AI video analytics for residential societies and gated communities
For society managers, committees and security heads who already run gate and perimeter cameras and need more than a recording. Eye AI runs on a computer in your security office, reads your existing cameras and logs vehicles, pedestrians and riders crossing the gate, activity at the perimeter and parking in common areas. Every event has a time and snapshot, so a dispute about who came in is answered from the log. It serves societies in South Asia, the Gulf and beyond.
What goes wrong on sites like yours
The gate register is handwritten and nobody can search it.
Vehicles linger in common areas and nobody knows how long.
Boundary walls and quiet corners go unwatched at night.
Residents dispute who entered, when, and in what vehicle.
A camera stops recording and the gap is found only after an incident.
What Eye AI does here
| Analytic | What it does on your site | Status |
|---|---|---|
| Line crossing and counting | Logs vehicles, people and riders entering and leaving at each gate, with direction | Live |
| Restricted-area alerts | Logs entry into perimeter or no-go zones | Live |
| Parking and dwell time | Marks vehicles in common areas as parked or passing, with durations | Live |
| Vehicle zone control | Logs any vehicle entering zones set aside for pedestrians | Live |
| Nothing-is-silent safety net | Shows movement the AI could not name | Live |
| Stream health | Records whether each camera was working | Live |
| Event history and reports | Searchable entry history with CSV export | Live |
| Number plates (ANPR) | Reads plates at the gate and logs them with the vehicle | Beta |
| Loitering detection | Logs people staying near gates or walls beyond your threshold | Beta |
A day on your kind of site
Imagine a society with a main gate, a service gate and a visitor car park. The manager draws a counting line at each gate and marks the car park as a dwell zone. On a weekend, the history shows vehicles and pedestrians entering and leaving by hour. A delivery van stops in the visitor car park; its visit is logged as parked with a duration. Later, a resident asks when a guest arrived. The manager filters the grid by gate and hour, opens the snapshots and finds the entry. Plate reading is only switched on at the main gate after a site survey confirms the camera angle suits it.
Reports and evidence you get
- Entry and exit logs for vehicles, people and riders, by gate and hour
- Parked or passing visits with durations
- Perimeter zone events with snapshots
- Plate log with snapshot (Beta, once the site is surveyed)
- CSV export and camera uptime history
Why existing cameras matter here
Societies have already paid for gate and perimeter cameras. Eye AI adds analytics to them, and resident video stays on a computer inside your premises.
Honest limits for this industry
- Counting tells you a vehicle entered; it cannot tell a resident's vehicle from a stranger's without plate reading.
- Plates are Beta and need a site survey; angle, glare, distance and night decide results.
- Crowded gate moments, with people behind vehicles, can cause missed or merged counts.
- Delivery riders on two-wheelers are counted, but small or far objects at night can be missed.
Questions
Can it tell residents' cars from visitors'?
Only with plate reading, which is Beta after a survey.
Does it log visitors?
It logs people and vehicles crossing the gate line, not who they are.
Can residents see the footage?
Access is controlled by your dashboard login.
Does video leave the society?
No. It is processed on-site.
Which of this looks like your site?
We read every request and reply within 24–48 hours (working days, Monday to Friday) with questions and a proposed solution.
Request a solution