided by plugins you enable per camera: a motion engine and an AI backend that matches your hardware. You choose and tune them in a camera's settings, see Set up sensors.
Each detection becomes part of an event. See Events & detections for how those are structured, and Recording (NVR) for browsing them.
The detection models themselves learn from frames the community labels and contributes. See Model training.