Stage one
AlmanoEye Light
- Watches every frame of every stream in real time
- Tracks people as anonymous skeletons, never as identities
- A learned motion model flags fight-like interaction, falls, panic and crowd pressure
The system, running
Two minutes inside the operator's screen.
A walkthrough of the working pilot: live detection on a street camera, a single incident opened and reviewed frame by frame with the reasoning shown, and the deployment view a commander would use to place units.
Recorded from the working pilot. The footage is public test material, not client cameras.
The problem
Cameras record. Almost no one watches.
European cities have invested heavily in CCTV, but the dominant use is forensic: footage is retrieved after the fact, to investigate what has already happened. The research on control rooms is consistent: one operator can genuinely attend to only a handful of screens, and vigilance decays sharply within the first half hour of a shift.
The gap between recording and watching is measured in minutes, and in an emergency minutes are the currency of survival. A person who collapses in view of an unmonitored camera has not been helped by that camera.
How it works
A two-stage system that reviews itself before it alarms anyone.
AlmanoEye mirrors how a good control room works, with a fast watcher and a careful reviewer, and applies that pattern to every camera, every second.
Stage two
AlmanoEye Heavy
- Replays the six seconds around each candidate event
- Detailed hand analysis: grabs, fist postures, contact between silhouettes
- Confirms the incident, or dismisses it with a written reason
Always in command
The operator
- Receives only reviewed incidents, each with a clip, a skeletal replay and the full evidence log
- Confirms or dismisses in one click
- Every decision becomes training data, so the system learns the city's own patterns
What it watches for
Three kinds of emergency, caught as they begin.
The system sees geometry and movement, never a face - in daylight, in darkness, in rain, in a crowd.
Violence, as it starts
A compact model reads limb kinematics rather than pixels, so it recognises the signature of an assault within the first seconds: in daylight, at night, in rain, in a crowd.
- Motion patterns
- First seconds
- Any light
Medical emergencies
Someone who falls and stays down triggers an escalating medical alert, including when the person becomes hard to see. A dedicated model is fine-tuned specifically on people lying on the ground.
- Falls
- Immobility
- Escalating alert
Crowd crush, before it is lethal
Continuous crowd-pressure estimation follows the physics of crowd disasters and warns while compression is still building, which matters for festivals, stations and match days.
- Festivals
- Stations
- Match days
Privacy by architecture
Safety without surveillance of identity.
AlmanoEye analyses how bodies move, never who people are. Detection runs on anonymous skeletal geometry: the system contains no facial recognition and no biometric identification. Everything runs on-premise, and no video frame leaves the building.
- No facial recognition
- No biometric identity
- Runs on-premise
- Skeleton-based analysis
This is a property of the architecture, not a setting that could be switched back on.
See it running on your own cameras.
AlmanoEye is a working pilot and we demonstrate it live. Tell us what you are responsible for keeping safe, and we will show you what the system sees.