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Use Case: Logistics

Cataloging System

The Snap Platform helps reduce returns on a manual box packing line. After packing, the boxes are placed onto a conveyor belt for sealing and shipping. By counting the number of packages on the line The Snap Platform collects a visual record of every package before shipping out of facility and understands shift by shift productivity.

Problem

Currently, no system can rapidly deploy an end-to-end system for automated capture and that includes searchable catalog of parts and a business intelligence layer. Hardware triggers are unreliable when boxes are touching each other.

The Overview Solution

Our Deep Learning triggering system enables a cheap overhead camera to capture, count and catalog all boxes passing on conveyor belt. The Snap Platform analytics engine shows which shifts are performing best, and displays realtime statuses on manual packaging throughput.

How does the system work?

High speed inspection

  • Deep learning based object tracking and triggering system captures only a single image of each box
  • Each box gets cropped from image, timestamped and saved to the catalog

Result

100% of packages are cataloged so returns can be better disputed. Better shift optimization increases productivity.

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