A compact and energy-efficient 10GigE camera is used in the quality assurance of chicken eggs. Because it is important to inspect the eggs from multiple angles, 21 cameras were installed above the conveyor belt. Despite this high number of cameras, the system requires only one switch and image processing with three GPUs.

For years, engineers in industrial imaging have struggled to build scalable, high-performance multi-camera systems that operate reliably in real-world, 24/7 environments. Applications demanding real-time analytics and AI-based processing introduce additional complexity. Systems that look good on paper often suffer in practice: frame drops under load, cameras drifting out of sync, or thermal issues that cause shutdowns. At Emergent Vision Technologies, we’ve spent more than a decade engineering solutions that address these challenges head-on. The result is a portfolio of vision tools that integrate seamlessly from sensor to insight – built for performance, reliability, and scale.
 

Compact and Power-Efficient 10GigE Camera

The Eros camera series is designed with demanding embedded and high-density applications in mind. At 29 × 29 mm, Eros is a small 10GigE vision camera – and it’s power-efficient: Depending on the interface, power consumption is as low as 3 W with SFP+ and up to 4.8 W with PoE. This low power footprint means reduced thermal output, which is crucial for compact systems where heat management is a challenge. Fewer watts mean fewer fans, less vibration, lower acoustic noise, and greater system stability.

The camera series also supports active lens control (EF, RF), offers both RJ45 and fiber (SFP+) connectivity, and features Sony and Gpixel sensors from 0.5 to 24.7 megapixels – giving engineers flexibility.
 

Solving the Multi-Camera Problem

Building multi-camera systems – 8, 16, or even 100+ cameras in perfect sync – often leads to hard technical limitations. Frame drops appear under load, camera sync fails over time, and CPUs become saturated. Many systems break down due to:

• Interfaces like USB3 or CoaXPress that don’t scale well
• Poor sync strategies using unreliable GPIO triggers or partial PTP implementations
• Host systems unable to handle multi-gigabit data across multiple channels

What makes Emergent different is our deep integration of hardware and software to optimize data movement from sensor to storage:

• Optimized GVSP implementation with zero-copy transfer, allowing direct (GPU) memory access and dramatically reducing CPU load compared to traditional buffer-copy approaches
• Hardware-based PTP (IEEE1588) synchronization for deterministic frame timing across all cameras
• Full support for GPU Direct on both Windows and Linux platforms
• Flexproc and Flextrans for offloading processing tasks to multiple compute nodes (CPU, GPU, Cloud)
• Scalable architecture verified in setups with 48+ cameras operating at full bandwidth

This tight coupling between interface hardware, optimized transport, and processing pipelines enables reliable and high-throughput performance that generic systems often fail to deliver.
 

Case Study: Egg Quality Inspection with AI Support

A client in the egg processing industry approached us after multiple failed attempts to build a robust, AI-powered, real-time inspection system. Their goal: inspect each egg from multiple angles using synchronized high-speed imaging and process it live with AI. Previous vendors had proposed multi-camera solutions that theoretically fit the requirements, but in reality could only support 4 to 5 low-speed cameras before dropping frames or falling out of sync. Systems overheated, CPUs overloaded, and their internal teams were left troubleshooting unreliable performance.

We worked closely with them to specify and build a tailored setup:

• 21 × HR-series 10GigE 5MP cameras (initial deployment)
• A single 10/25GigE switch
• One mid-size workstation with 3 GPUs
• Ecapture Pro software with custom plug-in support for their AI pipeline

The entire system was fully tested before shipment. We validated performance under full load, ensured consistent frame sync using PTP, confirmed zero-frame-loss capture to disk, and verified plug-in operation for inference. The user now has a deployed system in production, analyzing every egg in real time with high-resolution imaging, synchronized angles, and fast AI feedback - without bottlenecks or instability.

After validating the system and seeing the performance benefits, the customer is now planning to upgrade the full solution to Eros cameras to benefit from reduced power consumption, smaller footprint, and further simplified integration.