VSC523Q24.041P-000 B & R Automation
Wake Industrial LLC is not an authorized distributor of this product.
No Tariffs On US Orders- Straightforward Pricing: No Rush Fees, No Credit Card Fees
The B & R Automation VSC523Q24.041P-000 is a smart camera from the VS Smart Sensors series, equipped with a 3.5 MP resolution and a frame rate of 43 fps. It features a Cortex A9 i.MX6 quad core processor running at 800 MHz with 2 GB RAM and a 1 MB L2 cache. This integrated machine vision device offers several vision functions simultaneously and includes a deep learning variant.
To contact sales for pricing and lead time:
Payment Methods
Shipping Methods
Our Credentials
Product Description:
B&R Automation supplies the VSC523Q24.041P-000, a member of the VS Smart Sensors series and part of the Smart Camera product group. Within the integrated machine vision range, it combines an image sensor, optics, multicolored lighting, and an embedded quad-core processor. The result is a self-contained vision node that performs inspection, positioning, and barcode reading directly on conveyors or robotic cells, simplifying wiring and eliminating the need for a separate industrial PC.
The imaging block captures scenes at a native resolution of 3.5 MP, allowing fine feature discrimination across medium-size fields of view. A rolling shutter streams data at up to 43 fps, so fast indexing mechanisms can be monitored without missed frames. The factory-installed 1/1.8-inch lens has a focal length of 8 mm and an F4 aperture, and together with the 37° horizontal angle of view, it supports short working distances while limiting distortion. A sapphire glass front window carries an anti-reflective coating to maximize transmission, and the illumination path is matched to LED lens type 2 for consistent beam shaping. Sensor, lighting, and I/O connections are housed in an S-mount body, and the device runs a quad pipeline clocked at 800 MHz across 4 cores, shortening exposure-to-decision latency. Line-sensor functionality is disabled, keeping the model optimized for area imaging.
Processing tasks are executed by a Cortex-A9 i.MX6 quad-core SoC backed by 2 GB of DDR3 RAM and a 1 MB shared L2 cache, providing headroom for parallel algorithms. The onboard inference accelerator performs preprocessing so that classification, measurement, and blob analysis can run simultaneously. A radial lighting ring built from 16 LEDs, arranged as four multicolor segments, delivers selectable R/G/B/Lime channels for contrast tuning. This deep learning-capable unit ships as the Deep learning variant, making it suitable for feature detection models that benefit from convolutional networks.