AI video analytics for warehousing, distribution and loading bays
For warehouse and logistics operations heads who need to see where time and safety leak across racks, aisles, docks and the yard. Eye AI reads the CCTV you already have through an on-site computer. It counts vehicles and people at gates and dock doors, logs entries into aisles and restricted areas, and tells parked vehicles from passing ones, with a snapshot and time for each event.
What goes wrong on sites like yours
Trucks wait in the yard or at the dock and nobody can say how long.
People walk into live aisles and vehicle lanes with no record of how often.
Dock-door activity is guessed from paperwork rather than seen.
Visitors and unscheduled vehicles come and go with no searchable log.
A camera drops out and the gap is found only when footage is needed.
What Eye AI does here
| Analytic | What it does on your site | Status |
|---|---|---|
| Line crossing and counting | Counts vehicles and people at gates, lanes and dock doors, by direction | Live |
| Parking and dwell time | Times vehicles in yard bays and marks visits as parked or passing | Live |
| Restricted-area alerts | Logs entry into aisles, rack areas or restricted zones | Live |
| Vehicle zone control | Logs any vehicle entering a pedestrian lane or no-vehicle zone | Live |
| Nothing-is-silent safety net | Shows movement the AI could not name | Live |
| Event history and reports | Daily and monthly activity by hour, with CSV export | Live |
| Number plates (ANPR) | Reads plates at gates and lanes where the angle suits | Beta |
| Forklift and pedestrian safety | Distance warnings between forklifts and people | Launching with pilot partners |
| Loading and unloading monitoring | Dock activity timing for trucks | Launching with pilot partners |
| Blocked exits and fire routes | Flags objects left in exit zones | Launching with pilot partners |
A day on your kind of site
Imagine a distribution centre with one yard gate, six dock doors and a main aisle. The operations head draws a counting line at the gate and at each dock door, and marks the yard bays as dwell zones. By late morning the history shows how many vehicles entered, which ones stopped in the yard and for how long, and which passed through. Two people step into the main aisle zone; both entries are logged with snapshots. In the afternoon the safety net shows unidentified movement at a rear door and the supervisor checks the image. At day end, the manager filters the grid by dock door, exports a CSV and compares it with the dispatch sheet.
Reports and evidence you get
- Vehicle and people counts by gate, lane and dock door
- Visit start, end and duration, parked or passing
- Aisle and zone entry events with snapshots
- Day-by-hour grid and CSV export
- Camera uptime history
Why existing cameras matter here
Warehouses already have wide coverage on docks, yards and aisles. Using those streams avoids a camera project and keeps video on your network.
Honest limits for this industry
- Forklifts are not a distinct object type today; they may be missed or labelled as another vehicle.
- Matching a specific truck in and out needs plate reading, which is Beta and needs a site survey.
- Queue length and wait times are not offered; dwell gives per-vehicle times only.
- Racking, pallets and stacked loads block views, and night, rain and headlights reduce accuracy.
- Forklift, loading and blocked-exit analytics are in pilot, not available today.
Questions
Does it watch loading bays?
Counting and dwell are live. Loading and unloading monitoring is launching with pilot partners.
Can it spot forklift near-misses?
Not today. It is launching with pilot partners.
Can it tell our trucks from others?
Only with plate reading, which is Beta after a site survey.
Where is the data stored?
On the computer at your 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