BRICK Ultra for edge computing and industrial AI applications in networked infrastructures

We show how the BRICK Ultra can be used as a compact edge computing platform in a networked industrial environment - from production and infrastructure monitoring to digital control centers.

Modern edge and AI computing platform for industrial applications

An international industrial and infrastructure operator was planning to modernize its decentralized IT structure. The aim was to process data from machines, sensors and cameras directly on site, carry out AI-based evaluations in real time and only transfer relevant results to central cloud and control systems.

The company was looking for a compact industrial PC that could reliably handle edge AI workloads as well as classic automation and visualization tasks.

The challenge: Decentralized intelligence under real operating conditions

The hardware requirements were varied and demanding:

• Edge performance for AI applications: Local processing of image data, sensor information and key production figures in real time (Edge AI / Inference).

• Industrial automation & stability: Use in machine and system environments with 24/7 operation and high reliability.

• Limited space in decentralized installations: Installation directly on machines, in control cabinets or vehicle and infrastructure housings.

• Network and system integration: Secure connection to SCADA, ERP and cloud systems with simultaneous data pre-processing at the edge.

• Multi-display and control centre operation: Visualization of complex data situations in control rooms and monitoring systems.

The solution: BRICK Ultra as a compact edge AI and industrial platform

The choice fell on the BRICK Ultra from spo-comm, a particularly compact industrial PC that was specially developed for edge and embedded scenarios. The following features were decisive:

1. Ultra-compact design: Ideal for decentralized installations directly on machines, in vehicles or in confined infrastructure spaces.

2. AI-enabled CPU architecture: Supports modern AI workloads such as image processing, pattern recognition and edge inference directly on site - without permanent cloud dependency.

3. Fanless, robust design: low-maintenance, vibration-resistant and suitable for 24/7 continuous operation in industrial environments.

4. Flexible connectivity: Integration into industrial networks, machine control systems and higher-level IT systems thanks to extensive interfaces.

5. Visualization capability: Suitable for multi-display applications in control stations and control rooms for real-time monitoring of complex systems.

The implementation

The BRICK Ultra was installed decentrally at machines, infrastructure nodes and control points.

In production, it was used for local processing of sensor data and AI-supported analysis of camera images for quality control. In traffic and infrastructure scenarios, it was used for real-time monitoring of operating states and events.

At the same time, the system acted as an edge gateway: pre-processed data was filtered and only relevant information was forwarded to central platforms and cloud systems. In control centres, aggregated data came together in multi-display setups to visualize critical states.

Conclusion and outlook for edge AI and industrial digitalization

The BRICK Ultra is a powerful edge computing platform that is specially designed to meet the requirements of modern industrial, transportation and infrastructure environments.

The combination of compact design, AI-capable computing power and industrial-grade robustness enables reliable use directly at the point of origin of the data - where real-time decisions are crucial.

The BRICK Ultra therefore forms a scalable basis for future edge AI architectures, from smart factories and networked infrastructures to intelligent control and monitoring systems.