Video Surveillance & Analytics · Video Analytics
Analytics turn cameras into sensors: alerting operators to real events, filtering out nuisance motion and giving managers reliable data on people and vehicle movement.
Deep-learning analytics classify people and vehicles, so a moving shadow or swaying tree does not raise an alarm. We define rules for each camera — virtual tripwires, restricted zones, dwell time — and calibrate them on site. The same cameras can provide occupancy, queue and footfall data for facility and retail teams.
| Detection | People, vehicle and object classification |
|---|---|
| Rules | Line crossing, intrusion zones, loitering, left objects, wrong way |
| Business insight | People counting, occupancy, queue length and heat maps |
| Processing | On-camera (edge) or server-based analytics |
Configured to manufacturer guidance and integrated with your VMS using open metadata standards such as ONVIF Profile M where supported.
Analytics perform best when camera angle and rules are designed together. We validate each rule with real walk tests.
Analytics that count or classify can run without identifying individuals. We configure retention and access to match your privacy policy.
Running analytics on the camera reduces bandwidth; server-based analytics suit complex rules across many cameras.
Yes. Classifying people and vehicles filters out most environmental motion that triggers simple motion detection.
Often, yes — through server-based analytics or VMS plug-ins — depending on camera resolution and positioning.
Share floor plans, a BOQ or a short brief. Our engineers will size the Video Analytics design, recommend suitable equipment and confirm the next step for your site.
