AI vision systems are transforming industrial automation, delivering speeds and accuracy in manufacturing processes that were unimaginable just five years ago. But to unlock their full potential, these systems need more than just smart algorithms – high-speed, low-latency networking and reliable power delivery are crucial to ensuring seamless performance.

Traditionally, vision systems in manufacturing have been used for basic inspection tasks. Relying on pre-programmed rules and fixed algorithms, they can be highly effective in controlled environments where lighting, materials, and part shapes remain consistent, but are far less suited to complex or changing conditions. AI has transformed vision systems, enabling them to learn from data, adapt to new conditions, and take on increasingly complex manufacturing tasks.

Modern neural networks, powered by open-source frameworks like TensorFlow, don’t depend on predefined rules but instead learn by analysing thousands of images. By training a model to recognise patterns, an AI-driven vision system can classify objects, detect defects, and adjust to variations in the production environment, without requiring engineers to systematically program every possible scenario.
To bring these next-generation vision systems to industry, Brainboxes has developed a solution that integrates Power over Ethernet (PoE) Gigabit networking, Edge computing, and AI processing, enabling high-performance industrial cameras to connect with real-time machine learning inference.

Powering AI Vision Systems with PoE Gigabit Networking

To showcase the technology’s possibilities, Brainboxes has created an interactive demonstration where AI challenges humans to a game of rock-paper-scissors. While a fun way to engage with the system, it also demonstrates a powerful shift in industrial automation, where vision systems are moving beyond traditional inspection to enable real-time, intelligent decision-making on production lines and beyond.

Real-Time AI Processing at the Edge

Machine learning models can be trained on a laptop and deployed on Brainboxes’ BB-400 Industrial Edge Controller to run AI inference at the Edge, enabling real-time decisions without cloud-based processing and reducing both latency and bandwidth demands. With AI providing unprecedented intelligence, PoE Gigabit networking delivers the critical infrastructure needed to power and connect these vision systems. Brainboxes’ SW-595 PoE Gigabit and SFP industrial network switch supplies both power and high-speed data over a single Ethernet cable, eliminating the need for separate power sources and allowing cameras to be positioned almost anywhere.

Why PoE Gigabit is Essential for AI Vision Systems

• Power and Data Over a Single Cable – The SW-595 eliminates the need for separate power supplies, allowing cameras to be positioned in difficult-to-reach areas while ensuring high-speed data transmission.
• Ultra-Low Latency for Real-Time AI – AI vision systems require high-bandwidth, low-latency connectivity to process images instantly. The Gigabit speed of the SW-595 ensures smooth, real-time video streaming.
• Long-Distance Deployment – With SFP fibre connectivity, cameras can be installed far from processing units while maintaining fast, reliable data transfer—ideal for large-scale industrial applications.

The same principles demonstrated in Brainboxes’ AI-powered rock-paper-scissors game can be applied to solve complex engineering challenges across industry. AI-driven vision systems are already helping engineers instantly identify faults and improve quality control, reducing waste and inefficiencies. The technology also enables highly detailed inspections, detecting subtle defects like hairline cracks in metal components, flaws that would typically go unnoticed by traditional inspection methods.

Rather than relying on physical, locally-attached sensors, PoE-powered cameras capture real-time video, which is processed at the Edge by AI to count and classify widgets, ensuring optimal production flow. At the same time, remote condition monitoring is easier than ever, with AI tracking equipment wear, detecting anomalies, and instantly alerting engineers to maintenance needs, helping to prevent costly unplanned downtime.

See AI Vision in Action

For those looking to explore how AI vision systems could transform their own manufacturing operations, Brainboxes’ interactive rock-paper-scissors demo provides a firsthand look at real-time AI inference, ultra-low latency video streaming, and PoE Gigabit networking, giving engineers a chance to see cutting-edge AI vision technology in action.

Brainboxes will be showcasing the demo at global events throughout 2025