Solutions

Production line monitoring with computer vision

See when a line is running, stopped or slowed down — and why — without waiting for end-of-shift reports or wiring every machine.

Production line monitoring with computer vision uses cameras to observe machines, stations and product flow, and derives operational metrics such as running/stopped state, cycle time, output count and downtime.

The problem

Many plants still collect downtime and output data by hand. Short stops of one or two minutes rarely make it into the log, so performance losses stay hidden and OEE figures look better on paper than on the floor.

Older machines often have no accessible PLC data, which makes automated measurement expensive.

How it works

  1. 1Cameras covering stations, conveyors or machine outputs are connected over RTSP/ONVIF.
  2. 2Models detect product flow, machine activity and operator presence per station.
  3. 3Events are converted into running/stopped intervals, cycle times and counts.
  4. 4Shift dashboards show availability, performance indicators and downtime by station.

Existing IP cameras / NVR

RTSP / ONVIF streams

Edge device on-site

AI models + rules; video stays local

Events

Time, camera, zone, evidence frame

Dashboard, alerts, API

Notifications, relays, REST/webhook

Typical on-premise deployment. Cloud and hybrid options are also available.

What can be detected

  • Line or station stop, including micro-stops
  • Cycle time per unit or batch
  • Output count per station and shift
  • Station unattended while the line is running

Typical scenarios

  • Assembly and packing lines
  • Older machines without PLC connectivity
  • Bottleneck analysis across stations
  • Shift handover reporting

Deployment options

On-premise / edge

Analysis runs on hardware inside your network. Video does not leave the site; only events and metrics are stored or shared.

Cloud

Suitable for distributed, low-camera-count sites where central management matters more than keeping video on-site.

Hybrid

Video is processed on-site, while events, dashboards and multi-site reporting are managed centrally.

Working with existing cameras

  • The product flow or machine output must be visible in frame.
  • Higher frame rates are needed for fast lines; this is checked during camera assessment.
  • Most IP cameras and NVRs that provide RTSP or ONVIF streams can be connected, regardless of brand.
  • Before a pilot, sample footage from each candidate camera is reviewed for resolution, angle, distance and lighting.
  • Where a view is not suitable, the recommendation is usually to reposition the camera or add one — not to replace the whole system.

Integration

  • REST API / webhook to MES or ERP
  • Export of shift reports
  • Dashboard for supervisors and management

Privacy and security

  • No face recognition is used in safety and operations analytics; events describe what happened, not who.
  • On-premise processing keeps video inside your network.
  • Evidence clips, retention periods and user access are configurable and should follow your GDPR/KVKK policies.
  • Workplace monitoring should be introduced with clear employee information and, where applicable, consultation with employee representatives.

Limitations

  • Camera-derived metrics are as good as the view of the process; hidden steps need additional cameras or data sources.
  • Reason codes for stops may still need operator input or integration with existing systems.

How a pilot works

  1. 01

    Discovery

    We agree on the problem, the owner, the sites and what a successful outcome would look like.

  2. 02

    Camera assessment

    Sample footage from candidate cameras is reviewed for angle, resolution, distance and lighting.

  3. 03

    Use-case definition

    Events, zones, rules, alert recipients and success metrics are written down before deployment.

  4. 04

    Pilot deployment

    Edge hardware or cloud processing is set up and connected to the selected cameras.

  5. 05

    Validation

    Detections are checked against reviewed footage; true detections, false alarms and misses are counted per camera.

  6. 06

    Report

    Results, limitations and recommended changes are documented and shared with all stakeholders.

  7. 07

    Rollout decision

    Based on measured results, you decide whether and how to expand to more cameras, sites or use cases.

Frequently asked questions

Can you calculate OEE from cameras?

Cameras can provide running time, counts and cycle times, which cover availability and performance. Quality usually comes from inspection results or existing systems and can be combined via integration.

Do we need to connect to our PLCs?

No, but it is possible. Camera-based measurement works without PLC access, which is useful for older equipment.

Start with the cameras you already have

Send us a few frames from your cameras and the problem you want to solve. We will tell you honestly what is feasible.