AI camera people counting
Standard network cameras with counting intelligence built in: exact in/out, occupancy and queue metrics from the camera itself. Anonymous counting today, and one hardware investment that grows the day you need more.
Counting analytics built into the camera. Anonymous by default.
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Why AI cameras
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Analytics in the camera
Counting runs on the camera itself, so a single device covers detection, counting and delivery with no separate sensor unit to install.
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Exact counts and queues
Directional in/out counting, live occupancy and queue metrics at entrances, checkouts and service points.
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Anonymous counting by default
In counting mode, video is processed for analytics only. No personal images are stored and no individuals are identified.
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One platform, every method
AI camera data lands in the same analytics platform, dashboards and API as Wi-Fi, 3D sensor, LiDAR and cellular data.
How it works
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See
A standard network camera watches its zone, and the counting model runs directly on the device.
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Count, privately
In counting mode the video is analysed in the moment and only the numbers leave the camera. No personal images are stored.
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Analyse
Counts become in/out, occupancy, dwell and queue metrics for the covered point.
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Deliver
Metrics flow into the same API and dashboards as every other Bumbee Labs method, one source of truth.
What data you get from AI cameras
AI cameras are a precision method at defined points, with the practicality of standard camera hardware. Typical metrics:
- Exact in / out counts (directional line-crossing)
- Real-time occupancy and capacity against safe limits
- Queue length and waiting-time indicators at service points
- Dwell at the measured point
- Peaks & lows at the measured points
For whole-space paths and journeys, combine with Wi-Fi; for camera-free precision in open or dark areas, see LiDAR. The method grid shows what each delivers.
Counting intelligence where cameras already make sense
Many venues already think in cameras: entrances, checkouts, service desks, receptions. AI camera people counting puts the counting intelligence inside a standard network camera, so the device that watches a point can also measure it: exact directional in/out counts, live occupancy and queue metrics, delivered from the camera itself into the same analytics platform and API as every other Bumbee Labs method.
In counting mode the analysis happens in the moment and only numbers leave the camera. No personal images are stored and no individuals are identified. The output is a count, not footage.
Where AI cameras fit best
AI cameras earn their place where standard camera hardware is itself the advantage: sites that already run or plan camera infrastructure, checkout and service zones where queue metrics drive staffing, and organisations standardising on one hardware family across many locations. For classic overhead doorway precision, 3D sensors remain the specialist tool; for camera-free measurement in dark, outdoor or wide-open spaces, LiDAR extends the same precision without any imagery at all. All of it lands in one place, and a hybrid setup mixes methods freely.
One investment, more than one job
Most counting hardware does exactly one thing forever. Standard cameras don’t have to. The counting product is analytics-only and anonymous by default: numbers, never footage. But the day you want more from the same cameras, the system extends with video security capabilities on request. You decide if and when, you set what it covers, and your own security policy and legal basis govern it; the extension sits outside the DPA-approved counting method. Nothing is recorded unless you have chosen it, and the counting analytics stays anonymous either way.
For a buyer, that separation is the selling point, not the small print: the privacy review clears the counting on its own terms today, and the security option stays yours to take whenever the business case arrives. Measurement now, headroom built in.
One platform, whichever method measures
AI camera metrics arrive through the same data deliverables, dashboards and API as Wi-Fi, 3D sensor, LiDAR and cellular data. Methods differ; the source of truth does not.
AI cameras vs 3D sensors vs LiDAR
Three precision methods, three sweet spots. AI cameras use standard hardware; 3D sensors are purpose-built for counting; LiDAR is camera-free by physics.
| Capability | AI camera | 3D sensors | LiDAR |
|---|---|---|---|
| Exact in/out at a door | Yes | Yes | Yes |
| Real-time occupancy | Yes | Yes | Yes |
| Queue metrics at service points | Yes | Yes | Partial |
| Standard camera hardware | Yes | No | No |
| Works in total darkness | Partial | Partial | Yes |
| Image-free by design | No | Partial | Yes |
| Anonymous counting output | Yes | Yes | Yes |
| Optional video security extension | Yes | No | No |
- Full
- Partial
- Not available
Curious what this looks like for your venue?
One camera, two jobs
Counting is anonymous and aggregate: numbers, never footage. And when you want more from the hardware, the same cameras extend with video security under your control and your rules. Measurement today, headroom for tomorrow.
Telia's partnership with Bumbee Labs is important for us to expand our business. It allows us to develop our use cases for location and movement insights to be even more granular. By combining our anonymized and aggregated mobile network data with Bumbee Labs solution of GDPR-safe Wi-Fi probe data, we ensure that the collection of data follows the strictest guidelines of GDPR compliance all the way.
Frequently asked questions
How is this different from 3D sensor counting?
3D sensors are purpose-built counting devices using stereo vision or time-of-flight, typically mounted overhead at a door. AI cameras are standard network cameras with counting intelligence built in, which makes them practical where camera infrastructure already exists or is planned, and lets one device serve wider angles than a dedicated overhead sensor. Both deliver exact in/out and occupancy into the same platform.
Are images of people stored?
Not in counting mode. The camera analyses video in the moment and outputs numbers; no personal images are stored and no individuals are identified. If you separately choose a video security extension, recording is governed by your own security policy and legal basis, and it remains clearly separated from the counting analytics.
Can the cameras do more than counting?
Yes, and that is the point of choosing standard cameras: the hardware can grow with you. On request, the system extends with video security capabilities, configured by you and governed by your own security policy and legal basis (the extension sits outside the DPA-approved counting method). Counting stays anonymous either way: one investment, two jobs, on your terms.
When are AI cameras the right choice over LiDAR or 3D sensors?
Choose AI cameras where standard camera hardware is an advantage: existing camera points, service and checkout zones, or sites standardising on one hardware family. Choose LiDAR for dark, outdoor or wide-open areas where image-free measurement matters most, and 3D sensors for classic high-precision doorway counting. Many venues combine them through the same platform.