6G-XR

RACE-6G

image use case

The RACE-6G project successfully developed and deployed a innovative AI-driven industrial orchestration system that demonstrates the transformative potential of combining advanced connectivity with intelligent automation. Our team at Buontech Solutions created a comprehensive multi-agent system featuring an LLM-powered orchestrator that monitors and controls factory operations through real-time video analysis and autonomous decision-making.
The implemented solution integrates Unreal Engine 5.5 for photorealistic factory simulation with a sophisticated Python-based AI agent utilising Ollama and the Qwen3-VL vision model. Through WebRTC-based Pixel Streaming 2, the system captures high-definition video from multiple camera perspectives, analyses production line status in real-time, and automatically executes corrective actions when anomalies are detected. The architecture supports dynamic reconfiguration following Plug & Produce principles, enabling seamless integration of new equipment and rapid adaptation to changing production requirements. This practical demonstration validates how next-generation connectivity combined with edge AI can deliver the ultra-responsive, intelligent manufacturing environments essential for Industry 5.0.

Type of experiment:
Simulation/Emulation

Functionality:
Enhanced Mobile Broadband (eMBB)


Location(s):
Finland

Vertical sector(s):
Industry 4.0/ Manufacturing


replicable use case

This use case is replicable

Degree of replicability1:
38
1According to the Replicability Assessment Tool

High level of replicability : 61 < LR < 80

Good level of replicability: 31 < LR < 60

Low level of replicability: 00 < LR < 30


Project Open Call 3rd-party funding

6G-XR


Duration:

GA Number: 101096838

SNS JU Call (Stream):
Call 1
Stream C

This tool has received funding from the European Union’s Horizon Europe Research and Innovation programme under the SNS ICE project (Grant Agreement No 101095841)