ConveyorCount – AI Counting of Parts on a Conveyor Belt

Improve Your Counting Operations with AI

Conveyor Based Counting Solutions

ConveyorCount is a vision‑based automated counting system from Sciotex that automatically counts parts as they move on a conveyor using AI and machine vision. This system replaces slow, error‑prone manual counting with real‑time, high‑speed, and highly accurate counts directly from your production or packaging line.

Counts individual parts in motion on a conveyor.
Uses AI to distinguish and track parts even when they touch or partially overlap.
Works across a wide range of product shapes, sizes, and colors.
Can integrate with existing lines or as an independent system to improve QC.
Custom developed and built in-house here in the US.
Data remains on-premise without relaince on 3rd party APIs or cloud systems.

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Counting Consultation

What ConveyorCount Counts

ConveyorCount is designed for bulk product and parts counting directly on a moving belt.

Small manufactured parts (fasteners, hardware, molded components).
Consumer goods and packaged items (pouches, small cartons, blister packs).
Food and beverage items that can be visually separated on the belt.
Electronics and industrial components where piece‑accurate counts are critical.

The same platform can be tuned for different SKUs and product families through recipes, without mechanical changeover.

How ConveyorCount Works

ConveyorCount uses industrial cameras positioned over a conveyor combined with AI‑driven vision software, to identify and count each item as it passes through the viewing area.

High‑resolution cameras capture images or video frames at high speed.
Vision algorithms segment the image and detect individual parts based on shape, size, and position.
AI models handle touching and partially overlapping items, maintaining an accurate running count.
Counts are sent in real time to a PLC, HMI, or other control system for packing, labeling, or inventory.

Because counting is based on visual recognition rather than weight or volume, ConveyorCount does not rely on tight assumptions about product mass or fill.

Technology and AI Capabilities

ConveyorCount uses its own in-house developed AI systems developed here in the US. We do not rely on 3rd party APIs or cloud storage systems. This is important to our clients where IP or other part/product data should remain on-premise for security or competitive reasons.

Machine vision tools for object detection, tracking, and background suppression.
AI‑driven classification to recognize valid parts and ignore debris or foreign objects.
Handling of variable orientation, spacing, and minor overlap between items.
Optional real‑time quality checks, such as detecting missing features or damaged products while counting.

Performance and Throughput

ConveyorCount is built for continuous operation on conveyor lines or on the self-contained conveyor-based system shown here.

High‑speed operation keeps pace with modern packaging and processing lines.
Real‑time counts support on‑the‑fly case packing, kit building, validating product mix and batching.
Stable accuracy over long runs, without fatigue or drift counting parts with machine vision.
Scales from small pilot lines to large multi‑line facilities.

Sciotex engineers tune camera placement, field of view, lighting, and AI training algorithms to meet your cycle time and count‑accuracy targets.

ConveyorCount Demo Video

With ConveyorCount you get:

Proven conveyor counting architectures backed by industrial AI and machine vision expertise.
Custom engineering for your products, conveyor configuration, and control standards.
Data security keeping your data on-premise and your IP safe.
Long‑term support from a US‑based team focused on continually improving counting and inspection automation.