Video intelligence

Object recognition, video tracking, counting, and classification

Object recognition and tracking in video for counting, classification, event detection, safety monitoring, inventory observation, plant monitoring, and machine-adjacent automation.

Use this when a camera feed should become structured events: what object appeared, where it moved, how many passed, what class it belongs to, and whether an alert or action is needed.

Typical scope

  • Object detection, object tracking, counting in video, product classification, queue/flow counting, region crossing, and event-based alerts
  • Jetson Nano, embedded Linux, GStreamer, OpenCV, custom ML models, edge inference, and cloud AI summaries when needed
  • Data capture and labeling plans when the model needs examples from the real camera angle and real lighting

Common searches this fits

object recognition in videovideo tracking and countingobject counting cameraedge AI object detectionvideo classification automation

Questions this page answers

Can video count and classify objects automatically?

Yes, when the camera view, lighting, frame rate, object variation, and definition of each class are clear enough.

Can this run on the edge?

Many workloads can run on Jetson-class hardware or embedded Linux. Cloud AI can be added for summaries, review, or harder edge cases.

Next step

Send a small brief.

Include the board, sensors, machine interface, current failure, desired behavior, connectivity, dashboard or alert needs, and the artifact you need: IoT prototype, working firmware, data bridge, control box, edge AI workflow, OTA/telemetry plan, or vendor handoff packet.