AI people counting cameras
Standard network cameras with counting intelligence built in: exact in/out, occupancy and queue metrics from the camera itself. Counting is anonymous, and the same hardware investment can grow when 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, so all methods share 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 plan around cameras at entrances, checkouts, service desks and receptions. An AI people counting camera is a standard network camera with the counting intelligence built in, so the device that watches a point can also measure it. It delivers exact directional in/out counts, live occupancy and queue metrics 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 counting comes from Bumbee Labs, the company behind the only footfall method in Europe approved by a data protection authority, and the same privacy-first engineering that makes GDPR-compliant people counting possible runs every method we deliver.
What is an AI people counting camera?
An AI people counting camera is a standard network camera with a counting model built into the device. It analyses video in the moment and delivers exact directional in/out counts, live occupancy and queue metrics as numbers, with no footage leaving the camera. That separates it from conventional CCTV, which records images for people to review. A counting camera is configured to measure, and in counting mode no personal images are stored and no individuals are identified. It also differs from dedicated overhead 3D people counting sensors, which are purpose-built counting devices. An AI camera delivers exact in/out and occupancy on standard camera hardware, which makes it practical wherever camera infrastructure already exists or is planned. Either way, the numbers land in the same analytics platform as every other counting method.
Where AI cameras fit best
AI cameras fit best where standard camera hardware is itself an 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 gives the same precision without any imagery at all. Every method feeds the same platform, and a hybrid setup lets you mix them freely. If you already run Xovis 3D sensors, we process that data too.
Occupancy cameras: live capacity at a glance
An occupancy camera is the same AI counting camera doing its most time-critical job: keeping a live count of how many people are inside a zone right now. Directional in/out counts at each entrance and exit are aggregated continuously, so current occupancy is always entries minus exits. You can hold that live figure against safe capacity limits instead of relying on an estimate made from footfall totals.
The figure is anonymous and aggregate: it shows how many people are inside, not who they are, and it lands in the same dashboards and API as every other metric. For what venues do with live occupancy beyond capacity compliance, from staffing to crowd comfort, see real-time occupancy and crowd comfort.
People counting cameras for retail
In retail, people counting cameras measure the entrance and the checkouts at the same time. At the entrance, exact directional counts anchor the in-store conversion rate: entries against transactions, store by store. At checkouts and service points, queue length and waiting-time indicators show when queues are building. Those metrics drive staffing in the zones where sales are won and lost.
Because AI camera data lands in the same platform as Wi-Fi, 3D sensor and LiDAR data, a chain can add camera precision at the doors and service points that need it and keep identical metrics across the estate. The full retail picture, from capture rate to store-to-store benchmarking, is on retail footfall analytics.
One investment for counting and video security
Most counting hardware does one job for its whole life, but standard cameras can do more. The counting product is analytics-only and anonymous by default, and it produces numbers, never footage. If you later want more from the same cameras, the system can be extended with video security capabilities on request. You decide whether and when, and what it covers. Your own security policy and legal basis govern it, entirely separate from the anonymous counting analytics. Nothing is recorded unless you have chosen it, and the counting analytics stays anonymous either way.
For a buyer, that separation is the main advantage: the privacy review clears the counting on its own terms today, and the security option is yours to take up whenever there is a business case for it.
One platform for every counting method
AI camera metrics arrive through the same data deliverables, dashboards and API as Wi-Fi, 3D sensor, LiDAR and cellular data, so every method reports into one source of truth.
AI cameras vs 3D sensors vs LiDAR
All three are precision methods, each suited to different conditions. AI cameras use standard hardware, 3D sensors are purpose-built for counting, and LiDAR works without a camera at all.
| Capability | AI camera | 3D sensors | LiDAR |
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| 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 |
| Built to be image-free | 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?
The same cameras for counting and video security
Counting is anonymous and aggregate, and it produces numbers, never footage. When you want more from the hardware, the same cameras can be extended with video security, under your control and your rules.
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. That makes them practical where camera infrastructure already exists or is planned, and one device can cover 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.
Is camera-based people counting GDPR-compliant?
Camera-based counting can be GDPR-compliant when the system is built to count rather than to identify, and that is how these cameras run by default. In counting mode the video is analysed in the moment and only numbers leave the camera. No personal images are stored, no individuals are identified, and what you receive is an anonymous, aggregate count. The counting comes from Bumbee Labs, the company behind the only footfall method in Europe approved by a data protection authority, and the same privacy-first engineering runs every method we deliver, AI cameras included.
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 can be extended with video security capabilities that you configure and that your own security policy and legal basis govern, entirely separate from the anonymous counting analytics. Counting stays anonymous either way, and you decide whether the same cameras take on both jobs.
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.